<?xml version="1.0" encoding="UTF-8"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-16T21:27:42Z</responseDate><request metadataPrefix="oai_dc" verb="ListRecords">https://escholarship.org/oai</request><ListRecords><record><header><identifier>oai:escholarship.org:ark:/13030/qt946228s5</identifier><datestamp>2026-09-16T07:23:11Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt946228s5</dc:identifier><dc:title>The International Collaboration on Air Pollution and Pregnancy Outcomes: Initial Results</dc:title><dc:creator>Parker, Jennifer D</dc:creator><dc:creator>Rich, David Q</dc:creator><dc:creator>Glinianaia, Svetlana V</dc:creator><dc:creator>Leem, Jong Han</dc:creator><dc:creator>Wartenberg, Daniel</dc:creator><dc:creator>Bell, Michelle L</dc:creator><dc:creator>Bonzini, Matteo</dc:creator><dc:creator>Brauer, Michael</dc:creator><dc:creator>Darrow, Lyndsey</dc:creator><dc:creator>Gehring, Ulrike</dc:creator><dc:creator>Gouveia, Nelson</dc:creator><dc:creator>Grillo, Paolo</dc:creator><dc:creator>Ha, Eunhee</dc:creator><dc:creator>van den Hooven, Edith H</dc:creator><dc:creator>Jalaludin, Bin</dc:creator><dc:creator>Jesdale, Bill M</dc:creator><dc:creator>Lepeule, Johanna</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Morgan, Geoffrey G</dc:creator><dc:creator>Slama, Rémy</dc:creator><dc:creator>Pierik, Frank H</dc:creator><dc:creator>Pesatori, Angela Cecilia</dc:creator><dc:creator>Sathyanarayana, Sheela</dc:creator><dc:creator>Seo, Juhee</dc:creator><dc:creator>Strickland, Matthew</dc:creator><dc:creator>Tamburic, Lillian</dc:creator><dc:creator>Woodruff, Tracey J</dc:creator><dc:date>2011-07-01</dc:date><dc:description>BACKGROUND: The findings of prior studies of air pollution effects on adverse birth outcomes are difficult to synthesize because of differences in study design.
OBJECTIVES: The International Collaboration on Air Pollution and Pregnancy Outcomes was formed to understand how differences in research methods contribute to variations in findings. We initiated a feasibility study to a) assess the ability of geographically diverse research groups to analyze their data sets using a common protocol and b) perform location-specific analyses of air pollution effects on birth weight using a standardized statistical approach.
METHODS: Fourteen research groups from nine countries participated. We developed a protocol to estimate odds ratios (ORs) for the association between particulate matter ≤ 10 μm in aerodynamic diameter (PM₁₀) and low birth weight (LBW) among term births, adjusted first for socioeconomic status (SES) and second for additional location-specific variables.
RESULTS: Among locations with data for the PM₁₀ analysis, ORs estimating the relative risk of term LBW associated with a 10-μg/m³ increase in average PM₁₀ concentration during pregnancy, adjusted for SES, ranged from 0.63 [95% confidence interval (CI), 0.30-1.35] for the Netherlands to 1.15 (95% CI, 0.61-2.18) for Vancouver, with six research groups reporting statistically significant adverse associations. We found evidence of statistically significant heterogeneity in estimated effects among locations.
CONCLUSIONS: Variability in PM₁₀-LBW relationships among study locations remained despite use of a common statistical approach. A more detailed meta-analysis and use of more complex protocols for future analysis may uncover reasons for heterogeneity across locations. However, our findings confirm the potential for a diverse group of researchers to analyze their data in a standardized way to improve understanding of air pollution effects on birth outcomes.</dc:description><dc:subject>4202 Epidemiology (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Infant Mortality (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Climate-Related Exposures and Conditions (rcdc)</dc:subject><dc:subject>Maternal Health (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Perinatal Period - Conditions Originating in Perinatal Period (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>2.5 Research design and methodologies (aetiology) (hrcs-rac)</dc:subject><dc:subject>Air Pollution (mesh)</dc:subject><dc:subject>Birth Weight (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Feasibility Studies (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Low Birth Weight (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>International Cooperation (mesh)</dc:subject><dc:subject>Particle Size (mesh)</dc:subject><dc:subject>Particulate Matter (mesh)</dc:subject><dc:subject>Pilot Projects (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Pregnancy Outcome (mesh)</dc:subject><dc:subject>Premature Birth (mesh)</dc:subject><dc:subject>Research Design (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>Socioeconomic Factors (mesh)</dc:subject><dc:subject>air pollution</dc:subject><dc:subject>birth weight</dc:subject><dc:subject>ICAPPO</dc:subject><dc:subject>low birth weight</dc:subject><dc:subject>particulate matter</dc:subject><dc:subject>pregnancy</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Premature Birth (mesh)</dc:subject><dc:subject>Birth Weight (mesh)</dc:subject><dc:subject>Pregnancy Outcome (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Feasibility Studies (mesh)</dc:subject><dc:subject>Pilot Projects (mesh)</dc:subject><dc:subject>Air Pollution (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Particle Size (mesh)</dc:subject><dc:subject>Research Design (mesh)</dc:subject><dc:subject>International Cooperation (mesh)</dc:subject><dc:subject>Socioeconomic Factors (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Low Birth Weight (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Particulate Matter (mesh)</dc:subject><dc:subject>Air Pollution (mesh)</dc:subject><dc:subject>Birth Weight (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Feasibility Studies (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Low Birth Weight (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>International Cooperation (mesh)</dc:subject><dc:subject>Particle Size (mesh)</dc:subject><dc:subject>Particulate Matter (mesh)</dc:subject><dc:subject>Pilot Projects (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Pregnancy Outcome (mesh)</dc:subject><dc:subject>Premature Birth (mesh)</dc:subject><dc:subject>Research Design (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>Socioeconomic Factors (mesh)</dc:subject><dc:subject>05 Environmental Sciences (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>Toxicology (science-metrix)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:subject>41 Environmental sciences (for-2020)</dc:subject><dc:subject>42 Health sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/946228s5</dc:identifier><dc:identifier>https://escholarship.org/content/qt946228s5/qt946228s5.pdf</dc:identifier><dc:identifier>info:doi/10.1289/ehp.1002725</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Health Perspectives, vol 119, iss 7</dc:source><dc:coverage>1023 - 1028</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5723s6kf</identifier><datestamp>2026-09-16T07:19:07Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5723s6kf</dc:identifier><dc:title>Jet-like correlations with direct-photon and neutral-pion triggers at sNN=200&amp;nbsp;GeV</dc:title><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adkins, JK</dc:creator><dc:creator>Agakishiev, G</dc:creator><dc:creator>Aggarwal, MM</dc:creator><dc:creator>Ahammed, Z</dc:creator><dc:creator>Alekseev, I</dc:creator><dc:creator>Anderson, DM</dc:creator><dc:creator>Aparin, A</dc:creator><dc:creator>Arkhipkin, D</dc:creator><dc:creator>Aschenauer, EC</dc:creator><dc:creator>Ashraf, MU</dc:creator><dc:creator>Attri, A</dc:creator><dc:creator>Averichev, GS</dc:creator><dc:creator>Bai, X</dc:creator><dc:creator>Bairathi, V</dc:creator><dc:creator>Bellwied, R</dc:creator><dc:creator>Bhasin, A</dc:creator><dc:creator>Bhati, AK</dc:creator><dc:creator>Bhattarai, P</dc:creator><dc:creator>Bielcik, J</dc:creator><dc:creator>Bielcikova, J</dc:creator><dc:creator>Bland, LC</dc:creator><dc:creator>Bordyuzhin, IG</dc:creator><dc:creator>Bouchet, J</dc:creator><dc:creator>Brandenburg, JD</dc:creator><dc:creator>Brandin, AV</dc:creator><dc:creator>Bunzarov, I</dc:creator><dc:creator>Butterworth, J</dc:creator><dc:creator>Caines, H</dc:creator><dc:creator>de la Barca Sánchez, M Calderón</dc:creator><dc:creator>Campbell, JM</dc:creator><dc:creator>Cebra, D</dc:creator><dc:creator>Chakaberia, I</dc:creator><dc:creator>Chaloupka, P</dc:creator><dc:creator>Chang, Z</dc:creator><dc:creator>Chatterjee, A</dc:creator><dc:creator>Chattopadhyay, S</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Chen, JH</dc:creator><dc:creator>Cheng, J</dc:creator><dc:creator>Cherney, M</dc:creator><dc:creator>Christie, W</dc:creator><dc:creator>Contin, G</dc:creator><dc:creator>Crawford, HJ</dc:creator><dc:creator>Das, S</dc:creator><dc:creator>De Silva, LC</dc:creator><dc:creator>Debbe, RR</dc:creator><dc:creator>Dedovich, TG</dc:creator><dc:creator>Deng, J</dc:creator><dc:creator>Derevschikov, AA</dc:creator><dc:creator>di Ruzza, B</dc:creator><dc:creator>Didenko, L</dc:creator><dc:creator>Dilks, C</dc:creator><dc:creator>Dong, X</dc:creator><dc:creator>Drachenberg, JL</dc:creator><dc:creator>Draper, JE</dc:creator><dc:creator>Du, CM</dc:creator><dc:creator>Dunkelberger, LE</dc:creator><dc:creator>Dunlop, JC</dc:creator><dc:creator>Efimov, LG</dc:creator><dc:creator>Engelage, J</dc:creator><dc:creator>Eppley, G</dc:creator><dc:creator>Esha, R</dc:creator><dc:creator>Evdokimov, O</dc:creator><dc:creator>Eyser, O</dc:creator><dc:creator>Fatemi, R</dc:creator><dc:creator>Fazio, S</dc:creator><dc:creator>Federic, P</dc:creator><dc:creator>Fedorisin, J</dc:creator><dc:creator>Feng, Z</dc:creator><dc:creator>Filip, P</dc:creator><dc:creator>Fisyak, Y</dc:creator><dc:creator>Flores, CE</dc:creator><dc:creator>Fulek, L</dc:creator><dc:creator>Gagliardi, CA</dc:creator><dc:creator>Garand, D</dc:creator><dc:creator>Geurts, F</dc:creator><dc:creator>Gibson, A</dc:creator><dc:creator>Girard, M</dc:creator><dc:creator>Greiner, L</dc:creator><dc:creator>Grosnick, D</dc:creator><dc:creator>Gunarathne, DS</dc:creator><dc:creator>Guo, Y</dc:creator><dc:creator>Gupta, S</dc:creator><dc:creator>Gupta, A</dc:creator><dc:creator>Guryn, W</dc:creator><dc:creator>Hamad, AI</dc:creator><dc:creator>Hamed, A</dc:creator><dc:creator>Haque, R</dc:creator><dc:creator>Harris, JW</dc:creator><dc:creator>He, L</dc:creator><dc:creator>Heppelmann, S</dc:creator><dc:creator>Heppelmann, S</dc:creator><dc:creator>Hirsch, A</dc:creator><dc:creator>Hoffmann, GW</dc:creator><dc:creator>Horvat, S</dc:creator><dc:creator>Huang, T</dc:creator><dc:creator>Huang, B</dc:creator><dc:creator>Huang, X</dc:creator><dc:creator>Huang, HZ</dc:creator><dc:date>2016-09-01</dc:date><dc:description>Azimuthal correlations of charged hadrons with direct-photon (γdir) and neutral-pion (π0) trigger particles are analyzed in central Au+Au and minimum-bias p+p collisions at sNN=200&amp;nbsp;GeV in the STAR experiment. The charged-hadron per-trigger yields at mid-rapidity from central Au+Au collisions are compared with p+p collisions to quantify the suppression in Au+Au collisions. The suppression of the away-side associated-particle yields per γdir trigger is independent of the transverse momentum of the trigger particle (pTtrig), whereas the suppression is smaller at low transverse momentum of the associated charged hadrons (pTassoc). Within uncertainty, similar levels of suppression are observed for γdir and π0 triggers as a function of zT (≡pTassoc/pTtrig). The results are compared with energy-loss-inspired theoretical model predictions. Our studies support previous conclusions that the lost energy reappears predominantly at low transverse momentum, regardless of the trigger energy.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>nucl-ex</dc:subject><dc:subject>nucl-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ph</dc:subject><dc:subject>nucl-th</dc:subject><dc:subject>NSD-Relativistic Nuclear Collisions (c-lbnl-label)</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5723s6kf</dc:identifier><dc:identifier>https://escholarship.org/content/qt5723s6kf/qt5723s6kf.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.physletb.2016.07.046</dc:identifier><dc:type>article</dc:type><dc:source>Physics Letters B, vol 760</dc:source><dc:coverage>689 - 696</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6hm7b1fw</identifier><datestamp>2026-09-16T07:19:00Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6hm7b1fw</dc:identifier><dc:title>Study of the wave packet treatment of neutrino oscillation at Daya Bay</dc:title><dc:creator>Daya Bay Collaboration</dc:creator><dc:date>2017-09-01</dc:date><dc:description>The disappearance of reactor ν¯e$$\bar{
u }_e$$ observed by the Daya Bay experiment is examined in the framework of a model in which the neutrino is described by a wave packet with a relative intrinsic momentum dispersion σrel$$\sigma _\mathrm{{rel}}$$. Three pairs of nuclear reactors and eight antineutrino detectors, each with good energy resolution, distributed among three experimental halls, supply a high-statistics sample of ν¯e$$\bar{
u }_e$$ acquired at nine different baselines. This provides a unique platform to test the effects which arise from the wave packet treatment of neutrino oscillation. The modified survival probability formula was used to fit Daya Bay data, providing the first experimental limits: 2.38×10-17&amp;lt;σrel&amp;lt;0.23$$2.38 \times 10^{-17}&amp;lt; \sigma _\mathrm{{rel}} &amp;lt; 0.23$$. Treating the dimensions of the reactor cores and detectors as constraints, the limits are improved: 10-14≲σrel&amp;lt;0.23$$10^{-14} \lesssim \sigma _\text {rel} &amp;lt; 0.23$$, and an upper limit of σrel&amp;lt;0.20$$\sigma _\text {rel}&amp;lt;0.20$$ (which corresponds to σx≳10-11cm$$\sigma _x \gtrsim 10^{-11}\,\mathrm{{cm }}$$) is obtained. All limits correspond to a 95% C.L. Furthermore, the effect due to the wave packet nature of neutrino oscillation is found to be insignificant for reactor antineutrinos detected by the Daya Bay experiment thus ensuring an unbiased measurement of the oscillation parameters sin22θ13$$\sin ^22\theta _{13}$$ and Δm322$$\varDelta m^2_{32}$$ within the plane wave model.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ph</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5102 Atomic</dc:subject><dc:subject>molecular and optical physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6hm7b1fw</dc:identifier><dc:identifier>https://escholarship.org/content/qt6hm7b1fw/qt6hm7b1fw.pdf</dc:identifier><dc:identifier>info:doi/10.1140/epjc/s10052-017-4970-y</dc:identifier><dc:type>article</dc:type><dc:source>European Physical Journal C, vol 77, iss 9</dc:source><dc:coverage>606</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt98z4n251</identifier><datestamp>2026-09-16T07:18:20Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt98z4n251</dc:identifier><dc:title>Study of the spin and parity of the Higgs boson in diboson decays with the ATLAS detector</dc:title><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Agricola, J</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Alconada Verzini, MJ</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Alkire, SP</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Alvarez Gonzalez, B</dc:creator><dc:creator>Álvarez Piqueras, D</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amadio, BT</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Amaral Coutinho, Y</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Amor Dos Santos, SP</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Aperio Bella, L</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arduh, FA</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:creator>Arnal, V</dc:creator><dc:creator>Arnold, H</dc:creator><dc:creator>Arratia, M</dc:creator><dc:creator>Arslan, O</dc:creator><dc:creator>Artamonov, A</dc:creator><dc:date>2015-10-01</dc:date><dc:description>Studies of the spin, parity and tensor couplings of the Higgs boson in the H→ZZ∗→4ℓ$$H \rightarrow ZZ^{*} \rightarrow 4 \ell $$, H→WW∗→eνμν$$H \rightarrow WW^{*} \rightarrow e 
u \mu 
u $$ and H→γγ$$H \rightarrow \gamma \gamma $$ decay processes at the LHC are presented. The investigations are based on 25fb-1$$25\;\mathrm{fb}^{-1}$$ of pp collision data collected by the ATLAS experiment at s=7$$\sqrt{s}=7$$&amp;nbsp;TeV and s=8$$\sqrt{s}=8$$&amp;nbsp;TeV. The Standard Model (SM) Higgs boson hypothesis, corresponding to the quantum numbers JP=0+$$J^{P}=0^{+}$$, is tested against several alternative spin scenarios, including non-SM spin-0 and spin-2 models with universal and non-universal couplings to fermions and vector bosons. All tested alternative models are excluded in favour of the SM Higgs boson hypothesis at more than 99.9&amp;nbsp;% confidence level. Using the H→ZZ∗→4ℓ$$H \rightarrow ZZ^{*} \rightarrow 4 \ell $$ and H→WW∗→eνμν$$H \rightarrow WW^{*} \rightarrow e 
u \mu 
u $$ decays, the tensor structure of the interaction between the spin-0 boson and the SM vector bosons is also investigated. The observed distributions of variables sensitive to the non-SM tensor couplings are compatible with the SM predictions and constraints on the non-SM couplings are derived.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>ATLAS Collaboration</dc:subject><dc:subject>ATLAS Collaboration</dc:subject><dc:subject>ATLAS Collaboration</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5102 Atomic</dc:subject><dc:subject>molecular and optical physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/98z4n251</dc:identifier><dc:identifier>https://escholarship.org/content/qt98z4n251/qt98z4n251.pdf</dc:identifier><dc:identifier>info:doi/10.1140/epjc/s10052-015-3685-1</dc:identifier><dc:type>article</dc:type><dc:source>European Physical Journal C, vol 75, iss 10</dc:source><dc:coverage>476</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0mg400nc</identifier><datestamp>2026-09-16T07:18:05Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0mg400nc</dc:identifier><dc:title>ATLAS Run 1 searches for direct pair production of third-generation squarks at the Large Hadron Collider</dc:title><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Agricola, J</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Alconada Verzini, MJ</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Alkire, SP</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Alvarez Gonzalez, B</dc:creator><dc:creator>Álvarez Piqueras, D</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amadio, BT</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Amaral Coutinho, Y</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Amor Dos Santos, SP</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Aperio Bella, L</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arduh, FA</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:creator>Arnal, V</dc:creator><dc:creator>Arnold, H</dc:creator><dc:creator>Arratia, M</dc:creator><dc:creator>Arslan, O</dc:creator><dc:creator>Artamonov, A</dc:creator><dc:date>2015-10-01</dc:date><dc:description>This paper reviews and extends searches for the direct pair production of the scalar supersymmetric partners of the top and bottom quarks in proton–proton collisions collected by the ATLAS collaboration during the LHC Run 1. Most of the analyses use 20 fb-1$${\mathrm{fb}^{-1}}$$ of collisions at a centre-of-mass energy of s=8$$\sqrt{s} = 8$$ TeV, although in some case an additional 4.7fb-1$$4.7\ {\mathrm{fb}^{-1}}$$ of collision data at s=7$$\sqrt{s}= 7$$ TeV are used. New analyses are introduced to improve the sensitivity to specific regions of the model parameter space. Since no evidence of third-generation squarks is found, exclusion limits are derived by combining several analyses and are presented in both a simplified model framework, assuming simple decay chains, as well as within the context of more elaborate phenomenological supersymmetric models.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>ATLAS Publications</dc:subject><dc:subject>ATLAS Publications</dc:subject><dc:subject>ATLAS Publications</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5102 Atomic</dc:subject><dc:subject>molecular and optical physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0mg400nc</dc:identifier><dc:identifier>https://escholarship.org/content/qt0mg400nc/qt0mg400nc.pdf</dc:identifier><dc:identifier>info:doi/10.1140/epjc/s10052-015-3726-9</dc:identifier><dc:type>article</dc:type><dc:source>European Physical Journal C, vol 75, iss 10</dc:source><dc:coverage>510</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9412s913</identifier><datestamp>2026-09-16T07:17:44Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9412s913</dc:identifier><dc:title>LyaCoLoRe: synthetic datasets for current and future Lyman-α forest BAO surveys</dc:title><dc:creator>Farr, James</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>du Mas des Bourboux, Hélion</dc:creator><dc:creator>Muñoz-Gutiérrez, Andrea</dc:creator><dc:creator>Sánchez, F Javier</dc:creator><dc:creator>Pontzen, Andrew</dc:creator><dc:creator>González-Morales, Alma Xochitl</dc:creator><dc:creator>Alonso, David</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>Doel, Peter</dc:creator><dc:creator>Etourneau, Thomas</dc:creator><dc:creator>Guy, Julien</dc:creator><dc:creator>Le Goff, Jean-Marc</dc:creator><dc:creator>de la Macorra, Axel</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Pérez-Ràfols, Ignasi</dc:creator><dc:creator>Rich, James</dc:creator><dc:creator>Slosar, Anže</dc:creator><dc:creator>Tarle, Gregory</dc:creator><dc:creator>Yutong, Duan</dc:creator><dc:creator>Zhang, Kai</dc:creator><dc:date>2020-03-01</dc:date><dc:description>The statistical power of Lyman-α forest Baryon Acoustic Oscillation (BAO) measurements is set to increase significantly in the coming years as new instruments such as the Dark Energy Spectroscopic Instrument deliver progressively more constraining data. Generating mock datasets for such measurements will be important for validating analysis pipelines and evaluating the effects of systematics. With such studies in mind, we present LyaCoLoRe: a package for producing synthetic Lyman-α forest survey datasets for BAO analyses. LyaCoLoRe transforms initial Gaussian random field skewers into skewers of transmitted flux fraction via a number of fast approximations. In this work we explain the methods of producing mock datasets used in LyaCoLoRe, and then measure correlation functions on a suite of realisations of such data. We demonstrate that we are able to recover the correct BAO signal, as well as large-scale bias parameters similar to literature values. Finally, we briefly describe methods to add further astrophysical effects to our skewers—high column density systems and metal absorbers—which act as potential complications for BAO analyses.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>dark energy experiments</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>red-shift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9412s913</dc:identifier><dc:identifier>https://escholarship.org/content/qt9412s913/qt9412s913.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2020/03/068</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2020, iss 03</dc:source><dc:coverage>068 - 068</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9kg2s7vk</identifier><datestamp>2026-09-16T07:14:21Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9kg2s7vk</dc:identifier><dc:title>A novel DPH5-related diphthamide-deficiency syndrome causing embryonic lethality or profound neurodevelopmental disorder</dc:title><dc:creator>Shankar, Suma P</dc:creator><dc:creator>Grimsrud, Kristin</dc:creator><dc:creator>Lanoue, Louise</dc:creator><dc:creator>Egense, Alena</dc:creator><dc:creator>Willis, Brandon</dc:creator><dc:creator>Hörberg, Johanna</dc:creator><dc:creator>AlAbdi</dc:creator><dc:creator>Mayer, Klaus</dc:creator><dc:creator>Ütkür, Koray</dc:creator><dc:creator>Monaghan, Kristin G</dc:creator><dc:creator>Krier, Joel</dc:creator><dc:creator>Stoler, Joan</dc:creator><dc:creator>Alnemer, Maha</dc:creator><dc:creator>Shankar, Prabhu R</dc:creator><dc:creator>Schaffrath, Raffael</dc:creator><dc:creator>Alkuraya, Fowzan S</dc:creator><dc:creator>Brinkmann, Ulrich</dc:creator><dc:creator>Eriksson, Leif A</dc:creator><dc:creator>Lloyd, Kent</dc:creator><dc:creator>Rauen, Katherine A</dc:creator><dc:creator>Network, Undiagnosed Diseases</dc:creator><dc:creator>Acosta, Maria T</dc:creator><dc:creator>Adam, Margaret</dc:creator><dc:creator>Adams, David R</dc:creator><dc:creator>Alvey, Justin</dc:creator><dc:creator>Amendola, Laura</dc:creator><dc:creator>Andrews, Ashley</dc:creator><dc:creator>Ashley, Euan A</dc:creator><dc:creator>Azamian, Mahshid S</dc:creator><dc:creator>Bacino, Carlos A</dc:creator><dc:creator>Bademci, Guney</dc:creator><dc:creator>Balasubramanyam, Ashok</dc:creator><dc:creator>Baldridge, Dustin</dc:creator><dc:creator>Bale, Jim</dc:creator><dc:creator>Bamshad, Michael</dc:creator><dc:creator>Barbouth, Deborah</dc:creator><dc:creator>Bayrak-Toydemir, Pinar</dc:creator><dc:creator>Beck, Anita</dc:creator><dc:creator>Beggs, Alan H</dc:creator><dc:creator>Behrens, Edward</dc:creator><dc:creator>Bejerano, Gill</dc:creator><dc:creator>Bennet, Jimmy</dc:creator><dc:creator>Berg-Rood, Beverly</dc:creator><dc:creator>Bernstein, Jonathan A</dc:creator><dc:creator>Berry, Gerard T</dc:creator><dc:creator>Bican, Anna</dc:creator><dc:creator>Bivona, Stephanie</dc:creator><dc:creator>Blue, Elizabeth</dc:creator><dc:creator>Bohnsack, John</dc:creator><dc:creator>Bonner, Devon</dc:creator><dc:creator>Botto, Lorenzo</dc:creator><dc:creator>Boyd, Brenna</dc:creator><dc:creator>Briere, Lauren C</dc:creator><dc:creator>Brokamp, Elly</dc:creator><dc:creator>Brown, Gabrielle</dc:creator><dc:creator>Burke, Elizabeth A</dc:creator><dc:creator>Burrage, Lindsay C</dc:creator><dc:creator>Butte, Manish J</dc:creator><dc:creator>Byers, Peter</dc:creator><dc:creator>Byrd, William E</dc:creator><dc:creator>Carey, John</dc:creator><dc:creator>Carrasquillo, Olveen</dc:creator><dc:creator>Cassini, Thomas</dc:creator><dc:creator>Chang, Ta Chen Peter</dc:creator><dc:creator>Chanprasert, Sirisak</dc:creator><dc:creator>Chao, Hsiao-Tuan</dc:creator><dc:creator>Clark, Gary D</dc:creator><dc:creator>Coakley, Terra R</dc:creator><dc:creator>Cobban, Laurel A</dc:creator><dc:creator>Cogan, Joy D</dc:creator><dc:creator>Coggins, Matthew</dc:creator><dc:creator>Cole, F Sessions</dc:creator><dc:creator>Colley, Heather A</dc:creator><dc:creator>Cooper, Cynthia M</dc:creator><dc:creator>Cope, Heidi</dc:creator><dc:creator>Craigen, William J</dc:creator><dc:creator>Crouse, Andrew B</dc:creator><dc:creator>Cunningham, Michael</dc:creator><dc:creator>D'Souza, Precilla</dc:creator><dc:creator>Dai, Hongzheng</dc:creator><dc:creator>Dasari, Surendra</dc:creator><dc:creator>Davis, Joie</dc:creator><dc:creator>Dayal, Jyoti G</dc:creator><dc:creator>Deardorff, Matthew</dc:creator><dc:creator>Dell'Angelica, Esteban C</dc:creator><dc:creator>Dipple, Katrina</dc:creator><dc:creator>Doherty, Daniel</dc:creator><dc:creator>Dorrani, Naghmeh</dc:creator><dc:creator>Doss, Argenia L</dc:creator><dc:creator>Douine, Emilie D</dc:creator><dc:creator>Duncan, Laura</dc:creator><dc:creator>Earl, Dawn</dc:creator><dc:creator>Eckstein, David J</dc:creator><dc:creator>Emrick, Lisa T</dc:creator><dc:creator>Eng, Christine M</dc:creator><dc:creator>Esteves, Cecilia</dc:creator><dc:creator>Falk, Marni</dc:creator><dc:creator>Fernandez, Liliana</dc:creator><dc:creator>Fieg, Elizabeth L</dc:creator><dc:creator>Fisher, Paul G</dc:creator><dc:date>2022-07-01</dc:date><dc:description>PURPOSE: Diphthamide is a post-translationally modified histidine essential for messenger RNA translation and ribosomal protein synthesis. We present evidence for DPH5 as a novel cause of embryonic lethality and profound neurodevelopmental delays (NDDs).
METHODS: Molecular testing was performed using exome or genome sequencing. A targeted Dph5 knockin mouse (C57BL/6Ncrl-Dph5em1Mbp/Mmucd) was created for a DPH5 p.His260Arg homozygous variant identified in 1 family. Adenosine diphosphate-ribosylation assays in DPH5-knockout human and yeast cells and in silico modeling were performed for the identified DPH5 potential pathogenic variants.
RESULTS: DPH5 variants p.His260Arg (homozygous), p.Asn110Ser and p.Arg207Ter (heterozygous), and p.Asn174LysfsTer10 (homozygous) were identified in 3 unrelated families with distinct overlapping craniofacial features, profound NDDs, multisystem abnormalities, and miscarriages. Dph5 p.His260Arg homozygous knockin was embryonically lethal with only 1 subviable mouse exhibiting impaired growth, craniofacial dysmorphology, and multisystem dysfunction recapitulating the human phenotype. Adenosine diphosphate-ribosylation assays showed absent to decreased function in DPH5-knockout human and yeast cells. In silico modeling of the variants showed altered DPH5 structure and disruption of its interaction with eEF2.
CONCLUSION: We provide strong clinical, biochemical, and functional evidence for DPH5 as a novel cause of embryonic lethality or profound NDDs with multisystem involvement and expand diphthamide-deficiency syndromes and ribosomopathies.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3102 Bioinformatics and Computational Biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Biotechnology (rcdc)</dc:subject><dc:subject>Congenital Structural Anomalies (rcdc)</dc:subject><dc:subject>Brain Disorders (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Intellectual and Developmental Disabilities (IDD) (rcdc)</dc:subject><dc:subject>2.1 Biological and endogenous factors (hrcs-rac)</dc:subject><dc:subject>Adenosine Diphosphate (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Histidine (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Methyltransferases (mesh)</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>Mice</dc:subject><dc:subject>Inbred C57BL (mesh)</dc:subject><dc:subject>Neurodevelopmental Disorders (mesh)</dc:subject><dc:subject>Saccharomyces cerevisiae (mesh)</dc:subject><dc:subject>Saccharomyces cerevisiae Proteins (mesh)</dc:subject><dc:subject>Syndrome (mesh)</dc:subject><dc:subject>Nonverbal neurodevelopment delays</dc:subject><dc:subject>Novel gene discovery</dc:subject><dc:subject>Precision animal modeling</dc:subject><dc:subject>Precision genomics</dc:subject><dc:subject>Translational genetics</dc:subject><dc:subject>Undiagnosed Diseases Network</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Mice</dc:subject><dc:subject>Inbred C57BL (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>Saccharomyces cerevisiae (mesh)</dc:subject><dc:subject>Syndrome (mesh)</dc:subject><dc:subject>Methyltransferases (mesh)</dc:subject><dc:subject>Histidine (mesh)</dc:subject><dc:subject>Saccharomyces cerevisiae Proteins (mesh)</dc:subject><dc:subject>Adenosine Diphosphate (mesh)</dc:subject><dc:subject>Neurodevelopmental Disorders (mesh)</dc:subject><dc:subject>Nonverbal neurodevelopment delays</dc:subject><dc:subject>Novel gene discovery</dc:subject><dc:subject>Precision animal modeling</dc:subject><dc:subject>Precision genomics</dc:subject><dc:subject>Translational genetics</dc:subject><dc:subject>Adenosine Diphosphate (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Histidine (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Methyltransferases (mesh)</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>Mice</dc:subject><dc:subject>Inbred C57BL (mesh)</dc:subject><dc:subject>Neurodevelopmental Disorders (mesh)</dc:subject><dc:subject>Saccharomyces cerevisiae (mesh)</dc:subject><dc:subject>Saccharomyces cerevisiae Proteins (mesh)</dc:subject><dc:subject>Syndrome (mesh)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>1103 Clinical Sciences (for)</dc:subject><dc:subject>Genetics &amp; Heredity (science-metrix)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9kg2s7vk</dc:identifier><dc:identifier>https://escholarship.org/content/qt9kg2s7vk/qt9kg2s7vk.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.gim.2022.03.014</dc:identifier><dc:type>article</dc:type><dc:source>Genetics in Medicine, vol 24, iss 7</dc:source><dc:coverage>1567 - 1582</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0kk9m9v8</identifier><datestamp>2026-09-16T07:14:00Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0kk9m9v8</dc:identifier><dc:title>Measurements of the Higgs boson inclusive and differential fiducial cross-sections in the diphoton decay channel with pp collisions at s = 13 TeV with the ATLAS detector</dc:title><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abbott, DC</dc:creator><dc:creator>Abed Abud, A</dc:creator><dc:creator>Abeling, K</dc:creator><dc:creator>Abhayasinghe, DK</dc:creator><dc:creator>Abidi, SH</dc:creator><dc:creator>Aboulhorma, A</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Abusleme Hoffman, AC</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Achkar, B</dc:creator><dc:creator>Adam, L</dc:creator><dc:creator>Adam Bourdarios, C</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adamek, L</dc:creator><dc:creator>Addepalli, SV</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adiguzel, A</dc:creator><dc:creator>Adorni, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Afik, Y</dc:creator><dc:creator>Agapopoulou, C</dc:creator><dc:creator>Agaras, MN</dc:creator><dc:creator>Agarwala, J</dc:creator><dc:creator>Aggarwal, A</dc:creator><dc:creator>Agheorghiesei, C</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Ahmad, A</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Ahmed, WS</dc:creator><dc:creator>Ai, X</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Aizenberg, I</dc:creator><dc:creator>Akatsuka, S</dc:creator><dc:creator>Akbiyik, M</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Al Khoury, K</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albicocco, P</dc:creator><dc:creator>Alconada Verzini, MJ</dc:creator><dc:creator>Alderweireldt, S</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alfonsi, A</dc:creator><dc:creator>Alfonsi, F</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Ali, B</dc:creator><dc:creator>Ali, S</dc:creator><dc:creator>Aliev, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Allaire, C</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Alunno Camelia, E</dc:creator><dc:creator>Alvarez Estevez, M</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amaral Coutinho, Y</dc:creator><dc:creator>Ambler, A</dc:creator><dc:creator>Ambroz, L</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Amor Dos Santos, SP</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amos, KR</dc:creator><dc:creator>Amrouche, CS</dc:creator><dc:creator>Ananiev, V</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Andrean, SY</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antel, C</dc:creator><dc:creator>Anthony, MT</dc:creator><dc:creator>Antipov, E</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antrim, DJA</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Aparisi Pozo, JA</dc:creator><dc:creator>Aparo, MA</dc:creator><dc:creator>Aperio Bella, L</dc:creator><dc:creator>Aranzabal, N</dc:creator><dc:creator>Araujo Ferraz, V</dc:creator><dc:creator>Arcangeletti, C</dc:creator><dc:date>2022-08-02</dc:date><dc:description>A measurement of inclusive and differential fiducial cross-sections for the production of the Higgs boson decaying into two photons is performed using 139 fb−1 of proton-proton collision data recorded at s$$ \sqrt{s} $$ = 13 TeV by the ATLAS experiment at the Large Hadron Collider. The inclusive cross-section times branching ratio, in a fiducial region closely matching the experimental selection, is measured to be 67 ± 6 fb, which is in agreement with the state-of-the-art Standard Model prediction of 64 ± 4 fb. Extrapolating this result to the full phase space and correcting for the branching ratio, the total cross-section for Higgs boson production is estimated to be 58 ± 6 pb. In addition, the cross-sections in four fiducial regions sensitive to various Higgs boson production modes and differential cross-sections as a function of either one or two of several observables are measured. All the measurements are found to be in agreement with the Standard Model predictions. The measured transverse momentum distribution of the Higgs boson is used as an indirect probe of the Yukawa coupling of the Higgs boson to the bottom and charm quarks. In addition, five differential cross-section measurements are used to constrain anomalous Higgs boson couplings to vector bosons in the Standard Model effective field theory framework.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Hadron-Hadron Scattering</dc:subject><dc:subject>Higgs Physics</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>4902 Mathematical physics (for-2020)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0kk9m9v8</dc:identifier><dc:identifier>https://escholarship.org/content/qt0kk9m9v8/qt0kk9m9v8.pdf</dc:identifier><dc:identifier>info:doi/10.1007/jhep08(2022)027</dc:identifier><dc:type>article</dc:type><dc:source>Journal of High Energy Physics, vol 2022, iss 8</dc:source><dc:coverage>27</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4zg4j855</identifier><datestamp>2026-09-16T07:09:46Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4zg4j855</dc:identifier><dc:title>Summary of the ATLAS experiment’s sensitivity to supersymmetry after LHC Run 1 — interpreted in the phenomenological MSSM</dc:title><dc:creator>The ATLAS collaboration</dc:creator><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Agricola, J</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Alconada Verzini, MJ</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Alkire, SP</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Alvarez Gonzalez, B</dc:creator><dc:creator>Álvarez Piqueras, D</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amadio, BT</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Amaral Coutinho, Y</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Amor Dos Santos, SP</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Aperio Bella, L</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arduh, FA</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:creator>Arnold, H</dc:creator><dc:creator>Arratia, M</dc:creator><dc:creator>Arslan, O</dc:creator><dc:creator>Artamonov, A</dc:creator><dc:date>2015-10-01</dc:date><dc:description>A summary of the constraints from the ATLAS experiment on R-parity-conserving supersymmetry is presented. Results from 22 separate ATLAS searches are considered, each based on analysis of up to 20.3 fb−1 of proton-proton collision data at centre-of-mass energies of s=7$$ \sqrt{s}=7 $$ and 8 TeV at the Large Hadron Collider. The results are interpreted in the context of the 19-parameter phenomenological minimal supersymmetric standard model, in which the lightest supersymmetric particle is a neutralino, taking into account constraints from previous precision electroweak and flavour measurements as well as from dark matter related measurements. The results are presented in terms of constraints on supersymmetric particle masses and are compared to limits from simplified models. The impact of ATLAS searches on parameters such as the dark matter relic density, the couplings of the observed Higgs boson, and the degree of electroweak fine-tuning is also shown. Spectra for surviving supersymmetry model points with low fine-tunings are presented.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Hadron-Hadron Scattering</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>4902 Mathematical physics (for-2020)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4zg4j855</dc:identifier><dc:identifier>https://escholarship.org/content/qt4zg4j855/qt4zg4j855.pdf</dc:identifier><dc:identifier>info:doi/10.1007/jhep10(2015)134</dc:identifier><dc:type>article</dc:type><dc:source>Journal of High Energy Physics, vol 2015, iss 10</dc:source><dc:coverage>134</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5554g79p</identifier><datestamp>2026-09-16T07:09:30Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5554g79p</dc:identifier><dc:title>Z boson production in p+Pb collisions at sNN=5.02 TeV measured with the ATLAS detector</dc:title><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Agricola, J</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Verzini, MJ Alconada</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Alkire, SP</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Gonzalez, B Alvarez</dc:creator><dc:creator>Piqueras, D Álvarez</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amadio, BT</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Coutinho, Y Amaral</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Dos Santos, SP Amor</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Bella, L Aperio</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arduh, FA</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:creator>Arnal, V</dc:creator><dc:creator>Arnold, H</dc:creator><dc:creator>Arratia, M</dc:creator><dc:creator>Arslan, O</dc:creator><dc:creator>Artamonov, A</dc:creator><dc:date>2015-10-01</dc:date><dc:description>The ATLAS Collaboration measures the inclusive production of Z bosons via their decays into electron and muon pairs in p+Pb collisions at sNN=5.02TeV at the Large Hadron Collider. The measurements are made using data corresponding to integrated luminosities of 29.4 and 28.1 nb−1 for Z→ee and Z→μμ, respectively. The results from the two channels are consistent and combined to obtain a cross section times the Z→ℓℓ branching ratio, integrated over the rapidity region |yZ*|&amp;lt;3.5, of 139.8±4.8(statistical)±6.2(systematic)±3.8 (luminosity) nb. Differential cross sections are presented as functions of the Z boson rapidity and transverse momentum and compared with models based on parton distributions both with and without nuclear corrections. The centrality dependence of Z boson production in p+Pb collisions is measured and analyzed within the framework of a standard Glauber model and the model's extension for fluctuations of the underlying nucleon-nucleon scattering cross section.</dc:description><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>nucl-ex</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5554g79p</dc:identifier><dc:identifier>https://escholarship.org/content/qt5554g79p/qt5554g79p.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevc.92.044915</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review C, vol 92, iss 4</dc:source><dc:coverage>044915</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6jr842t9</identifier><datestamp>2026-09-16T07:09:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6jr842t9</dc:identifier><dc:title>Study of (W/Z)H production and Higgs boson couplings using H→ W W∗ decays with the ATLAS detector</dc:title><dc:creator>The ATLAS collaboration</dc:creator><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimoto, G</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Alconada Verzini, MJ</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Alkire, SP</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Alvarez Gonzalez, B</dc:creator><dc:creator>Álvarez Piqueras, D</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amadio, BT</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Amaral Coutinho, Y</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Amor Dos Santos, SP</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Aperio Bella, L</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arduh, FA</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:creator>Arnal, V</dc:creator><dc:creator>Arnold, H</dc:creator><dc:creator>Arratia, M</dc:creator><dc:creator>Arslan, O</dc:creator><dc:date>2015-08-01</dc:date><dc:description>A search for Higgs boson production in association with a W or Z boson, in the H→ W W∗ decay channel, is performed with a data sample collected with the ATLAS detector at the LHC in proton-proton collisions at centre-of-mass energies s=7$$ \sqrt{s}=7 $$ TeV and 8 TeV, corresponding to integrated luminosities of 4.5 fb−1 and 20.3 fb−1, respectively. The WH production mode is studied in two-lepton and three-lepton final states, while two- lepton and four-lepton final states are used to search for the ZH production mode. The observed significance, for the combined W H and ZH production, is 2.5 standard deviations while a significance of 0.9 standard deviations is expected in the Standard Model Higgs boson hypothesis. The ratio of the combined W H and ZH signal yield to the Standard Model expectation, μV H , is found to be μV&amp;nbsp;H = 3.0− 1.1+ 1.3(stat.)− 0.7+ 1.0(sys.) for the Higgs boson mass of 125.36 GeV. The W H and ZH production modes are also combined with the gluon fusion and vector boson fusion production modes studied in the H → W W∗ → ℓνℓν decay channel, resulting in an overall observed significance of 6.5 standard deviations and μggF + VBF + VH = 1. 16− 0.15+ 0.16(stat.)− 0.15+ 0.18(sys.). The results are interpreted in terms of scaling factors of the Higgs boson couplings to vector bosons (κV ) and fermions (κF ); the combined results are: |κV| = 1.06− 0.10+ 0.10, |κF| = 0. 85− 0.20+ 0.26.</dc:description><dc:subject>Hadron-Hadron Scattering</dc:subject><dc:subject>Higgs physics</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>4902 Mathematical physics (for-2020)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6jr842t9</dc:identifier><dc:identifier>https://escholarship.org/content/qt6jr842t9/qt6jr842t9.pdf</dc:identifier><dc:identifier>info:doi/10.1007/jhep08(2015)137</dc:identifier><dc:type>article</dc:type><dc:source>Journal of High Energy Physics, vol 2015, iss 8</dc:source><dc:coverage>137</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4j20m6kr</identifier><datestamp>2026-09-16T07:08:36Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4j20m6kr</dc:identifier><dc:title>The East River, Colorado, Watershed: A Mountainous Community Testbed for Improving Predictive Understanding of Multiscale Hydrological–Biogeochemical Dynamics</dc:title><dc:creator>Hubbard, Susan S</dc:creator><dc:creator>Williams, Kenneth Hurst</dc:creator><dc:creator>Agarwal, Deb</dc:creator><dc:creator>Banfield, Jillian</dc:creator><dc:creator>Beller, Harry</dc:creator><dc:creator>Bouskill, Nicholas</dc:creator><dc:creator>Brodie, Eoin</dc:creator><dc:creator>Carroll, Rosemary</dc:creator><dc:creator>Dafflon, Baptiste</dc:creator><dc:creator>Dwivedi, Dipankar</dc:creator><dc:creator>Falco, Nicola</dc:creator><dc:creator>Faybishenko, Boris</dc:creator><dc:creator>Maxwell, Reed</dc:creator><dc:creator>Nico, Peter</dc:creator><dc:creator>Steefel, Carl</dc:creator><dc:creator>Steltzer, Heidi</dc:creator><dc:creator>Tokunaga, Tetsu</dc:creator><dc:creator>Tran, Phuong A</dc:creator><dc:creator>Wainwright, Haruko</dc:creator><dc:creator>Varadharajan, Charuleka</dc:creator><dc:date>2018-01-01</dc:date><dc:description>Core Ideas     Development of a 300‐km 2 mountainous headwater testbed began in 2016 in the East River.    The testbed can be used to explore how watershed changes impact downgradient water availability and quality.   System‐of‐system, scale‐adaptive approaches can potentially improve watershed dynamics simulation.   We have new approaches to monitor and simulate water partitioning and system responses.   The East River watershed has been developed as a “community” testbed.     Extreme weather, fires, and land use and climate change are significantly reshaping interactions within watersheds throughout the world. Although hydrological–biogeochemical interactions within watersheds can impact many services valued by society, uncertainty associated with predicting hydrology‐driven biogeochemical watershed dynamics remains high. With an aim to reduce this uncertainty, an approximately 300‐km 2 mountainous headwater observatory has been developed at the East River, CO, watershed of the Upper Colorado River Basin. The site is being used as a testbed for the Department of Energy supported Watershed Function Project and collaborative efforts. Building on insights gained from research at the “sister” Rifle, CO, site, coordinated studies are underway at the East River site to gain a predictive understanding of how the mountainous watershed retains and releases water, nutrients, carbon, and metals. In particular, the project is exploring how early snowmelt, drought, and other disturbances influence hydrological–biogeochemical watershed dynamics at seasonal to decadal timescales. A system‐of‐systems perspective and a scale‐adaptive simulation approach, involving the combined use of archetypal watershed subsystem “intensive sites” are being tested at the site to inform aggregated watershed predictions of downgradient exports. Complementing intensive site hydrological, geochemical, geophysical, microbiological, geological, and vegetation datasets are long‐term, distributed measurement stations and specialized experimental and observational campaigns. Several recent research advances provide insights about the intensive sites as well as aggregated watershed behavior. The East River “community testbed” is currently hosting scientists from more than 30 institutions to advance mountainous watershed methods and understanding.</dc:description><dc:subject>3707 Hydrology (for-2020)</dc:subject><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>0406 Physical Geography and Environmental Geoscience (for)</dc:subject><dc:subject>0503 Soil Sciences (for)</dc:subject><dc:subject>0703 Crop and Pasture Production (for)</dc:subject><dc:subject>Environmental Engineering (science-metrix)</dc:subject><dc:subject>3707 Hydrology (for-2020)</dc:subject><dc:subject>4106 Soil sciences (for-2020)</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4j20m6kr</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.2136/vzj2018.03.0061</dc:identifier><dc:type>article</dc:type><dc:source>Vadose Zone Journal, vol 17, iss 1</dc:source><dc:coverage>1 - 25</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7kr074xs</identifier><datestamp>2026-09-16T07:08:31Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7kr074xs</dc:identifier><dc:title>Inclusive J/ψ production at forward and backward rapidity in p-Pb collisions at sNN=8.16 TeV</dc:title><dc:creator>The ALICE collaboration</dc:creator><dc:creator>Acharya, S</dc:creator><dc:creator>Acosta, F T-</dc:creator><dc:creator>Adamová, D</dc:creator><dc:creator>Adolfsson, J</dc:creator><dc:creator>Aggarwal, MM</dc:creator><dc:creator>Aglieri Rinella, G</dc:creator><dc:creator>Agnello, M</dc:creator><dc:creator>Agrawal, N</dc:creator><dc:creator>Ahammed, Z</dc:creator><dc:creator>Ahn, SU</dc:creator><dc:creator>Aiola, S</dc:creator><dc:creator>Akindinov, A</dc:creator><dc:creator>Al-Turany, M</dc:creator><dc:creator>Alam, SN</dc:creator><dc:creator>Albuquerque, DSD</dc:creator><dc:creator>Aleksandrov, D</dc:creator><dc:creator>Alessandro, B</dc:creator><dc:creator>Alfaro Molina, R</dc:creator><dc:creator>Ali, Y</dc:creator><dc:creator>Alici, A</dc:creator><dc:creator>Alkin, A</dc:creator><dc:creator>Alme, J</dc:creator><dc:creator>Alt, T</dc:creator><dc:creator>Altenkamper, L</dc:creator><dc:creator>Altsybeev, I</dc:creator><dc:creator>Andrei, C</dc:creator><dc:creator>Andreou, D</dc:creator><dc:creator>Andrews, HA</dc:creator><dc:creator>Andronic, A</dc:creator><dc:creator>Angeletti, M</dc:creator><dc:creator>Anguelov, V</dc:creator><dc:creator>Anson, C</dc:creator><dc:creator>Antičić, T</dc:creator><dc:creator>Antinori, F</dc:creator><dc:creator>Antonioli, P</dc:creator><dc:creator>Anwar, R</dc:creator><dc:creator>Apadula, N</dc:creator><dc:creator>Aphecetche, L</dc:creator><dc:creator>Appelshäuser, H</dc:creator><dc:creator>Arcelli, S</dc:creator><dc:creator>Arnaldi, R</dc:creator><dc:creator>Arnold, OW</dc:creator><dc:creator>Arsene, IC</dc:creator><dc:creator>Arslandok, M</dc:creator><dc:creator>Audurier, B</dc:creator><dc:creator>Augustinus, A</dc:creator><dc:creator>Averbeck, R</dc:creator><dc:creator>Azmi, MD</dc:creator><dc:creator>Badalà, A</dc:creator><dc:creator>Baek, YW</dc:creator><dc:creator>Bagnasco, S</dc:creator><dc:creator>Bailhache, R</dc:creator><dc:creator>Bala, R</dc:creator><dc:creator>Baldisseri, A</dc:creator><dc:creator>Ball, M</dc:creator><dc:creator>Baral, RC</dc:creator><dc:creator>Barbano, AM</dc:creator><dc:creator>Barbera, R</dc:creator><dc:creator>Barile, F</dc:creator><dc:creator>Barioglio, L</dc:creator><dc:creator>Barnaföldi, GG</dc:creator><dc:creator>Barnby, LS</dc:creator><dc:creator>Barret, V</dc:creator><dc:creator>Bartalini, P</dc:creator><dc:creator>Barth, K</dc:creator><dc:creator>Bartsch, E</dc:creator><dc:creator>Bastid, N</dc:creator><dc:creator>Basu, S</dc:creator><dc:creator>Batigne, G</dc:creator><dc:creator>Batyunya, B</dc:creator><dc:creator>Batzing, PC</dc:creator><dc:creator>Bazo Alba, JL</dc:creator><dc:creator>Bearden, IG</dc:creator><dc:creator>Beck, H</dc:creator><dc:creator>Bedda, C</dc:creator><dc:creator>Behera, NK</dc:creator><dc:creator>Belikov, I</dc:creator><dc:creator>Bellini, F</dc:creator><dc:creator>Bello Martinez, H</dc:creator><dc:creator>Bellwied, R</dc:creator><dc:creator>Beltran, LGE</dc:creator><dc:creator>Belyaev, V</dc:creator><dc:creator>Bencedi, G</dc:creator><dc:creator>Beole, S</dc:creator><dc:creator>Bercuci, A</dc:creator><dc:creator>Berdnikov, Y</dc:creator><dc:creator>Berenyi, D</dc:creator><dc:creator>Bertens, RA</dc:creator><dc:creator>Berzano, D</dc:creator><dc:creator>Betev, L</dc:creator><dc:creator>Bhaduri, PP</dc:creator><dc:creator>Bhasin, A</dc:creator><dc:creator>Bhat, IR</dc:creator><dc:creator>Bhatt, H</dc:creator><dc:creator>Bhattacharjee, B</dc:creator><dc:creator>Bhom, J</dc:creator><dc:creator>Bianchi, A</dc:creator><dc:creator>Bianchi, L</dc:creator><dc:creator>Bianchi, N</dc:creator><dc:date>2018-07-01</dc:date><dc:description>Inclusive J/ψ production is studied in p-Pb interactions at a centre-of-mass energy per nucleon-nucleon collision sNN=8.16$$ \sqrt{s_{\mathrm{NN}}}=8.16 $$ TeV, using the ALICE detector at the CERN LHC. The J/ψ meson is reconstructed, via its decay to a muon pair, in the centre-of-mass rapidity intervals 2.03 &amp;lt; ycms &amp;lt; 3.53 and −4.46 &amp;lt; ycms &amp;lt; −2.96, where positive and negative ycms refer to the p-going and Pb-going direction, respectively. The transverse momentum coverage is pT &amp;lt; 20 GeV/c. In this paper, ycms- and pT-differential cross sections for inclusive J/ψ production are presented, and the corresponding nuclear modification factors RpPb are shown. Forward results show a suppression of the J/ψ yield with respect to pp collisions, concentrated in the region pT ≲ 5 GeV/c. At backward rapidity no significant suppression is observed. The results are compared to previous measurements by ALICE in p-Pb collisions at sNN=5.02$$ \sqrt{s_{\mathrm{NN}}}=5.02 $$ TeV and to theoretical calculations. Finally, the ratios RFB between forward- and backward-ycmsRpPb values are shown and discussed.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Heavy Ion Experiments</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>4902 Mathematical physics (for-2020)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7kr074xs</dc:identifier><dc:identifier>https://escholarship.org/content/qt7kr074xs/qt7kr074xs.pdf</dc:identifier><dc:identifier>info:doi/10.1007/jhep07(2018)160</dc:identifier><dc:type>article</dc:type><dc:source>Journal of High Energy Physics, vol 2018, iss 7</dc:source><dc:coverage>160</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt88q1z652</identifier><datestamp>2026-09-16T07:08:24Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt88q1z652</dc:identifier><dc:title>Complexation and Redox Buffering of Iron(II) by Dissolved Organic Matter</dc:title><dc:creator>Daugherty, Ellen E</dc:creator><dc:creator>Gilbert, Benjamin</dc:creator><dc:creator>Nico, Peter S</dc:creator><dc:creator>Borch, Thomas</dc:creator><dc:date>2017-10-03</dc:date><dc:description>Iron (Fe) bioavailability depends upon its solubility and oxidation state, which are strongly influenced by complexation with natural organic matter (NOM). Despite observations of Fe(II)-NOM associations under conditions favorable for Fe oxidation, the molecular mechanisms by which NOM influences Fe(II) oxidation remain poorly understood. In this study, we used X-ray absorption spectroscopy to determine the coordination environment of Fe(II) associated with NOM (as-received and chemically reduced) at pH 7, and investigated the effect of NOM complexation on Fe(II) redox stability. Linear combination fitting of extended X-ray absorption fine structure (EXAFS) data using reference organic ligands demonstrated that Fe(II) was complexed primarily by carboxyl functional groups in reduced NOM. Functional groups more likely to preserve Fe(II) represent much smaller fractions of NOM-bound Fe(II). Fe(II) added to anoxic solutions of as-received NOM oxidized to Fe(III) and remained organically complexed. Iron oxidation experiments revealed that the presence of reduced NOM limited Fe(II) oxidation, with over 50% of initial Fe(II) remaining after 4 h. These results suggest reduced NOM may preserve Fe(II) by functioning both as redox buffer and complexant, which may help explain the presence of Fe(II) in oxic circumneutral waters.</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>3701 Atmospheric Sciences (for-2020)</dc:subject><dc:subject>3703 Geochemistry (for-2020)</dc:subject><dc:subject>34 Chemical Sciences (for-2020)</dc:subject><dc:subject>Buffers (mesh)</dc:subject><dc:subject>Ferrous Compounds (mesh)</dc:subject><dc:subject>Iron (mesh)</dc:subject><dc:subject>Oxidation-Reduction (mesh)</dc:subject><dc:subject>X-Ray Absorption Spectroscopy (mesh)</dc:subject><dc:subject>Iron (mesh)</dc:subject><dc:subject>Ferrous Compounds (mesh)</dc:subject><dc:subject>Buffers (mesh)</dc:subject><dc:subject>Oxidation-Reduction (mesh)</dc:subject><dc:subject>X-Ray Absorption Spectroscopy (mesh)</dc:subject><dc:subject>Buffers (mesh)</dc:subject><dc:subject>Ferrous Compounds (mesh)</dc:subject><dc:subject>Iron (mesh)</dc:subject><dc:subject>Oxidation-Reduction (mesh)</dc:subject><dc:subject>X-Ray Absorption Spectroscopy (mesh)</dc:subject><dc:subject>Environmental Sciences (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/88q1z652</dc:identifier><dc:identifier>https://escholarship.org/content/qt88q1z652/qt88q1z652.pdf</dc:identifier><dc:identifier>info:doi/10.1021/acs.est.7b03152</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Science and Technology, vol 51, iss 19</dc:source><dc:coverage>11096 - 11104</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9h16m8gk</identifier><datestamp>2026-09-16T07:08:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9h16m8gk</dc:identifier><dc:title>The Relative Importance of Saturated Silica Sand Interfacial and Pore Fluid Geochemistry on the Spectral Induced Polarization Response</dc:title><dc:creator>Peruzzo, Luca</dc:creator><dc:creator>Schmutz, Myriam</dc:creator><dc:creator>Franceschi, Michel</dc:creator><dc:creator>Wu, Yuxin</dc:creator><dc:creator>Hubbard, Susan S</dc:creator><dc:date>2018-05-01</dc:date><dc:description>Abstract  Adsorption at the solid‐pore fluid interface is a key mechanism controlling the mobility of nutrients and contaminants in subsurface soils and sediments. The spectral induced polarization (SIP) method has been shown to be sensitive to the quantity and type of adsorbed ions. Extending previous results, we investigated the relevance of pH, solution conductivity, and ion type on the SIP response of saturated silica sand. We also performed adsorption experiments to evaluate whether adsorption plays a relevant role on the effect of saturating solution conductivity and pH. Given their environmental relevance and different electrochemical characteristics, we focused on exploring the influence of Cu 2+ and Na + adsorption on the SIP signature. The adsorption results confirm the expected and modeled pH influence on the adsorption of both Cu 2+ and Na + . The measured quadrature conductivity spectra indicate that pH and solution conductivity control the electrical double layer electrochemical state and its capacitive behavior. On the contrary, no appreciable SIP signal changes are associated with ion substitution. The adsorption experiments highlight low values of site occupancy for Na and Cu, which suggests that the effects of pH and fluid conductivity are unrelated to their control on the ion adsorption. We interpret the solution conductivity as a proxy for ionic strength. The relative importance of pH and solution conductivity over ion type helps to further constrain the interpretation of SIP results in field geochemical and biogeochemical characterization and monitoring. 
Key Points    Quadrature conductivity decreases with increasing solution conductivity and/or decreasing pH   No appreciable differences in spectral induced polarization signatures are associated with changes in the Cu/Na concentration ratios   The effects of pH and fluid conductivity on the induced polarization response appear to be unrelated to their control on the adsorption</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>3706 Geophysics (for-2020)</dc:subject><dc:subject>SIP</dc:subject><dc:subject>adsorption</dc:subject><dc:subject>silica</dc:subject><dc:subject>copper</dc:subject><dc:subject>sodium</dc:subject><dc:subject>quadrature conductivity</dc:subject><dc:subject>0404 Geophysics (for)</dc:subject><dc:subject>3706 Geophysics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9h16m8gk</dc:identifier><dc:identifier>https://escholarship.org/content/qt9h16m8gk/qt9h16m8gk.pdf</dc:identifier><dc:identifier>info:doi/10.1029/2017jg004364</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Geophysical Research Biogeosciences, vol 123, iss 5</dc:source><dc:coverage>1702 - 1718</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1nf13338</identifier><datestamp>2026-09-16T07:08:14Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1nf13338</dc:identifier><dc:title>Commemorating Dr. Gudmundur “Bo” Bodvarsson (1951–2006), a Leader of the Deep Unsaturated Flow and Transport Investigations</dc:title><dc:creator>Tsang, Chin-Fu</dc:creator><dc:creator>Lippmann, Marcelo</dc:creator><dc:creator>Dobson, Patrick</dc:creator><dc:creator>Tsang, Yvonne</dc:creator><dc:creator>Faybishenko, Boris</dc:creator><dc:creator>Benson, Sally</dc:creator><dc:creator>Birkholzer, Jens</dc:creator><dc:creator>Finsterle, Stefan</dc:creator><dc:creator>Hawkes, Daniel</dc:creator><dc:creator>Hubbard, Susan</dc:creator><dc:creator>Kneafsey, Timothy</dc:creator><dc:creator>Liu, Hui-Hai</dc:creator><dc:creator>Oldenburg, Curtis M</dc:creator><dc:creator>Pruess, Karsten</dc:creator><dc:creator>Sonnenthal, Eric</dc:creator><dc:creator>Villavert, Maryann</dc:creator><dc:creator>Wang, Joseph</dc:creator><dc:creator>Wu, Yu-Shu</dc:creator><dc:creator>Zimmerman, Robert W</dc:creator><dc:date>2018-01-01</dc:date><dc:description>The Special Issue “Water and Solute Transport in Vadose Zone” in the journal Water is dedicated to the memory of Dr. Gudmundur “Bo” Bodvarsson, the former director of the Earth Sciences Division of Lawrence Berkeley National Laboratory (http://eesa.lbl.gov/profiles/gudmundur-bo-sbodvarsson/).[...]</dc:description><dc:subject>3707 Hydrology (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>4106 Soil Sciences (for-2020)</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1nf13338</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.3390/w10010018</dc:identifier><dc:type>article</dc:type><dc:source>Water, vol 10, iss 1</dc:source><dc:coverage>18</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4693w533</identifier><datestamp>2026-09-16T07:08:07Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4693w533</dc:identifier><dc:title>Erratum to: Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at s=8TeV with the ATLAS detector</dc:title><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdel Khalek, S</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abi, B</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Agustoni, M</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimoto, G</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Alconada Verzini, MJ</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexandre, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allison, LJ</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Alvarez Gonzalez, B</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Amaral Coutinho, Y</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Amor Dos Santos, SP</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Anduaga, XS</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Aperio Bella, L</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arduh, FA</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:creator>Arnal, V</dc:creator><dc:creator>Arnold, H</dc:creator><dc:creator>Arratia, M</dc:creator><dc:creator>Arslan, O</dc:creator><dc:date>2015-09-01</dc:date><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5102 Atomic</dc:subject><dc:subject>molecular and optical physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4693w533</dc:identifier><dc:identifier>https://escholarship.org/content/qt4693w533/qt4693w533.pdf</dc:identifier><dc:identifier>info:doi/10.1140/epjc/s10052-015-3639-7</dc:identifier><dc:type>article</dc:type><dc:source>European Physical Journal C, vol 75, iss 9</dc:source><dc:coverage>408</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6z60f62r</identifier><datestamp>2026-09-16T07:07:38Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6z60f62r</dc:identifier><dc:title>Search for new resonances in Wγ and Zγ final states in pp collisions at s=8 TeV with the ATLAS detector</dc:title><dc:creator>Collaboration, ATLAS</dc:creator><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Khalek, S Abdel</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abi, B</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Agustoni, M</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimoto, G</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Verzini, MJ Alconada</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexandre, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allison, LJ</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Almond, J</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Gonzalez, B Alvarez</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Coutinho, Y Amaral</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Dos Santos, SP Amor</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Anduaga, XS</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonaki, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Bella, L Aperio</dc:creator><dc:creator>Apolle, R</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Aracena, I</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:date>2014-11-01</dc:date><dc:description>This Letter presents a search for new resonances decaying to final states with a vector boson produced in association with a high transverse momentum photon, Vγ, with V=W(→ℓν) or Z(→ℓ+ℓ−), where ℓ=e or μ. The measurements use 20.3 fb−1 of proton–proton collision data at a center-of-mass energy of s=8&amp;nbsp;TeV recorded with the ATLAS detector. No deviations from the Standard Model expectations are found, and production cross section limits are set at 95% confidence level. Masses of the hypothetical aT and ωT states of a benchmark Low Scale Technicolor model are excluded in the ranges [275,960] GeV and [200,700]∪[750,890] GeV, respectively. Limits at 95% confidence level on the production cross section of a singlet scalar resonance decaying to Zγ final states have also been obtained for masses below 1180 GeV.</dc:description><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6z60f62r</dc:identifier><dc:identifier>https://escholarship.org/content/qt6z60f62r/qt6z60f62r.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.physletb.2014.10.002</dc:identifier><dc:type>article</dc:type><dc:source>Physics Letters B, vol 738</dc:source><dc:coverage>428 - 447</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4z30n0xg</identifier><datestamp>2026-09-16T07:07:27Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4z30n0xg</dc:identifier><dc:title>How Proton Incorporation Reshapes Lattice Dynamics In BaSnO3‐Type Proton Conductors</dc:title><dc:creator>Braun, Artur</dc:creator><dc:creator>Rulev, Alexey</dc:creator><dc:creator>Nagasawa, Nobumoto</dc:creator><dc:creator>Wang, Hongxin</dc:creator><dc:creator>Bendikov, Tatyana</dc:creator><dc:creator>Pomjakushin, Vladimir</dc:creator><dc:creator>Kunz, Martin</dc:creator><dc:creator>Yoda, Yoshitaka</dc:creator><dc:creator>Chen, Qianli</dc:creator><dc:creator>Cramer, Stephen P</dc:creator><dc:date>2026-06-15</dc:date><dc:description>Proton conduction in acceptor-doped perovskites is fundamentally a vibronic process: mobile  and  do not move independently, but dynamically co-vibrate with the surrounding oxygen-metal framework. Direct experimental evidence for this behavior is presented using in situ  nuclear resonance vibrational spectroscopy (NRVS) on hydrated, deuterated, and dry  . Hydration induces systematic redistributions in the Sn-projected phonon density of states (PDOS), including an upshift of the first spectral moment by about 0.4&amp;nbsp;meV, indicating a stiffening of the extended Sn-O&amp;nbsp;network. H/D isotopic substitution leaves the Sn-projected PDOS largely unchanged, with only subtle isotope-dependent spectral reweighting, demonstrating that protonic degrees of freedom are not localized oscillators but are embedded in collective lattice modes. These results are rationalized using a classical coupled proton-phonon oscillator model that links the observed PDOS variations to changes in effective force constants and vibrational mass terms. The model captures how  and  participate in cooperative lattice dynamics rather than forming isolated OH/OD&amp;nbsp;entities. Overall, NRVS probes proton-lattice coupling in ceramic proton conductors and quantitatively describes how protonic defects modulate host lattice dynamics to enable phonon-assisted long-range proton&amp;nbsp;transport.</dc:description><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>5104 Condensed Matter Physics (for-2020)</dc:subject><dc:subject>NRVS</dc:subject><dc:subject>lattice dynamics</dc:subject><dc:subject>phonon dos</dc:subject><dc:subject>proton conductor</dc:subject><dc:subject>proton–phonon coupling</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4z30n0xg</dc:identifier><dc:identifier>https://escholarship.org/content/qt4z30n0xg/qt4z30n0xg.pdf</dc:identifier><dc:identifier>info:doi/10.1002/advs.76065</dc:identifier><dc:type>article</dc:type><dc:source>Advanced Science, vol 13, iss 50</dc:source><dc:coverage>e76065</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt92s8348k</identifier><datestamp>2026-09-16T07:04:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt92s8348k</dc:identifier><dc:title>Search for the Standard Model Higgs boson decay to μ+μ− with the ATLAS detector</dc:title><dc:creator>Collaboration, ATLAS</dc:creator><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Khalek, S Abdel</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abi, B</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Agustoni, M</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimoto, G</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Verzini, MJ Alconada</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexandre, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allison, LJ</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Almond, J</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Gonzalez, B Alvarez</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Coutinho, Y Amaral</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Dos Santos, SP Amor</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Anduaga, XS</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonaki, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Bella, L Aperio</dc:creator><dc:creator>Apolle, R</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Aracena, I</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:date>2014-11-01</dc:date><dc:description>A search is reported for Higgs boson decay to μ+μ− using data with an integrated luminosity of 24.8 fb−1collected with the ATLAS detector in pp collisions at s=7and8 TeV at the CERN Large Hadron Collider. The observed dimuon invariant mass distribution is consistent with the Standard Model background-only hypothesis in the 120–150 GeV search range. For a Higgs boson with a mass of 125.5 GeV, the observed (expected) upper limit at the 95% confidence level is 7.0 (7.2) times the Standard Model expectation. This corresponds to an upper limit on the branching ratio BR(H→μ+μ−) of 1.5×10−3.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/92s8348k</dc:identifier><dc:identifier>https://escholarship.org/content/qt92s8348k/qt92s8348k.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.physletb.2014.09.008</dc:identifier><dc:type>article</dc:type><dc:source>Physics Letters B, vol 738, iss 1</dc:source><dc:coverage>68 - 86</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2n37d0bv</identifier><datestamp>2026-09-16T07:04:04Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2n37d0bv</dc:identifier><dc:title>Measurement of differential production cross-sections for a Z boson in association with b-jets in 7 TeV proton-proton collisions with the ATLAS detector</dc:title><dc:creator>The ATLAS collaboration</dc:creator><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdel Khalek, S</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abi, B</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Agustoni, M</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimoto, G</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Alconada Verzini, MJ</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexandre, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allison, LJ</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Almond, J</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Alvarez Gonzalez, B</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Amaral Coutinho, Y</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Amor Dos Santos, SP</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Anduaga, XS</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonaki, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Aperio Bella, L</dc:creator><dc:creator>Apolle, R</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Aracena, I</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:date>2014-10-01</dc:date><dc:description>Measurements of differential production cross-sections of a Z boson in association with b-jets in pp collisions at s=7$$ \sqrt{s}=7 $$ TeV are reported. The data analysed correspond to an integrated luminosity of 4.6 fb−1 recorded with the ATLAS detector at the Large Hadron Collider. Particle-level cross-sections are determined for events with a Z boson decaying into an electron or muon pair, and containing b-jets. For events with at least one b-jet, the cross-section is presented as a function of the Z boson transverse momentum and rapidity, together with the inclusive b-jet cross-section as a function of b-jet transverse momentum, rapidity and angular separations between the b-jet and the Z boson. For events with at least two b-jets, the cross-section is determined as a function of the invariant mass and angular separation of the two highest transverse momentum b-jets, and as a function of the Z boson transverse momentum and rapidity. Results are compared to leading-order and next-to-leading-order perturbative QCD calculations.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>4902 Mathematical Physics (for-2020)</dc:subject><dc:subject>49 Mathematical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Electroweak interaction</dc:subject><dc:subject>Hadron-Hadron Scattering</dc:subject><dc:subject>QCD</dc:subject><dc:subject>Heavy quark production</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>4902 Mathematical physics (for-2020)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2n37d0bv</dc:identifier><dc:identifier>https://escholarship.org/content/qt2n37d0bv/qt2n37d0bv.pdf</dc:identifier><dc:identifier>info:doi/10.1007/jhep10(2014)141</dc:identifier><dc:type>article</dc:type><dc:source>Journal of High Energy Physics, vol 2014, iss 10</dc:source><dc:coverage>141</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4s0364ns</identifier><datestamp>2026-09-16T07:03:16Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4s0364ns</dc:identifier><dc:title>Measurement of charged-particle spectra in Pb+Pb collisions at sNN=2.76 TeV with the ATLAS detector at the LHC</dc:title><dc:creator>The ATLAS collaboration</dc:creator><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdel Khalek, S</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abi, B</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Agustoni, M</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimoto, G</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Alconada Verzini, MJ</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexandre, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allison, LJ</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Alvarez Gonzalez, B</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Amaral Coutinho, Y</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Amor Dos Santos, SP</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Anduaga, XS</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Aperio Bella, L</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arduh, FA</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:creator>Arnal, V</dc:creator><dc:creator>Arnold, H</dc:creator><dc:creator>Arratia, M</dc:creator><dc:date>2015-09-01</dc:date><dc:description>Charged-particle spectra obtained in Pb+Pb interactions at sNN=2.76$$ \sqrt{s_{\mathrm{NN}}}=2.76 $$ TeV and pp interactions at sNN=2.76$$ \sqrt{s_{\mathrm{NN}}}=2.76 $$ TeV with the ATLAS detector at the LHC are presented, using data with integrated luminosities of 0.15 nb−1 and 4.2 pb−1, respectively, in a wide transverse momentum (0.5 &amp;lt; pT&amp;lt; 150 GeV) and pseudorapidity (|η| &amp;lt; 2) range. For Pb+Pb collisions, the spectra are presented as a function of collision centrality, which is determined by the response of the forward calorimeters located on both sides of the interaction point. The nuclear modification factors RAA and RCP are presented in detail as a function of centrality, pT and η. They show a distinct pT-dependence with a pronounced minimum at about 7 GeV. Above 60 GeV, RAA is consistent with a plateau at a centrality-dependent value, within the uncertainties. The value is 0.55 ± 0.01(stat.) ± 0.04(syst.) in the most central collisions. The RAA distribution is consistent with flat |η| dependence over the whole transverse momentum range in all centrality classes.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>QCD</dc:subject><dc:subject>Heavy Ions</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>nucl-ex</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>4902 Mathematical physics (for-2020)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4s0364ns</dc:identifier><dc:identifier>https://escholarship.org/content/qt4s0364ns/qt4s0364ns.pdf</dc:identifier><dc:identifier>info:doi/10.1007/jhep09(2015)050</dc:identifier><dc:type>article</dc:type><dc:source>Journal of High Energy Physics, vol 2015, iss 9</dc:source><dc:coverage>50</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt857837c4</identifier><datestamp>2026-09-16T07:02:55Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt857837c4</dc:identifier><dc:title>ATLAS Collaboration</dc:title><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Abeloos, B</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Agricola, J</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Verzini, MJ Alconada</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Alkire, SP</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Gonzalez, B Alvarez</dc:creator><dc:creator>Piqueras, D Álvarez</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amadio, BT</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Coutinho, Y Amaral</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Dos Santos, SP Amor</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Bella, L Aperio</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arduh, FA</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:creator>Arnold, H</dc:creator><dc:creator>Arratia, M</dc:creator><dc:creator>Arslan, O</dc:creator><dc:creator>Artamonov, A</dc:creator><dc:creator>Artoni, G</dc:creator><dc:date>2016-12-01</dc:date><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/857837c4</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1016/s0375-9474(16)30232-9</dc:identifier><dc:type>article</dc:type><dc:source>Nuclear Physics A, vol 956</dc:source><dc:coverage>922 - 944</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2mr4m2xf</identifier><datestamp>2026-09-16T06:58:42Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2mr4m2xf</dc:identifier><dc:title>Measurements of four-lepton production in pp collisions at s=8&amp;nbsp;TeV with the ATLAS detector</dc:title><dc:creator>Collaboration, ATLAS</dc:creator><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Agricola, J</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Verzini, MJ Alconada</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Alkire, SP</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Gonzalez, B Alvarez</dc:creator><dc:creator>Piqueras, D Álvarez</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amadio, BT</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Coutinho, Y Amaral</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Dos Santos, SP Amor</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Bella, L Aperio</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arduh, FA</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:creator>Arnold, H</dc:creator><dc:creator>Arratia, M</dc:creator><dc:creator>Arslan, O</dc:creator><dc:creator>Artamonov, A</dc:creator><dc:date>2016-02-01</dc:date><dc:description>The four-lepton (4ℓ, ℓ=e,μ) production cross section is measured in the mass range from 80 to 1000 GeV using 20.3 fb−1 of data in pp collisions at s=8&amp;nbsp;TeV collected with the ATLAS detector at the LHC. The 4ℓ events are produced in the decays of resonant Z and Higgs bosons and the non-resonant ZZ continuum originating from qq¯, gg, and qg initial states. A total of 476 signal candidate events are observed with a background expectation of 26.2±3.6 events, enabling the measurement of the integrated cross section and the differential cross section as a function of the invariant mass and transverse momentum of the four-lepton system.In the mass range above 180 GeV, assuming the theoretical constraint on the qq¯ production cross section calculated with perturbative NNLO QCD and NLO electroweak corrections, the signal strength of the gluon-fusion component relative to its leading-order prediction is determined to be μgg=2.4±1.0&amp;nbsp;(stat.)±0.5&amp;nbsp;(syst.)±0.8&amp;nbsp;(theory).</dc:description><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2mr4m2xf</dc:identifier><dc:identifier>https://escholarship.org/content/qt2mr4m2xf/qt2mr4m2xf.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.physletb.2015.12.048</dc:identifier><dc:type>article</dc:type><dc:source>Physics Letters B, vol 753</dc:source><dc:coverage>552 - 572</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt48c1v6zd</identifier><datestamp>2026-09-16T06:58:29Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt48c1v6zd</dc:identifier><dc:title>Constraints on non-Standard Model Higgs boson interactions in an effective Lagrangian using differential cross sections measured in the H→γγ decay channel at s=8&amp;nbsp;TeV with the ATLAS detector</dc:title><dc:creator>Collaboration, ATLAS</dc:creator><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Agricola, J</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Verzini, MJ Alconada</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Alkire, SP</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Gonzalez, B Alvarez</dc:creator><dc:creator>Piqueras, D Álvarez</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amadio, BT</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Coutinho, Y Amaral</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Dos Santos, SP Amor</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Bella, L Aperio</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arduh, FA</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:creator>Arnal, V</dc:creator><dc:creator>Arnold, H</dc:creator><dc:creator>Arratia, M</dc:creator><dc:creator>Arslan, O</dc:creator><dc:date>2016-02-01</dc:date><dc:description>The strength and tensor structure of the Higgs boson's interactions are investigated using an effective Lagrangian, which introduces additional CP-even and CP-odd interactions that lead to changes in the kinematic properties of the Higgs boson and associated jet spectra with respect to the Standard Model. The parameters of the effective Lagrangian are probed using a fit to five differential cross sections previously measured by the ATLAS experiment in the H→γγ decay channel with an integrated luminosity of 20.3 fb−1 at s=8&amp;nbsp;TeV. In order to perform a simultaneous fit to the five distributions, the statistical correlations between them are determined by re-analysing the H→γγ candidate events in the proton–proton collision data. No significant deviations from the Standard Model predictions are observed and limits on the effective Lagrangian parameters are derived. The statistical correlations are made publicly available to allow for future analysis of theories with non-Standard Model interactions.</dc:description><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/48c1v6zd</dc:identifier><dc:identifier>https://escholarship.org/content/qt48c1v6zd/qt48c1v6zd.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.physletb.2015.11.071</dc:identifier><dc:type>article</dc:type><dc:source>Physics Letters B, vol 753</dc:source><dc:coverage>69 - 85</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1498w339</identifier><datestamp>2026-09-16T06:54:46Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1498w339</dc:identifier><dc:title>Detecting Hot Spots of Methane Flux Using Footprint‐Weighted Flux Maps</dc:title><dc:creator>Rey‐Sanchez, Camilo</dc:creator><dc:creator>Arias‐Ortiz, Ariane</dc:creator><dc:creator>Kasak, Kuno</dc:creator><dc:creator>Chu, Housen</dc:creator><dc:creator>Szutu, Daphne</dc:creator><dc:creator>Verfaillie, Joseph</dc:creator><dc:creator>Baldocchi, Dennis</dc:creator><dc:date>2022-08-01</dc:date><dc:description>In this study, we propose a new technique for mapping the spatial heterogeneity in gas exchange around flux towers using flux footprint modeling and focusing on detecting hot spots of methane (CH4) flux. In the first part of the study, we used a CH4 release experiment to evaluate three common flux footprint models: the Hsieh model (Hsieh et&amp;nbsp;al., 2000), the Kljun model (Kljun et&amp;nbsp;al., 2015), and the K &amp;amp; M model (Kormann and Meixner, 2001), finding that the K &amp;amp; M model was the most accurate under these conditions. In the second part of the study, we introduce the Footprint-Weighted Flux Map, a new technique to map spatial heterogeneity in fluxes. Using artificial CH4 release experiments, natural tracer approaches and flux chambers we mapped the spatial flux heterogeneity, and detected and validated a hot spot of CH4 flux in a oligohaline restored marsh. Through chamber measurements during the months of April and May, we found that fluxes at the hot spot were on average as high as 6589&amp;nbsp;±&amp;nbsp;7889&amp;nbsp;nmol m-2 s-1 whereas background flux from the open water were on average 15.2&amp;nbsp;±&amp;nbsp;7.5&amp;nbsp;nmol m-2 s-1. This study provides a novel tool to evaluate the spatial heterogeneity of fluxes around eddy-covariance towers and creates important insights for the interpretation of hot spots of CH4 flux, paving the way for future studies aiming to understand subsurface biogeochemical processes and the microbiological conditions that lead to the occurrence of hot spots and hot moments of CH4 flux.</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>3703 Geochemistry (for-2020)</dc:subject><dc:subject>methane</dc:subject><dc:subject>hot spots</dc:subject><dc:subject>flux footprint</dc:subject><dc:subject>eddy covariance</dc:subject><dc:subject>wetlands</dc:subject><dc:subject>chambers</dc:subject><dc:subject>chambers</dc:subject><dc:subject>eddy covariance</dc:subject><dc:subject>flux footprint</dc:subject><dc:subject>hot spots</dc:subject><dc:subject>methane</dc:subject><dc:subject>wetlands</dc:subject><dc:subject>0404 Geophysics (for)</dc:subject><dc:subject>3706 Geophysics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1498w339</dc:identifier><dc:identifier>https://escholarship.org/content/qt1498w339/qt1498w339.pdf</dc:identifier><dc:identifier>info:doi/10.1029/2022jg006977</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Geophysical Research Biogeosciences, vol 127, iss 8</dc:source><dc:coverage>e2022jg006977</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5wf090r0</identifier><datestamp>2026-09-16T06:54:33Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5wf090r0</dc:identifier><dc:title>Effects of Noninvasive Cervical Vagal Nerve Stimulation on Cognitive Performance But Not Brain Activation in Healthy Adults</dc:title><dc:creator>Klaming, Ruth</dc:creator><dc:creator>Simmons, Alan N</dc:creator><dc:creator>Spadoni, Andrea D</dc:creator><dc:creator>Lerman, Imanuel</dc:creator><dc:date>2022-04-01</dc:date><dc:description>OBJECTIVES: While preliminary evidence suggests that noninvasive vagal nerve stimulation (nVNS) may enhance cognition, to our knowledge, no study has directly assessed the effects of nVNS on brain function and cognitive performance in healthy individuals. The aim of this study was therefore to assess whether nVNS enhances complex visuospatial problem solving in a normative sample. Functional magnetic resonance imaging (fMRI) was used to examine underlying neural substrates.
MATERIAL AND METHODS: Participants received transcutaneous cervical nVNS (N&amp;nbsp;= 15) or sham (N&amp;nbsp;= 15) stimulation during a 3 T fMRI scan. Stimulation lasted for 2 min at 24 V for nVNS and at 4.5 V for sham. Subjects completed a matrix reasoning (MR) task in the scanner and a forced-choice recognition task outside the scanner. An analysis of variance (ANOVA) was used to assess group differences in cognitive performance. And linear mixed effects (LMEs) regression analysis was used to assess main and interaction effects of experimental groups, level of MR task difficulty, and recall accuracy on changes in blood oxygen level-dependent (BOLD) signal.
RESULTS: Subjects who received nVNS showed higher accuracy for both easy (p&amp;nbsp;= 0.017) and hard (p&amp;nbsp;= 0.013) items of the MR task, slower reaction times for hard items (p&amp;nbsp;= 0.014), and fewer false negative errors during the forced-choice recognition task (p&amp;nbsp;= 0.047). MR task difficulty related to increased activation in frontoparietal regions (p &amp;lt; 0.001). No difference between nVNS and sham stimulation was found on BOLD response during performance of the MR task.
CONCLUSIONS: We hypothesize that nVNS increased attention compared to sham, and that this effect led to enhanced executive functions, and consequently to better performance on visuospatial reasoning and recognition tasks. Results provide initial support that nVNS may be a low-risk, low-cost treatment for cognitive disorders.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>Biomedical Imaging (rcdc)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>Basic Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Mental Health (rcdc)</dc:subject><dc:subject>Mental health (hrcs-hc)</dc:subject><dc:subject>Neurological (hrcs-hc)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Brain (mesh)</dc:subject><dc:subject>Cognition (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Magnetic Resonance Imaging (mesh)</dc:subject><dc:subject>Transcutaneous Electric Nerve Stimulation (mesh)</dc:subject><dc:subject>Vagus Nerve Stimulation (mesh)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>Basic Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>1.1 Normal biological development and functioning (hrcs-rac)</dc:subject><dc:subject>1 Underpinning research (hrcs-rac)</dc:subject><dc:subject>Mental health (hrcs-hc)</dc:subject><dc:subject>Neurological (hrcs-hc)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Brain (mesh)</dc:subject><dc:subject>Cognition (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Magnetic Resonance Imaging (mesh)</dc:subject><dc:subject>Transcutaneous Electric Nerve Stimulation (mesh)</dc:subject><dc:subject>Vagus Nerve Stimulation (mesh)</dc:subject><dc:subject>Attention</dc:subject><dc:subject>cervical noninvasive vagal nerve stimulation</dc:subject><dc:subject>cognition</dc:subject><dc:subject>functional magnetic resonance imaging</dc:subject><dc:subject>Attention</dc:subject><dc:subject>cervical noninvasive vagal nerve stimulation</dc:subject><dc:subject>cognition</dc:subject><dc:subject>functional magnetic resonance imaging</dc:subject><dc:subject>1103 Clinical Sciences (for)</dc:subject><dc:subject>1109 Neurosciences (for)</dc:subject><dc:subject>1702 Cognitive Sciences (for)</dc:subject><dc:subject>Neurology &amp; Neurosurgery (science-metrix)</dc:subject><dc:subject>3202 Clinical sciences (for-2020)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5wf090r0</dc:identifier><dc:identifier>https://escholarship.org/content/qt5wf090r0/qt5wf090r0.pdf</dc:identifier><dc:identifier>info:doi/10.1111/ner.13313</dc:identifier><dc:type>article</dc:type><dc:source>Neuromodulation Technology at the Neural Interface, vol 25, iss 3</dc:source><dc:coverage>424 - 432</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt351951kq</identifier><datestamp>2026-09-16T06:51:26Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt351951kq</dc:identifier><dc:title>RETRACTED: Investigation of the GeneXpert® CT/NG assay for use with male pharyngeal and rectal swabs</dc:title><dc:creator>Geiger, Rechel</dc:creator><dc:creator>Smith, David M</dc:creator><dc:creator>Little, Susan J</dc:creator><dc:creator>Mehta, Sanjay R</dc:creator><dc:date>2017-02-01</dc:date><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>3204 Immunology (for-2020)</dc:subject><dc:subject>1103 Clinical Sciences (for)</dc:subject><dc:subject>1108 Medical Microbiology (for)</dc:subject><dc:subject>1117 Public Health and Health Services (for)</dc:subject><dc:subject>Public Health (science-metrix)</dc:subject><dc:subject>3202 Clinical sciences (for-2020)</dc:subject><dc:subject>3204 Immunology (for-2020)</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/351951kq</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1177/0956462416665059</dc:identifier><dc:type>multimedia</dc:type><dc:source>International Journal of STD &amp; AIDS, vol 28, iss 2</dc:source><dc:coverage>np1 - np3</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt18w6k3sr</identifier><datestamp>2026-09-16T06:51:23Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt18w6k3sr</dc:identifier><dc:title>Soft x-ray ptychography studies of nanoscale magnetic and structural correlations in thin SmCo5 films</dc:title><dc:creator>Shi, X</dc:creator><dc:creator>Fischer, P</dc:creator><dc:creator>Neu, V</dc:creator><dc:creator>Elefant, D</dc:creator><dc:creator>Lee, JCT</dc:creator><dc:creator>Shapiro, DA</dc:creator><dc:creator>Farmand, M</dc:creator><dc:creator>Tyliszczak, T</dc:creator><dc:creator>Shiu, H-W</dc:creator><dc:creator>Marchesini, S</dc:creator><dc:creator>Roy, S</dc:creator><dc:creator>Kevan, SD</dc:creator><dc:date>2016-02-29</dc:date><dc:description>High spatial resolution magnetic x-ray spectromicroscopy at x-ray photon energies near the cobalt L3 resonance was applied to probe an amorphous 50 nm thin SmCo5 film prepared by off-axis pulsed laser deposition onto an x-ray transparent 200 nm thin Si3N4 membrane. Alternating gradient magnetometry shows a strong in-plane anisotropy and an only weak perpendicular magnetic anisotropy, which is confirmed by magnetic transmission soft x-ray microscopy images showing over a field of view of 10 μm a primarily stripe-like domain pattern but with local labyrinth-like domains. Soft x-ray ptychography in amplitude and phase contrast was used to identify and characterize local magnetic and structural features over a field of view of 1 μm with a spatial resolution of about 10 nm. There, the magnetic labyrinth domain patterns are accompanied by nanoscale structural inclusions that are primarily located in close proximity to the magnetic domain walls. Our analysis suggests that these inclusions are nanocrystalline Sm2Co17 phases with nominally in-plane magnetic anisotropy.</dc:description><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>5104 Condensed Matter Physics (for-2020)</dc:subject><dc:subject>MSD-General (c-lbnl-label)</dc:subject><dc:subject>MSD-Magnetic Materials (c-lbnl-label)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>10 Technology (for)</dc:subject><dc:subject>Applied Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/18w6k3sr</dc:identifier><dc:identifier>https://escholarship.org/content/qt18w6k3sr/qt18w6k3sr.pdf</dc:identifier><dc:identifier>info:doi/10.1063/1.4942776</dc:identifier><dc:type>article</dc:type><dc:source>Applied Physics Letters, vol 108, iss 9</dc:source><dc:coverage>094103</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0rp6r560</identifier><datestamp>2026-09-16T06:47:07Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0rp6r560</dc:identifier><dc:title>Search for high-mass diphoton resonances in pp collisions at s=8 TeV with the ATLAS detector</dc:title><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Khalek, S Abdel</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abi, B</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Agustoni, M</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimoto, G</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Verzini, MJ Alconada</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexandre, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allison, LJ</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Gonzalez, B Alvarez</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Coutinho, Y Amaral</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Dos Santos, SP Amor</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Anduaga, XS</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Bella, L Aperio</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arduh, FA</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:creator>Arnal, V</dc:creator><dc:creator>Arnold, H</dc:creator><dc:creator>Arratia, M</dc:creator><dc:creator>Arslan, O</dc:creator><dc:date>2015-08-01</dc:date><dc:description>This article describes a search for high-mass resonances decaying to a pair of photons using a sample of 20.3 fb-1 of pp collisions at s=8 TeV recorded with the ATLAS detector at the Large Hadron Collider. The data are found to be in agreement with the Standard Model prediction, and limits are reported in the framework of the Randall-Sundrum model. This theory leads to the prediction of graviton states, the lightest of which could be observed at the Large Hadron Collider. A lower limit of 2.66 (1.41) TeV at 95% confidence level is set on the mass of the lightest graviton for couplings of k/M¯Pl=0.1 (0.01).</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0rp6r560</dc:identifier><dc:identifier>https://escholarship.org/content/qt0rp6r560/qt0rp6r560.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevd.92.032004</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 92, iss 3</dc:source><dc:coverage>032004</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6tg997r9</identifier><datestamp>2026-09-16T06:46:47Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6tg997r9</dc:identifier><dc:title>Measurement of the Azimuthal Angle Dependence of Inclusive Jet Yields in Pb+Pb Collisions at sNN=2.76 TeV with the ATLAS Detector</dc:title><dc:creator>Aad, G</dc:creator><dc:creator>Abajyan, T</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Khalek, S Abdel</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abi, B</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Addy, TN</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Aefsky, S</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Agustoni, M</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmad, A</dc:creator><dc:creator>Ahsan, M</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimoto, G</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alam, MA</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Verzini, MJ Alconada</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alessandria, F</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexandre, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Aliev, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allison, LJ</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Allwood-Spiers, SE</dc:creator><dc:creator>Almond, J</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alon, R</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Gonzalez, B Alvarez</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Coutinho, Y Amaral</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Ammosov, VV</dc:creator><dc:creator>Dos Santos, SP Amor</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Anduaga, XS</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonaki, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Bella, L Aperio</dc:creator><dc:creator>Apolle, R</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Aracena, I</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arfaoui, S</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, E</dc:creator><dc:date>2013-10-11</dc:date><dc:description>Measurements of the variation of inclusive jet suppression as a function of relative azimuthal angle, Δφ, with respect to the elliptic event plane provide insight into the path-length dependence of jet quenching. ATLAS has measured the Δφ dependence of jet yields in 0.14 nb(-1) of √(s(NN))=2.76 TeV Pb+Pb collisions at the LHC for jet transverse momenta p(T)&amp;gt;45 GeV in different collision centrality bins using an underlying event subtraction procedure that accounts for elliptic flow. The variation of the jet yield with Δφ was characterized by the parameter, v(2)(jet), and the ratio of out-of-plane (Δφ~π/2) to in-plane (Δφ~0) yields. Nonzero v(2)(jet) values were measured in all centrality bins for p(T)&amp;lt;160 GeV. The jet yields are observed to vary by as much as 20% between in-plane and out-of-plane directions.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>ATLAS Collaboration</dc:subject><dc:subject>ATLAS Collaboration</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>01 Mathematical Sciences (for)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6tg997r9</dc:identifier><dc:identifier>https://escholarship.org/content/qt6tg997r9/qt6tg997r9.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevlett.111.152301</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review Letters, vol 111, iss 15</dc:source><dc:coverage>152301</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9gj237vf</identifier><datestamp>2026-09-16T06:46:29Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9gj237vf</dc:identifier><dc:title>Search for photonic signatures of gauge-mediated supersymmetry in 8 TeV pp collisions with the ATLAS detector</dc:title><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Agricola, J</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Verzini, MJ Alconada</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Alkire, SP</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Gonzalez, B Alvarez</dc:creator><dc:creator>Piqueras, D Álvarez</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amadio, BT</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Coutinho, Y Amaral</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Dos Santos, SP Amor</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Bella, L Aperio</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arduh, FA</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:creator>Arnal, V</dc:creator><dc:creator>Arnold, H</dc:creator><dc:creator>Arratia, M</dc:creator><dc:creator>Arslan, O</dc:creator><dc:creator>Artamonov, A</dc:creator><dc:date>2015-10-01</dc:date><dc:description>A search is presented for photonic signatures motivated by generalized models of gauge-mediated supersymmetry breaking. This search makes use of 20.3 fb-1 of proton-proton collision data at √s = 8 TeV recorded by the ATLAS detector at the LHC, and explores models dominated by both strong and electroweak production of supersymmetric partner states. Four experimental signatures incorporating an isolated photon and significant missing transverse momentum are explored. These signatures include events with an additional photon, lepton, b-quark jet, or jet activity not associated with any specific underlying quark flavor. No significant excess of events is observed above the Standard Model prediction and model-dependent 95% confidence-level exclusion limits are set.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9gj237vf</dc:identifier><dc:identifier>https://escholarship.org/content/qt9gj237vf/qt9gj237vf.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevd.92.072001</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 92, iss 7</dc:source><dc:coverage>072001</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1052j40s</identifier><datestamp>2026-09-16T06:46:09Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1052j40s</dc:identifier><dc:title>Summary of the searches for squarks and gluinos using s=8 TeV pp collisions with the ATLAS experiment at the LHC</dc:title><dc:creator>The ATLAS collaboration</dc:creator><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Agricola, J</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Alconada Verzini, MJ</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Alkire, SP</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Alvarez Gonzalez, B</dc:creator><dc:creator>Álvarez Piqueras, D</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amadio, BT</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Amaral Coutinho, Y</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Amor Dos Santos, SP</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Aperio Bella, L</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arduh, FA</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:creator>Arnal, V</dc:creator><dc:creator>Arnold, H</dc:creator><dc:creator>Arratia, M</dc:creator><dc:creator>Arslan, O</dc:creator><dc:date>2015-10-01</dc:date><dc:description>A summary is presented of ATLAS searches for gluinos and first- and second-generation squarks in final states containing jets and missing transverse momentum, with or without leptons or b-jets, in the s=8$$ \sqrt{s}=8 $$ TeV data set collected at the Large Hadron Collider in 2012. This paper reports the results of new interpretations and statistical combinations of previously published analyses, as well as a new analysis. Since no significant excess of events over the Standard Model expectation is observed, the data are used to set limits in a variety of models. In all the considered simplified models that assume R-parity conservation, the limit on the gluino mass exceeds 1150 GeV at 95% confidence level, for an LSP mass smaller than 100 GeV. Furthermore, exclusion limits are set for left-handed squarks in a phenomenological MSSM model, a minimal Supergravity/Constrained MSSM model, R-parity-violation scenarios, a minimal gauge-mediated supersymmetry breaking model, a natural gauge mediation model, a non-universal Higgs mass model with gaugino mediation and a minimal model of universal extra dimensions.</dc:description><dc:subject>Supersymmetry</dc:subject><dc:subject>Hadron-Hadron Scattering</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>4902 Mathematical physics (for-2020)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1052j40s</dc:identifier><dc:identifier>https://escholarship.org/content/qt1052j40s/qt1052j40s.pdf</dc:identifier><dc:identifier>info:doi/10.1007/jhep10(2015)054</dc:identifier><dc:type>article</dc:type><dc:source>Journal of High Energy Physics, vol 2015, iss 10</dc:source><dc:coverage>54</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0x3912k9</identifier><datestamp>2026-09-16T06:45:51Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0x3912k9</dc:identifier><dc:title>Measurement of the forward-backward asymmetry of electron and muon pair-production in pp collisions at s=7 TeV with the ATLAS detector</dc:title><dc:creator>The ATLAS collaboration</dc:creator><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdel Khalek, S</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abi, B</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Agustoni, M</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimoto, G</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Alconada Verzini, MJ</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexandre, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allison, LJ</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Almond, J</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Alvarez Gonzalez, B</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Amaral Coutinho, Y</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Amor Dos Santos, SP</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Anduaga, XS</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonaki, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Aperio Bella, L</dc:creator><dc:creator>Apolle, R</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Aracena, I</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:date>2015-09-01</dc:date><dc:description>This paper presents measurements from the ATLAS experiment of the forward-backward asymmetry in the reaction pp → Z/γ* → l+l−, with l being electrons or muons, and the extraction of the effective weak mixing angle. The results are based on the full set of data collected in 2011 in pp collisions at the LHC at (Formula presented.), corresponding to an integrated luminosity of 4.8 fb−1. The measured asymmetry values are found to be in agreement with the corresponding Standard Model predictions. The combination of the muon and electron channels yields a value of the effective weak mixing angle of sin2θeff lept = 0.2308 ± 0.0005(stat.) ± 0.0006(syst.) ± 0.0009(PDF), where the first uncertainty corresponds to data statistics, the second to systematic effects and the third to knowledge of the parton density functions. This result agrees with the current world average from the Particle Data Group fit.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Hadron-Hadron Scattering</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>4902 Mathematical physics (for-2020)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0x3912k9</dc:identifier><dc:identifier>https://escholarship.org/content/qt0x3912k9/qt0x3912k9.pdf</dc:identifier><dc:identifier>info:doi/10.1007/jhep09(2015)049</dc:identifier><dc:type>article</dc:type><dc:source>Journal of High Energy Physics, vol 2015, iss 9</dc:source><dc:coverage>49</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt57k8d4zg</identifier><datestamp>2026-09-16T06:45:39Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt57k8d4zg</dc:identifier><dc:title>Search for low-scale gravity signatures in multi-jet final states with the ATLAS detector at s=8 TeV</dc:title><dc:creator>The ATLAS collaboration</dc:creator><dc:creator>Aad, G</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdallah, J</dc:creator><dc:creator>Abdinov, O</dc:creator><dc:creator>Aben, R</dc:creator><dc:creator>Abolins, M</dc:creator><dc:creator>AbouZeid, OS</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abreu, H</dc:creator><dc:creator>Abreu, R</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, DL</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adomeit, S</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Agatonovic-Jovin, T</dc:creator><dc:creator>Aguilar-Saavedra, JA</dc:creator><dc:creator>Ahlen, SP</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Akerstedt, H</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimoto, G</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albrand, S</dc:creator><dc:creator>Alconada Verzini, MJ</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexander, G</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alio, L</dc:creator><dc:creator>Alison, J</dc:creator><dc:creator>Alkire, SP</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Altheimer, A</dc:creator><dc:creator>Alvarez Gonzalez, B</dc:creator><dc:creator>Álvarez Piqueras, D</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Amadio, BT</dc:creator><dc:creator>Amako, K</dc:creator><dc:creator>Amaral Coutinho, Y</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Amor Dos Santos, SP</dc:creator><dc:creator>Amorim, A</dc:creator><dc:creator>Amoroso, S</dc:creator><dc:creator>Amram, N</dc:creator><dc:creator>Amundsen, G</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Ancu, LS</dc:creator><dc:creator>Andari, N</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, CF</dc:creator><dc:creator>Anders, G</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Anderson, KJ</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Andrei, V</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angelozzi, I</dc:creator><dc:creator>Anger, P</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anghinolfi, F</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Anjos, N</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Antonov, A</dc:creator><dc:creator>Antos, J</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:creator>Aperio Bella, L</dc:creator><dc:creator>Arabidze, G</dc:creator><dc:creator>Arai, Y</dc:creator><dc:creator>Araque, JP</dc:creator><dc:creator>Arce, ATH</dc:creator><dc:creator>Arduh, FA</dc:creator><dc:creator>Arguin, J-F</dc:creator><dc:creator>Argyropoulos, S</dc:creator><dc:creator>Arik, M</dc:creator><dc:creator>Armbruster, AJ</dc:creator><dc:creator>Arnaez, O</dc:creator><dc:creator>Arnal, V</dc:creator><dc:creator>Arnold, H</dc:creator><dc:creator>Arratia, M</dc:creator><dc:creator>Arslan, O</dc:creator><dc:date>2015-07-01</dc:date><dc:description>A search for evidence of physics beyond the Standard Model in final states with multiple high-transverse-momentum jets is performed using 20.3 fb−1 of proton-proton collision data at s=8$$ \sqrt{s}=8 $$ TeV recorded by the ATLAS detector at the LHC. No significant excess of events beyond Standard Model expectations is observed, and upper limits on the visible cross sections for non-Standard Model production of multi-jet final states are set. A wide variety of models for black hole and string ball production and decay are considered, and the upper limit on the cross section times acceptance is as low as 0.16 fb at the 95% confidence level. For these models, excluded regions are also given as function of the main model parameters.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>4902 Mathematical Physics (for-2020)</dc:subject><dc:subject>49 Mathematical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Exotics</dc:subject><dc:subject>Hadron-Hadron Scattering</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>4902 Mathematical physics (for-2020)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/57k8d4zg</dc:identifier><dc:identifier>https://escholarship.org/content/qt57k8d4zg/qt57k8d4zg.pdf</dc:identifier><dc:identifier>info:doi/10.1007/jhep07(2015)032</dc:identifier><dc:type>article</dc:type><dc:source>Journal of High Energy Physics, vol 2015, iss 7</dc:source><dc:coverage>32</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt00v8m23w</identifier><datestamp>2026-09-16T06:42:36Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt00v8m23w</dc:identifier><dc:title>Radiogenic and muon-induced backgrounds in the LUX dark matter detector</dc:title><dc:creator>Akerib, DS</dc:creator><dc:creator>Araújo, HM</dc:creator><dc:creator>Bai, X</dc:creator><dc:creator>Bailey, AJ</dc:creator><dc:creator>Balajthy, J</dc:creator><dc:creator>Bernard, E</dc:creator><dc:creator>Bernstein, A</dc:creator><dc:creator>Bradley, A</dc:creator><dc:creator>Byram, D</dc:creator><dc:creator>Cahn, SB</dc:creator><dc:creator>Carmona-Benitez, MC</dc:creator><dc:creator>Chan, C</dc:creator><dc:creator>Chapman, JJ</dc:creator><dc:creator>Chiller, AA</dc:creator><dc:creator>Chiller, C</dc:creator><dc:creator>Coffey, T</dc:creator><dc:creator>Currie, A</dc:creator><dc:creator>de Viveiros, L</dc:creator><dc:creator>Dobi, A</dc:creator><dc:creator>Dobson, J</dc:creator><dc:creator>Druszkiewicz, E</dc:creator><dc:creator>Edwards, B</dc:creator><dc:creator>Faham, CH</dc:creator><dc:creator>Fiorucci, S</dc:creator><dc:creator>Flores, C</dc:creator><dc:creator>Gaitskell, RJ</dc:creator><dc:creator>Gehman, VM</dc:creator><dc:creator>Ghag, C</dc:creator><dc:creator>Gibson, KR</dc:creator><dc:creator>Gilchriese, MGD</dc:creator><dc:creator>Hall, C</dc:creator><dc:creator>Hertel, SA</dc:creator><dc:creator>Horn, M</dc:creator><dc:creator>Huang, DQ</dc:creator><dc:creator>Ihm, M</dc:creator><dc:creator>Jacobsen, RG</dc:creator><dc:creator>Kazkaz, K</dc:creator><dc:creator>Knoche, R</dc:creator><dc:creator>Larsen, NA</dc:creator><dc:creator>Lee, C</dc:creator><dc:creator>Lindote, A</dc:creator><dc:creator>Lopes, MI</dc:creator><dc:creator>Malling, DC</dc:creator><dc:creator>Mannino, R</dc:creator><dc:creator>McKinsey, DN</dc:creator><dc:creator>Mei, D-M</dc:creator><dc:creator>Mock, J</dc:creator><dc:creator>Moongweluwan, M</dc:creator><dc:creator>Morad, J</dc:creator><dc:creator>Murphy</dc:creator><dc:creator>Nehrkorn, C</dc:creator><dc:creator>Nelson, H</dc:creator><dc:creator>Neves, F</dc:creator><dc:creator>Ott, RA</dc:creator><dc:creator>Pangilinan, M</dc:creator><dc:creator>Parker, PD</dc:creator><dc:creator>Pease, EK</dc:creator><dc:creator>Pech, K</dc:creator><dc:creator>Phelps, P</dc:creator><dc:creator>Reichhart, L</dc:creator><dc:creator>Shutt, T</dc:creator><dc:creator>Silva, C</dc:creator><dc:creator>Solovov, VN</dc:creator><dc:creator>Sorensen, P</dc:creator><dc:creator>O’Sullivan, K</dc:creator><dc:creator>Sumner, TJ</dc:creator><dc:creator>Szydagis, M</dc:creator><dc:creator>Taylor, D</dc:creator><dc:creator>Tennyson, B</dc:creator><dc:creator>Tiedt, DR</dc:creator><dc:creator>Tripathi, M</dc:creator><dc:creator>Uvarov, S</dc:creator><dc:creator>Verbus, JR</dc:creator><dc:creator>Walsh, N</dc:creator><dc:creator>Webb, R</dc:creator><dc:creator>White, JT</dc:creator><dc:creator>Witherell, MS</dc:creator><dc:creator>Wolfs, FLH</dc:creator><dc:creator>Woods, M</dc:creator><dc:creator>Zhang, C</dc:creator><dc:date>2015-03-01</dc:date><dc:description>The Large Underground Xenon (LUX) dark matter experiment aims to detect rare low-energy interactions from Weakly Interacting Massive Particles (WIMPs). The radiogenic backgrounds in the LUX detector have been measured and compared with Monte Carlo simulation. Measurements of LUX high-energy data have provided direct constraints on all background sources contributing to the background model. The expected background rate from the background model for the 85.3day WIMP search run is (2.6±0.2stat±0.4sys)×10-3 events keVee-1kg-1day-1 in a 118kg fiducial volume. The observed background rate is (3.6±0.4stat)×10-3 events keVee-1kg-1day-1, consistent with model projections. The expectation for the radiogenic background in a subsequent one-year run is presented.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>LUX</dc:subject><dc:subject>Dark matter</dc:subject><dc:subject>Radioactive background</dc:subject><dc:subject>Material screening</dc:subject><dc:subject>Simulation</dc:subject><dc:subject>astro-ph.IM</dc:subject><dc:subject>astro-ph.IM</dc:subject><dc:subject>physics.ins-det</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/00v8m23w</dc:identifier><dc:identifier>https://escholarship.org/content/qt00v8m23w/qt00v8m23w.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.astropartphys.2014.07.009</dc:identifier><dc:type>article</dc:type><dc:source>Astroparticle Physics, vol 62</dc:source><dc:coverage>33 - 46</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0kn0p46z</identifier><datestamp>2026-09-16T06:42:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0kn0p46z</dc:identifier><dc:title>Associations of per- and polyfluoroalkyl substances (PFAS) and their mixture with oxidative stress biomarkers during pregnancy</dc:title><dc:creator>Taibl, Kaitlin R</dc:creator><dc:creator>Schantz, Susan</dc:creator><dc:creator>Aung, Max</dc:creator><dc:creator>Padula, Amy</dc:creator><dc:creator>Geiger, Sarah</dc:creator><dc:creator>Smith, Sabrina</dc:creator><dc:creator>Park, June-Soo</dc:creator><dc:creator>Milne, Ginger L</dc:creator><dc:creator>Robinson, Joshua F</dc:creator><dc:creator>Woodruff, Tracey J</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Eick, Stephanie M</dc:creator><dc:date>2022-11-01</dc:date><dc:description>BACKGROUND: Oxidative stress from excess reactive oxygen species (ROS) is a hypothesized contributor to preterm birth. Per- and polyfluoroalkyl substances (PFAS) exposure is reported to generate ROS in laboratory settings, and is linked to adverse birth outcomes globally. However, to our knowledge, the relationship between PFAS and oxidative stress has not been examined in the context of human pregnancy.
OBJECTIVE: To investigate the associations between prenatal PFAS exposure and oxidative stress biomarkers among pregnant people.
METHODS: Our analytic sample included 428 participants enrolled in the Illinois Kids Development Study and Chemicals In Our Bodies prospective birth cohorts between 2014 and 2019. Twelve PFAS were measured in second trimester serum. We focused on seven PFAS that were detected in&amp;nbsp;&amp;gt;65&amp;nbsp;% of participants. Urinary levels of 8-isoprostane-prostaglandin-F2α, prostaglandin-F2α, 2,3-dinor-8-iso-PGF2α, and 2,3-dinor-5,6-dihydro-8-iso-PGF2α were measured in the second and third trimesters as biomarkers of oxidative stress. We fit linear mixed-effects models to estimate individual associations between PFAS and oxidative stress biomarkers. We used quantile g-computation and Bayesian kernel machine regression (BKMR) to assess associations between the PFAS mixture and averaged oxidative stress biomarkers.
RESULTS: Linear mixed-effects models showed that an interquartile range increase in perfluorooctane sulfonic acid (PFOS) was associated with an increase in 8-isoprostane-prostaglandin-F2α (β&amp;nbsp;=&amp;nbsp;0.10, 95&amp;nbsp;% confidence interval&amp;nbsp;=&amp;nbsp;0, 0.20). In both quantile g-computation and BKMR, and across all oxidative stress biomarkers, PFOS contributed the most to the overall mixture effect. The six remaining PFAS were not significantly associated with changes in oxidative stress biomarkers.
CONCLUSIONS: Our study is the first to investigate the relationship between PFAS exposure and biomarkers of oxidative stress during human pregnancy. We found that PFOS was associated with elevated levels of oxidative stress, which is consistent with prior work in animal models and cell lines. Future research is needed to understand how prenatal PFAS exposure and maternal oxidative stress may affect fetal development.</dc:description><dc:subject>3215 Reproductive Medicine (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>Maternal Health (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Endocrine Disruptors (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Pregnancy (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Perinatal Period - Conditions Originating in Perinatal Period (rcdc)</dc:subject><dc:subject>2.2 Factors relating to the physical environment (hrcs-rac)</dc:subject><dc:subject>2.1 Biological and endogenous factors (hrcs-rac)</dc:subject><dc:subject>Reproductive health and childbirth (hrcs-hc)</dc:subject><dc:subject>Alkanesulfonic Acids (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Bayes Theorem (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:subject>Dimaprit (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Fluorocarbons (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Oxidative Stress (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Premature Birth (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>Reactive Oxygen Species (mesh)</dc:subject><dc:subject>PFAS</dc:subject><dc:subject>Oxidative stress</dc:subject><dc:subject>Mixtures</dc:subject><dc:subject>Maternal and child health</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Premature Birth (mesh)</dc:subject><dc:subject>Reactive Oxygen Species (mesh)</dc:subject><dc:subject>Alkanesulfonic Acids (mesh)</dc:subject><dc:subject>Fluorocarbons (mesh)</dc:subject><dc:subject>Dimaprit (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Bayes Theorem (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>Oxidative Stress (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:subject>Maternal and child health</dc:subject><dc:subject>Mixtures</dc:subject><dc:subject>Oxidative stress</dc:subject><dc:subject>PFAS</dc:subject><dc:subject>Alkanesulfonic Acids (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Bayes Theorem (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:subject>Dimaprit (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Fluorocarbons (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Oxidative Stress (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Premature Birth (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>Reactive Oxygen Species (mesh)</dc:subject><dc:subject>Environmental Sciences (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0kn0p46z</dc:identifier><dc:identifier>https://escholarship.org/content/qt0kn0p46z/qt0kn0p46z.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.envint.2022.107541</dc:identifier><dc:type>article</dc:type><dc:source>Environment International, vol 169</dc:source><dc:coverage>107541</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3bz9842w</identifier><datestamp>2026-09-16T06:40:38Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3bz9842w</dc:identifier><dc:title>Mercury Telluride Quantum Dots with High Photoluminescent Quantum Yields Throughout the Shortwave Infrared</dc:title><dc:creator>Coffey, Belle</dc:creator><dc:contributor>Caram, Justin R</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>Mercury telluride (HgTe) quantum dots (QDs) are a unique class of nanocrystals with optical bandgap tunability from the visible to the mid-wave infrared, high photoluminescent quantum yields (PLQY), low temperature syntheses, and are oxygen stable. HgTe QDs have been demonstrated as the leading material performing in new infrared photoconductors and focal plane arrays, however the demonstration of smaller HgTe QDs in photoluminescent applications in the near and shortwave infrared are significantly less studied. In this dissertation, we explore how new synthetic methods can isolate HgTe QDs with superior optical properties in the NIR/SWIR, and further demonstrate those applications in novel photoluminescent applications of HgTe QDs. Chapter 1 introduces infrared photophysics, provides a foundation for understanding the historical background and structure of quantum dots, and summarizes the current challenges and research directions of HgTe QDs that are addressed throughout the dissertation. In chapter 2, we demonstrate a novel synthetic method to isolate HgTe QDs with near-unity PLQY values in the near and shortwave infrared. Utilizing the slow reaction kinetics of mercury carboxylate based Hg(OAc)2 in oleylamine, we perform a low temperature reaction (0 ºC), which isolates ultrasmall HgTe quantum dots (&amp;lt; 2 nm in diameter). These QDs are some of the smallest isolated in literature, providing a new platform to utilize HgTe QDs as NIR emitters. The QDs maintain bright photoluminescence (PL) in the solid state, allowing for the first single particle PL study of HgTe QDs, providing invaluable insight into the homogenous/inhomogeneous spectral broadening observed in HgTe QD based systems. In chapter 3, we explore how to optimize our previous synthetic method outlined in chapter 2 in order to grow larger QDs with high PLQY farther into the shortwave infrared. The synthetic method outlined in Chapter 2 isolate high-quality HgTe quantum dots, but it is limited in the size and subsequent PL wavelengths that can be achieved. Therefore, we employ an additional reaction phase where a slow injection of tellurium precursor occurs, which enables significant tuning of the QD size and PL. Through the optimized slow injection procedure, HgTe quantum dots are synthesized with PL out to 1600 nm while still maintaining high photoluminescent quantum yield values. These QDs maintain significantly higher photoluminescent quantum yield values to other HgTe quantum dots and infrared emitting nanocrystals. We perform in depth optical characterization into their molar extinction coefficients and post-synthetic surface treatments to enhance optical stability and photoluminescent quantum yields. Finally, we demonstrate the application of the HgTe quantum dots as contrast agents for in-vivo shortwave infrared imaging of mice, a novel application space for photoluminescent HgTe QDs. In chapter 4, we explore the application of HgTe quantum dots as triplet sensitizers for shortwave infrared to visible triplet-triplet annihilation photon upconversion. This work is still in progress, and results are based on currently available data. Currently, lead sulfide (PbS) QDs are the leading sensitizer used for solid state infrared to visible photon upconversion. Since our synthesized HgTe QDs display higher PLQY, we were motivated to investigate HgTe QDs as a new triplet sensitizer for infrared to visible upconversion, and to directly compare their performance to PbS QDs of similar optical bandgaps. Throughout chapter 4, we demonstrate that HgTe QDs outperform PbS quantum dots as triplet sensitizers in upconversion films. HgTe QD films show improved upconversion quantum yields (up to an order of magnitude higher), greater absorbance, and enhanced upconversion stability over time. Additionally, HgTe QD sensitized upconversion can be accomplished without any exciton transmitter ligands, whereas it is a staple in all other nanocrystal based sensitizer films for efficient upconversion. Finally, we speculate on reasons for the enhanced improvement in HgTe quantum dots and future directions to complete the work.</dc:description><dc:subject>Chemistry</dc:subject><dc:subject>Materials science</dc:subject><dc:subject>Quantum physics</dc:subject><dc:subject>Nanocrystals</dc:subject><dc:subject>Photophysics</dc:subject><dc:subject>Short wave infrared</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3bz9842w</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4jd7q7fj</identifier><datestamp>2026-09-16T06:40:33Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4jd7q7fj</dc:identifier><dc:title>Cylindrical Micelle-Forming Conjugated Polyelectrolytes: Connecting Molecular Design, Self-Assembly, Photophysics, Doping and Charge Transport</dc:title><dc:creator>Liu, Xinyu</dc:creator><dc:contributor>Tolbert, Sarah SHT</dc:contributor><dc:contributor>Rubin, Yves YR</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>Semiconducting conjugated polymers combine tunable electronic and optical properties with mechanical flexibility and solution processability, enabling broad applications. Most conjugated polymers are hydrophobic and require processing from halogenated organic solvents, but conjugated polyelectrolytes (CPEs) containing ionic side chains provide a platform for water-processable electronic and optoelectronic materials. Many CPEs are conformationally disordered in water, but cylindrical micelles, with straightened conjugated backbones, can be induced to form if specific molecular design rules are met.This dissertation examines how molecular structure controls cylindrical micelle formation and how supramolecular organization influences photophysics, chemical doping, solid-state structure, and charge transport. Specifically, it investigates how backbone structure, side-chain chemistry, solution environment, and doping method regulate polymer organization in solution and in the solid state, and how these structural changes translate into material function. These relationships are investigated using polymer synthesis, solution-phase small-angle X-ray scattering (SAXS), grazing-incidence wide- and small-angle X-ray scattering (GIWAXS/GISAXS), steady-state and time-resolved optical spectroscopy, electrochemistry, atomic-force microscopy, and electrical measurements.Chapter 2 establishes aqueous chemical doping of a cationic micelle-forming CPE using Fe(III)-halide dopants. Cylindrical morphology persists during doping, enabling direct deposition of conductive films from doped aqueous solutions. Chapter 3 examines how ionic side-chain chemistry regulates self-assembly and doping by comparing cationic, zwitterionic, and anionic CPEs with a common backbone. In anionic CPEs, sulfonate side chains act as intrinsic counterions that reduce Coulombic trapping of charge carriers, enabling conductivities above 20 S cm–1. Chapter 4 demonstrates that incorporating oligoether side chains into anionic CPEs improves micelle morphology, but increases local conformational disorder and localizes charge carriers, shifting the balance between ionic and electronic transport. Chapter 5 examines the photophysics of micelle-forming polymers, showing that cylindrical micelle formation strengthens J-type electronic coupling, red-shifts fluorescence, increases excited-state lifetimes and quantum yield, and improves solid-state carrier mobility. Finally, chapter 6 investigates how counter-anion identity governs carrier speciation, solid-state structure, and conductivity. Blend-doped films exhibit the highest conductivity by achieving high carrier density without bipolaron formation or doping-induced structural disorder. Together, these studies establish cylindrical micelle formation as an effective supramolecular strategy for controlling the optical, electronic, and transport properties of water-processable semiconducting polymers.</dc:description><dc:subject>Chemistry</dc:subject><dc:subject>Physical chemistry</dc:subject><dc:subject>Polymer chemistry</dc:subject><dc:subject>Molecular chemistry</dc:subject><dc:subject>Charge Transport</dc:subject><dc:subject>Conjugated Polyelectrolyte</dc:subject><dc:subject>Molecular Engineering</dc:subject><dc:subject>Self-Assembly</dc:subject><dc:subject>Semiconducting Polymers</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4jd7q7fj</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1fj6q041</identifier><datestamp>2026-09-16T06:40:28Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1fj6q041</dc:identifier><dc:title>Integrated Inline Coagulation - Hydrocyclone Separation Pretreatment for Reverse Osmosis Feedwater</dc:title><dc:creator>Banerjee, Devajyoti Bedahuti</dc:creator><dc:contributor>Srivastava, Samanvaya</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>Reverse osmosis (RO) is central to advanced water reuse; however, particulate and colloidal fouling can severely curtail its performance, creating a need for effective, compact pretreatment that reduces particulate loading to downstream filtration and provides RO feed. This thesis evaluates a new integrated continuous-flow pretreatment process combining inline coagulation, hydrocyclonic separation, and downstream microfiltration for secondary-treated municipal wastewater. Laboratory experiments used selected coagulants [aluminum chloride (AlCl3), ferric chloride (FeCl3), polyaluminum chloride (PAC), and polyacrylamide (PAM)] to determine the effects of coagulant type, dosage, and dosing sequence. Sequential addition of a metal coagulant followed by PAM provided enhanced floc formation and improved downstream filtration performance. The integrated pretreatment process was evaluated as a function of feed flow rate, convective residence time, coagulant dosage, and sequential coagulant–flocculant conditions. Among the coagulant–flocculant systems investigated, sequential AlCl₃–PAM dosing provided enhanced floc formation, with hydrocyclone turbidity reduction approaching 90% and suspended matter removal approaching 80%, substantially reducing the particulate mass transferred to downstream microfiltration. At selected coagulant and flocculant doses of 12 mg/L Al³⁺ and 9 mg/L PAM, determined from the inline coagulation and hydrocyclonic separation experiments, the integrated process provided a final filtrate turbidity of ~0.03 NTU using a 1 µm microfilter and ~0.30 NTU using a 5 µm microfilter, both substantially below the 1 NTU RO feedwater target. In comparison, when raw water with a turbidity of ~2.5 NTU was directly filtered using 1 and 5 µm microfilters, the resulting filtrate turbidities were ~1.2 and ~1.5 NTU, respectively. Thus, direct filtration of untreated water using either pore size did not achieve the target RO feedwater turbidity threshold. Effective floc formation and separation were achieved within short convective residence times, representing more than a 70% reduction relative to conventional coagulation–sedimentation pretreatment. Overall, the results demonstrate that rapid inline coagulation coupled with hydrocyclonic separation can remove suspended particulate matter before downstream filtration. Importantly, achieving the targeted RO feedwater turbidity (&amp;lt;1 NTU) using a 5 µm microfilter demonstrates the potential to reduce dependence on finer downstream filtration, supporting the development of a compact, continuous pretreatment approach for RO-based water reuse applications.</dc:description><dc:subject>Chemical engineering</dc:subject><dc:subject>Materials science</dc:subject><dc:subject>Hydraulic engineering</dc:subject><dc:subject>Hydrocyclonic seperation</dc:subject><dc:subject>Inline Coagulation</dc:subject><dc:subject>Microfilteration</dc:subject><dc:subject>RO feed pretreatment</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1fj6q041</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8p5019qj</identifier><datestamp>2026-09-16T06:40:23Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8p5019qj</dc:identifier><dc:title>High-throughput Fiber-coupled Plasmonic Terahertz Spectroscopy Systems</dc:title><dc:creator>Jiang, Xinghe</dc:creator><dc:contributor>Jarrahi, Mona</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>Terahertz time-domain spectroscopy (THz-TDS) has become a vital tool in biomedical diagnostics, security screening, and non-destructive inspection. Terahertz photon energies match molecular rotational and vibrational transitions yet remain non-ionizing, allowing samples to be probed without damage. By coherently measuring the terahertz electric field in the time domain, THz-TDS extracts a material's complex refractive index over a broad frequency range. Conventional systems, however, are built around free-space femtosecond lasers and mechanical delay lines, making them bulky, alignment-sensitive, and confined to specialized laboratories.During my doctoral studies, I designed and built two fiber-coupled THz-TDS architectures that address these limitations. The first is a compact, telecom-compatible system based on bias-free plasmonic photoconductive nanoantenna arrays, driven by a femtosecond fiber oscillator and a custom pair of polarization-maintaining fiber amplifiers. A fiber-coupled motorized delay line rapidly scans the pump–probe delay, and real-time readout of the stage position compensates for timing errors introduced by high-speed motion, enabling reliable, high-throughput measurements in a small footprint. Operating at 1550 nm, however, imposes a trade-off, since the narrow bandgap of photo-absorbing substrates results in low dark resistance levels, which degrade the radiation efficiency of photoconductive sources and the detection sensitivity of photoconductive detectors used in THz-TDS systems.The second system is designed to operate at 800 nm, where wider-bandgap, higher-dark-resistance photo-absorbing substrates enable higher-performance photoconductive terahertz sources and detectors. Hollow-core anti-resonant fiber delivers high-power femtosecond pulses almost entirely through air, avoiding pulse broadening from chromatic dispersion and nonlinear distortion. The resulting system, the first fiber-coupled high-optical-power THz-TDS system operating at 800 nm, uses plasmonic nanoantenna arrays for terahertz generation and detection, offering significantly higher dynamic ranges compared with commercially available fiber-coupled THz-TDS systems.Finally, a developed THz-TDS system based on plasmonic nanoantenna arrays is integrated with deep neural networks for pixel-level identification and classification of pharmaceuticals and explosives. Using a pulse-based chemical classification method resilient to environmental variations and sample inconsistencies, the system achieved an average accuracy of 88.83% in identifying concealed chemicals beneath opaque paper, demonstrating strong generalization and highlighting the promise of pairing terahertz spectroscopy with neural networks for sensitive and specific chemical detection in operationally relevant settings.</dc:description><dc:subject>Electrical engineering</dc:subject><dc:subject>Computer engineering</dc:subject><dc:subject>Biomedical engineering</dc:subject><dc:subject>Nanoscience</dc:subject><dc:subject>Terahertz</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8p5019qj</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt66x7k46k</identifier><datestamp>2026-09-16T06:40:19Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt66x7k46k</dc:identifier><dc:title>Sarcospan Gene Therapy as a Treatment for Duchenne Muscular Dystrophy</dc:title><dc:creator>Nelson, Donovan King</dc:creator><dc:contributor>Crosbie, Rachelle H</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>Duchenne muscular dystrophy (DMD) is a progressive muscle disease caused by loss of dystrophin, resulting in destabilization of the dystrophin-glycoprotein complex and increased susceptibility of the sarcolemma to contraction-induced damage. Sarcospan (SSPN) is a small transmembrane protein associated with multiple laminin-binding adhesion complexes, and transgenic SSPN overexpression has previously been shown to improve sarcolemmal stability and dystrophic pathology in mdx mice. The present study evaluated adeno-associated virus (AAV)-mediated delivery of SSPN as a strategy to increase SSPN expression and support compensatory cell–matrix adhesion in dystrophin-deficient skeletal muscle. Neonatal mdx mice received systemic MyoAAV4E-SSPN or saline by temporal vein injection at postnatal day 2 or 4, and quadriceps muscle was collected at 11 weeks of age. AAV-mediated SSPN expression was evaluated by immunofluorescence and immunoblotting, while vector genome abundance was assessed by quantitative PCR. Co-immunofluorescence was used to examine SSPN localization alongside utrophin and β1D integrin. Central nucleation and intracellular IgG accumulation were evaluated as indicators of dystrophic pathology and sarcolemmal membrane damage, respectively. AAV-mediated delivery produced detectable SSPN expression and sarcolemmal localization in dystrophin-deficient skeletal muscle, although SSPN protein levels varied substantially among individual animals and ranged from approximately 3.6% to 58.8% of wild-type levels. Vector genome abundance also varied considerably and was not significantly associated with SSPN protein expression. SSPN localized at the sarcolemma alongside utrophin and β1D integrin, although changes in the abundance or recruitment of these compensatory adhesion proteins were not quantitatively evaluated. Sarcolemmal SSPN fluorescence was similarly variable and was not significantly associated with total SSPN protein expression measured by immunoblot. Increased SSPN expression was not significantly associated with either central nucleation or the number of IgG-positive myofibers. Together, these findings demonstrate the feasibility of using MyoAAV4E-mediated delivery to introduce SSPN into dystrophin-deficient skeletal muscle while identifying substantial variability in vector abundance and SSPN expression as important limitations of the current approach. The relatively low SSPN expression achieved may have limited the ability to detect improvements in dystrophic pathology. Further optimization of AAV-SSPN delivery to achieve higher and more consistent SSPN expression will be necessary to determine whether AAV-mediated SSPN delivery can reproduce the therapeutic benefits previously demonstrated with transgenic SSPN overexpression.</dc:description><dc:subject>Physiology</dc:subject><dc:subject>Biology</dc:subject><dc:subject>Genetics</dc:subject><dc:subject>Adeno-associated virus</dc:subject><dc:subject>Duchenne muscular dystrophy</dc:subject><dc:subject>Gene therapy</dc:subject><dc:subject>Sarcolemmal stability</dc:subject><dc:subject>Sarcospan</dc:subject><dc:subject>Skeletal muscle</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/66x7k46k</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt53s9p3mq</identifier><datestamp>2026-09-16T06:40:14Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt53s9p3mq</dc:identifier><dc:title>Educator as Learner: The Role of Transformative Learning in Elevating Faculty Work and Experiences</dc:title><dc:creator>Choe, Catherine</dc:creator><dc:contributor>Rios-Aguilar, Cecilia</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>The purpose of this study was to explore how faculty working in a First Year Experience (FYE) program at a California community college perceived their role as an educator, as well as how participation in FYE affected pedagogical approaches and the creation and sustainment of communities of teaching and communities of practice. This study used Mezirow’s (1991) theory of transformative learning as its overarching theoretical framework, supplemented by Habermas’ (1981) theory of communicative action and learner-centered approaches (Baxter &amp;amp; Gray, 2002; Warmer, 2001), to guide its examination of faculty approaches to instructional strategies, serving as channels for them to become institutional change agents and contribute to pedagogical change at the departmental, institutional, and disciplinary levels. This qualitative single-site case study consisted of interviews and classroom observations with 15 faculty housed within the FYE program at Bay College, in addition to document analysis of their course syllabi and an observation of the FYE faculty meeting that semester. The study’s findings highlighted how participants built communities of practice in FYE, namely through exchanging syllabi and sharing common themes and assignments, which led to interdisciplinary collaborations anchored by strong leadership. Participants were also able to find and foster these communities through formal and informal professional development and mentorship opportunities. However, many participants found college leadership treatment of faculty during contract negotiations to be dismissive and disrespectful, which contrasted complimentary surface-level messaging on campus. Participants cited inequitable allocations of work, such as through increased classroom caps and enforced unnecessary days on campus, that signaled distrust towards faculty and a fundamental misunderstanding of their work. Thus, I propose a model based on the study’s findings that showcases the mutuality of faculty-student learning as facilitated through a structured support program incentivizing collaboration within an institutional context, such as FYE. The study’s findings reveal the need for administration to be more receptive to qualitative indicators of success, such as individual student stories, in measuring outcomes away from purely numbers-driven criteria, in addition to offloading excess faculty work and providing legislative guidance that can help facilitate parallel trajectories of educator and student growth.</dc:description><dc:subject>Higher education</dc:subject><dc:subject>Pedagogy</dc:subject><dc:subject>Community college education</dc:subject><dc:subject>Communities of practice</dc:subject><dc:subject>Community colleges</dc:subject><dc:subject>Faculty identity</dc:subject><dc:subject>First Year Experience</dc:subject><dc:subject>Pedagogical change</dc:subject><dc:subject>Transformative learning</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/53s9p3mq</dc:identifier><dc:identifier>https://escholarship.org/content/qt53s9p3mq/qt53s9p3mq.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5910s632</identifier><datestamp>2026-09-16T06:40:08Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5910s632</dc:identifier><dc:title>Counterion Effects in Fluorous Fluorophores: From Fundamental Studies to Multimodal Fluorescence Imaging</dc:title><dc:creator>Lin, Helen</dc:creator><dc:contributor>Sletten, Ellen M</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>Fluorescence imaging of perfluorocarbons (PFCs) requires fluorophores that are soluble in the fluorous phase, a class of molecules termed fluorofluorophores. While fluorofluorophores enable visualization of PFCs across biological systems, the low dielectric constant and high oxygen solubility of the fluorous phase substantially diminish their brightness and photostability. This dissertation demonstrates that counterion identity, an often-overlooked structural feature of cationic fluorophores, is a potent and generalizable handle for overcoming these limitations, exploiting the uniquely strong ion-pairing environment of the fluorous phase to modulate fluorophore electronics without altering the covalent chromophore scaffold. Beginning with a foundational cyanine system and extending to near-infrared, shortwave infrared, and rhodamine-based fluorofluorophores, this work establishes design principles for counterion-based fluorophore optimization and translates these improvements into diverse biological imaging applications, concluding with an initial effort to develop a fluorous-soluble singlet oxygen probe for quantitative singlet oxygen sensing.
      Chapter One is a perspective on the fundamental physicochemical properties of perfluorocarbons and their resulting utility in biomedicine, including oxygen delivery, drug delivery, and diagnostic imaging. The development of fluorofluorophores is introduced, along with the persistent photophysical challenges, diminished brightness, accelerated photobleaching, and aggregation, that arise from fluorophore solubilization in the non-polarizable, oxygen-rich fluorous phase.
      Chapter Two describes counterion exchange as a strategy to enhance the brightness and photostability of a fluorous pentamethine cyanine dye (FCy5). Exchanging the native chloride counterion for bulkier, fluorinated aryl borate anions promotes the ideal polymethine state, increasing brightness up to 6-fold and photostability up to 55-fold. Mechanistic studies attribute the photostabilization primarily to counterion-dependent modulation of intersystem crossing rather than steric protection of the polymethine chain, establishing a framework for understanding counterion effects on both brightness and photodegradation.
      Chapter Three extends this counterion exchange strategy to two near-infrared heptamethine cyanine fluorofluorophores, achieving up to 10-fold brightness and 60-fold photostability enhancements in perfluorooctyl bromide. These improvements are translated across increasingly complex biological models, including imaging of perfluorocarbon nanoemulsion uptake in macrophages, visualization of ferrofluid droplet actuation for mechanobiology studies in zebrafish, and high-resolution shortwave infrared vasculature imaging in mice, demonstrating that solution-phase counterion effects reliably transfer to in vivo imaging performance.
      Chapter Four reports the first systematic investigation of counterion effects on the one- and two-photon photophysical properties of a fluorous rhodamine dye. Unlike the centrosymmetric polymethine scaffold, rhodamine symmetry is governed by the dihedral angle between a pendant phenyl ring and the xanthene core, a conformational parameter shown to be tunable by counterion identity in addition to the electronic distribution within the xanthene core. Two-photon spectroscopy resolves counterion-dependent changes in molecular symmetry that are not apparent from one-photon measurements alone, further establishing a correlation between the molecular symmetry of rhodamines and their brightness. The brightest counterion-exchanged derivative is then applied to two-photon imaging of oil droplet force sensors in mouse embryos, enabling deepertissue imaging and successful three-dimensional reconstruction in previously inaccessible anatomical regions.
      Chapter Five describes preliminary efforts to develop a fluorous-soluble singlet oxygen probe, Singlet Oxygen Fluorous Rhodamine (SOFR), by appending an anthracene quenching moiety to the rhodamine scaffold characterized in Chapter Four. SOFR exhibits a dose-dependent fluorescence turn-on in response to singlet oxygen and qualitatively reproduces established trends in singlet oxygen generation among fluorous photosensitizers. Quantitative benchmarking against singlet oxygen phosphorescence, however, reveals that the extent of anthracene-mediated fluorescence quenching limits the probe's dynamic range, identifying a clear target for future probe optimization and underscoring the continued need for fluorous-compatible tools to quantify photosensitizer performance within the fluorous phase.</dc:description><dc:subject>Chemistry</dc:subject><dc:subject>Organic chemistry</dc:subject><dc:subject>Bioengineering</dc:subject><dc:subject>Biological Imaging</dc:subject><dc:subject>Counterion</dc:subject><dc:subject>Fluorescence</dc:subject><dc:subject>Fluorofluorophore</dc:subject><dc:subject>Perfluorocarbon</dc:subject><dc:subject>Photophysics</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5910s632</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3j41m6b9</identifier><datestamp>2026-09-16T06:40:03Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3j41m6b9</dc:identifier><dc:title>Machine Learning Algorithm Application and Development for Predicting and Understanding Organic Reactivity</dc:title><dc:creator>Min, Daniel Seungwook</dc:creator><dc:contributor>Doyle, Abigail G</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>Chapter 1 reports a method for a stereoconvergent synthesis of trisubstituted alkenes in two steps from simple ketone starting materials. The key step is a nickel-catalyzed reduction of the corresponding enol tosylates that predominantly relies on a monophosphine ligand to direct the stereoconvergent formation of either the E- or Z-trisubstituted alkene products. Reaction optimization was accomplished using a data science workflow including monophosphine training set design, statistical modeling, and multiobjective Bayesian optimization. The optimization campaign significantly improved access to both the E- and Z-trisubstituted products in up to ∼90:10 diastereoselectivity and &amp;gt;90% yield. After identifying superior ligands using training set design, only 25 reactions were required for each objective (E- and Z-isomer formation) to converge on improved reaction parameters from a search space of ∼30,000 potential conditions using the EDBO+ platform. Additionally, a hierarchical machine learning model was developed to predict the stereoselectivity of untested monophosphine ligands to achieve a validation mean absolute error (MAE) of 7.1% selectivity (0.21 kcal/mol). Ultimately, we present a synergistic data science workflow leveraging the integration of training set design, statistical modeling, and Bayesian optimization, thereby expanding access to stereodefined trisubstituted alkenes.Chapter 2 reports end-to-end computational pipeline for the structural modeling, analysis, and visualization of ternary complexes in targeted protein degradation (TPD). TPD provides access to a large previously considered ‘undruggable’ portion of the human proteome. Computational methods offer the ability to probe the ligand binding pose and predict structural ensembles without the experimental constraints required for biophysical techniques such as X-ray crystallography or cryogenic electron microscopy. However, there remains a critical need for high-throughput, automated tools capable of accurately predicting and analyzing ternary complex structures that underlie TPD mechanisms. The workflow presented in this work ensures ease of use and lowers the barrier to entry for non-expert users, while maintaining flexibility for advanced applications. The pipeline is broadly applicable to any E3 ligase and is generalizable across different degradation modalities, including both PROTACs and molecular glues. We demonstrate its utility through case studies involving IKZF1 and GSPT1 in complex with cereblon, underscoring its potential to accelerate the evaluation of candidate degraders and to streamline structure-based design in targeted protein degradation research.Chapter 3 reports the development of an undergraduate organic chemistry laboratory to introduce students to modern applications of data science tools and machine learning algorithms in organic chemistry. Data science and machine learning have become increasingly applied to organic chemistry systems built upon physical organic principles of reactivity to better analyze and interpret data. Given that postexperimental analysis is central to any scientific study, we envision&amp;nbsp;that the incorporation of these techniques at an introductory level into the undergraduate chemistry education curriculum will be invaluable in exposing students to contemporary research tools and working with shared data. Herein we describe a two-part experiment, using the experimentally straightforward Claisen–Schmidt aldol condensation reaction with commercially available reagents, to introduce concepts of computational featurization and data processing for multivariate linear regression models at the undergraduate level that can easily be incorporated into organic instructional laboratories.Chapter 4 outlines the prediction of electron density of a molecule using a transformer based model. The electron density of a molecule provides all ground state physical properties of a molecule. Despite this significance, traditional quantum mechanical methods such as density functionary theory are often too expensive for large systems. In this chapter, I implement a transformers-based model, the foundational model used in large language models, to predict the electron density of an organic molecule given the SMILES string and its atomic coordinates. A transformer is chosen as it demonstrated a very strong performance in many fields, including language translation, protein folding, and reaction prediction. The QM96 dataset was used as the trainset, which includes 134k organic molecules consisting of atoms C, H, O, N, and F. A script filtered out files with incorrect formatting, incorrect SMILES strings, and duplicates, yielding approximately 100k molecules. The model was based on the original transformer architecture, with key modifications to accommodate the data structure, such as the continuous electron density values in contrast to the discrete vocabularies predicted in language translation, 3D nature of the electron density, much smaller data size. Interpretability of the model was also analyzed through inspecting the attention weights that give insight to how the transformer exploits the atomic tokens in different chemical contexts.</dc:description><dc:subject>Organic chemistry</dc:subject><dc:subject>Computational chemistry</dc:subject><dc:subject>Artificial intelligence</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3j41m6b9</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6vk1d1zw</identifier><datestamp>2026-09-16T06:39:57Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6vk1d1zw</dc:identifier><dc:title>When is a Model a Method? Architectural Empiricism in Eero Saarinen &amp;amp; Associates, 1948-1961</dc:title><dc:creator>Gu, Jia Yi Yi</dc:creator><dc:contributor>Lavin, Sylvia</dc:contributor><dc:contributor>Osman, Michael</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>This dissertation investigates architectural modelling in the office of Eero Saarinen &amp;amp; Associates as a history of uncodified empiricism—asking how an office working without formal protocols, measurable outputs, or a written record still produced evidence sufficient to move decisions, persuade clients, and claim professional authority. Rather than understanding these practices as craft-based or institutionalized science, the research explores how distinctions disintegrated within the inventive modalities of modelmaking developed in the office. The first chapter traces the office’s transition from presentation models to study models through the Jefferson National Expansion Memorial competition. In a heightened accusation of plagiarism, Saarinen mobilizes models both rhetorically and as evidence of a design process, reframing model-making as an event of iterative discovery. The second chapter examines model-making through the office’s development of thin-shell concrete designs for projects such as TransWorld Airlines Flight Center and Dulles International Airport, where techniques drawn from industrial modeling, topographic mapping, and military crafting position physical models as instruments for discovering form and as a site of production through which Saarinen maintained design decisions as the office and its corporate clientele expanded. The third chapter follows the development of material mock-ups for Deere Administrative Center as a site where ES&amp;amp;A manufactured empirical certainty about a material whose defining architectural value—weathering—had not yet occurred. Across these three commissions, modelmaking emerges as a design method capable of generating its own genres of evidence, through which ES&amp;amp;A managed uncertainty and constructed its own architectural authority.</dc:description><dc:subject>History</dc:subject><dc:subject>Architecture</dc:subject><dc:subject>architectural empiricism</dc:subject><dc:subject>architectural modeling</dc:subject><dc:subject>design method</dc:subject><dc:subject>Eero Saarinen &amp; Associates</dc:subject><dc:subject>postwar corporate architecture</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6vk1d1zw</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8hx9k0nz</identifier><datestamp>2026-09-16T06:39:51Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8hx9k0nz</dc:identifier><dc:title>Homomorphic Directional Beamforming and Near-Field Localization with Analog True Time Delay Arrays</dc:title><dc:creator>Pehlivan, Ibrahim</dc:creator><dc:contributor>Cabric, Danijela</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>Future wireless applications continue the trend of increasingly demanding bandwidth, data rates, and connectivity, forcing systems to operate at higher frequencies to exploit the abundant bandwidth and with more antennas to exploit array gain and beamforming capabilities. However, the increasing array aperture and bandwidth start to challenge the established channel and array response assumptions, and these changing assumptions require both new array architectures and new algorithms suited to the changing channel characteristics. First, the frequency dependency of the array can no longer be ignored, requiring true-time-delay (TTD)-based array architectures to enable low-cost frequency-dependent control. Furthermore, as the array aperture grows, more users fall into the near-field region, complicating the beamforming design, since the user channel now depends on both angle and distance. This also complicates localization and beam training, as the search must now be performed over both distance and angle. TTD arrays, originally proposed to overcome the frequency dependency caused by the fixed antenna spacing, have also been utilized to realize split beampatterns which map subbands to different spatial regions, allowing the serving of multiple users at different angles with only a single RF chain. However, current algorithms for split beampattern generation either require high computational complexity or memory, or cannot operate under frequency dependency, while heuristic models are restricted and reduce usability. In Chapter 2, we propose a fast and efficient split beampattern synthesis algorithm based on the mathematical structure of the split-beam synthesis problem, which requires only a fixed generator beampattern dictionary, resulting in a low-cost alternative that also provides fairness. However, the parameters of the proposed algorithm are not optimized for the average received power. In Chapter 3, we propose a data-driven parameter optimization approach for the proposed algorithm to maximize the average received power, and show that the optimized algorithm matches a low-complexity state-of-the-art benchmark algorithm while providing a fairer power distribution among subbands. Likewise, the near-field beam training problem is addressed in Chapter 4, where we show that, by utilizing TTD arrays and a special configuration called rainbow beams, we can virtually partition the array into far-field-operating sub-arrays, recover each sub-array’s signal in post-processing, determine each sub-array’s angle, and localize the user with triangulation. Therefore, this thesis provides strong solutions to the rising challenges of next-generation wireless systems by addressing both of the changing assumptions.</dc:description><dc:subject>Electrical engineering</dc:subject><dc:subject>Computer engineering</dc:subject><dc:subject>Information technology</dc:subject><dc:subject>homomorphic directional beamforming</dc:subject><dc:subject>near-field localization</dc:subject><dc:subject>split beampattern syhthesis</dc:subject><dc:subject>true-time-delay arrays</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8hx9k0nz</dc:identifier><dc:identifier>https://escholarship.org/content/qt8hx9k0nz/qt8hx9k0nz.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3tq9f8k8</identifier><datestamp>2026-09-16T06:39:47Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3tq9f8k8</dc:identifier><dc:title>Investigating how the transcriptional control of CCA1 expression shapes plant physiology</dc:title><dc:creator>bashor, tyler dalton</dc:creator><dc:contributor>Pruneda-Paz, Jose</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>The Arabidopsis thaliana circadian clock coordinates metabolism and development with environmental conditions and is controlled in part by the transcription factor CIRCADIAN CLOCK ASSOCIATED 1 (CCA1). Prior studies characterized the role of CCA1 in plant physiology by using lines carrying CCA1 loss-of-function and gain-of-function alleles, thus missing how subtle modifications of CCA1 expression may influence plant functions. As CCA1 expression largely relies on the CCA1 gene promoter activity, we hypothesized that changes to this regulatory region may result in uniquely altered CCA1 expression patterns and provide novel mechanistic insights to understand how CCA1 regulates plant growth and development. Here, we&amp;nbsp;used CRISPR-Cas9 genome editing to perform a targeted deletion of the CCA1 promoter, and analyzed its impact on the CCA1 promoter activity, as well as circadian function, plant growth and development. Our results show that the targeted deletion in the mutant characterized in this study, results in unique clock and plant development phenotypes, which we anticipate may inform on the mechanisms underlying clock control of plant physiology.</dc:description><dc:subject>Biology</dc:subject><dc:subject>Physiology</dc:subject><dc:subject>Plant sciences</dc:subject><dc:subject>Genetics</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3tq9f8k8</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8j578806</identifier><datestamp>2026-09-16T06:39:42Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8j578806</dc:identifier><dc:title>The natural history of an abundant soil bacterium: Niche differentiation and adaptation of Curtobacterium</dc:title><dc:creator>Barron Sandoval, Alberto</dc:creator><dc:contributor>Martiny, Jennifer B.H.</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Microbial communities play an essential role in sustaining ecosystem processes and life on Earth. As such, the field of microbial ecology has gradually shifted from establishing taxonomic patterns of distribution to identifying the traits that dictate where different microorganisms live to isolating the eco-evolutionary processes that create and maintain these patterns. Yet our understanding of these matters still largely reflects broad taxonomic levels. For soil bacteria in particular, most studies rely on highly conserved markers (e.g., the 16S rRNA gene). However, genomic variation at these scales overlooks substantial trait divergence that is potentially ecologically relevant. As a result, our understanding of how closely related lineages, akin to bacterial species, partition the soil environment and assemble into communities remains limited. In this dissertation I aimed to address this gap by using the Curtobacterium genus, an abundant bacterial taxon in soil leaf litter, as a model organism and ask: 1) How does the distribution of different lineages of Curtobacterium change along environmental gradients? 2) Does the phenotypic characterization of representative isolates of these lineages align with the biogeographic patterns observed? and 3) Are the biogeographic and phenotypic patterns observed a result of local adaptation to combinations of environmental conditions?In the first section of this dissertation, I addressed the first two questions by conducting a large-scale survey on 24 locations across California to capture a wide environmental gradient in terms climate, ecosystems and vegetation types. I collected both grass and dominant-vegetation litter at each site to decouple substrate effects from climate, and isolated Curtobacterium strains from these samples for phenotypic characterization. Using metagenomic sequencing I characterized microbial communities, and applied random forest modeling, distance-based ordination, and lab-based thermal and pH performance curves to link lineages distributions to environmental drivers. Overall Curtobacterium abundance was primarily predicted by both litter chemistry (cellulose content) and climate. The four most abundant ecotypes (lineages) exhibited distinct biogeographic patterns: ecotype IIIA was more abundant in cooler, wetter sites with lignin-rich litter, while ecotypes IC and IVB were associated with warmer, drier conditions, and ecotype IIG showed broader thermal tolerance. These field patterns were corroborated by phenotypic data, with ecotype IC showing significantly higher temperature and pH optima than IIIA. These results demonstrate that Curtobacterium ecotypes undergo niche partitioning shaped by both climate and litter chemistry and suggest that accounting for heterogeneity in the soil substrate can reveal underlying climate signal.To test whether these biogeographic and phenotypic patterns reflect adaptation, in the second section of this dissertation I addressed the third question by conducting a replicated reciprocal transplant anchored at a focal site in southern California and replicated across a subset of eight sites from the initial survey. I manipulated site (as a proxy of climate), leaf litter substrate and inoculum community origin, to tease apart the effect of these three factors on compositional responses and asses the adaptive response of individual ecotypes to the experimental manipulations. Transplanted communities shifted in composition toward that of the native away community, with both climate and litter substrate chemistry independently driving convergence. These patterns were consistent across two phylogenetic scales: the whole bacterial community and the genus Curtobacterium, for which independent biogeographic and phenotypic evidence supports ecotypic differentiation along the same environmental axes. Specifically, the four most abundant Curtobacterium ecotypes shifted in relative abundance across transplant paths in directions predicted by their thermal preferences and biogeographic distributions, suggesting that community-level convergence reflects the sorting of evolutionarily differentiated lineages rather than stochastic assembly. Together, these results demonstrate that leaf litter bacterial communities are locally adapted to both climate and litter substrate chemistry and establish community-level convergence as a metric for detecting local adaptation in microbial systems where individual-level approaches remain infeasible. As microbial communities underpin critical ecosystem processes including decomposition and nutrient cycling, understanding the eco-evolutionary mechanisms that structure their diversity across environmental gradients has important implications for predicting how these processes will respond to ongoing environmental change.</dc:description><dc:subject>Ecology</dc:subject><dc:subject>Microbiology</dc:subject><dc:subject>Molecular biology</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8j578806</dc:identifier><dc:identifier>https://escholarship.org/content/qt8j578806/qt8j578806.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4wt1r6kv</identifier><datestamp>2026-09-16T06:39:37Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4wt1r6kv</dc:identifier><dc:title>Conserved functions of the stomatal CO2-sensing subunit HIGH LEAF TEMPERATURE 1 kinase in rice</dc:title><dc:creator>Huynh, Sarah</dc:creator><dc:contributor>Schroeder, Julian I</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Stomata are pores located in the plant epidermis that play a pivotal role in maintaining the balance of CO2 intake and transpired water loss. In Arabidopsis, mutation of the Raf-like protein kinase HIGH LEAF TEMPERATURE 1 (HT1) severely impairs low CO2-induced stomatal opening response and reduces stomatal conductance without disruption to abscisic acid (ABA)-mediated stomatal closing, making HT1 a potential target for improving water use efficiency in crops. In Arabidopsis, HT1 interacts with MITOGEN ACTIVATED PROTEIN KINASE 12 and 4 (MPK12/4) to form the main stomatal CO2 sensor. Here, targeted mutagenesis of HT1.1 and HT1.2 in Oryza sativa ssp. Kitaake (rice) was used to determine if HT1 function is conserved in the two closest rice homologs of Arabidopsis HT1. Infrared thermal imaging and time-resolved gas exchange show ht1.1/1.2 double mutants displayed elevated leaf temperatures and an impaired CO2 stomatal response, while ht1.1 single mutants are comparable to wild-type. Split luciferase complementation indicated stronger interaction between rice HT1.2 and rice MPK2, the closest homolog to AtMPK12/4. Assimilation rate in ht1.1/1.2 double mutants decreased at higher light intensity compared to wildtype, but additional photosynthetic metrics and plant growth analyses revealed no significant differences between ht1 mutants and wildtype under growth room conditions. These results underscore the conserved function of HT1 in a C3 grass species and support previous findings that HT1 is a promising target in developing crop varieties with improved performance under water-limited conditions.</dc:description><dc:subject>Plant sciences</dc:subject><dc:subject>Cellular biology</dc:subject><dc:subject>Physiology</dc:subject><dc:subject>Genetics</dc:subject><dc:subject>CRISPR/Cas9</dc:subject><dc:subject>HIGH LEAF TEMPERATURE 1</dc:subject><dc:subject>Kitaake rice</dc:subject><dc:subject>Plant physiology</dc:subject><dc:subject>Water Use Efficiency (WUE)</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4wt1r6kv</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0wb9x85j</identifier><datestamp>2026-09-16T06:39:32Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0wb9x85j</dc:identifier><dc:title>Deep Circulation, Contaminant Mobility, and Seafloor Observations in San Pedro Basin, CA</dc:title><dc:creator>Kreitzer, Zachary Austin</dc:creator><dc:contributor>Terrill, Eric</dc:contributor><dc:contributor>Merrifield, Sophia</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>The San Pedro Basin (SPB) is a deep borderland basin in the Southern California Bight containing DDT-contaminated sediments, yet the physical processes governing sediment mobilization, transport, and redistribution remain poorly constrained. This study integrates long-term hydrographic observations from the San Pedro Ocean Time-series (SPOT) with near-bottom mooring measurements to characterize deep-ocean circulation, bottom boundary-layer dynamics, and sediment resuspension potential. Hydrographic observations indicate weak stratification below the 740 m sill and minimal seasonal or interannual variability, consistent with prolonged isolation of deep-basin waters. Relationships between deep-water density, dissolved oxygen, and the Niño 3 index are weak, suggesting limited penetration of ENSO-related variability into the deep basin. Near-bottom Acoustic Doppler Current Profiler (ADCP) measurements show that bottom current variability is dominated by semidiurnal tides, with secondary contributions from diurnal and near-inertial motions. Estimated bed shear stresses were generally weak, with intermittent spring tide maxima approaching theoretical erosion thresholds. Comparisons with cohesive sediment erosion models suggest that widespread resuspension is unlikely under typical conditions. Seafloor imagery collected at the sediment core locations shows evidence of biogenic activity, suggesting a potential pathway for sediment suspension and subsequent water column transport, in addition to the potential for contaminant transfer into the marine food web. Together, these results suggest that deep SPB circulation is dominated by weak tidal forcing that intermittently enhances bottom shear stress while promoting long-term retention of contaminated sediments within the basin.</dc:description><dc:subject>Physical oceanography</dc:subject><dc:subject>Geophysics</dc:subject><dc:subject>Environmental science</dc:subject><dc:subject>DDT</dc:subject><dc:subject>resuspension</dc:subject><dc:subject>San Pedro Basin</dc:subject><dc:subject>Shear Stress</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0wb9x85j</dc:identifier><dc:identifier>https://escholarship.org/content/qt0wb9x85j/qt0wb9x85j.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5591v9v8</identifier><datestamp>2026-09-16T06:39:27Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5591v9v8</dc:identifier><dc:title>LNG1-induced cellular hyper-elongation alters leaf shape and mesophyll development in Arabidopsis thaliana true leaves</dc:title><dc:creator>Mayer, Kurt Matias</dc:creator><dc:contributor>Muroyama, Andrew</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>In Arabidopsis thaliana, epidermal pavement cells form interlocking patterns that control overall leaf shape, while spongy mesophyll cells create air spaces that enable efficient gas exchange for photosynthesis. Cortical microtubules are a major determinant of cell shape and guide expansion during growth. The TON-TRM-PP2A (TTP) complex stabilizes microtubules, and overexpression of LONGFOLIA 1 (LNG1) causes cells to preferentially expand along the leaf’s proximodistal axis, producing elongated leaves. In contrast, OVATE FAMILY PROTEIN 2 (OFP2) regulates elongation in the transverse direction, resulting in shorter, wider leaves when overexpressed. While the effects of LNG1 and OFP2 overexpression on epidermal cell morphology have been previously studied, the biological mechanisms underlying directional control of cell expansion are not fully elucidated. In particular, the impact of ectopic stabilization of cortical microtubules on the mesophyll remains unknown. To identify additional mechanisms associated with cell expansion, we compared the transcriptomes derived from true leaves overexpressing LNG1. We found several phytohormone-related pathways were downregulated upon LNG1 overexpression, implying that hormone signaling may be involved in the observed cell elongation phenotype. Additionally, we measured how LNG1 and OFP2 overexpression altered epidermal and spongy mesophyll cell expansion. We found that cells overexpressing LNG1 were significantly smaller than their wild-type counterparts; notably spongy mesophyll cells were smaller and more rounded, suggesting a potential role for LNG1 in mesophyll microtubule alignment. Moreover, we identified that OFP2-overexpression did not significantly affect cell size or change mesophyll morphology. We propose that phytohormones may facilitate anisotropic cell expansion, and LNG1 may impact spongy mesophyll development.</dc:description><dc:subject>Cellular biology</dc:subject><dc:subject>Microbiology</dc:subject><dc:subject>Biochemistry</dc:subject><dc:subject>Expansion</dc:subject><dc:subject>LNG1</dc:subject><dc:subject>OFP2</dc:subject><dc:subject>TTP</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5591v9v8</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt16v4776n</identifier><datestamp>2026-09-16T06:39:22Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt16v4776n</dc:identifier><dc:title>Associations between baleen whale acoustic occurrence and oceanographic conditions near the South Shetland Islands, Antarctica</dc:title><dc:creator>Schriber, Nicole</dc:creator><dc:contributor>Baumann-Pickering, Simone</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>The Antarctic Peninsula is undergoing rapid environmental change while several baleen whale species continue to recover from historical exploitation. Understanding how whales respond to this dynamic ecosystem is therefore important for identifying the environmental processes that shape feeding habitat. This study examines the acoustic occurrence of humpback (Megaptera novaeangliae), fin (Balaenoptera physalus), and blue whales (B. musculus) near the South Shetland Islands across three site-year deployments between 2014 and 2016. Passive acoustic recordings were used to quantify humpback whale song and non-song vocalizations, fin whale 20 Hz calls, and blue whale Z- and D-calls. Generalized additive models related acoustic occurrence to environmental variables describing mesoscale circulation, hydrography, primary productivity, and sea ice. Acoustic patterns differed between species, call types, and sites. Fin whale calling showed the clearest seasonality, blue whale Z-calls were persistent year-round, blue whale D-calls occurred in brief episodic events, and humpback whale acoustic occurrence varied strongly among sites. Final models explained 22-69% of deviance, and environmental relationships were predominantly nonlinear. Finite-size Lyapunov exponent (FSLE) magnitude, orientation, or both were retained in 10 of 12 models, making mesoscale structure the most consistently selected environmental component. Chlorophyll a was significant in nine models, while temperature, salinity, and dissolved oxygen anomalies, particularly at 130-222 m, were also frequently retained. These results suggest that baleen whale acoustic occurrence near the South Shetland Islands is associated with interacting patterns of mesoscale circulation, water mass variability, productivity, sea ice, and species- or behavior-specific habitat use.</dc:description><dc:subject>Biological oceanography</dc:subject><dc:subject>Wildlife conservation</dc:subject><dc:subject>Ecology</dc:subject><dc:subject>Conservation biology</dc:subject><dc:subject>Antarctica</dc:subject><dc:subject>cetaceans</dc:subject><dc:subject>habitat modeling</dc:subject><dc:subject>mysticetes</dc:subject><dc:subject>passive acoustic monitoring</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/16v4776n</dc:identifier><dc:identifier>https://escholarship.org/content/qt16v4776n/qt16v4776n.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt23z6g10r</identifier><datestamp>2026-09-16T06:39:17Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt23z6g10r</dc:identifier><dc:title>Large-Scale Multi-Physics Topology Optimization with the Level Set Method</dc:title><dc:creator>Jauregui, Carolina Miranda</dc:creator><dc:contributor>Kim, Hyunsun Alicia</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>There are two main types of topology optimization techniques: density-based methods (DTO) and boundary-based methods–the most popular of which are level set methods (LSTO). DTO is very straightforward to implement, but can have difficulties with getting rid of grey densities for clear 0-1 results. Level set topology optimization, due to being a boundary-based method, has a clear definition of the boundary, but has a reputation for being slow to converge, inefficient, and difficult to implement. This work seeks to prove that these drawbacks can be resolved with applying appropriate implementations of the level set method and structuring the methodology in such a way that different techniques for sensitivity calculations can be used.This dissertation presents a modular, large-scale, and multi-physics level set topology optimization method. Its five main contributions are: (1) Large-scale efficient level set topology optimization, (2) an exploration on the impact of different objective functions on thermoelastic topology optimization problems, (3) a modularized general description of topology optimization, (4) guidelines for making findable, accessible, interoperable, and reusable research software, and (5) large-scale multi-physics level set topology optimization software.      Hay dos tipos de técnicas de optimización topológica: métodos basados en densidad (DTO) y métodos basados en la forma del diseño. El más popular de los métodos de la forma son los métodos del conjunto de nivel (LSTO). DTO tiene una implementación muy directa pero puede tener dificultades en deshacerse de densidades grises para tener resultados claros que son de 0 o 1. LSTO, por ser un método basado en la forma, tiene una clara definición de la forma del diseño, pero también una reputación por ser lenta para converger, ineficiente, y difícil para implementar. Este trabajo busca probar que estos problemas se pueden resolver con la aplicación apropiada de algoritmos para el método del conjunto de nivel y estructurando la metodología en una manera que deja que se puedan usar diferentes técnicas para calcular la derivada.Esta tesis presenta un método de escala grande, multiple físicas, y modular para optimización topológica del método del conjunto de nivel (LSTO). Sus cinco mayores contribuciones son: (1) Eficiente LSTO de grande escala, (2) una exploración del impacto de diferentes objetivos en problemas termoelasticos, (3) una descripción general y modularizado de optimización topológica, (4) una guía para aplicar los principios FAIR de software de investigación, y (5) LSTO software de escala grande y multiple físicas.</dc:description><dc:subject>Engineering</dc:subject><dc:subject>Applied mathematics</dc:subject><dc:subject>Mechanical engineering</dc:subject><dc:subject>large-scale</dc:subject><dc:subject>level set method</dc:subject><dc:subject>multi-physics</dc:subject><dc:subject>OpenMDAO</dc:subject><dc:subject>OpenVDB</dc:subject><dc:subject>topology optimization</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/23z6g10r</dc:identifier><dc:identifier>https://escholarship.org/content/qt23z6g10r/qt23z6g10r.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6rp2676b</identifier><datestamp>2026-09-16T06:39:12Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6rp2676b</dc:identifier><dc:title>The Blemish of a Criminal Record: Criminal Record Stigma, Gendered Labor Markets, and Hiring Discrimination</dc:title><dc:creator>Williams, Taryn Deanne</dc:creator><dc:contributor>Okhuysen, Gerardo</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>An estimated 79 million people in the United States have a criminal record (Sawyer, Nam-Sonenstein, &amp;amp; Wagner, 2026), and each year hundreds of thousands of people leave incarceration and enter a labor market that systematically excludes them (Hwang &amp;amp; Phillips, 2020). Despite decades of research documenting the employment consequences of criminal records, four important questions remain unsettled: which social judgments translate a record into exclusion; whether women with records are judged more harshly than men, as prescriptive gender expectations predict; whether the penalty depends on the gendered structure of the occupational context; and whether the negative inferences a record activates can be countered by information applicants supply. This dissertation addresses these questions across two empirical papers and five studies, combining a correspondence audit, three experiments, and a qualitative content analysis, followed by an integrative general discussion.Chapter 2, Marked and Marginalized: Examining Gendered Hiring Discrimination Against Formerly Incarcerated Job Seekers, takes a field-based approach. Drawing on labor market stratification theory, stigma theory, and the lack of fit framework, it argues that the employment consequences of a criminal record are not uniform but are conditioned by the gendered structure of occupational opportunity. Study 1 is a correspondence audit in which matched pairs of fictitious applicants, one disclosing a criminal record and one not, apply to real masculine-typed and feminine-typed entry-level job postings in Southern California. Pilot data (24 matched pairs) established the feasibility of the procedure. At the July 2026 interim window, applications had been submitted to 247 matched pairs; the 112 pairs with settled outcomes show a directionally consistent record penalty (32.1% vs. 27.7% callbacks), with the gap appearing almost entirely within feminine-typed postings; the remaining pairs were completing their observation windows. Data collection closed under a calendar-based stopping rule documented before the final waves' outcome data were examined, and the dissertation reports the full settled sample of 247 matched pairs. The callback figures above reflect the 112 pairs whose observation windows had closed at the interim analysis; final analyses will use all 247. Study 2 is a directed qualitative content analysis of 2,788 open-ended hiring justifications collected in the Chapter 3 experiments; first-pass coding of the full corpus is complete, with interrater reliability validation underway. Preliminary patterns indicate that a record does not simply lower evaluations but reorganizes the criteria of evaluation, and that feminine-typed job contexts increase the salience of the record itself.Chapter 3, Fitting the Mold? Gender-Typed Jobs, Criminal Record Stigma, and Social Judgment Interventions, takes an experimental approach. Drawing on the Stereotype Content Model and the lack of fit framework, it examines why criminal records lower the evaluations that hiring decision-makers form of applicants, when that damage intensifies, and whether it can be reduced. Across three online experiments with U.S. adults who have experience making or influencing hiring decisions (total N = 2,753), a criminal record consistently reduced hirability through lower perceived warmth and competence, and disaggregating warmth revealed that perceived morality (the component concerning honesty, trustworthiness, and ethical conduct), not sociability (the component concerning friendliness and approachability), carried the warmth-based penalty in all three studies (Study 1, N = 146). Study 2 (N = 1,508) demonstrated that the record penalty is significantly amplified in feminine-typed jobs relative to masculine-typed ones and that this amplification operates specifically through the warmth pathway. Study 3 (N = 1,099) tested two resume-based signals, internal warmth framing and externally validated warmth-related credentials; both improved social judgment perceptions and indirectly increased hirability, but neither reduced the disparity between applicants with and without records. Across all studies, applicant gender did not moderate the record penalty, a consistent, large-sample null that points to job context, rather than applicant gender, as the more consequential structural condition.Chapter 4 integrates the findings across methods, develops the dissertation's contributions to theory on stigma, social judgment, and labor market stratification, and draws out implications for employers, workforce reintegration programs, and policymakers. Together, the chapters identify perceived morality as the operative psychological pathway of criminal record stigma, job gender-type as the structural condition that amplifies it, and applicant-level resume signals as limited but meaningful tools that improve evaluations without closing the underlying gap.</dc:description><dc:subject>Criminology</dc:subject><dc:subject>Sociology</dc:subject><dc:subject>Organizational behavior</dc:subject><dc:subject>Management</dc:subject><dc:subject>Criminal Record Stigma</dc:subject><dc:subject>Formerly Incarcerated Job Seeker</dc:subject><dc:subject>Gender-Typed Occupations</dc:subject><dc:subject>Hiring Discrimination</dc:subject><dc:subject>Perceived Morality</dc:subject><dc:subject>Stereotype Content Model</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6rp2676b</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3tg9c2dg</identifier><datestamp>2026-09-16T06:39:07Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3tg9c2dg</dc:identifier><dc:title>Methods to Reduce Seismic-induced Damage in Reinforced Concrete Core Wall Buildings</dc:title><dc:creator>Lee, Kyoungyeon</dc:creator><dc:contributor>Tsampras, Georgios</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Reinforced-concrete core wall buildings can experience significant structural and nonstructural damage during strong earthquakes due to factors including higher-mode effects, kinematic compatibility between the seismic and gravity load-resisting systems, inter-story drift demands, and residual deformation. This dissertation investigates methods to reduce such damage by controlling horizontal force transfer between floors and the core wall, modifying the gravity-load path, and strategically distributing floor mass along the building height.
      The use of modified friction-based force-limiting connections with predetermined discrete-variable friction forces, termed Modified FDs, in reinforced-concrete core wall buildings was evaluated. Pareto front analysis of parametric simulations of simplified two-dimensional models was used to explore the connection design space. A three-dimensional 18-story core wall building model with experimentally calibrated wall piers was then subjected to 13 design-level bidirectional ground motions. Compared with conventional monolithic connections, the Modified FDs reduced the magnitude and variability of peak floor acceleration, core-wall base shear, base torsional moment, and wall-base strain responses while producing comparable drift demands. Their controlled inelastic response mitigated shear-dominant higher-mode effects without excessive connection deformation.
      A historical overview and state-of-the-art review of suspended-floor building systems was also conducted. In these systems, floors are suspended from the roof or an intermediate level by hangers. A dataset of 87 constructed buildings showed that suspended-floor systems have been used worldwide, including in active seismic regions. The review documented their historical development, architectural, constructional, and structural characteristics, connection details, reported problems, retrofit solutions, and seismic behavior. Floor-to-core connections were identified as a primary factor governing horizontal force transfer, relative displacement, and seismic performance.
      Finally, numerical earthquake simulations of 12-story core wall building models were performed to evaluate the effects of suspended floors, force-limiting floor-to-core connections, and strategic vertical floor mass distributions. Suspended floors enhanced core-wall flexural capacity and reduced peak and residual curvature demands. Lowering the vertical center of floor mass reduced inter-story drift but increased acceleration and shear demands. Force-limiting connections reduced force and acceleration demands without increasing inter-story drift. The combined use of suspended floors, force-limiting connections, and strategic vertical floor mass distribution provided complementary benefits and improved the seismic performance of reinforced-concrete core wall buildings.</dc:description><dc:subject>Engineering</dc:subject><dc:subject>Geological engineering</dc:subject><dc:subject>Architectural engineering</dc:subject><dc:subject>Civil engineering</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3tg9c2dg</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6xt9z3mz</identifier><datestamp>2026-09-16T06:39:01Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6xt9z3mz</dc:identifier><dc:title>Role of TREM2 in regulating myeloid cell immune responses to Toxoplasma gondii infection</dc:title><dc:creator>Debray, Hannah Z</dc:creator><dc:contributor>Lodoen, Melissa B</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Toxoplasma gondii is an intracellular protozoan parasite that infects approximately one-third of the global population and poses a significant threat to immunocompromised individuals and developing fetuses. Effective innate immune responses are essential for limiting parasite replication before adaptive immunity is established, yet the molecular mechanisms coordinating these responses remain incompletely understood. Triggering receptor expressed on myeloid cells 2 (TREM2) is a DAP12-associated receptor best known for its roles in tissue homeostasis and neurodegenerative disease, but its function during acute parasitic infection has remained largely unexplored.This dissertation investigates the role of TREM2 in regulating innate immunity during acute intraperitoneal T. gondii infection. Using TREM2-deficient mice, bone marrow-derived macrophages, bone marrow chimeras, flow cytometry, confocal microscopy, and transcriptomic analyses, we demonstrate that TREM2 is required for effective host defense against acute toxoplasmosis. TREM2 deficiency resulted in increased parasite burden, excessive inflammation, tissue pathology, and reduced survival. Mechanistically, TREM2 promoted macrophage antimicrobial function by enhancing phagocytosis and supporting lysosomal activity through an emergency response kinase (ERK)-dependent pathway. Pharmacological inhibition of ERK partially restored antimicrobial function in TREM2-deficient macrophages, identifying a potential signaling mechanism underlying these defects. In addition, TREM2 coordinated early recruitment of monocytes and neutrophils to the site of infection. Transcriptomic analysis of recruited inflammatory monocytes revealed reduced expression of migration-associated genes, while bone marrow chimera experiments demonstrated that impaired myeloid recruitment was driven by hematopoietic TREM2 deficiency. Collectively, these findings support a model in which TREM2 integrates antimicrobial activity, cellular migration, and inflammatory regulation to coordinate effective innate immune responses during acute T. gondii infection. More broadly, this work suggests that TREM2 functions within cooperative receptor signaling networks that orchestrate multiple aspects of myeloid cell biology, providing new insight into mechanisms of host defense and identifying potential therapeutic targets for infectious and inflammatory diseases.</dc:description><dc:subject>Immunology</dc:subject><dc:subject>Cellular biology</dc:subject><dc:subject>Genetics</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6xt9z3mz</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3z38c2vp</identifier><datestamp>2026-09-16T06:38:56Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3z38c2vp</dc:identifier><dc:title>Electron Microscopy of Dynamic Soft Matter and Nanoscale Materials: Integrating Liquid-Phase Transmission Electron Microscopy, Physics-Based Simulation, and Deep Learning</dc:title><dc:creator>Li, Zhaoxu</dc:creator><dc:contributor>Patterson, Joseph</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Electron microscopy provides direct access to nanoscale structure, but quantitative interpretation is difficult when specimens are dynamic, weakly scattering, surrounded by liquid or vitreous ice, or sampled incompletely. This dissertation develops a traceable framework that combines liquid-phase transmission electron microscopy (LPTEM), cryogenic electron microscopy (cryo-EM), molecular dynamics, multislice image simulation, and deep learning. Across four studies, each conclusion is matched to directly measured image observables and to the reference information actually available.First, electrochemical LPTEM was used to examine FFssFF-derived peptide coacervates through one three-cycle cyclic-voltammetry (CV) recording before electrochemical impedance spectroscopy (EIS) and two three-cycle recordings after EIS in one liquid-cell field. Initial domains were approximately 100–500 nm in projected diameter. Recording A showed no prominent resolved CV peak and minimal morphological change under the combined electrochemical and imaging conditions. The largest qualitative transition occurred across EIS: coacervate boundaries appeared sharper, while numerous smaller, lower-contrast aggregates appeared in the surrounding field. The impedance response had a predominantly capacitive appearance and lacked a resolved charge-transfer semicircle over the measured frequency range. During the subsequent CV recordings, small aggregates progressively diminished and the same four tracked domains lost projected area. Median endpoint area changes were +0.98%, −7.41%, and −20.67% in Recordings A, B, and C, respectively. These observations establish a time-associated sequence of projected morphological change, but they do not isolate bias from electron exposure, identify a unique chemical mechanism, or equate projected contrast with mass or composition. Second, cryo-EM measurements were used to constrain atomistic CSH–CSSC fiber models, which were converted into multislice TEM images for comparison with experiment in a common image domain. The experimentally measured individual-fiber diameter was 5.42 ± 1.55 nm, whereas the defocus-weighted simulated diameter was 4.78 ± 0.66 nm. Systematic simulations showed that defocus and water thickness altered apparent fiber width and contrast. Because the experimental diameter also informed the radial restraint, this agreement is interpreted as an image-domain consistency test rather than independent structural validation. The forward-modeling strategy was then extended to generate 500 physics-informed synthetic TEM image–reference pairs for low-contrast nanofiber segmentation. A U-Net trained exclusively on these data achieved Dice 0.9547, intersection over union 0.9134, and centerline Dice 0.9969 on the 78-image synthetic test set. In unlabeled experimental TEM images, its predictions followed many visually recognizable fiber-like trajectories, providing qualitative correspondence but not a quantitative estimate of experimental accuracy. Finally, TSGNet was evaluated for generating intermediate projections in sparse simulated scanning transmission electron microscopy tilt series. Relative to linear interpolation, TSGNet improved the reported image-level mean-squared error, peak signal-to-noise ratio, and structural similarity. Insertion of the generated projections reduced both surface Chamfer distance and volumetric root-mean-square error relative to matched sparse baselines at every reported nominal tilt increment from 2° to 20° under both simulated configurations. These comparisons were made against a dense-series reconstruction reference and do not establish experimental dose reduction or acquisition-time savings. Collectively, the studies show how synchronized in situ imaging, physically grounded forward simulation, and learning-based inference can extend electron microscopy toward traceable quantitative analysis while preserving the distinction between direct observations, model-based references, synthetic-domain evaluation, and experimental validation.</dc:description><dc:subject>Engineering</dc:subject><dc:subject>Materials science</dc:subject><dc:subject>Biomedical engineering</dc:subject><dc:subject>Nanotechnology</dc:subject><dc:subject>Bioengineering</dc:subject><dc:subject>Electron tomography</dc:subject><dc:subject>Liquid-phase TEM</dc:subject><dc:subject>Machine Learning</dc:subject><dc:subject>TEM</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3z38c2vp</dc:identifier><dc:identifier>https://escholarship.org/content/qt3z38c2vp/qt3z38c2vp.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5876w1b7</identifier><datestamp>2026-09-16T06:38:52Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5876w1b7</dc:identifier><dc:title>Nitrogen-source-specific utilization of biodegradable plastic monomers by heterotrophic marine  bacteria</dc:title><dc:creator>Garcia, Diego</dc:creator><dc:contributor>Barbeau, Katherine</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>In response to the accumulation of plastic waste in the environment, the development of degradable bioplastics as an alternative has been highly sought after, yet should certain bioplastics succeed the non-biodegradable plastics, there may be implications of how the accumulation of this more bioavailable form of plastic impact the carbon cycle, particularly in&amp;nbsp;the marine environment, where nutrient conditions are diverse and play an important biological role in carbon utilization. This Thesis examines the model marine bacterium Alteromonas macleodii ATCC 27126’s ability to utilize 3-Hydroxybutyrate (3HB), a monomer of the bioplastic Polyhydroxybutyrate (PHB) among glucose, galactose, and maltose, components of natural polysaccharides and certain bioplastics, depending on the provision of reduced nitrogen (NH4) or oxidized (NO3). According to Optical Density (OD600) growth curves, cell counts, and respiration determined by the INT Reduction method, 3HB resulted in peak biomass levels comparable to the sugars, but led to slower growth and was less efficiently incorporated into biomass; this may imply that at a metabolic level, PHB, or organic acid-based bioplastics, is more recalcitrant and may sink as Particulate Organic Carbon (POC), but when degraded, less PHB-derived biomass would sink as POC. With the more bioavailable NH4 as the sole nitrogen source, 3HB resulted in higher peak levels of biomass and a marginally higher growth efficiency when compared to NO3, yet the nitrogen-source preference was flipped towards NO3 with the sugars. These results add nuance to designing replete conditions in laboratory studies, as more bioavailable substrates do not innately result in better growth.</dc:description><dc:subject>Microbiology</dc:subject><dc:subject>Chemical oceanography</dc:subject><dc:subject>Plastics</dc:subject><dc:subject>Biogeochemistry</dc:subject><dc:subject>Biogeochemical Cycling</dc:subject><dc:subject>Bioplastic</dc:subject><dc:subject>Carbon Cycling</dc:subject><dc:subject>Carbon Sequestration</dc:subject><dc:subject>Nitrogen Cycling</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5876w1b7</dc:identifier><dc:identifier>https://escholarship.org/content/qt5876w1b7/qt5876w1b7.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8j13h28j</identifier><datestamp>2026-09-16T06:38:47Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8j13h28j</dc:identifier><dc:title>Prickle Stabilizes Polarized Actin-Microtubule Architecture Downstream of Wnt-PCP Signaling During Commissural Axon Guidance</dc:title><dc:creator>Powell, Nathan</dc:creator><dc:contributor>Zou, Yimin</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Precise anterior-posterior (A-P) turning of dorsal spinal commissural axons (DSC) at the spinal cord midline is essential for neural circuit assembly. Here, post-crossing axons are directed into the correct longitudinal pathways that connect distant interneuron networks. After crossing the midline, these axons encounter a Wnt gradient that directs anterior turning through non-canonical Wnt/PCP signaling (Wnt/Planar Cell Polarity). While core PCP proteins such as Dishevelled (Dvl), Frizzled (Fzd), Celsr, and Vangl are required for this guidance decision, it remains unclear how PCP signaling converts these extracellular cues into directed growth. Here, we examined the role of the core PCP protein Prickle (PK) in post-crossing guidance. Conditional deletion (cKO) of PK1 and PK2 in post-mitotic neurons revealed randomized post-crossing trajectories and a significant reduction in coherent anterior turning, indicating PK is required for directional guidance. Analysis of commissural growth cones revealed disrupted localization of core PCP proteins, alongside impaired cytoskeletal organization, including disrupted actin-microtubule coordination and altered distribution of key cytoskeletal-associated proteins such as CLIP1, CLASP1, Myosin V, and Myosin IIB. Together, these findings identify PK as a critical downstream integrator that enables coupling of PCP signaling to cytoskeletal remodeling. Our results support a model in which PK allows for the conversion of extracellular polarity cues into stable asymmetry required for reliable directional extension after midline crossing. Given the broad importance of PCP signaling in nervous system development, these findings may also provide insight into mechanisms underlying neurodevelopmental disorders associated with disrupted neuronal connectivity.</dc:description><dc:subject>Biology</dc:subject><dc:subject>Neurosciences</dc:subject><dc:subject>Biomedical engineering</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8j13h28j</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8fq6s8bt</identifier><datestamp>2026-09-16T06:38:42Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8fq6s8bt</dc:identifier><dc:title>Investigating the Role of Cytoskeletal Dynamics in Polarity-Induced Membrane Curvature in Arabidopsis thaliana</dc:title><dc:creator>Goetz, Madison Erinn</dc:creator><dc:contributor>Muroyama, Andrew</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Polarity domains and the cytoskeleton are fundamental regulators of plant cell morphogenesis. Although interactions between these cellular components have been extensively studied in several plant cell types, their role in shaping stomatal lineage ground cells (SLGCs) remains poorly understood. We investigated the relationship between the BASL/BRX polarity domain, cytoskeletal organization and localized membrane deformation during Arabidopsis thaliana stomatal lineage development. Quantitative membrane curvature analysis revealed that regions of the plasma membrane associated with the BASL/BRX polarity crescent undergo significantly greater outward membrane deformation than non-polarized membrane regions, demonstrating that lobing occurs preferentially within polarized domains. This curvature asymmetry was abolished in basl-2 mutants, indicating that BASL-dependent polarity appears necessary for the spatial bias of membrane deformation within SLGCs.To determine whether cytoskeletal dynamics contribute to this process, membrane curvature was quantified in 1) seedlings treated with drugs that perturb the cytoskeleton and 2) mutants that affect cytoskeletal organization. Disruption of either microtubules or actin filaments significantly reduced polarity-associated lobing, while stabilization treatments altered the magnitude of membrane deformation without eliminating preferential growth within polarized regions. Together these findings demonstrate that localized membrane deformation in SLGC depends on both the establishment of BASL/BRX polarity domains as well as proper cytoskeletal organization. These findings support a model in which polarity domains coordinate cytoskeletal dynamics to direct cell shape changes during epidermal cell development.</dc:description><dc:subject>Biology</dc:subject><dc:subject>Cellular biology</dc:subject><dc:subject>Molecular biology</dc:subject><dc:subject>Epidemiology</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8fq6s8bt</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1m01c21t</identifier><datestamp>2026-09-16T06:38:38Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1m01c21t</dc:identifier><dc:title>A Climatology of Cutoff Lows and their Precipitation Contributions in the U.S. West Coast</dc:title><dc:creator>Hurley, Kyle</dc:creator><dc:contributor>Becker, Janet M</dc:contributor><dc:contributor>Merrifield, Mark A</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>A recently developed cutoff low catalog and a long-term precipitation dataset from 1982 to 2024 were analyzed to examine how cutoff lows contribute to annual and seasonal precipitation variability across the U.S. West Coast (USWC) compared to atmospheric rivers (ARs). Assessments were conducted for three regions: Southern California (SoCal), Northern California (NorCal), and the Pacific Northwest (PNW). On average, 5% of the total precipitation was associated with cutoff lows only, while 48% was associated with ARs only across all three regions. While the relative precipitation contributions from cutoff lows were &amp;lt;5% in the PNW and NorCal, the SoCal region received 9% of its total precipitation from cutoff lows, underscoring their greater importance in SoCal. The PNW and NorCal regions had their peak cutoff low precipitation contributions from May to July, while SoCal’s peak was from September to November. Cutoff lows were most frequent in different regions and months, with SoCal having the most frequent landfalling occurrences. The PNW experienced its highest average cutoff low frequencies from January to May, whereas NorCal had its highest average cutoff low frequencies from March to May, and September to November. SoCal’s highest average cutoff low frequencies occurred between September and November. While the PNW accounted for the largest total precipitation across the USWC, SoCal had the largest share of precipitation associated with cutoff lows. Precipitation from cutoff lows in SoCal accounted for ~41% of all cutoff low precipitation of the USWC, with the PNW accounting for ~26% and NorCal accounting for ~33%.</dc:description><dc:subject>Meteorology</dc:subject><dc:subject>Atmospheric sciences</dc:subject><dc:subject>Thermodynamics</dc:subject><dc:subject>Atmospheric Rivers</dc:subject><dc:subject>Climatology</dc:subject><dc:subject>Cutoff lows</dc:subject><dc:subject>Precipitation</dc:subject><dc:subject>U.S. West Coast</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1m01c21t</dc:identifier><dc:identifier>https://escholarship.org/content/qt1m01c21t/qt1m01c21t.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0rs3p6sg</identifier><datestamp>2026-09-16T06:38:33Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0rs3p6sg</dc:identifier><dc:title>Influence of CRWN Proteins on Nuclear Migration During Asymmetric Cell Division in Arabidopsis thaliana</dc:title><dc:creator>Van Maele, Daniella</dc:creator><dc:contributor>Muroyama, Andrew</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Plants undergo asymmetric cell divisions (ACDs) to generate cell diversity in both shoots and roots. During the development of Arabidopsis thaliana roots and leaves, stereotyped nuclear migrations control ACD orientation. During ACD in the stomatal lineage in the leaf epidermis, nuclear migrations are oriented relative to the position of a polarity domain defined by BASL and BRXf proteins. However, the pathways controlling ACD-associated nuclear migrations have yet to be fully elucidated. CROWDED NUCLEI (CRWN) proteins are essential for maintaining nuclear morphology and genome function. Previous research has shown that mutations in members of the CRWN family decreased stomatal density, raising the possibility that CRWNs can influence nuclear migrations and ACD frequency. To investigate whether CRWNs influence ACD-associated nuclear migrations, we generated crwn mutant plant lines with fluorescent reporters to track nuclear movement and performed live-cell time-lapse imaging during early leaf development to quantify nuclear movement and morphology. We found that nuclear migrations were altered in crwn1, revealing a previously unappreciated role for these proteins in division-associated nuclear migration. In parallel, we conducted lateral root initiation assays to determine if CRWNs are important for lateral root initiation, another developmental process that relies on ACDs. In crwn mutants, we observed significant differences in lateral root emergence, indicating that CRWNs may be important for ACDs in roots as well. By establishing CRWNs as novel regulators of ACDs and nuclear positioning, this work provides new insight into nuclear lamina function and potential pathways for manipulating plant architecture in agricultural settings to combat climate change.</dc:description><dc:subject>Cellular biology</dc:subject><dc:subject>Developmental biology</dc:subject><dc:subject>Plant sciences</dc:subject><dc:subject>Biochemistry</dc:subject><dc:subject>Climate change</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0rs3p6sg</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2wh2p349</identifier><datestamp>2026-09-16T06:38:28Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2wh2p349</dc:identifier><dc:title>Identification and Functional Characterization of Long Non-Coding RNAs Targeting SARS-CoV-2</dc:title><dc:creator>Sun, Amanda</dc:creator><dc:contributor>Rana, Tariq</dc:contributor><dc:contributor>Murre, Cornelis</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Long non-coding RNAs (lncRNAs) regulate gene expression and immune responses, but their roles in host defense against SARS-CoV-2 remain incompletely understood. This study aimed to identify antiviral lncRNAs and investigate their potential mechanisms of action during viral infection. Using a CRISPR activation-based screen in A549-ACE2 human lung epithelial cells, we identified multiple antiviral lncRNA candidates. Among these, LNCD (anonymized)&amp;nbsp;demonstrated the strongest and most consistent antiviral activity. To investigate the mechanism underlying this antiviral phenotype, bulk RNA sequencing was performed and revealed increased expression of IFN signal pathway related genes, with IFNB1, IFNL1, and IFNL3 among the most strongly upregulated genes, suggesting that LNCD may restrict SARS-CoV-2 by regulating interferon signaling. The breadth of LNCD-mediated antiviral activity was further evaluated using additional RNA viruses. LNCD overexpression reduced viral RNA abundance following infection with influenza A virus H1N1, Zika virus, and human coronavirus OC43, accompanied by increased expression of interferon-related genes. In contrast, a conserved 132-nucleotide region of LNCD was found not to reproduce the antiviral effect against SARS-CoV-2 or the other tested RNA viruses, suggesting that the antiviral activity of LNCD may require the full-length transcript. Overall, this study identifies LNCD as a previously uncharacterized antiviral lncRNA with activity against SARS-CoV-2 and multiple RNA viruses. These findings provide insight into lncRNA-mediated regulation of interferon-associated antiviral immunity and establish a foundation for future investigation of LNCD-interacting factors and its potential application in RNA-based antiviral strategies.</dc:description><dc:subject>Biology</dc:subject><dc:subject>Genetics</dc:subject><dc:subject>Immunology</dc:subject><dc:subject>Virology</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2wh2p349</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8jn9t75k</identifier><datestamp>2026-09-16T06:38:22Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8jn9t75k</dc:identifier><dc:title>Fentanyl dependence modulates homeostatic and hedonic feeding behavior</dc:title><dc:creator>Liaw, Leanne</dc:creator><dc:contributor>Telese, Francesca</dc:contributor><dc:contributor>Smith, Monique</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Opioid Use Disorder (OUD) has been a leading driver of overdose mortality in the United States. Chronic opioid use is associated with weight loss and appetite suppression, and clinical studies have noted patients’ longer-term shifts toward weight gain and preference for high-sugar diets as they experience opioid withdrawal and abstinence.To understand whether this feeding behavior reflects a purely homeostatic caloric recovery or changes in hedonic reward processing, this thesis tested the hypothesis that fentanyl dependence produces alterations in hedonic valuation that persist into abstinence. This hypothesis was tested using a feeding assay, weight-loss-matched food restriction paradigm, and sucrose preference testing across defined treatment, withdrawal, and abstinence phases. Feeding assays showed fentanyl-treated mice exhibited progressive weight loss to ~9% from baseline and a ~35% reduction in chow consumption during the treatment phase that was then followed by a compensatory rebound feeding during withdrawal. Results from the food-restriction experiment indicated food-restricted mice recapitulated the weight-loss phenotype during the treatment phase but recovered to their baseline weights following refeeding. In contrast, fentanyl-treated mice’s weight loss persisted through the abstinence phase. Sucrose preference ratio (SPR) analyses revealed a decline in sucrose preference within the fentanyl-treated group between withdrawal and abstinence that was not seen in food-restricted or vehicle-treated groups. This study’s findings suggest fentanyl dependence’s effects on reward-related behavior are partially dissociable from caloric deficit alone. This work overall supports a model in which fentanyl exposure produces persistent alterations in reward valuation, providing insights into feeding and metabolic disturbances during opioid recovery.</dc:description><dc:subject>Behavioral sciences</dc:subject><dc:subject>Biology</dc:subject><dc:subject>Neurosciences</dc:subject><dc:subject>Behavioral psychology</dc:subject><dc:subject>Clinical psychology</dc:subject><dc:subject>caloric restriction</dc:subject><dc:subject>Fentanyl dependence</dc:subject><dc:subject>Hedonic feeding</dc:subject><dc:subject>Homeostatic feeding regulation</dc:subject><dc:subject>Opioid withdrawal</dc:subject><dc:subject>Sucrose preference</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8jn9t75k</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0sx117m4</identifier><datestamp>2026-09-16T06:38:22Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0sx117m4</dc:identifier><dc:title>A hERG blocker facilitates K+ channel current by promoting pore opening while blocking</dc:title><dc:creator>Docken, Steffen S</dc:creator><dc:creator>Marquis, Matthew J</dc:creator><dc:creator>Ngo, Khoa</dc:creator><dc:creator>Wada, Yuumu</dc:creator><dc:creator>Kita, Satomi</dc:creator><dc:creator>Yarov-Yarovoy, Vladimir</dc:creator><dc:creator>Clancy, Colleen E</dc:creator><dc:creator>Vorobyov, Igor</dc:creator><dc:creator>Lewis, Timothy J</dc:creator><dc:creator>Furutani, Kazuharu</dc:creator><dc:creator>Sack, Jon T</dc:creator><dc:date>2026-11-02</dc:date><dc:description>Many drugs that block voltage-gated K+ channels encoded by the human ether-à-go-go-related gene (hERG) can cause long QT syndrome and life-threatening cardiac arrhythmias, yet the molecular mechanisms that determine this risk remain unclear. A process that may counteract arrhythmogenic hERG block, termed facilitation, is common to many clinically approved hERG blockers, including nifekalant, amiodarone, promethazine, imipramine, nortriptyline, haloperidol, verapamil, carvedilol, metoprolol, propranolol, quinidine, fluoxetine, and chlorpheniramine. Facilitation is an increase in hERG current, under certain conditions, due to these blockers. Here, we propose that an agonism-while-blocking mechanism underpins facilitation. We focus on nifekalant, a class III antiarrhythmic drug and exemplar hERG blocker that induces facilitation. We tested the hypothesis that nifekalant opens hERG channel gates while blocking, and that unblocking of these open-yet-blocked channels results in supranormal hERG current. We developed rate-theory kinetic models to identify features of agonism-while-blocking that produce facilitation. We generated atomistic models that predict that nifekalant blocks the hERG conduction path while modulating the intracellular conduction gate. Voltage-clamp measurements revealed that agonism-while-blocking can result in nifekalant block and facilitation. We speculate that this agonism-while-blocking mechanism contributes to the relative safety of hERG blockers that induce facilitation.</dc:description><dc:subject>3208 Medical Physiology (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>Rare Diseases (rcdc)</dc:subject><dc:subject>Congenital Heart Disease (rcdc)</dc:subject><dc:subject>Cardiovascular (rcdc)</dc:subject><dc:subject>Heart Disease (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>5.1 Pharmaceuticals (hrcs-rac)</dc:subject><dc:subject>Cardiovascular (hrcs-hc)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Ether-A-Go-Go Potassium Channels (mesh)</dc:subject><dc:subject>Potassium Channel Blockers (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Pyrimidinones (mesh)</dc:subject><dc:subject>Ion Channel Gating (mesh)</dc:subject><dc:subject>Anti-Arrhythmia Agents (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Pyrimidinones (mesh)</dc:subject><dc:subject>Anti-Arrhythmia Agents (mesh)</dc:subject><dc:subject>Potassium Channel Blockers (mesh)</dc:subject><dc:subject>Ion Channel Gating (mesh)</dc:subject><dc:subject>Ether-A-Go-Go Potassium Channels (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Ether-A-Go-Go Potassium Channels (mesh)</dc:subject><dc:subject>Potassium Channel Blockers (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Pyrimidinones (mesh)</dc:subject><dc:subject>Ion Channel Gating (mesh)</dc:subject><dc:subject>Anti-Arrhythmia Agents (mesh)</dc:subject><dc:subject>0606 Physiology (for)</dc:subject><dc:subject>1116 Medical Physiology (for)</dc:subject><dc:subject>Physiology (science-metrix)</dc:subject><dc:subject>3101 Biochemistry and cell biology (for-2020)</dc:subject><dc:subject>3109 Zoology (for-2020)</dc:subject><dc:subject>3208 Medical physiology (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0sx117m4</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1085/jgp.202614015</dc:identifier><dc:type>article</dc:type><dc:source>Journal of General Physiology, vol 158, iss 6</dc:source><dc:coverage>e202614015</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt63q5p8d3</identifier><datestamp>2026-09-16T06:38:17Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt63q5p8d3</dc:identifier><dc:title>Identification of the CAG-Repeat mRNA Interactome as Therapeutic Targets for Huntington’s Disease</dc:title><dc:creator>Nguyen, Chloe</dc:creator><dc:contributor>Yeo, Eugene</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Huntington’s Disease (HD) is a uniformly fatal neurological disease characterized by cognitive decline and motor deficits resulting from neuronal loss in the basal ganglia. The genetic hallmark is a trinucleotide CAG repeat expansion (≥ 36 repeats) in exon 1 of the&amp;nbsp;huntingtin (HTT) gene. Although HD has largely been considered a proteinopathy driven by toxic polyglutamine (polyQ) aggregation, current therapeutic strategies targeting polyQ have been fruitless in modulating HD progression. Emerging evidence has implicated the expanded mutant HTT RNA (mtHTT) itself as a driver of neuronal dysfunction. Specifically, mtHTT has the capacity to oligomerize into RNA foci, disrupting the RNA-protein landscape by recruiting and sequestering RNA-binding proteins (RBPs) critical for cell survival.Using proximity labeling strategies, we characterized proteins that interact with mtHTT reporter constructs harboring expanded repeats in HEK293T models, revealing preferential binding to proteins involved in stress granule (SG) assembly, RNA metabolism, intracellular trafficking, and more. Narrowing candidates to SG-associated proteins, we validated direct mtHTT-RBP interactions in disease-relevant striatal neuron models through RNA immunoprecipitation. We further assessed the therapeutic potential of targeting SG-associated proteins using small molecule inhibition (SMI). Treatment with SMI resulted in altered mtHTT RNA-RBP binding dynamics and reduced pathogenic polyQ aggregation. Together, these findings support a promising model in which cytoplasmic stress granule components operates as neuroprotective partners to engage mtHTT and limit its translational activity into toxic polyQ species, offering a novel therapeutic avenue for HD rescue.</dc:description><dc:subject>Neurosciences</dc:subject><dc:subject>Biology</dc:subject><dc:subject>Molecular biology</dc:subject><dc:subject>Biochemistry</dc:subject><dc:subject>Immunology</dc:subject><dc:subject>Huntington's Disease</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/63q5p8d3</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7f61s53d</identifier><datestamp>2026-09-16T06:38:11Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7f61s53d</dc:identifier><dc:title>Multi-Thermochronometer Constraints on Cretaceous to Cenozoic Exhumation of the Northern Peninsular Ranges Batholith</dc:title><dc:creator>Bush, Madison</dc:creator><dc:contributor>Odlum, Margo</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>The Peninsular Ranges Batholith (PRB) preserves an important record of the magmatic and tectonic evolution of southern California from the Jurassic through the Cenozoic. Although previous low-temperature thermochronologic studies indicate Late Cretaceous to Paleogene cooling, a dearth of low-temperature thermochronology constraints along the San Jacinto and Elsinore fault systems has limited the ability to distinguish exhumation associated with transform faulting from older subduction-related processes. To address this uncertainty, samples along the traces of these faults were targeted to evaluate the spatio-temporal trends in pluton crystallization and exhumation. New LA-ICP-MS zircon and apatite U-Pb geochronology and apatite (U-Th)/He thermochronology along with inverse thermal history modeling is used to constrain the timing of crystallization and exhumation within the northern PRB. Zircon and apatite U-Pb ages record mid- to Late Cretaceous pluton emplacement and cooling within the mid- to upper crust. Apatite (U-Th)/He dates from eight samples range from ~76 to 7.2 Ma, with most ages between ~76 and 40 Ma, recording Late Cretaceous to middle Eocene cooling. Inverse thermal history modeling indicates two regional cooling phases, occurring at 75-68 Ma and 55-40 Ma, along with localized Miocene-Pliocene cooling between 12-7 Ma. The Late Cretaceous cooling phase is interpreted to record the transition from normal-angle subduction to shallow slab subduction. The Paleocene-Eocene cooling phase reflects regional uplift, denudation, and erosion during shallow slab subduction. Although modern topography of the region is strongly influenced by the San Jacinto and Elsinore faults, thermochronologic data indicate that most exhumation is associated with the paleo-subduction margin processes.</dc:description><dc:subject>Geology</dc:subject><dc:subject>Geophysics</dc:subject><dc:subject>Plate tectonics</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7f61s53d</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6538p7tn</identifier><datestamp>2026-09-16T06:38:05Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6538p7tn</dc:identifier><dc:title>Coherence from interference: a solvable model of sub-GeV dark matter-nucleus scattering</dc:title><dc:creator>Lin, Lynn</dc:creator><dc:contributor>Lin, Tongyan</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Dark matter interactions with nuclei transition between two regimes: coherent scattering, in which single phonons are produced, and scattering off individual nuclei, which produces nuclear recoils. Understanding this transition requires understanding multiphonon excitations, which are important for interpreting low-threshold direct detection experiments but are computationally prohibitive to calculate. In this thesis, we employ a one-dimensional crystal lattice model in which dark matter scattering can be computed exactly. We show that the only difference between coherent and incoherent scattering is that conservation of crystal momentum is enforced in the coherent case. The momentum conservation constraint becomes less important as more phonons are produced, yielding the transition to incoherent scattering. Using numerical calculations of the one-dimensional structure factor, we also obtain quantitative validation of the incoherent approximation for computing sub-GeV dark matter scattering in realistic three-dimensional crystals.</dc:description><dc:subject>Physics</dc:subject><dc:subject>Particle physics</dc:subject><dc:subject>Theoretical physics</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6538p7tn</dc:identifier><dc:identifier>https://escholarship.org/content/qt6538p7tn/qt6538p7tn.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9c93285v</identifier><datestamp>2026-09-16T06:38:00Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9c93285v</dc:identifier><dc:title>Low light conditions enhance socially rewarded olfactory learning acquisition in honey bees</dc:title><dc:creator>Byrd, Joseph Adam</dc:creator><dc:contributor>Nieh, James</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>The ability of honey bees (Apis mellifera) to learn associations between cues and rewards facilitates their efficient foraging in complex and changing environments. Olfactory conditioning of the proboscis extension response (PER) has provided a powerful model for understanding learning through simple conditioning, particularly in the acquisition of foraging-site information. Most conditioning experiments use sucrose as an unconditioned stimulus (US), but recent work has shown that simple antennal contact with a nestmate alone can act as appetitive reinforcement. Preliminary work also suggests that associative learning rates may improve in low light, much like the internal environment of the hive.  Here, I use both ‘socially’ and sucrose rewarded differential olfactory conditioning assays to test whether ambient light conditions may modulate learning. Harnessed foragers were trained to discriminate between two floral odorants, where one odor (CS+) predicted reward and the other odor (CS−) predicted no reward. Learning was quantified as PER during CS+ presentation prior to US delivery across repeated trials. I find that in socially rewarded bees, conditioned PER increases more steeply in red light than white light (P = 0.0023). Ambient light had no effect on sucrose reinforced learning (P = 0.053). In conclusion, I find that social contact indeed serves as an appetitive US, however its utility as a reinforcer seems impacted by ambient light conditions. This result may be tied to the sensory ecology of the waggle dance, as it occurs within the darkness of the hive.</dc:description><dc:subject>Animal sciences</dc:subject><dc:subject>Ecology</dc:subject><dc:subject>Biology</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9c93285v</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt85n5c4rq</identifier><datestamp>2026-09-16T06:37:58Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt85n5c4rq</dc:identifier><dc:title>Eight quick tips for data-model integration in ecology</dc:title><dc:creator>Balstad, Laurinne J</dc:creator><dc:creator>Brennan, Joe</dc:creator><dc:creator>Baskett, Marissa L</dc:creator><dc:creator>Berglund, Mattea K</dc:creator><dc:creator>Blundell, Mei Z</dc:creator><dc:creator>Bolin, Jessica A</dc:creator><dc:creator>Briggs, Amy A</dc:creator><dc:creator>Fisher, Mary C</dc:creator><dc:creator>Heggerud, Christopher M</dc:creator><dc:creator>Jarvis-Cross, Madeline</dc:creator><dc:creator>Mossman, Lauren</dc:creator><dc:creator>Odell, Andrea N</dc:creator><dc:creator>Paige, Jennifer</dc:creator><dc:creator>Pelletier, Sophia</dc:creator><dc:creator>Provost, Mikaela M</dc:creator><dc:contributor>Palagi, Patricia M</dc:contributor><dc:date>2026-07-20</dc:date><dc:subject>01 Mathematical Sciences (for)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>08 Information and Computing Sciences (for)</dc:subject><dc:subject>Bioinformatics (science-metrix)</dc:subject><dc:rights>CC-BY-NC-SA</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/85n5c4rq</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1371/journal.pcbi.1014524</dc:identifier><dc:type>article</dc:type><dc:source>PLOS Computational Biology, vol 22, iss 7</dc:source><dc:coverage>e1014524</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt88z874mh</identifier><datestamp>2026-09-16T06:37:55Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt88z874mh</dc:identifier><dc:title>Mechanisms of the Sex-Dependent Effects of Early-Life Adversity on Reward Behaviors</dc:title><dc:creator>Taniguchi, Lara</dc:creator><dc:contributor>Baram, Tallie Z.</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Early-life adversity (ELA) is a risk factor for human affective disorders involving dysregulated reward behaviors. In our limited bedding and nesting mouse model, ELA induces anhedonia-like behaviors in adult male mice while increasing motivation for rewards in adult females, indicating sex-dependent disruption of reward circuit operations. Searching for potential underlying circuit mechanisms of these disruptions of reward behavior, we identified a novel projection from the basolateral amygdala (BLA) to the nucleus accumbens (NAc) that expresses the stress-sensitive neuropeptide corticotropin-releasing hormone (CRH), together with the neurotransmitter GABA. To test the contribution of this projection to reward deficits in adult male and female mice reared in ELA conditions, we conducted the following experiments: Adult male and female CRH-Cre mice raised in control or ELA conditions received bilateral excitatory or inhibitory Cre-dependent DREADDs in the BLA, with clozapine N-oxide or vehicle delivered bilaterally to the NAc medial shell during reward behaviors. Cell identity was determined via immunostaining and electrophysiology. Tissue clearing, light sheet fluorescence microscopy, and deep learning pipelines were used to map brain-wide CRH BLA axonal projections. Bilateral chemogenetic manipulations in male mice demonstrated inhibitory effects of the CRH/GABA BLA→NAc projection on reward behaviors in control mice and inhibiting the projection rescued reward deficits in ELA male mice. In females, neither excitation nor inhibition influenced reward seeking behaviors. Molecular and electrophysiological cell-identities of the projection did not vary by sex. By contrast, comprehensive whole-brain mapping uncovered subtle differences in axonal terminals in the NAc as well as elsewhere, which were both sex- and ELA-dependent. Because these changes did not explain the apparent lack of effect of bilateral chemogenetic manipulations of the projection on female reward behaviors, we tested the hypothesis that ipsilateral and contralateral CRH/GABA BLA→NAc projections may have opposing effects on reward behavior that cancel out when both are manipulated concurrently. Results of ongoing studies support this hypothesis. In summary, the CRH/GABA BLA→NAc projection that influences reward behaviors in males differs structurally and functionally in females, uncovering potential mechanisms for the profound sex-specific impacts of ELA on reward behaviors. Further investigation of this projection will give us a deeper understanding of intrinsic sex differences in the organization of the reward circuitry and the effects of ELA on reward behaviors that underlie many mood disorders.</dc:description><dc:subject>Neurosciences</dc:subject><dc:subject>Mental health</dc:subject><dc:subject>Sexuality</dc:subject><dc:subject>basolateral amygdala</dc:subject><dc:subject>corticotropin-releasing hormone</dc:subject><dc:subject>early-life adversity</dc:subject><dc:subject>nucleus accumbens</dc:subject><dc:subject>reward circuit</dc:subject><dc:subject>sex differences</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/88z874mh</dc:identifier><dc:identifier>https://escholarship.org/content/qt88z874mh/qt88z874mh.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0097c8j6</identifier><datestamp>2026-09-16T06:37:49Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0097c8j6</dc:identifier><dc:title>Environmentally Aware Autonomy to Optimize UUV Acoustic Communications</dc:title><dc:creator>Morales, Adam</dc:creator><dc:contributor>Terrill, Eric</dc:contributor><dc:contributor>Merrifield, Sophia</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Reliable underwater acoustic communication is important for Unmanned Underwater Vehicle (UUV) operations but is affected by environmental conditions and vehicle geometry. The objective of this research was to identify factors affecting acoustic communication performance for a REMUS 100 UUV and to develop autonomous behaviors that could improve communication reliability during mission execution.
      Laboratory and field experiments conducted through the Scripps Institution of Oceanography (SIO) Coastal Observing Research and Development Center (CORDC) evaluated the effects of vehicle self-noise, vehicle depth, and vehicle orientation on communication performance using a WHOI Micromodem-2 operating at 25 kHz. Communication success was evaluated under varying operating conditions, and BELLHOP acoustic propagation modeling was used to support interpretation of depth-dependent communication performance.
      Results showed that changes in vehicle propulsion RPM produced minimal changes in acoustic energy near the communication frequency and did not provide a strong basis for adaptive behavior development. In contrast, communication performance varied with vehicle depth and orientation relative to the receiver, identifying both as controllable parameters that could be used by the vehicle to respond to communication degradation. Based on these findings, autonomous depth-seeking and broadside-deviation behaviors were developed and integrated into the REMUS 100 software architecture. Field testing demonstrated that the vehicle could autonomously modify its depth or orientation following communication degradation and subsequently return to the planned mission trackline. Successful communication recovery was observed during both adaptive behavior assessments, demonstrating that communication status can be incorporated into UUV autonomy and used to influence vehicle motion in response to degraded underwater acoustic communication conditions.</dc:description><dc:subject>Ocean engineering</dc:subject><dc:subject>Acoustics</dc:subject><dc:subject>Communication</dc:subject><dc:subject>Naval engineering</dc:subject><dc:subject>Acoustic Communication</dc:subject><dc:subject>Unmanned Underwater Vehicle</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0097c8j6</dc:identifier><dc:identifier>https://escholarship.org/content/qt0097c8j6/qt0097c8j6.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt54m0m95p</identifier><datestamp>2026-09-16T06:37:44Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt54m0m95p</dc:identifier><dc:title>Development and application of metabolic engineering strategies to increase the production of biological products in yeast</dc:title><dc:creator>Siddappa, Tharini</dc:creator><dc:contributor>Da Silva, Nancy A</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>The non-conventional yeast Kluyveromyces marxianus is thermotolerant, acid tolerant, and grows on a wide variety of substrates including glycerol, xylose, and lactose which can be derived from biofuel production waste, lignocellulosic biomass, and waste whey, respectively. K. marxianus is also the fastest growing eukaryote known with a growth rate twice that of Baker’s yeast. These attributes make this yeast species an excellent industrial organism. We have previously shown that K. marxianus is a promising heterologous host for the production of polyketides, a class of diverse molecules that are of interest due to their clinical and chemically relevant properties. In our current work, we have used both computational methods and rational pathway analysis to identify several gene modifications to increase flux towards polyketide precursor molecules and to reduce byproduct accumulation in K. marxianus during cultivation on xylose and lactose. Using a robust RNA polymerase II driven CRISPR-Cas9 system we developed, multiple gene knockouts and gene overexpression were shown to substantially increase synthesis of polyketides triacetic acid lactone (TAL) and 6-methylsalisylic acid (6-MSA) in this non-conventional yeast species. We were able to achieve a 1.9-fold increase in TAL titer and 5.6-fold increase in 6-MSA titer by (1) knocking out pathways that direct carbon to byproducts such as glycogen and gluconeogenesis and (2) overexpressing enzymes that increase the availability of metabolites necessary for polyketide production.As an alternative to investigating genotype-to-phenotype relationships by in silico and rational engineering methods, genome-scale gRNA libraries can provide information about an organism in a high-throughput manner. We have applied a gRNA library to identify essential genes in K. marxianus in various growth conditions. We have also paired our gRNA library with a metabolite biosensor and identified several gene knockouts predicted to increase polyketide production. With this library workflow, our initial efforts increased 6-MSA production up to 2.5-fold using this reverse engineering method.The spatial organization of molecules can be engineered using synthetic scaffolds to hold enzymes in proximity, thus increasing the pathway efficiency. Metabolon assembly provides a strategy to increase pathway efficiency without the need for genomic modifications. Cas6-mediated scaffolding systems utilize RNA-RNA hybridization to bring protein-RNA complexes into proximity. We expanded our Cas6-mediated scaffolding system to K. marxianus and have shown in an initial study that this system successfully increased IAA production.</dc:description><dc:subject>Chemical engineering</dc:subject><dc:subject>Bioengineering</dc:subject><dc:subject>Molecular biology</dc:subject><dc:subject>Genetics</dc:subject><dc:subject>genome-scale metabolic model</dc:subject><dc:subject>gRNA library</dc:subject><dc:subject>Kluyveromyces marxianus</dc:subject><dc:subject>metabolic engineering</dc:subject><dc:subject>metabolite biosensor</dc:subject><dc:subject>polyketide synthesis</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/54m0m95p</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3fb6r3pr</identifier><datestamp>2026-09-16T06:37:39Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3fb6r3pr</dc:identifier><dc:title>Chalcone and Nitro-Aromatic Derivatives to Treat Human African Trypanosomiasis</dc:title><dc:creator>Kaur, Yashpreet</dc:creator><dc:contributor>Caffrey, Conor R</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Human African trypanosomiasis (HAT), caused by Trypanosoma brucei, is a neglected tropical disease of sub-Saharan Africa. Current chemotherapies are limited by toxicity, drug resistance and difficulties in drug administration, underscoring the need for new drugs with improved efficacy and safety. This study evaluates three classes of compounds for antitrypanosomal activity: pyrazolyl acrylamide-chalcone conjugates, nitroquinoline derivatives and nitroquinolone derivatives. Compounds were screened in vitro against T. b. brucei (Lister 427) using a resazurin-based viability assay to measure the EC50 value (i.e., concentration needed to decrease parasite growth by 50%). Cytotoxicity was similarly measured in vitro using human embryonic kidney (HEK)293 cells to determine the CC50 value (i.e., the concentration needed to decrease cell growth by 50%). The selectivity index (SI) was calculated as CC50/EC50. Structure-activity relationships (SAR) were analyzed to identify the structural determinants associated with potency and selectivity. Several of the pyrazolyl acrylamide-chalcone derivatives demonstrated sub-micromolar EC50 values between 0.245 and 0.520 µM, with robust SIs &amp;gt; 50. Antiparasitic activity was enhanced by electron-withdrawing substituents, particularly halogen and nitro groups on the chalcone aromatic ring. The nitroquinoline derivatives, if active at all, demonstrated low-micromolar antiparasitic activities but modest SIs of 2.7 – 6.3, while the nitroquinolone analogs displayed sub- to low-micromolar antitrypanosomal activities with, again, modest SIs of 0.4 – 8.3, highlighting the generally smaller therapeutic windows of both series. The data generated and the associated SAR suggest that the pyrazolyl acrylamide–chalcone scaffold is a promising starting point for further medicinal chemistry to deliver safer and more effective HAT treatments.</dc:description><dc:subject>Pharmaceutical sciences</dc:subject><dc:subject>Biology</dc:subject><dc:subject>Chemistry</dc:subject><dc:subject>Parasitology</dc:subject><dc:subject>Biochemistry</dc:subject><dc:subject>Chalcones</dc:subject><dc:subject>Human African Trypanosomiasis</dc:subject><dc:subject>Nitroaromatics</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3fb6r3pr</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7bk6w5s8</identifier><datestamp>2026-09-16T06:37:34Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7bk6w5s8</dc:identifier><dc:title>Evaluating Assisted Gene Flow Compatibility, Phenology, and Leaf Traits Across Eschscholzia californica Populations</dc:title><dc:creator>Hubbard, Jasmine</dc:creator><dc:contributor>Cleland, Elsa</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Assisted gene flow has been proposed as a management tool to introduce alleles from one population into a specific local population lacking those adaptations, however it has rarely been tested in herbaceous plants. Eschscholzia californica spans a wide environmental range, with greater drought adaptation in Southern populations; hence, it provides an ideal model system to study AGF. To study potential benefits and detriments of assisted gene flow in this species, we crossed 16 different populations found throughout California with two focal dam populations from Northern California (MCLA and FORT) and grew the resulting seeds in a common garden experiment, testing for drought adaptations. Our results reveal that the effects of AGF are highly population-specific. Our study found evidence of potential pre-zygotic and post-zygotic incompatibility, particularly in the more northern and mesic population, MCLA, as pollination success and average seed yield were significantly lower in crosses with more distant sires. Furthermore, early life history traits exhibited evidence of heavy maternal effects, with FORT crosses emerging about 2 days earlier on average than MCLA crosses, regardless of sire origin. However, offspring phenology and leaf traits displayed more complex interactions later in the season. Geographic distance between the dam and sire populations and sire aridity increased drought escape adaptations in the F1 offspring including earlier flowering timing, along with higher specific leaf area and more leaf dissection compared to the F1 offspring from more northern sires. Overall, these findings suggest that the success of AGF depends on both the dam and sire contexts, emphasizing the importance of considering compatibility genetically, genetically, and geographically in restoration.</dc:description><dc:subject>Ecology</dc:subject><dc:subject>Plant sciences</dc:subject><dc:subject>Evolution &amp; development</dc:subject><dc:subject>Conservation biology</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7bk6w5s8</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2j86d6qc</identifier><datestamp>2026-09-16T06:37:29Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2j86d6qc</dc:identifier><dc:title>Mechanistic Dissection of Anti-PD-1 Mediated PD-1 Agonism</dc:title><dc:creator>Song, Xiaoxian</dc:creator><dc:contributor>Hui, Enfu</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Programmed cell death protein 1 (PD-1) is an inhibitory immune checkpoint receptor predominantly expressed on activated T cells that maintains peripheral tolerance by suppressing T cell effector functions. Consequently, agonistic anti-PD-1 antibodies have emerged as promising therapeutic candidates for autoimmune diseases, which are often driven by aberrant activation of autoreactive T cells. However, the molecular mechanisms governing antibody-mediated PD-1 agonism remain poorly understood. Fc gamma receptors (FcγRs) are cell surface receptors expressed on immune cells that facilitate antibody crosslinking by serving as scaffolds for Fc domain engagement. While the FcγR-mediated antibody crosslinking is essential for the agonistic activity of antibodies targeting multiple TNFR family receptors, how it governs anti-PD-1 agonistic functions is poorly shown. In this study, I established a co-culture system consisting of OT-I CD8+ T cells and mFcγRIIb+ B16-OVA melanoma cells to evaluate the agonistic activity of anti-PD-1 antibodies. I found that both the well characterized PD-1 blocking antibodies RMP1-14 and 29F.1A12, as well as the agonist antibody RMP1-30, suppressed T-cell effector function in an mFcγRIIb- dependent manner, suggesting that blocking antibodies can also exhibit agonistic activity when captured by FcγRs. Consistent with these functional findings, I further used a reconstituted T cell-supported lipid bilayer system and found that FcγR-captured anti-PD-1 antibodies induced robust PD-1 clustering and Shp2 recruitment at the immune synapse, a key biophysical property featuring PD-1 signaling. In contrast, neither PD-1 clustering nor Shp2 recruitment was observed in the absence of FcγRs. Together, these data provide direct functional evidence and mechanistic insights of anti-PD-1 induced PD-1 agonism.</dc:description><dc:subject>Biology</dc:subject><dc:subject>Cellular biology</dc:subject><dc:subject>Immunology</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2j86d6qc</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4gr281rj</identifier><datestamp>2026-09-16T06:37:24Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4gr281rj</dc:identifier><dc:title>Phylogenomics of Deep-Sea Slickheads and Tubeshoulders (Alepocephaliformes)</dc:title><dc:creator>O'Brien, Megan Elizabeth</dc:creator><dc:contributor>Arcila, Dahiana K</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>The order Alepocephaliformes (slickheads and tubeshoulders) is a diverse group of mesopelagic and bathypelagic fishes characterized by scaleless heads and, in platytroctids, a tube organ behind the cleithrum that excretes bioluminescent fluid. Although Alepocephaliformes is placed as the sister group of Ostariophysi, the largest radiation of freshwater fishes, relationships within the order have remained poorly resolved because most species are rare, poorly sampled, and frequently described from juvenile specimens. 
      Here, we present the most densely sampled phylogeny of the order to date, comprising 1,094 exonic, 17 legacy nuclear and 10 mitochondrial markers and including 86 of 147 described species across 31 of the 33 recognized genera. This degree of taxonomic coverage was achieved by generating short-read genomes for 46 species, historical DNA sequencing from three species (Rinoctes, Searsia, Searsioides) lacking any fresh tissue samples collected during the last three decades, extracting for ultraconserved elements exonic regions in common for five species, and utilizing published legacy markers and genomic data for 31 species. Our tree resolves Alepocephalidae as paraphyletic, with Platytroctidae and Bathylaco nigricans nested within it, and identifies several of the largest genera as non-monophyletic, including Conocara, Alepocephalus, and Rouleina. We then quantified body and head shape variation across more than 300 specimens using linear measurements following those in the FishShapes dataset. Our preliminary results contradict the hypothesis of a clear shape difference between families, with implications for body-plan evolution across deep-sea fish lineages more broadly. These analyses establish a phylogenomic and morphometric framework for Alepocephaliformes.</dc:description><dc:subject>Biology</dc:subject><dc:subject>Marine geology</dc:subject><dc:subject>Biological oceanography</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4gr281rj</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9w6266sw</identifier><datestamp>2026-09-16T06:37:19Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9w6266sw</dc:identifier><dc:title>Genomic Characterization of Carbon Dioxide-Responsive Mutants in Brachypodium distachyon via Bulked Segregant Analysis and Transcriptomic Platform Development</dc:title><dc:creator>Gu, Kathy Yu Xuan</dc:creator><dc:contributor>Schroeder, Julian I</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Plants respond to changing atmospheric CO₂ concentrations through signaling networks that regulate stomatal aperture, but the genetic mechanisms underlying these responses remain incompletely understood. The model grass Brachypodium distachyon provides a useful system for investigating CO₂-responsive phenotypes. This thesis develops, validates, and applies computational genomics workflows to characterize genetic variants associated with CO₂-responsive mutants in Brachypodium distachyon.A short-read bulked segregant analysis (BSA) pipeline was first validated using the chill1 mutant. The analysis reproduced the previously reported QTL signal on chromosome Bd3 and identified BdMPK5 as the primary candidate gene, consistent with Lopez et al. (2024). The validated pipeline was then applied to the semi-dominant chill15 mutant; however, no statistically significant QTLs were detected, likely due to reduced allele-frequency contrasts and limitations in sequencing depth. A PacBio HiFi long-read variant analysis workflow was also developed and applied to the chill15 dataset. Although uneven sequencing coverage prevented identification of definitive candidate loci, the workflow was established as a reusable framework for future long-read BSA studies in Brachypodium distachyon.In parallel, the Encyclogenia platform, a Python- and SQLite-based transcriptomic expression query tool integrating microarray and RNA-seq datasets, was expanded through integration and curation of guard cell datasets, improved statistical analysis and query handling, and enhanced cross-platform compatibility. These improvements support comparative transcriptomic analysis and candidate gene evaluation across multiple datasets. Together, this work provides computational frameworks for genetic mapping of CO₂-responsive mutants, expands transcriptomic resources for future functional genomics studies, and provides a foundation for studies of stomatal signaling mechanisms.</dc:description><dc:subject>Biology</dc:subject><dc:subject>Cellular biology</dc:subject><dc:subject>Molecular biology</dc:subject><dc:subject>Genetics</dc:subject><dc:subject>Brachypodium distachyon</dc:subject><dc:subject>Bulked Segregant Analysis</dc:subject><dc:subject>Guard Cells</dc:subject><dc:subject>Long-Read Sequencing</dc:subject><dc:subject>Mutation Mapping</dc:subject><dc:subject>RNA-seq</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9w6266sw</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5cb2v008</identifier><datestamp>2026-09-16T06:37:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5cb2v008</dc:identifier><dc:title>Progress Towards the Genetic Mapping of the EMS-Induced chill15 Mutant in Brachypodium distachyon</dc:title><dc:creator>Hoang, Trevor</dc:creator><dc:contributor>Schroeder, Julian I</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>With the increase in carbon dioxide (CO2) concentrations in the atmosphere, comes a change in major abiotic factors such as drought, heat stress and water loss. These stresses contribute to crop failures worldwide and can lead to food insecurity in the long term. Plants respond to increased CO2 by closing their stomata which can lead to an increase in water use efficiency (WUE). As such, an increased need in studying the mechanisms behind how plants respond to high CO2 and drought conditions is required in order to mitigate the effects of these pressures. Brachypodium distachyon is a grass that is becoming increasingly studied as a model organism due to its close genetic similarity to important cereal crops. Using an infrared camera, an unbiased forward genetic screen was conducted by Lopez et al 2024 on over 1000 individual EMS mutagenized B, distachyon lines in the M5 generation. Plants were exposed to high CO2 in order to induce stomatal closure. Using canopy leaf temperature as an indicator, those with cooler temperatures were identified as putative mutants with inhibited stomatal response and were isolated. Among the mutants isolated, the two strongest lines were chill1 and chill15 which both show increased tolerance to high CO2 response. Lopez et al 2024 has mapped chill1 to Mitogen Activated Protein Kinase 5 (BdMPK5) however work is still being conducted on chill15 to identify the mutation that is causing the observed phenotype. Short read whole genome sequencing and subsequent bulked segregant analyses (BSA) have been conducted on the chill15 genome and revealed 46 candidate mutations that may be responsible for the phenotype. Using Sanger sequencing, 11 of the 46 candidate mutations were confirmed to be in the genome. In an attempt to narrow the pool of candidate mutations, an additional F2 generation was screened and brought into the F3 generation for confirmation that homozygous plants were selected. Although the chill15-like pool was found to be mostly heterozygous, plants were pooled for long read PacBio Revio sequencing. Following sequencing, ongoing genetic and bioinformatic analysis are being conducted to identify possible candidate mutations for the phenotype.</dc:description><dc:subject>Biology</dc:subject><dc:subject>Botany</dc:subject><dc:subject>Cellular biology</dc:subject><dc:subject>Plant sciences</dc:subject><dc:subject>Genetics</dc:subject><dc:subject>CO2 Response</dc:subject><dc:subject>Plant Biology</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5cb2v008</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9984h7qd</identifier><datestamp>2026-09-16T06:37:08Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9984h7qd</dc:identifier><dc:title>Design and Optimization of Small Molecules for Neurodegenerative, Oncological and Parasitic Diseases</dc:title><dc:creator>Yohannan, Darius Jordan</dc:creator><dc:contributor>Caffrey, Conor</dc:contributor><dc:contributor>Yang, Jerry</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>My dissertation is divided into three chapters covering projects in neurodegenerative disease, parasitic diseases, and oncology. 	Chapter 1 describes the design and synthesis of mammalian suppressor of tauopathy 2 (MSUT2) inhibitors. MSUT2 is a poly(A)RNA deadenylase that modulates transcript fate. MSUT2 overexpression exacerbates tau-mediated neurotoxicity and is a validated target for the treatment of tauopathy. I synthesized 47 thiochromenothiazoles, which were evaluated in an MSUT2 fluorescence polarization assay. I elucidated structure-activity relationships for the MSUT2/poly(A)RNA binding interaction. A minimal structural pharmacophore was identified, and a novel class of bisaminothiazoles was discovered with improved potency from additional screening utilizing this pharmacophore. Also, I designed and synthesized two chemical probes for target engagement studies. These confirmed that the thiochromenothiazoles competitively bind to MSUT2 in a conformation consistent with the SAR described. 
	Chapter 2 focuses on the biological evaluation and optimization of thiophenylpyrimidines (TPPs) which paralyze Schistosoma mansoni, a flatworm parasite that causes the neglected tropical disease, schistosomiasis. The TPPs, derived from a class of microtubule (MT)-active pyrimidines, have been studied extensively for their anti-tauopathy effects. To allow for in vivo efficacy and mechanism-of-action studies in schistosome-infected mice, I resynthesized the lead TPP at hundred-milligram scale. The lead TPP demonstrates modest anti-schistosomal efficacy in vivo and modulates ribonucleoprotein complex assembly and eukaryotic translation initiation; importantly, tubulin is not a target. Further, I designed and synthesized 18 new pyrimidines, including a class of bis-phenylpyrimidines (BPDs), to expand the SAR and structure-property relationships for this compound class. These studies highlighted the necessity for hydrophobic worm-ligand interactions and identified novel areas of the pyrimidine scaffold for further exploration. 
	Chapter 3 focuses on developing a set of FTO molecular glue degraders and optimizing a class of oxetane-based FTO inhibitors in cancer. The m6A demethylase, fat mass and obesity-associated protein (FTO), is oncogenic and overexpressed in many cancers, where hyper-demethylation influences tumor growth, stemness, and metastasis. I designed and synthesized eight degraders and 18 oxetane-based inhibitors, which were evaluated against patient-derived gastric cancer cells. A submicromolar degrader was identified, and elucidation of the SAR highlighted novel areas for further exploration, including bioisosteric replacements of the oxetane scaffold.</dc:description><dc:subject>Organic chemistry</dc:subject><dc:subject>Pharmacology</dc:subject><dc:subject>Oncology</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9984h7qd</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1963997s</identifier><datestamp>2026-09-16T06:37:02Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1963997s</dc:identifier><dc:title>Friction-based Structural Components for Earthquake-Resistant Buildings</dc:title><dc:creator>Chen, Kaixin</dc:creator><dc:contributor>Tsampras, Georgios</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Friction-based structural components have been developed and used in earthquake-resistant buildings for seismic response modification purposes. They can provide high initial stiffness, decoupled strength and stiffness, and energy dissipation, through relatively simple designs. If properly designed, they can be damage-free after earthquakes. However, their broader application requires further understanding at multiple levels. At the material level, the mechanical and tribological properties of composite friction materials remain insufficiently understood for earthquake structural engineering applications. At the component level, conventional friction-based components can be sensitive to machining tolerances, and friction shim inspection and replacement may require removal of external clamping parts, which can be time-consuming. In addition, friction-based components typically have near-zero post-elastic stiffness, which may lead to excessive connection displacement demands in specific applications.
      This dissertation investigates friction-based structural components through material-level experimental characterization and component-level development, testing, and assessment. At the material level, composite friction materials were characterized through tensile tests, bearing tests, bolt relaxation tests, and friction tests. The effects of material constituents, normal load, sliding velocity, displacement history, cumulative displacement, and dwell time were investigated. At the component level, two design concepts were studied. The first used initially loose steel washer plates in slotted-bolted friction-based components to reduce sensitivity to machining tolerances and to achieve accelerated repairability. The connection was evaluated through component-level tests and its implementation in a full-scale shaking table test of a three-story steel braced frame with sliding slabs. The second, termed the Modified Friction Device, was developed to generate predetermined discrete variable forces at target displacement levels. Its response was evaluated through reduced-scale and full-scale experimental testing. 
      The material-level results of this dissertation provide information for selecting composite friction materials for use in friction-based components for structural engineering applications. Friction-based components with loose-washer-plates design concept generated stable Coulomb-type force-displacement responses without enforcing tight machining tolerances and allowed rapid friction shim replacement. The Modified Friction Device developed the intended discrete variable friction force at predetermined displacement levels, and tests validated its kinematics and design parameters adjustability. Overall, this dissertation improves the understanding, design, and performance of friction-based components for use in earthquake-resistant structures.</dc:description><dc:subject>Engineering</dc:subject><dc:subject>Geophysics</dc:subject><dc:subject>Materials science</dc:subject><dc:subject>Civil engineering</dc:subject><dc:subject>Earthquake engineering</dc:subject><dc:subject>Experimental testing</dc:subject><dc:subject>Friction materials</dc:subject><dc:subject>Friction-based structural component</dc:subject><dc:subject>Structural connections</dc:subject><dc:subject>Structural engineering</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1963997s</dc:identifier><dc:identifier>https://escholarship.org/content/qt1963997s/qt1963997s.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4mf6r093</identifier><datestamp>2026-09-16T06:36:54Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4mf6r093</dc:identifier><dc:title>The Impact of Cmah Gene Deletion on Lipid Membrane Ordering and Mitochondrial Network in Relation to Hypoxic Tolerance</dc:title><dc:creator>Aziz, Rita Ezzat</dc:creator><dc:contributor>Breen, Ellen C</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>The inactivation of the cytidine monophospho-N-acetylneuraminic acid hydroxylase (CMAH) gene in pinnipeds occurred ~40 Mya and remains active in cetaceans. Pinnipeds and cetaceans are both excellent divers and do so without sustaining hypoxic injury, but the pinnipeds do so on a larger scale. Among the pinnipeds, northern elephant seals are one of the deepest divers capable of reaching depths as great of 1500 meters and dive for as long as 77 minutes. The potential role of the inactive Cmah gene in the peripheral oxygen transport of diving marine mammals has yet to be elucidated.  To address this knowledge gap, two Cmah-dependent adaptations were investigated. 1) the three-dimensional structural organization of myofiber mitochondrial networks and 2) the endothelial cell membrane lipid ordering response to hypoxia. Quantitative morphometry of the mitochondrial networks was obtained using SBF-SEM and segmentation with the aid of AMIRA software. Lipid ordering indices were measured in endothelial cells with Laurdan staining and detection in live cells by confocal microscopy. Pinniped (Northern elephant seal) and mouse (WT and Cmah-/-) skeletal myofibers suggest that inactivation of the Cmah gene is accompanied by mitochondria that are more connected with increased intermitochondrial junctions (IMJs), and a larger, less spherical geometry. Detection of lipid ordering in pinniped (grey seal) endothelial cells revealed a rapid decrease in the lipid ordering index in response to a decline in extracellular pO2 that remained decreased after re-oxygenation. Cmah expression in grey seal EC also resulted in a lower lipid ordering index that did not respond to a change in extracellular pO2. The inactivation of the CMAH gene in pinnipeds is accompanied by unique oxygen storage and diffusion mechanisms that may contribute to hypoxic tolerance and endurance while diving. These adaptations provide a new avenue of possible prevention of ischemic and hypoxic injuries. </dc:description><dc:subject>Physiology</dc:subject><dc:subject>Cellular biology</dc:subject><dc:subject>Molecular biology</dc:subject><dc:subject>Genetics</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4mf6r093</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4900569g</identifier><datestamp>2026-09-16T06:36:49Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4900569g</dc:identifier><dc:title>Examining the Collateral Consequences of Proactive Policing Strategies: A Case Study of the L.A.P.D.’s Operation L.A.S.E.R.</dc:title><dc:creator>Apolinar, Cristian</dc:creator><dc:contributor>Owens, Emily</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>The present dissertation examines the collateral consequences of proactive policing strategies, using the Los Angeles Police Department’s Operation L.A.S.E.R. as a case study. Rather than evaluating the program solely as a crime-control strategy, this dissertation asks how the intervention affected crime, educational outcomes, and neighborhood desirability in Los Angeles. The introductory chapter traces its development, expansion, criticism, and termination. Chapter 1 evaluates whether the 2015 expansion reduced crime without displacement into adjacent, non-treated census blocks. Division-, zone-, and block-level analyses find mixed evidence of crime reduction and little evidence of displacement. Chapter 2 examines whether exposure to Operation L.A.S.E.R. was associated with changes in assessment scores among Los Angeles Unified School District high school students. Active exposure was associated with lower assessment scores in nearly every all-student and student-subgroup analysis, though no association was statistically significant at conventional levels. Lastly, Chapter 3 examines neighborhood desirability through single-family home sale prices. Treatment was concentrated in Hispanic-majority, renter-heavy neighborhoods and associated with higher logged sale prices. Pooled officer-presence estimates were positive, though not statistically significant at conventional levels, and higher sale prices did not coincide with rapid demographic turnover.</dc:description><dc:subject>Criminology</dc:subject><dc:subject>Law enforcement</dc:subject><dc:subject>Public policy</dc:subject><dc:subject>Collateral Consequences</dc:subject><dc:subject>Crime Displacement</dc:subject><dc:subject>Educational Outcomes</dc:subject><dc:subject>Hot Spot Policing</dc:subject><dc:subject>Neighborhood Desirability</dc:subject><dc:subject>Proactive Policing</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4900569g</dc:identifier><dc:identifier>https://escholarship.org/content/qt4900569g/qt4900569g.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5hj0n5r6</identifier><datestamp>2026-09-16T06:36:43Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5hj0n5r6</dc:identifier><dc:title>Characterizing VIOLET: The Impact of Biofouling on Optical Performance and Taxonomic Observations in an In-Situ Optical Imaging System</dc:title><dc:creator>Constantino, Nicholas</dc:creator><dc:contributor>Jaffe, Jules</dc:contributor><dc:contributor>Decima, Moira</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>This thesis aims to determine the capabilities of the G2-MACRO-SPC, also known as “VIOLET”, a minimally invasive optical system capable of identifying and imaging copepods in situ. The primary focus is to determine how the optical performance of the system degrades over time due to biofouling, and how the taxonomic distribution observed by the system changes with optical performance. Image data was continuously collected, with computer vision extracting regions of interest. The system was not cleaned, and the degradation in optical performance was determined by measuring the contrast change over time with a 1951 USAF resolution test chart. The system’s contrast dropped below threshold values between 8 and 17 days. A downward trend was observed in the ROI areas, indicating that the system under samples smaller organisms as the optical degradation worsens. Additionally, with a baseline of 0% misidentified, the neural network misidentified 41% of the copepods after 8 days with the VIOLET moored vertically, and 30% of rod-shaped ROIs (diatom chains and seagrass that appear as straight lines). 74% of the copepods and 71% of the rod-shaped ROIs were misidentified after 12 days of simulated degradation with the VIOLET installed horizontally to the seafloor. When the experiment with the VIOLET installed horizontally was repeated, 69% of copepods and 68% of the rod-like ROIs were misidentified after 17 days of simulated degradation. These findings suggest the VIOLET should be cleaned at least every 8 days, and the methodology establishes a framework for determining the best cleaning efficiency of in-situ optical systems.</dc:description><dc:subject>Biological oceanography</dc:subject><dc:subject>Computer engineering</dc:subject><dc:subject>Ocean engineering</dc:subject><dc:subject>Biofouling</dc:subject><dc:subject>Characterization</dc:subject><dc:subject>In-Situ</dc:subject><dc:subject>Optical Imaging</dc:subject><dc:subject>Scripps Plankton Camera</dc:subject><dc:subject>Taxonomic Classification</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5hj0n5r6</dc:identifier><dc:identifier>https://escholarship.org/content/qt5hj0n5r6/qt5hj0n5r6.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt78q5x7r0</identifier><datestamp>2026-09-16T06:36:38Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt78q5x7r0</dc:identifier><dc:title>Investigating the Effects of Ketone Body Supplementation on Astrocytes in Tauopathy</dc:title><dc:creator>Di Silvestri, Julia</dc:creator><dc:contributor>Chen, Xu</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Alzheimer’s disease (AD) is a fatal neurodegenerative disease marked by the pathological accumulation of amyloid β and tau protein. While multiple drugs are approved for treatment in AD patients, none meaningfully alter the progression of the disease. Recent studies have highlighted the prominence of metabolic dysfunction in AD, sparking an interest in metabolism-based therapies. Ketone body supplementation has shown evidence of alleviating cognitive symptoms in patients, as well as ameliorating tau pathology in animal and neuron culture models.&amp;nbsp;However, there has been limited investigation into how ketone body supplementation alters astrocytic behavior, and specifically metabolism, in the setting of tauopathy. To address this question, we assessed morphological, transcriptional, and functional effects of ketone bodies on astrocytes in in vivo and in vitro tauopathy models. Through single-nucleus RNA sequencing of tauopathy mice, we observed that βHB supplementation could rescue reactive markers and deficits in cholesterol synthesis gene expression in astrocytes. Bulk RNA sequencing using primary astrocyte culture showed that direct application of βHB on astrocytes can also increase expression of cholesterol synthesis genes, but tau fibril alone may not be sufficient to drive a deficit in this pathway. Taking advantage of the stereospecificity of BDH1, the enzyme responsible for the first step of the breakdown of βHB, we found that the observed effects of βHB on astrocytes may be largely attributed to ketolysis-independent mechanisms. Overall, this work identifies astrocyte metabolism as a potential target of the beneficial effects of βHB in tauopathy and sets the groundwork for further research into how restoration of astrocytic cholesterol homeostasis affects broader outcomes in disease.</dc:description><dc:subject>Neurosciences</dc:subject><dc:subject>Pathology</dc:subject><dc:subject>Biochemistry</dc:subject><dc:subject>Genetics</dc:subject><dc:subject>Alzheimer's Disease</dc:subject><dc:subject>Astrocyte</dc:subject><dc:subject>Ketone</dc:subject><dc:subject>Tau</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/78q5x7r0</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4g33h6vf</identifier><datestamp>2026-09-16T06:36:33Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4g33h6vf</dc:identifier><dc:title>Applications of Fourier Transform Infrared (FT-IR) Spectroscopy for Fish Identification Using Scales and Otoliths</dc:title><dc:creator>Callahan, Sarah Grace</dc:creator><dc:contributor>Semmens, Brice X.</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>The ability to accurately identify fish species is crucial for fisheries management and stock assessments. Traditional techniques such as morphological or genetic analysis can be costly, time-consuming, and often destructive to the sample. This study evaluates the utility of Fourier transform infrared (FT-IR) spectroscopy as a rapid, cost-effective, and non-destructive tool for fish identification. I collected spectral data from both otoliths and scales of several recreationally important fish in California. I standardized the data following quality control and then used principal component analysis (PCA) to reduce dimensionality prior to performing linear discriminant analysis (LDA). The spectral data collected from the scales consistently displayed higher classification accuracy than spectral data from the otoliths. This may be due to stronger organic signatures in the scales that are associated with a greater abundance of organic material, particularly proteins such as collagen, relative to otoliths. The greater variability exhibited in the otolith spectra may reflect the heterogeneity in calcium carbonate composition across the growth regions of the samples. Overall, classification performance varied among species, with some displaying relatively high discrimination and others limited by small sample sizes and overlapping spectral features. Overall, the findings of this study support FT-IR spectroscopy as a promising and efficient tool for fish species identification with applications for fisheries monitoring and the field of ecological and paleo research.</dc:description><dc:subject>Biological oceanography</dc:subject><dc:subject>Aquatic sciences</dc:subject><dc:subject>Analytical chemistry</dc:subject><dc:subject>Fish Identification</dc:subject><dc:subject>Fisheries Science</dc:subject><dc:subject>FT-IR Spectroscopy</dc:subject><dc:subject>Marine Biology</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4g33h6vf</dc:identifier><dc:identifier>https://escholarship.org/content/qt4g33h6vf/qt4g33h6vf.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt49z6405b</identifier><datestamp>2026-09-16T06:36:28Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt49z6405b</dc:identifier><dc:title>Overcoming Fabrication and Operation Challenges for Practical All-Solid-State Batteries</dc:title><dc:creator>Lee, Dong Ju</dc:creator><dc:contributor>Chen, Zheng</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>All-solid-state batteries (ASSBs) are promising alternatives to conventional lithium-ion batteries (LIBs), replacing flammable organic liquid electrolytes with safer inorganic solid-state electrolytes (SSEs). Despite significant advancements in SSE materials, the commercialization of ASSBs remains impeded by the emergent challenges in their fabrication and operation. This dissertation presents scalable fabrication techniques alongside novel structural and materials designs to achieve stable operation of ASSBs. First, the role of polytetrafluoroethylene (PTFE) binder on the physical, chemical, and electrochemical properties of SSE separator films during solvent-free dry-processing is investigated. Second, a new dry-process approach that fabricates a thin SSE separator layer while establishing intimate physical contact with a thick cathode layer is developed, enabling stable operation under low stack pressure (2 MPa). Next, a silicon (Si)-metal alloy composite anode that electro-chemo-mechanically stabilizes the large volume changes of Si anodes under low stack pressure is developed. Lastly, tin (Sn)-based foil anode using multi-dimensional engineering strategies is explored, demonstrating Sn as a promising alloy anode for low-stack pressure operation. Together, these studies address critical manufacturing and operational bottlenecks, bringing ASSBs a step closer to commercialization.</dc:description><dc:subject>Energy</dc:subject><dc:subject>Chemical engineering</dc:subject><dc:subject>Materials science</dc:subject><dc:subject>Engineering</dc:subject><dc:subject>Batteries</dc:subject><dc:subject>Solid-State Batteries</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/49z6405b</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3jm8z1r1</identifier><datestamp>2026-09-16T06:36:23Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3jm8z1r1</dc:identifier><dc:title>Systematics and taxonomic revision of eastern Pacific Grimothea (Crustacea; Decapoda; Munididae)</dc:title><dc:creator>Goutzioulis, Nicholas</dc:creator><dc:contributor>Rouse, Greg</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Three species of the squat lobster genus Grimothea (Leach, 1821) dominate the east Pacific coast, Grimothea monodon (Milne-Edwards, 1837), Grimothea planipes (Stimpson, 1860), and Grimothea quadrispina (Benedict, 1902). The three species all exhibit similar pelagic and benthic phenotypes and swarming behaviors. The aim of this study is to determine the validity of G. monodon, G. planipes and G. quadrispina as distinct species using molecular data. Based on the mitochondrial DNA (cytochrome oxidase subunit 1 (COI) gene and nuclear histone H3 (HH3) gene we show that Grimothea planipes is synonymous with G. monodon as a single species inhabiting a range from California to Concepción, Chile. We synonymize these species under the senior synonym Grimothea monodon. Utilizing multi-loci phylogenetic analysis of two mitochondrial genes (COI and 16S) and one nuclear gene (Histone H3), Grimothea quadrispina is recovered as a sister species to G. monodon (=G. planipes).</dc:description><dc:subject>Systematic biology</dc:subject><dc:subject>Biology</dc:subject><dc:subject>Cellular biology</dc:subject><dc:subject>Molecular biology</dc:subject><dc:subject>Genetics</dc:subject><dc:subject>Grimothea monodon</dc:subject><dc:subject>Grimothea planipes</dc:subject><dc:subject>Munididae</dc:subject><dc:subject>systematics</dc:subject><dc:subject>taxonomy</dc:subject><dc:subject>tuna crab</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3jm8z1r1</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt05v6m49c</identifier><datestamp>2026-09-16T06:36:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt05v6m49c</dc:identifier><dc:title>Lagrangian drifter measurements of the effects of seaweed cultivation on seawater carbon chemistry on a nearshore coral reef in Okinawa, Japan</dc:title><dc:creator>Thornton, Finian</dc:creator><dc:contributor>Andersson, Andreas J</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Ocean acidification (OA) and deoxygenation (collectively OAD) increasingly threaten coral reefs, which support marine biodiversity and human economic activity. Seaweed farms have been proposed to locally mitigate OAD conditions by removing dissolved inorganic carbon (DIC) and enhancing pH and dissolved oxygen (DO), but empirical evidence has been limited. Here, we investigated the effects of seaweed farming on net community production (NCPDIC, NCPDO), net community calcification (NCC), and seawater chemistry on a back reef lagoon system in Onna, Okinawa, Japan. Lagrangian drifters were used to measure and calculate rates of NCP, NCC, pH, and aragonite saturation state (Ωarag) in December 2022, April 2023, January 2024, and May 2024. The April 2023 and May 2024 surveys coincided with the annual maximum extents of seaweed cultivation (0.16 and 0.14 km2 respectively). Mean NCP and NCC were positive across sessions, but had high variability. Under saturating solar radiation, we observed elevated NCPDIC and NCPDO in April 2023 compared to January 2024, and stronger increases in pH and Ωarag in April 2023 and in May 2024 than in January 2024. Changes in pH and Ωarag were driven by NCPDIC, which was itself driven by temperature and solar radiation. We noted that NCC had a minor effect on the carbonate chemistry system relative to NCP. While we observed biogeochemical signals consistent with biotically-driven OAD modulation, the lack of spring survey control groups limits our ability to decisively attribute this modulation to the seaweed farm.</dc:description><dc:subject>Biology</dc:subject><dc:subject>Ecology</dc:subject><dc:subject>Inorganic chemistry</dc:subject><dc:subject>Coral</dc:subject><dc:subject>Ocean acidification</dc:subject><dc:subject>Seaweed</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/05v6m49c</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3hq3g1ss</identifier><datestamp>2026-09-16T06:36:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3hq3g1ss</dc:identifier><dc:title>Hydrodynamics and kinematics of glass catfish schools</dc:title><dc:creator>Anuszczyk, Aniela Katherine</dc:creator><dc:contributor>Di Santo, Valentina</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Fishes swimming in schools are hypothesized to reduce locomotor cost by exploiting the vortex wakes generated by their neighbors, a mechanism proposed five decades ago and since supported indirectly via computational and mathematical simulations. Direct evidence has remained out of reach because the opaque bodies of schooling fishes block the optical access particle image velocimetry (PIV) requires to resolve flow. We removed this barrier using the naturally transparent glass catfish (Kryptopterus vitreolus), enabling PIV to resolve the flow field within the interior of a freely swimming five-fish school. We combined time-resolved PIV, acquired with a galvanometer-driven mirror light-sheet system, with simultaneous digitization of each individual’s midline across six flow speeds (1.75–2.50 body lengths per second), linking local flow structures to individual swimming kinematics. Schools most often adopted an in-line formation, followed by staggered, phalanx, and diamond formations. Individuals identified as interacting with a neighbor’s wake, or benefiting from a channeling effect in phalanx formation, swam with reduced effort relative to other fish at higher flow speeds. This provided direct kinematic evidence for a hydrodynamic benefit of schooling that has previously been inferred only from computational and metabolic studies. This benefit was not uniform: effort, tail-beat phase, and wake circulation each varied by formation in ways that did not consistently align with one another, while Strouhal numbers throughout remained within the range associated with efficient oscillatory propulsion. These results indicate that schooling fishes draw on more than one distinct hydrodynamic mechanism depending on their spatial arrangement within the group, and demonstrate that optically transparent species offer a tractable route to directly testing long-standing hydrodynamic hypotheses of collective swimming.</dc:description><dc:subject>Biomechanics</dc:subject><dc:subject>Limnology</dc:subject><dc:subject>Biophysics</dc:subject><dc:subject>collective behavior</dc:subject><dc:subject>fish schooling</dc:subject><dc:subject>particle image velocimetry</dc:subject><dc:subject>swimming kinematics</dc:subject><dc:subject>vortex interactions</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3hq3g1ss</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2996w29c</identifier><datestamp>2026-09-16T06:36:08Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2996w29c</dc:identifier><dc:title>The Endocrine System in Neurodegenerative Disease: Hormonal Signaling in Alzheimer’s Pathology</dc:title><dc:creator>Abrass, Madeline</dc:creator><dc:contributor>Rosenfeld, Michael G</dc:contributor><dc:date>2026-09-15</dc:date><dc:description>Alzheimer’s disease (AD) disproportionately affects women, where women are at nearly twice the risk of getting AD compared to men. Some of this disparity has been linked to the hormonal changes that women experience before, during, and after menopause. Estrogen and progesterone play important roles in regulating neuroinflammation, gene expression, and amyloid-beta (Aβ) clearance—pathways disrupted in AD. This study investigates how estradiol (E2) and progesterone (P4) impact the transcription of hormone-responsive and AD-related genes in SIM-A9 microglial cells. Gene expression levels of ApoE, Greb1, Pgr, and Kcnk5 were quantified following hormone treatments, both alone and in the presence of Aβ.E2 treatment significantly upregulated Greb1 and ApoE expression, particularly at 10.0 and 100 µg/mL. Kcnk5, a gene linked to glial ion channel activity, was strongly induced at 100 µg/mL E2. P4 treatment also increased Pgr and ApoE expression, and notably upregulated Greb1, suggesting possible hormonal pathway cross-talk. When cells were pre-treated with Aβ, all target gene expressions were suppressed. E2 alone rescued ApoE and Greb1 expression, while P4 only restored Pgr levels. Combination hormone treatment did not produce synergistic effects.These findings highlight estrogen’s broad transcriptional influence and its potential for reversing Aβ-induced microglial dysfunction. This study underscores the importance of considering hormone-specific and gene-specific responses when designing therapeutic interventions. The results support early estrogen-based treatment strategies in women at risk for AD and provide molecular insight into sex-specific vulnerability in neurodegeneration.</dc:description><dc:subject>Biology</dc:subject><dc:subject>Neurosciences</dc:subject><dc:subject>Pathology</dc:subject><dc:subject>Endocrinology</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2996w29c</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2kf0v4f8</identifier><datestamp>2026-09-16T06:36:03Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2kf0v4f8</dc:identifier><dc:title>The Company You Keep: CryoEM in Cellular Contexts Across the Tree of Life</dc:title><dc:creator>Agnew, Angela</dc:creator><dc:contributor>Zhou, Hong</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>Cellular function depends on the spatial organization of proteins within their native environment. Although traditional structural biology has yielded high-resolution structures of both isolated and complexing proteins, many fundamental questions require studying these structures, particularly large assemblies responsible for cellular organization, in their original or near-native contexts. Recent advances in cryo-electron microscopy, tomography, and sample preparation now make it possible to visualize macromolecular architecture from cellular extracts or directly inside cells. Here, we apply these approaches to five case studies depicting protein assemblies from both protozoan and methanogenic archaeal systems. The former is a model parasite organism but lacks contextual views of essential cytoskeletal components, and the latter lacks the molecular toolkit for extensive protein enrichment and characterization, necessitating native structure methods. By combining cryoET with subtomogram averaging and single-particle cryoEM we elucidate massive cytoskeletal structures and ID novel proteins comprising the Trypanosoma&amp;nbsp;brucei paraflagellar rod and subpellicular array. Then, applying these techniques to the members of Methanosarcina, Methanosaeta, and Methanospirillum results in identification of new structures of the PLP synthase, ATP synthase, and the sheathed cell end architecture, shedding light on fundamental cellular processes involved in energy generation and locomotion. These studies demonstrate how modern cryoEM methodologies can reveal cellular organization that is difficult to capture using purified samples alone, or in biological systems which remain recalcitrant to traditional molecular biology methods.</dc:description><dc:subject>Biochemistry</dc:subject><dc:subject>Cellular biology</dc:subject><dc:subject>Biology</dc:subject><dc:subject>Molecular biology</dc:subject><dc:subject>CryoEM</dc:subject><dc:subject>CryoET</dc:subject><dc:subject>Flagella</dc:subject><dc:subject>Methanogens</dc:subject><dc:subject>Structural Biology</dc:subject><dc:subject>Trypanosomes</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2kf0v4f8</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4bk4510z</identifier><datestamp>2026-09-16T06:35:58Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4bk4510z</dc:identifier><dc:title>For the Quiet Star</dc:title><dc:creator>Ridley, Stephen</dc:creator><dc:contributor>Krouse, Ian</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>A meditation on solace, gentle steps and the space between moments, For the Quiet Star is framed by a simple structure: from nothing, into something, and back to nothing. To capture this, the pitched percussion and string sections are approached sonically, and presented with timbral pairings.Vibraphones are bowed throughout, in unison with high strings, creating a hybrid color. To match this sound, the strings play without vibrato throughout the piece, producing a glassy, transparent texture that merges with the sustain of the bowed vibraphones. This combination forms a core sound world for the work.By contrast, when marimbas are dominating the texture, short string sounds are used as the colorizing element, creating a kind of blended, string-timbred marimba.The vibraphones also anchor the pitch content with simultaneous low and high pedal points, one at each extreme of the instrument's range. Within that large interval, an incantatory string melody pushes toward moments of arrival. Rather than continuing to develop, these moments are static, allowed to sit in consonance for a listener to observe.Dictated by the form, the middle of the piece is the most active section. A stream of sixteenth notes is always felt in 4, but the subdivisions shift between groups of 5, 4 and 3, creating a lurching until the arrival of a true 4/4, and the climax of the work.</dc:description><dc:subject>Musical composition</dc:subject><dc:subject>Music</dc:subject><dc:subject>Music theory</dc:subject><dc:subject>Chamber</dc:subject><dc:subject>Marimba</dc:subject><dc:subject>Percussion</dc:subject><dc:subject>Strings</dc:subject><dc:subject>Tonal</dc:subject><dc:subject>Vibraphone</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4bk4510z</dc:identifier><dc:identifier>https://escholarship.org/content/qt4bk4510z/qt4bk4510z.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt05s79065</identifier><datestamp>2026-09-16T06:35:53Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt05s79065</dc:identifier><dc:title>Interface Engineering for Efficient and Stable Perovskite Thin-Film Solar Cells</dc:title><dc:creator>Yang, Wenxin</dc:creator><dc:contributor>Yang, Yang</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>Metal-halide perovskite solar cells have attracted tremendous interest because of their compatibility with low-temperature processing, strong optical absorption, defect tolerance, and tunable electronic structures. Despite rapid improvements in power conversion efficiency, their practical deployment remains limited by insufficient operational stability. Interfaces are particularly important because they simultaneously govern charge extraction, non-radiative recombination, ionic redistribution, chemical reactions, and, at buried interfaces, the formation of the perovskite absorber itself. This dissertation investigates how molecularly engineered polymeric interfaces can regulate these coupled electronic, ionic, and structural processes to improve both the efficiency and long-term stability of perovskite solar cells.Chapter One introduces the fundamental properties and stability challenges of metal-halide perovskites, with particular emphasis on the multifunctional roles of interfaces. Electronic defect passivation, ionic and chemical stabilization, and buried-interface regulation of nucleation and crystal growth are established as complementary strategies for interface engineering. Chapter Two focuses on defect passivation at the exposed perovskite surface. hree polymeric modifiers, including poly(vinyl acetate), polyethylene glycol, and poly(9-vinylcarbazole), are systematically compared to establish a molecular design principle linking electronic structure and steric accessibility with defect-interaction strength. Stronger Lewis-base interactions with undercoordinated Pb species suppress non-radiative recombination, improve charge transport, and substantially enhance device efficiency and operational stability. Chapter Three extends the discussion from the exposed surface to the buried interface, highlighting its dual role as a dynamic ionic boundary during operation and as a template for perovskite formation during fabrication. Chapter Four identifies cross-interface Sn redistribution from SnO2 into the perovskite absorber as an important degradation pathway during prolonged operation. Sn migration is accompanied by chemical-state evolution, while ultrathin polymeric interlayers increase the energetic barrier for ionic transport and suppress Sn redistribution, leading to markedly improved long-term stability. Chapter Five demonstrates that the same buried interlayers also regulate perovskite formation by modifying wettability, interfacial contact, crystallization, phase quality, and defect formation. These changes reduce non-radiative recombination and enable high-efficiency small-area devices and modules. Together, these studies establish polymeric interface engineering as a strategy for simultaneously controlling defect chemistry, ionic transport, buried-interface evolution, and perovskite formation, providing design principles for efficient and durable perovskite photovoltaics.</dc:description><dc:subject>Materials science</dc:subject><dc:subject>Energy</dc:subject><dc:subject>Electrical engineering</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/05s79065</dc:identifier><dc:identifier>https://escholarship.org/content/qt05s79065/qt05s79065.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt54w03477</identifier><datestamp>2026-09-16T06:35:48Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt54w03477</dc:identifier><dc:title>Statistical Evidence, Individual Evidence, and Fairness in the Courtroom: A Moral Solution to Puzzles in Legal Proof</dc:title><dc:creator>Mackenzie, Mikaela Grace</dc:creator><dc:contributor>Hieronymi, Pamela</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>This dissertation defends a moral solution, specifically a solution about fairness, to a puzzle regarding the use of statistical evidence in legal proceedings.To illustrate the puzzle, consider a popular toy case: the mere fact that the majority of attendees in the stadium gatecrashed does not, by itself, seem sufficient to find any one attendee liable. This seems so even if the statistic raises the probability of the disputed fact to a level seemingly high enough to meet the burden of proof (i.e. more likely than not). It is said that all there is, in this case, is “bare” statistical evidence (BSE), and we need "individualized" evidence (IE) for the defendant’s liability. But what differentiates IE from BSE which makes the former but not the latter appropriate for findings of liability (or guilt)?Numerous attempts are made to answer this puzzle. This dissertation critically discusses some influential proposals alongside more recent proposals.One influential proposal makes use of the notion of causation arguing that whereas the factfinder believes IE has a causal connection to the purported fact (of the defendant’s guilt or liability), the factfinder does not believe BSE bears this causal connection.Another influential proposal makes use of the notion of Truth-Sensitivity from the philosophical literature on knowledge arguing that while BSE fails to produce verdicts which are Truth-Sensitive, IE successfully produces Truth-Sensitive verdicts such that: had the defendant not been the perpetrator, the factfinder would not have found them guilty or liable.These proposals are intuitively appealing. However, they are mercilessly objected to. Recent scholarship attempts to refine earlier proposals, clarifying causation and Truth-Sensitivity. However, they still face problems. The primary problem is that the notions of causation and Truth-Sensitivity still lack clarity.In response to the problems, I propose a diagnosis which makes use of fairness: finding on the basis of BSE is unfair because if we made a policy of it, there would be unjust outcomes—innocent people being arbitrarily punished. Whereas a policy of finding on IE does not guarantee unjust outcomes.</dc:description><dc:subject>Philosophy</dc:subject><dc:subject>Epistemology</dc:subject><dc:subject>Ethics</dc:subject><dc:subject>Logic</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/54w03477</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8w04j5pq</identifier><datestamp>2026-09-16T06:35:43Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8w04j5pq</dc:identifier><dc:title>Native American Tuition Waivers: Uncovering the Complexity of Eligibility, Native Identities, &amp;amp; Improvements for the Future</dc:title><dc:creator>Wyatt, Avory</dc:creator><dc:contributor>Marin, Ananda M</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>Over the past decade, a significant number of higher education institutions across the US have sought to expand education access by establishing tuition waivers for Native American students. A tuition waiver commonly provides free or reduced tuition for Native American students who can meet the eligibility criteria set by an institution. As support for Native students through the form of tuition waivers continues to expand, there is a critical need for institutions to understand both the positive and negative impacts of tuition waivers beyond the benefits of financial assistance. In this thesis, I explore the impact of Native American tuition waivers by focusing on the University of California’s Native American Opportunity Plan (NAOP) and Native student experiences with the NAOP at UCLA. Through interviews with Native students from diverse tribal community connections and racial identities, this study highlights the importance of recognizing the complexity of contemporary Native identities and addressing barriers for Native students beyond financial access. The findings suggest that tuition waivers can be most effective when paired with intentional learning about Native communities on behalf of institutions, and sustained support systems that promote Native student retention and pathways toward graduation. In addition, I offer recommendations based on Native student’s experiences for expanding tuition waiver eligibility to include the highest number of eligible students.</dc:description><dc:subject>Native American studies</dc:subject><dc:subject>Higher education</dc:subject><dc:subject>Education policy</dc:subject><dc:subject>Native American</dc:subject><dc:subject>Native Identity</dc:subject><dc:subject>Native Student Experiences</dc:subject><dc:subject>Native Student Support</dc:subject><dc:subject>Tribal Critical Race Theory</dc:subject><dc:subject>Tuition Waiver</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8w04j5pq</dc:identifier><dc:identifier>https://escholarship.org/content/qt8w04j5pq/qt8w04j5pq.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt38j8p7z3</identifier><datestamp>2026-09-16T06:35:38Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt38j8p7z3</dc:identifier><dc:title>Structure and Kinetic Engineering of Nanostructured Multi-Element Doped Ni-Rich Cathodes for Fast-Charging Lithium-ion Batteries</dc:title><dc:creator>Shao, Yikun</dc:creator><dc:contributor>Tolbert, Sarah H</dc:contributor><dc:date>2026-09-11</dc:date><dc:description>Fast charging of Ni-rich layered oxide cathodes is limited by slow Li⁺ transport and large structural changes at high states of charge. This thesis investigated nanostructuring and multi-element doping as a combined strategy for developing cobalt-free Ni-rich cathodes. NM-MgNbMo, NM-MgAlMo, and NM-MgTiNbMo were synthesized using a polymer-assisted micelle-templated sol–gel method and compared with bulk and less porous NMC-811. X-ray diffraction confirmed the layered α-NaFeO₂-type structure and distinct interlayer spacings; NM-MgNbMo had the least apparent cation mixing and largest spacing, supporting easier Li⁺ transport and faster kinetics, while partial disorder may provide a stabilizing pillaring effect. NM-MgNbMo exhibited the best high-rate performance among the doped samples, maintaining approximately 36 mAh/g at 32C when the capacity of bulk NMC-811 approached zero. CV and GITT measurements were also consistent with comparatively low apparent polarization for NM-MgNbMo. After 1000 cycles at 8C, NM-MgNbMo retained the highest absolute capacity, whereas NM-MgTiNbMo showed the highest fractional retention from a lower initial capacity. Operando X-ray diffraction showed substantially smaller c-lattice changes in the doped samples than in the NMC-811 references. Overall, NM-MgNbMo provided the best balance between high-rate capacity and structural stability, while NM-MgTiNbMo favored structural stability at the cost of accessible capacity.</dc:description><dc:subject>Materials science</dc:subject><dc:subject>Engineering</dc:subject><dc:subject>Physical chemistry</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/38j8p7z3</dc:identifier><dc:identifier>https://escholarship.org/content/qt38j8p7z3/qt38j8p7z3.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6n95x19d</identifier><datestamp>2026-09-16T06:35:33Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6n95x19d</dc:identifier><dc:title>Uncovering Cell State Transition Driver Genes Through Applied Critical Transition Theory</dc:title><dc:creator>Silkwood, Kai Haskell</dc:creator><dc:contributor>Lander, Arthur</dc:contributor><dc:date>2026-09-14</dc:date><dc:description>Cell state transitions can be modeled as critical transitions marked by an increase in gene-gene correlation among a subset of expressed genes. These genes, the cell state transition drivers, are of interest for their role in guiding the cell into a new state in response to some signal. Single cell RNA sequencing (scRNAseq) should allow us to measure these changes in correlation across a transition trajectory. However, the distribution of scRNAseq counts does not fit the expectations that traditional correlation analyses rely on, leading to millions of false discoveries. Here, I develop a method to accurately calculate and statistically validate gene-gene correlations from scRNAseq data. Then, I demonstrate that those same principles can be used to derive statistics for feature selection tasks and that using those statistics leads to better clustering results. Because critical transition theory predicts that correlations among driver genes rise as the cell approaches the tipping point and decay once they enter a new state, transient peaks in correlation should mark candidate transition drivers. Therefore, I propose a method for analyzing gene-gene correlation trajectories which uncovers cell state transition driver genes. This method captures known cell state transition drivers in epithelial to mesenchymal transition and neuromesodermal progenitor differentiation. Finally, I use this method to identify SHH-expression driver genes PITX2 and NPAS3 in the developing chick frontonasal prominence. The importance of these genes is then experimentally validated through knockout experiments. These developments allow for principled correlation analyses of scRNAseq datasets and demonstrate the utility of applied critical transition theory in identifying critical transition driver genes.</dc:description><dc:subject>Biology</dc:subject><dc:subject>Cellular biology</dc:subject><dc:subject>Developmental biology</dc:subject><dc:subject>Genetics</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6n95x19d</dc:identifier><dc:identifier>https://escholarship.org/content/qt6n95x19d/qt6n95x19d.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt78h7h8zh</identifier><datestamp>2026-09-16T06:35:27Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt78h7h8zh</dc:identifier><dc:title>Narrativas no reparadoras de la enfermedad: padecimiento psíquico, identidad y autoridad interpretativa en la literatura y el cine</dc:title><dc:creator>Álvarez Zanza, Natalia</dc:creator><dc:contributor>Pichon-Rivière, Rocío</dc:contributor><dc:date>2026-09-14</dc:date><dc:description>This doctoral dissertation examines the forms of representation of mental suffering in a comparative corpus of literature and film, from the perspective of the medical humanities. The corpus brings together Torcuato Luca de Tena's Los renglones torcidos de Dios (1979) and Dennis Lehane's Shutter Island (2003); the Diarios and poetic work of Alejandra Pizarnik; and Alejandro Amenábar's Abre los ojos (1997), David Lynch's Lost Highway (1997) and Mulholland Drive (2001), and Iván Zulueta's Arrebato (1979/1980). Through close reading, formal analysis, historical contextualization, and engagement with illness-narrative theory, this study examines how these works articulate the relationships between suffering, identity, diagnosis, and interpretive authority. The first chapter shows how the psychiatric hospital is configured as a space of care, confinement, surveillance, and institutional production of truth, while the gothic-detective structure transforms the investigation of a crime into a dispute over the credibility and identity of the institutionalized subject. The second shifts this conflict to Pizarnik's writing, where clinical, psychoanalytic, and literary languages run through the subject's relationship with itself without fully defining it, and where silence, fragmentation, and images of loss or dispossession function as procedures of working-through rather than as mere symptoms. The third analyzes how the cinematic body, editing, sound, and temporality transpose this instability into the organization of perception, implicating the spectator in the act of interpretation as well. On this basis, the dissertation proposes the notion of the non-restitutive narrative of illness to describe literary and cinematic forms of suffering that do not subordinate it to a full restitution of health or identity. In critical dialogue with Arthur W. Frank's typology, this category is not proposed as a fourth mode alongside restitution, quest, and chaos narratives, but rather as a different analytical axis that makes it possible to separate two acts that may coincide but are not equivalent: organizing an experience and repairing it. The comparative analysis further shows that the unequal distribution of interpretive authority constitutes a cross-cutting problem, one also framed in terms of epistemic injustice. The dissertation's contribution to medical humanities thus lies in shifting attention from the mere thematic presence of illness toward the forms that render suffering legible, and in proposing an ethics of interpretation that does not make coherence, explanation, or cure necessary conditions for these experiences to be recognized and heard.</dc:description><dc:subject>Literature</dc:subject><dc:subject>Cinematography</dc:subject><dc:subject>Medicine</dc:subject><dc:subject>Epistemology</dc:subject><dc:subject>Film studies</dc:subject><dc:subject>epistemic injustice</dc:subject><dc:subject>identity</dc:subject><dc:subject>illness narratives</dc:subject><dc:subject>literature and film</dc:subject><dc:subject>medical humanities</dc:subject><dc:subject>non-reparative narratives</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/78h7h8zh</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1gj6v58k</identifier><datestamp>2026-09-16T06:35:23Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1gj6v58k</dc:identifier><dc:title>Virtues for Public Philosophers: Five Epistemically Ameliorative Regulative Ideals</dc:title><dc:creator>Read, James Patrick</dc:creator><dc:contributor>Ellis, Jonathan</dc:contributor><dc:date>2026-08-27</dc:date><dc:description>The present work examines five virtues that promise to be helpful for public philosophers as they seek to promote knowledge in non-academic or non-traditional spaces through teaching and dialogue. These five virtues, in order of discussion, are self-forgetfulness, graciousness, Murdochian charity, creativity, and courage. In particular, these virtues promise to be epistemically ameliorative, by which I mean they help public philosophers both promote norms of reasoning that are conducive to knowledge in others, but also in themselves. The ineliminable dialogue at philosophy’s core is a key theme in this work, as is reflected in appendix 1, which serves as a model both for myself and others who are interested in a public-facing philosophy in the spirit of Plato and Socrates. Appendix 2 examines the public philosopher’s epistemic life as it intersects with a challenging case in aesthetics. Appendices 3 and 4 serve as creative prose expressions of the virtues recommended here for public philosophers, in either professional or non-professional settings, while only the former (appendix 3) is non-fiction. Appendices 5 and 6 serve as meditations on writing – part of being a public philosopher involves writing in a way that earns attention from that public – and here again there is a split between non-fiction and fiction, appendix 5 being a non-fictional, faithful examination of the anxieties of Simone Weil, whereas appendix 6 is a fictional poem grounded in metaphor, written to distill the spirit of what I take to be Weil’s most exciting, provocative, and instructive work, Gravity and Grace.</dc:description><dc:subject>Philosophy</dc:subject><dc:subject>Ethics</dc:subject><dc:subject>Epistemology</dc:subject><dc:subject>Metaphysics</dc:subject><dc:subject>AMELIORATIVE</dc:subject><dc:subject>EPISTEMIC</dc:subject><dc:subject>IDEALS</dc:subject><dc:subject>PHILOSOPHER</dc:subject><dc:subject>PUBLIC</dc:subject><dc:subject>VIRTUE</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1gj6v58k</dc:identifier><dc:identifier>https://escholarship.org/content/qt1gj6v58k/qt1gj6v58k.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8gx9f8sq</identifier><datestamp>2026-09-16T06:35:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8gx9f8sq</dc:identifier><dc:title>Converging Assemblages:  Medieval Textiles of Central Asia, Iran, and India (c. 9th-13th centuries)</dc:title><dc:creator>Nishanova, Bermet</dc:creator><dc:contributor>Patel, Alka</dc:contributor><dc:date>2026-09-14</dc:date><dc:description>The “corpus” of medieval textiles from Central Asia, Iran, and India — spanning roughly the 9th to the early 13th centuries — constitutes one of the most technically complex and historiographically fragmented bodies of objects in the study of Islamic art. The period is characterized by successive political rearticulations by the Samanid, Ghaznavid, Qarakhanid, Seljuk, and Shansabani governments, which administered the interregional spaces that had long been shaped by Iranian, Indic, and steppe cultural frameworks. The period is also characterized by the growing prevalence of Islam, which emerges as the increasingly dominant, albeit internally diverse, religious tradition. Here, textiles can rarely be attributed to specific workshops or provenances; yet, their fibers, dyes, and woven structures nonetheless carry recoverable historical meaning — one that this study argues can be accessed through examining the processes of their making.By analyzing according to the framework of converging assemblages, I argue that textiles from this medieval interregional space are transformed through their constituent parts, participating at each level of production in various socio-political dialogues and contexts. This ontological reframing of the textile medium certainly responds to the longstanding marginalization of textiles within art history, where their technical complexity and elusive provenance have kept them at the periphery of scholarly attention despite the common recognition of the medium’s deep entrenchment in the material and ceremonial life of the medieval world. Following this framework, the dissertation examines textiles through five successive scales of inquiry, each building on the last. In Chapter 2, I begin with the “raw” materials — fibers such as wool, silk, and cotton —examining their production via spindle whorls, tracing their local and interregional dimensions, and references made to these fibers in geographic literature. I also conduct close fiber analysis to suggest how certain regional (local) qualities of fibers likely rendered them desirable in global markets. This study then turns to dyes and colorants of textiles, examining a group of Central Asian kesi silk slit-tapestries to argue that natural dyes occupied a morally ambiguous position in the increasingly Islamic milieu. I examine polychrome here as it was possibly received by the elite Central Asian and Iranian audiences trained in adab and through the interpretive lens of būqalamūn. In Chapter 3, then, I refer to būqalamūn and connect the term with broader contemporaneous considerations of color, light, and wonder, which reframed and ameliorated the unstable chromatic surfaces as occasions for cultivated perception. The subsequent examination of textile production in Chapter 4 proposes a prosopographic understanding of the textile artist as a collective body, distributing the “body” across domestic, workshop, and itinerant spaces. I refer to the “textile making” community as having embodied, intergenerational knowledge that is further shaped by interregional networks and material culture beyond the fixed urban workshops that authors have traditionally privileged. In Chapter 5, I consider how this “textile making” context shaped woven structures and examine how the final “woven structures” were likely perceived by referring to medieval Islamic optical theory. Here, I position plain-woven mulḥam, double- and triple-weave, samite, and proto-lampas textiles as surfaces designed to activate different modes of haptic and contemplative looking. Finally, this dissertation traces various ornamental motifs, specifically focusing on the "star and cross" motif, found on textiles and other media to examine how textiles participated in historically grounded intermedial assemblages. Specifically, I suggest how the star and cross motif constituted and sustained elite and cosmopolitan princely spaces across a broad social spectrum. Medieval textiles from Central Asia, Iran, and India have been studied piecemeal within the separate disciplinary specializations of Islamic, pre-Islamic, and South Asian art history. The field of art history has yet to produce a study that addresses their material processes of making and the medium as primary historical evidence, rather than mere evidence of other media’s interregional movement. This dissertation intervenes at this point, taking a material and technical approach to the medium and deriving evidence from fiber analysis, dye identification, weave structure, and literary sources to argue that the meanings of textiles are generated not only in their use and display, but at every stage of their convergence.</dc:description><dc:subject>Art history</dc:subject><dc:subject>South Asian studies</dc:subject><dc:subject>Medieval history</dc:subject><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8gx9f8sq</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0dz4h4f2</identifier><datestamp>2026-09-16T06:35:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0dz4h4f2</dc:identifier><dc:title>Physical Trapping of Insects (Bed Bugs, Cimex lectularius L.)</dc:title><dc:creator>Liu, Patrick</dc:creator><dc:contributor>Loudon, Catherine</dc:contributor><dc:date>2026-09-14</dc:date><dc:description>The common bed bug (Cimex lectularius) is a pervasive global pest exhibiting widespread resistance to chemical insecticides, necessitating the development of alternative physical management strategies. This research investigates the efficacy of physical trapping mechanisms inspired by the microscopic trichomes of bean leaves and examines the underlying kinematics of bed bug locomotion across terrains to inform trap design. To evaluate physical trapping efficacy, a novel leaf-derived trapping material (LDTM) was developed to prevent the rapid deterioration of trapping ability typically observed in fresh leaves. The LDTM’s trapping efficacy was first tested in both horizontal and vertical orientations using fresh leaves as a positive control. In a separate evaluation, the LDTM was compared against four standard commercial pitfall and adhesive traps to measure overall capture efficacy. To understand how bed bugs physically interact with these surfaces, high-speed video tracking was utilized to quantify locomotion. Tarsal coordinates and stride timing were analyzed as bed bugs navigated vertical inclines, natural leaves, increased weights and micro-fabricated biomimetic hook arrays. The LDTM successfully captured all evaluated life stages in both a horizontal and vertical orientation. When evaluated against commercial pest management options, the LDTM outperformed three of the four standard pitfall and sticky traps, demonstrating significantly higher capture rates, particularly for bed bug nymphs. Kinematic analysis revealed that bed bugs utilized conserved foot placements when walking. When challenged with vertical orientations or a heavier posterior center of mass from a recent blood meal, they maintain their exact stepping coordinates. Instead, they adapt to these challenges through altered stride timing and postural shifts, such as holding forelegs on the substrate for a longer proportion of the stride cycle, to prevent falling off the substrate. However, navigating the micro-fabricated biomimetic arrays forced spatial adaptations that directly impacted physical trap efficacy. Homogeneous “Tall” hook arrays effectively engaged tarsi and maintained structural integrity. Conversely, heterogeneous arrays had reduced snag rates; the shorter hooks between the larger ones altered the insect’s spatial footprint, and provided footholds that allowed bed bugs to generate sufficient mechanical leverage to forcefully fracture the taller hooks.</dc:description><dc:subject>Biology</dc:subject><dc:subject>Entomology</dc:subject><dc:subject>Environmental science</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0dz4h4f2</dc:identifier><dc:identifier/><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0vm1m6g5</identifier><datestamp>2026-09-16T06:35:07Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0vm1m6g5</dc:identifier><dc:title>The Latent Image: Photography, Infrastructure, and the Imagination of Vietnam under French Rule (1887-1954)</dc:title><dc:creator>Le, Kien Minh</dc:creator><dc:contributor>Hilderbrand, Lucas</dc:contributor><dc:date>2026-09-14</dc:date><dc:description>This dissertation argues that photography functioned as an inadvertent infrastructure of Vietnamese nationalist imagining under French colonial rule—a byproduct of colonial administration rather than its aim. Examining French Indochina from the 1880s to the end of empire in 1945, it follows the camera through the three institutions Benedict Anderson identified as the engines of colonial nationalism: the census, the map, and the museum. Three case studies anchor the argument. The first traces photographic identification through the penitentiary, the immigration depot, and the taxation office, where the camera fixed the colonial subject as a filed and retrievable document. The second follows aerial photography into the cadastre, where the medium measured and taxed the land. The third examines the archaeology of Champa, showing how photography constituted “Cham art” as a twentieth-century colonial creation. Across these sites, the dissertation reconceives the colonial photograph not as illustration but as infrastructure—a sociotechnical system that worked by becoming invisible, and that depended at every point on Vietnamese labor the colonial record rendered anonymous. Photography was at once an instrument of colonial power and a medium the colonized reappropriated; the unified “Vietnam” it helped make imaginable was a precondition of decolonization the colonizer never intended to supply.</dc:description><dc:subject>History</dc:subject><dc:subject>Asian studies</dc:subject><dc:subject>Film studies</dc:subject><dc:subject>Infrastructure</dc:subject><dc:subject>Labor</dc:subject><dc:subject>Media</dc:subject><dc:subject>Nationalism</dc:subject><dc:subject>Photography</dc:subject><dc:subject>Vietnam</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0vm1m6g5</dc:identifier><dc:identifier>https://escholarship.org/content/qt0vm1m6g5/qt0vm1m6g5.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1pp5363f</identifier><datestamp>2026-09-16T06:35:02Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1pp5363f</dc:identifier><dc:title>Let That Window Be A Door</dc:title><dc:creator>Hithe, Alexis</dc:creator><dc:contributor>Miller, Nicole</dc:contributor><dc:contributor>Childs, Dennis R.</dc:contributor><dc:date>2026-09-14</dc:date><dc:description>A thesis introducing briefly the diverging image among other conclusions drawn around art and art practice, as it pertains to the work of alexis hithe towards the completion of a master’s degree of fine art. Discussed at length are the compelling forces, strategies, theories and practices that guide and shape the work, which typically consists of experimental moving image, light and conceptual installations. This writing may also serve as a non-linear recollection of a temporal experience of the graduate program in Visual Art at University of California San Diego. Do not think of this document as a graveyard, but perhaps a carving or a whisper.</dc:description><dc:subject>African American studies</dc:subject><dc:subject>Fine arts</dc:subject><dc:subject>Film studies</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1pp5363f</dc:identifier><dc:identifier>https://escholarship.org/content/qt1pp5363f/qt1pp5363f.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7rq5k10r</identifier><datestamp>2026-09-16T06:34:57Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7rq5k10r</dc:identifier><dc:title>Genomic, Proteomic and Computational Approaches to the Study of Host-Microbe Systems</dc:title><dc:creator>Penunuri, Gabriel</dc:creator><dc:contributor>DuBois, Rebecca</dc:contributor><dc:date>2026-08-25</dc:date><dc:description>Host-microbe systems are core to some of biology's most consequential interactions, from the pathogens that drive infectious disease to intracellular symbionts mitigating vector-borne disease transmission. Yet unlike the model organisms that have driven most of modern molecular biology, the microbes at the center of these interactions are rarely genetically tractable. Many intracellular bacteria cannot be cultured outside a host, resist standard tools for genetic manipulation, and are annotated largely by homology to distantly related free-living relatives. This dissertation develops genomic, proteomic, and computational methods to work around this lack of infrastructure and contribute techniques and tools to the study and further understanding of host-microbe systems. Using Wolbachia cultured in Drosophila melanogaster cell lines, I demonstrate that chemical mutagenesis can be used to perturb intracellular genomes leaving a detectable mutational signal. I employ a low error rate sequencing technique to record and model the mutational landscape left by the mutagen ethyl methanesulfonate (EMS) demonstrating its use for mutagenesis screens of intracellular bacteria. I next utilize structural proteome datasets to screen host-microbe proteomes for strong candidates of molecular mimicry, microbe proteins that have coevolved a eukaryotic-like domain or structure and suggest use for host manipulation or microbe survival in the host environment. Building off of this screen for novel effectors through structural alignments I develop and test a distributed computing system for performing large scale systematic literature reviews. Altogether these projects represent generalizable approaches to the study of host-microbe systems reaching from classically studied and thoroughly understood to novel and non-model systems.</dc:description><dc:subject>Bioinformatics</dc:subject><dc:subject>Microbiology</dc:subject><dc:subject>Molecular biology</dc:subject><dc:subject>Bioengineering</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-SA</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7rq5k10r</dc:identifier><dc:identifier>https://escholarship.org/content/qt7rq5k10r/qt7rq5k10r.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7v15d1jd</identifier><datestamp>2026-09-16T06:34:24Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7v15d1jd</dc:identifier><dc:title>Performance of Strong-Motion Instrumentation During Fires</dc:title><dc:creator>Skolnik, Derek</dc:creator><dc:creator>Saifullah, M Khalid</dc:creator><dc:creator>Emberley, Richard</dc:creator><dc:creator>Sorosh, Shokrullah</dc:creator><dc:creator>Zhang, Jiachen</dc:creator><dc:creator>Hutchinson, Tara</dc:creator><dc:date>2026-07-13</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7v15d1jd</dc:identifier><dc:identifier>https://escholarship.org/content/qt7v15d1jd/qt7v15d1jd.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7rh2d52v</identifier><datestamp>2026-09-16T06:34:20Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7rh2d52v</dc:identifier><dc:title>Post-Earthquake Damage Assessment Using a UAV-Acquired Photogrammetry Model</dc:title><dc:creator>Lozano Bravo, Hilda</dc:creator><dc:creator>Ji, Ruipu</dc:creator><dc:creator>Lo, Eric</dc:creator><dc:creator>Norton, Tanner</dc:creator><dc:creator>Driscoll, John</dc:creator><dc:creator>Zhang, Jiachen</dc:creator><dc:creator>Zazueta Hernandez, Isabella</dc:creator><dc:creator>Romo Andrade, Abraham</dc:creator><dc:creator>Hutchinson, Tara</dc:creator><dc:creator>Kuester, Falko</dc:creator><dc:date>2026-07-13</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7rh2d52v</dc:identifier><dc:identifier>https://escholarship.org/content/qt7rh2d52v/qt7rh2d52v.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1j5023j2</identifier><datestamp>2026-09-16T06:34:16Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1j5023j2</dc:identifier><dc:title>Multi-View UAV-Based Imagery for Seismic Displacement Tracking of a Full-Scale 10-Story Cold-Formed Steel Building</dc:title><dc:creator>Ji, Ruipu</dc:creator><dc:creator>Zhang, Jiachen</dc:creator><dc:creator>Lo, Eric</dc:creator><dc:creator>Norton, Tanner</dc:creator><dc:creator>Driscoll, John</dc:creator><dc:creator>Kuester, Falko</dc:creator><dc:creator>Schafer, Benjamin</dc:creator><dc:creator>Hutchinson, Tara</dc:creator><dc:date>2026-07-13</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1j5023j2</dc:identifier><dc:identifier>https://escholarship.org/content/qt1j5023j2/qt1j5023j2.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4496k1bm</identifier><datestamp>2026-09-16T06:34:11Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4496k1bm</dc:identifier><dc:title>Implementation Strategies and Utility of a Multi-sensor Suite Deployed in a Full-scale 10-story Building Shake Table Test Program</dc:title><dc:creator>Sorosh, Shokrullah</dc:creator><dc:creator>Zhang, Jiachen</dc:creator><dc:creator>Lotfizadeh, Koorosh</dc:creator><dc:creator>Haddadi, Hamid</dc:creator><dc:creator>Swensen, Daniel</dc:creator><dc:creator>Branum, Dave</dc:creator><dc:creator>Kohler, Monica</dc:creator><dc:creator>Guy, Richard</dc:creator><dc:creator>Skolnik, Derek</dc:creator><dc:creator>Saifullah, M Khalid</dc:creator><dc:creator>Schafer, Benjamin</dc:creator><dc:creator>Hutchinson, Tara</dc:creator><dc:date>2026-07-13</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4496k1bm</dc:identifier><dc:identifier>https://escholarship.org/content/qt4496k1bm/qt4496k1bm.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5x86k8x4</identifier><datestamp>2026-09-16T06:33:44Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5x86k8x4</dc:identifier><dc:title>Cosmological constraints from a joint DESI DR1 Full-Shape and DR2 BAO</dc:title><dc:creator>Forero-Sánchez, D</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Verde, L</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Blake, C</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Castander, FJ</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Joyce, R</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kneib, J</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Lamman, C</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlafly, EF</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zhao, C</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2026-06-01</dc:date><dc:description>We present a cosmological analysis combining full-shape (FS) clustering measurements from the Dark Energy Spectroscopic Instrument (DESI) DR1 with baryon acoustic oscillation (BAO) measurements from DESI DR2. To achieve a robust combination that accounts for the correlation between the two data releases, we employ the ShapeFit compression method and estimate the joint covariance using EZmocks. This compressed approach inherently mitigates the prior volume effects that have previously dominated Bayesian constraints from DESI data with minimal external priors. Consequently, we obtain — for the first time within a Bayesian framework — reliable DESI-only constraints on extensions to ΛCDM using only a Big Bang Nucleosynthesis prior on the baryon density and a wide prior on the spectral index. In flat ΛCDM, we find Ω m = 0.3035 ± 0.0085, h = 0.6876 ± 0.0059, and σ 8 = 0.822 ± 0.034. For the w 0 wa CDM dynamical dark energy model, we measure w 0 = -0.49 ± 0.25 and wa = -1.52 ± 0.77, improving constraints by ∼ 30% relative to the analogous DR1 measurement and reducing the discrepancy with ΛCDM to 1.4σ when compared to BAO only analyses. We also report competitive limits on the sum of neutrino masses and spatial curvature. This work demonstrates that the ShapeFit compression provides a prior-robust and computationally efficient pathway to constrain beyond-ΛCDM physics with large-scale structure.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Generic health relevance (hrcs-hc)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5x86k8x4</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1088/1475-7516/2026/06/043</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2026, iss 06</dc:source><dc:coverage>043</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt32p4s5xx</identifier><datestamp>2026-09-16T06:21:48Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt32p4s5xx</dc:identifier><dc:title>Measurements of Quasar Proximity Zones with the Lyα Forest of DESI Y1 Quasars</dc:title><dc:creator>Hada, Ryuichiro</dc:creator><dc:creator>Martini, Paul</dc:creator><dc:creator>Weinberg, David H</dc:creator><dc:creator>Zheng, Zheng</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Joyce, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lamman, C</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2026-05-20</dc:date><dc:description>The intergalactic medium (IGM) around a quasar is shaped by its dense environment and by its excess ionizing radiation, which form a “quasar proximity zone” whose size and anisotropy depend on the quasar’s halo mass, luminosity, age, and radiation geometry. Using over 10,000 quasar pairs from the Dark Energy Spectroscopic Instrument (DESI) Year 1 data, with projected comoving separations r⊥ &amp;lt; 2h−1 Mpc, we investigate how the proximity zone of foreground quasars at z ∼ 2–3.5 affects Lyα absorption in their background quasars. The large DESI sample enables unprecedented precision in measuring this “transverse proximity” effect, allowing a detailed investigation of the signal’s dependence on the projected separation of quasar pairs and the luminosity of the foreground quasar. We find that enhanced gas clustering near quasars dominates over their ionizing effect, leading to stronger absorption on neighboring sightlines. Under the assumption that quasar ionizing luminosity is isotropic and steady, we infer the IGM overdensity profile in the vicinity of quasars, finding overdensities as high as Δ ∼ 10 at comoving distance ∼1h−1 Mpc from the most luminous systems. Surprisingly, however, we find no significant dependence of the proximity profile on the luminosity of the foreground quasar. This lack of luminosity dependence could reflect a cancellation between higher ionizing flux and higher gas overdensity, or it could indicate that quasar emission is highly time-variable or anisotropic, so that the observed luminosity does not trace the ionizing flux on nearby sightlines.</dc:description><dc:subject>5109 Space Sciences (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0306 Physical Chemistry (incl. Structural) (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/32p4s5xx</dc:identifier><dc:identifier>https://escholarship.org/content/qt32p4s5xx/qt32p4s5xx.pdf</dc:identifier><dc:identifier>info:doi/10.3847/1538-4357/ae644b</dc:identifier><dc:type>article</dc:type><dc:source>The Astrophysical Journal, vol 1003, iss 1</dc:source><dc:coverage>94</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0h54z28q</identifier><datestamp>2026-09-16T06:21:40Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0h54z28q</dc:identifier><dc:title>Parallel Runtime Interface for Fortran (PRIF) Specification, Revision 0.8</dc:title><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Rasmussen, Katherine</dc:creator><dc:creator>Rouson, Damian</dc:creator><dc:creator>Richardson, Brad</dc:creator><dc:creator>Pailleux, Jean-Didier</dc:creator><dc:creator>Renault, Etienne</dc:creator><dc:date>2026-05-28</dc:date><dc:description>This document specifies an interface to support the multi-image parallelism features of Fortran, named the Parallel Runtime Interface for Fortran (PRIF). PRIF is a solution in which a runtime library is primarily responsible for implementing coarray allocation, deallocation and accesses, image synchronization, atomic operations, events, teams and collective subroutines. The Fortran compiler is responsible for transforming the invocation of Fortran-level multi-image parallelism features into procedure calls to the necessary PRIF subroutines. The interface is designed for portability across shared- and distributed-memory machines, different operating systems, and multiple architectures. Implementations of this interface are intended as an augmentation for the compiler's own runtime library. With an implementation-agnostic interface, alternative parallel runtime libraries may be developed that support the same interface. One benefit of this approach is the ability to vary the communication substrate. A central aim of this document is to define a parallel runtime interface in standard Fortran syntax, which enables us to leverage Fortran to succinctly express various properties of the procedure interfaces, including argument attributes.</dc:description><dc:subject>Caffeine</dc:subject><dc:subject>Coarray</dc:subject><dc:subject>Compilers</dc:subject><dc:subject>Fortran</dc:subject><dc:subject>Library specification</dc:subject><dc:subject>Parallel programming</dc:subject><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0h54z28q</dc:identifier><dc:identifier>https://escholarship.org/content/qt0h54z28q/qt0h54z28q.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S4Z88F</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2rd9f0bn</identifier><datestamp>2026-09-16T06:20:52Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2rd9f0bn</dc:identifier><dc:title>Extensive analysis of reconstruction algorithms for DESI 2024 baryon acoustic oscillations</dc:title><dc:creator>Chen, X</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Paillas, E</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Padmanabhan, N</dc:creator><dc:creator>White, M</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>McDonald, P</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Variu, A</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Hadzhiyska, B</dc:creator><dc:creator>Hanif, MMS</dc:creator><dc:creator>Forero-Sánchez, D</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Mena-Fernández, J</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Nikakhtar, F</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Rashkovetskyi, M</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Ruggeri, R</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Saulder, C</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Smith, A</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Valcin, D</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yuan, S</dc:creator><dc:creator>Zhou, R</dc:creator><dc:date>2026-05-01</dc:date><dc:description>Reconstruction of the baryon acoustic oscillation (BAO) signal has been a standard procedure in BAO analyses over the past decade and has helped to improve the BAO parameter precision by a factor of ∼2 on average. The Dark Energy Spectroscopic Instrument (DESI) BAO analysis for the first year (DR1) data uses the “standard” reconstruction framework, in which the displacement field is estimated from the observed density field by solving the linearized continuity equation in redshift space, and galaxy and random positions are shifted in order to partially remove non-linearities. There are several approaches to solving for the displacement field in real survey data, including the multigrid (MG), iterative Fast Fourier Transform (iFFT), and iterative Fast Fourier Transform particle (iFFTP) algorithms. In this work, we analyze these algorithms and compare them with various metrics including two-point statistics and the displacement itself using realistic DESI mocks. We focus on three representative DESI samples, the emission line galaxies (ELG), quasars (QSO), and the bright galaxy sample (BGS), which cover the extreme redshifts and number densities, and potential wide-angle effects. We conclude that the MG and iFFT algorithms agree within 0.4% in post-reconstruction power spectrum on BAO scales with the RecSym convention, which does not remove large-scale redshift space distortions (RSDs), in all three tracers. The RecSym convention appears to be less sensitive to displacement errors than the RecIso convention, which attempts to remove large-scale RSDs. However, iFFTP deviates from the first two; thus, we recommend against using iFFTP without further development. In addition, we provide the optimal settings for reconstruction for five years of DESI observation. The analyses presented in this work pave the way for DESI DR1 analysis as well as future BAO analyses.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2rd9f0bn</dc:identifier><dc:identifier>https://escholarship.org/content/qt2rd9f0bn/qt2rd9f0bn.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2026/05/001</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2026, iss 05</dc:source><dc:coverage>001</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0c6806m4</identifier><datestamp>2026-09-16T06:20:38Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0c6806m4</dc:identifier><dc:title>Newark’s Implementation of a Lower Voting Age: Research Brief</dc:title><dc:creator>Wray-Lake, Laura</dc:creator><dc:creator>Mirra, Nicole</dc:creator><dc:creator>Rottenberg, Julia</dc:creator><dc:date>2026-05-04</dc:date><dc:description>Newark, New Jersey implemented a voting age of 16 for school board elections in April of 2025. This research brief presents findings from a multi-method implementation study. We interviewed 11 stakeholders about implementation successes and challenges. Qualitative insights were supplemented by survey findings from 334 11th and 12th graders in Newark. Implementation successes included high registration numbers and strong coalition building across organizations. However, Newark faced challenges to implementation, including limited accessibility, voter education, and time. These findings can inform Newark and other cities interested in implementing a lower voting age.</dc:description><dc:subject>adolescents</dc:subject><dc:subject>policy</dc:subject><dc:subject>voting</dc:subject><dc:subject>voting age</dc:subject><dc:subject>youth</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0c6806m4</dc:identifier><dc:identifier>https://escholarship.org/content/qt0c6806m4/qt0c6806m4.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2hp2p8vf</identifier><datestamp>2026-09-16T06:20:33Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2hp2p8vf</dc:identifier><dc:title>Beam-energy dependence of correlations between mean transverse momentum and anisotropic flow of charged particles in Au+Au collisions at RHIC</dc:title><dc:creator>Aboona, BE</dc:creator><dc:creator>Adam, J</dc:creator><dc:creator>Agakishiev, G</dc:creator><dc:creator>Aggarwal, I</dc:creator><dc:creator>Aggarwal, MM</dc:creator><dc:creator>Ahammed, Z</dc:creator><dc:creator>Aitbayev, A</dc:creator><dc:creator>Alekseev, I</dc:creator><dc:creator>Alpatov, E</dc:creator><dc:creator>Alshammri, AK</dc:creator><dc:creator>Aparin, A</dc:creator><dc:creator>Aslam, S</dc:creator><dc:creator>Atchison, J</dc:creator><dc:creator>Averichev, GS</dc:creator><dc:creator>Bairathi, V</dc:creator><dc:creator>Bao, X</dc:creator><dc:creator>Barik, P</dc:creator><dc:creator>Barish, K</dc:creator><dc:creator>Behera, S</dc:creator><dc:creator>Bhagat, P</dc:creator><dc:creator>Bhasin, A</dc:creator><dc:creator>Bhatta, S</dc:creator><dc:creator>Bordyuzhin, IG</dc:creator><dc:creator>Brandenburg, JD</dc:creator><dc:creator>Brandin, AV</dc:creator><dc:creator>Broodo, C</dc:creator><dc:creator>Cai, XZ</dc:creator><dc:creator>Caines, H</dc:creator><dc:creator>De La Barca Sánchez, M Calderón</dc:creator><dc:creator>Cebra, D</dc:creator><dc:creator>Ceska, J</dc:creator><dc:creator>Chakaberia, I</dc:creator><dc:creator>Chang, YS</dc:creator><dc:creator>Chang, Z</dc:creator><dc:creator>Chatterjee, A</dc:creator><dc:creator>Chen, D</dc:creator><dc:creator>Chen, JH</dc:creator><dc:creator>Chen, L</dc:creator><dc:creator>Chen, Q</dc:creator><dc:creator>Chen, W</dc:creator><dc:creator>Chen, Z</dc:creator><dc:creator>Cheng, J</dc:creator><dc:creator>Cheng, Y</dc:creator><dc:creator>Christie, W</dc:creator><dc:creator>Chu, X</dc:creator><dc:creator>Corey, S</dc:creator><dc:creator>Crawford, HJ</dc:creator><dc:creator>Dale-Gau, G</dc:creator><dc:creator>Das, A</dc:creator><dc:creator>De Souza Lemos, D</dc:creator><dc:creator>Dedovich, TG</dc:creator><dc:creator>Deppner, IM</dc:creator><dc:creator>Derevschikov, AA</dc:creator><dc:creator>Deshpande, A</dc:creator><dc:creator>Dhamija, A</dc:creator><dc:creator>Dimri, A</dc:creator><dc:creator>Dixit, P</dc:creator><dc:creator>Dong, X</dc:creator><dc:creator>Drachenberg, JL</dc:creator><dc:creator>Duckworth, E</dc:creator><dc:creator>Dunlop, JC</dc:creator><dc:creator>El-Feky, YS</dc:creator><dc:creator>Engelage, J</dc:creator><dc:creator>Eppley, G</dc:creator><dc:creator>Esumi, S</dc:creator><dc:creator>Evdokimov, O</dc:creator><dc:creator>Eyser, O</dc:creator><dc:creator>Fan, B</dc:creator><dc:creator>Fang, Y</dc:creator><dc:creator>Fatemi, R</dc:creator><dc:creator>Fazio, S</dc:creator><dc:creator>Feng, H</dc:creator><dc:creator>Feng, Y</dc:creator><dc:creator>Finch, E</dc:creator><dc:creator>Fisyak, Y</dc:creator><dc:creator>Flor, FA</dc:creator><dc:creator>Fu, B</dc:creator><dc:creator>Fu, C</dc:creator><dc:creator>Fu, T</dc:creator><dc:creator>Gao, T</dc:creator><dc:creator>Gao, Y</dc:creator><dc:creator>Garcia, G</dc:creator><dc:creator>Geurts, F</dc:creator><dc:creator>Gibson, A</dc:creator><dc:creator>Giri, A</dc:creator><dc:creator>Gopal, K</dc:creator><dc:creator>Gou, X</dc:creator><dc:creator>Grosnick, D</dc:creator><dc:creator>Gu, A</dc:creator><dc:creator>Gu, J</dc:creator><dc:creator>Gupta, A</dc:creator><dc:creator>Hamed, A</dc:creator><dc:creator>Hamilton, RJ</dc:creator><dc:creator>Han, J</dc:creator><dc:creator>Han, X</dc:creator><dc:creator>Harasty, MD</dc:creator><dc:creator>Harris, JW</dc:creator><dc:creator>Harrison-Smith, H</dc:creator><dc:creator>Havener, LB</dc:creator><dc:creator>He, XH</dc:creator><dc:date>2026-05-01</dc:date><dc:description>The correlation between the mean transverse momentum, [p T], and the squared anisotropic flow, v n 2 , on an event-by-event basis has been suggested to be influenced by the initial conditions in heavy-ion collisions. We present measurements of the variances and covariance of [p T] and v n 2 , along with their dimensionless ratio, for Au+Au collisions at various beam energies: s N N = 14.6, 19.6, 27, 54.4, and 200 GeV. Our measurements reveal a distinct energy-dependent behavior in the variances and covariances. In addition, the dimensionless ratio displays a similar behavior across different beam energies. We compare our measurements with hydrodynamic models and similar measurements from Pb+Pb collisions at the Large Hadron Collider (LHC). These findings provide valuable insights into the beam energy dependence of the specific shear viscosity (η/s) and initial-state effects, allowing for differentiating between different initial-state models.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Collectivity</dc:subject><dc:subject>Correlation</dc:subject><dc:subject>Shear viscosity</dc:subject><dc:subject>Transverse momentum correlations</dc:subject><dc:subject>NSD-Relativistic Nuclear Collisions (c-lbnl-label)</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2hp2p8vf</dc:identifier><dc:identifier>https://escholarship.org/content/qt2hp2p8vf/qt2hp2p8vf.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.physletb.2026.140378</dc:identifier><dc:type>article</dc:type><dc:source>Physics Letters B, vol 876</dc:source><dc:coverage>140378</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9x11123q</identifier><datestamp>2026-09-16T06:17:39Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9x11123q</dc:identifier><dc:title>Idiomatic Vibe Testing with Julienne</dc:title><dc:creator>Rasmussen, Katherine</dc:creator><dc:creator>Rouson, Damian</dc:creator><dc:creator>Bonachea, Dan</dc:creator><dc:date>2026-04-08</dc:date><dc:description>Historically, the role of natural language in programs was confined primarily to comments that have no direct influence on runtime behavior. With the rise of vibe coding, natural language becomes central to code generation via prompt engineering with a large language model (LLM). One fundamental problem, however, lies in natural language’s inherent ambiguity. By contrast, standardized programming languages greatly reduce ambiguity by formally defining syntax and specifying detailed semantics in a written language standard. To leverage such formality and specifications in vibe coding, a user might consider replacing or augmenting natural language with code. If the prompt includes unit tests, then the tests serve both as instructions for what the LLM-generated code must do and a tool for verifying that the generated code accomplishes the desired task.

This tutorial unifies the above two themes by enabling users to write unit tests that take the form of natural language using specific idioms defined by the Julienne correctness-checking framework (https://go.lbl.gov/julienne). Julienne further unifies unit testing with runtime verification by supporting the use of the same idioms in assertions.

This tutorial will introduce the idioms first released in Julienne 2.1.0 in May 2025. For example, the statement “x .approximates. y .within. tolerance” reads naturally as a sentence while instructing Julienne to verify that “|x-y| &amp;lt; tolerance”, report the result, and provide rich diagnostic information if the condition is not met. The tutorial will explain how to use Julienne idioms to write unit tests external to user code or assertions inside user code. Finally, the tutorial will introduce a novel paradigm, idiomatic vibe testing, in which LLM prompts include Julienne unit tests written with Julienne idioms.

Attendees will also see the use of Julienne idioms in correctness checks for Berkeley Lab software projects, including the recently released Formal package (https://go.lbl.gov/formal), a domain specific language (DSL) embedded in Fortran. Formal software abstractions mimic tensor calculus expressions, thereby codifying the language of mathematics.</dc:description><dc:subject>AstraAI</dc:subject><dc:subject>Caffeine</dc:subject><dc:subject>Fiats</dc:subject><dc:subject>Formal</dc:subject><dc:subject>Fortran</dc:subject><dc:subject>Julienne</dc:subject><dc:subject>LLM</dc:subject><dc:subject>Unit testing</dc:subject><dc:subject>Vibe coding</dc:subject><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9x11123q</dc:identifier><dc:identifier>https://escholarship.org/content/qt9x11123q/qt9x11123q.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S4302N</dc:identifier><dc:type>non_textual</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7v77b9ds</identifier><datestamp>2026-09-16T06:17:27Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7v77b9ds</dc:identifier><dc:title>Physical Damage-Measured Response Correlation for Nonstructural Components Tested under Multi-Hazard (Earthquake and Fire) Demands in the CFS10 Building</dc:title><dc:creator>Singh, Amanpreet</dc:creator><dc:creator>Sorosh, Shokrullah</dc:creator><dc:creator>Zhang, Xianzhao</dc:creator><dc:creator>Zhang, Jiachen</dc:creator><dc:creator>Rukundo, Fidence Cyizere</dc:creator><dc:creator>Eladly, Mohammed</dc:creator><dc:creator>Ji, Ruipu</dc:creator><dc:creator>Rivera, Daniel</dc:creator><dc:creator>Padgett, Lynn</dc:creator><dc:creator>Meacham, Brian J</dc:creator><dc:creator>Gernay, Thomas</dc:creator><dc:creator>Emberley, Richard L</dc:creator><dc:creator>Schafer, Benjamin W</dc:creator><dc:creator>Hutchinson, Tara C</dc:creator><dc:date>2026-04-27</dc:date><dc:description>This paper is the second of a set presented within the session: Findings from the CFS10 Multi-Hazard Test Program. The emphasis within this article is to highlight correlations between physical damage to nonstructural components and systems with measured response during a suite of 18 earthquake tests and 2 subsequent fire tests. This damage was documented within a 10-story cold-formed steel-framed building test specimen outfitted with various nonstructural components, including suspended ceilings, architectural finishes, a resilient stair system, windows and doors, pressurized fire sprinkler and gas piping systems, and roof-mounted mechanical equipment. The test building and multi-hazard protocol are described in the session companion paper. This paper provides test observations correlated with measured engineering demand parameters such as floor acceleration, building inter-story drift, or peak local temperature responses and offers related literature emerging from the project. Damage data and functionality checks will support development of fragility functions for these nonstructural systems for use in recovery-based frameworks.</dc:description><dc:subject>4005 Civil Engineering (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>33 Built Environment and Design (for-2020)</dc:subject><dc:subject>11 Sustainable Cities and Communities (sdg)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7v77b9ds</dc:identifier><dc:identifier>https://escholarship.org/content/qt7v77b9ds/qt7v77b9ds.pdf</dc:identifier><dc:identifier>info:doi/10.1061/9780784486924.024</dc:identifier><dc:type>article</dc:type><dc:source>Structures Congress 2026</dc:source><dc:coverage>298 - 310</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8pf0j51w</identifier><datestamp>2026-09-16T06:17:24Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8pf0j51w</dc:identifier><dc:title>Overview of the CFS10 Program: Full-Scale Shake Table Earthquake and Fire Testing of a 10-Story Cold-Formed Steel Building</dc:title><dc:creator>Hutchinson, Tara C</dc:creator><dc:creator>Zhang, Jiachen Charlie</dc:creator><dc:creator>Sorosh, Shokrullah</dc:creator><dc:creator>Ji, Ruipu</dc:creator><dc:creator>Rivera, Daniel</dc:creator><dc:creator>Zhang, Xianzhao</dc:creator><dc:creator>Singh, Amanpreet</dc:creator><dc:creator>Rukundo, Fidence Cyizere</dc:creator><dc:creator>Eladly, Mohammed M</dc:creator><dc:creator>Jones, Harry</dc:creator><dc:creator>Karns, Jesse</dc:creator><dc:creator>Padgett, Lynn</dc:creator><dc:creator>Emberley, Richard</dc:creator><dc:creator>Gernay, Thomas</dc:creator><dc:creator>Meacham, Brian</dc:creator><dc:creator>Schafer, Benjamin W</dc:creator><dc:date>2026-04-27</dc:date><dc:description>This paper is the first in a pair presented within the session: Findings from the CFS10 Multi-Hazard Test Program. The emphasis within this article is to, in brevity, describe the scope of a landmark full-scale 10-story cold-formed steel (CFS) framed building tested under multi-hazard (earthquake and fire) scenarios at the UC San Diego 6-DOF Large High-Performance Outdoor Shake Table (LHPOST6). Coined CFS10, this unique building specimen is designed beyond current code height limits, adopting advances in cold-formed steel shear wall detailing, varied construction modalities, and enriched with nonstructural components and systems. The landmark CFS10 building specimen was subjected to extreme multi-hazard (earthquake and fire) loading conditions. This paper sets the framework for presentations to be shared at the Congress, while also aiding in ongoing documentation of findings from the program.</dc:description><dc:subject>4005 Civil Engineering (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>11 Sustainable Cities and Communities (sdg)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8pf0j51w</dc:identifier><dc:identifier>https://escholarship.org/content/qt8pf0j51w/qt8pf0j51w.pdf</dc:identifier><dc:identifier>info:doi/10.1061/9780784486924.021</dc:identifier><dc:type>article</dc:type><dc:source>Structures Congress 2026</dc:source><dc:coverage>264 - 277</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8jk2j49r</identifier><datestamp>2026-09-16T06:17:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8jk2j49r</dc:identifier><dc:title>Preliminary Evidence that Combination Oral Contraceptive Use in Young Adult Women Is Associated with the Endocrine Stress Response to High-Dose Alcohol</dc:title><dc:creator>Anthenelli, Robert M</dc:creator><dc:creator>Momper, Jeremiah</dc:creator><dc:creator>Pharm.D</dc:creator><dc:creator>Suhandynata, Raymond</dc:creator><dc:creator>Henrickson, Cassandra A</dc:creator><dc:creator>McKenna, Benjamin S</dc:creator><dc:date>2026-05-01</dc:date><dc:subject>3215 Reproductive Medicine (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Clinical Trials and Supportive Activities (rcdc)</dc:subject><dc:subject>Contraception/Reproduction (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Substance Misuse (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Basic Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Alcoholism</dc:subject><dc:subject>Alcohol Use and Health (rcdc)</dc:subject><dc:subject>3.1 Primary prevention interventions to modify behaviours or promote wellbeing (hrcs-rac)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>1109 Neurosciences (for)</dc:subject><dc:subject>1117 Public Health and Health Services (for)</dc:subject><dc:subject>Substance Abuse (science-metrix)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:subject>5202 Biological psychology (for-2020)</dc:subject><dc:subject>5203 Clinical and health psychology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8jk2j49r</dc:identifier><dc:identifier>https://escholarship.org/content/qt8jk2j49r/qt8jk2j49r.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.alcohol.2026.01.120</dc:identifier><dc:type>article</dc:type><dc:source>Alcohol, vol 132</dc:source><dc:coverage>68</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt90j6b8rn</identifier><datestamp>2026-09-16T06:16:56Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt90j6b8rn</dc:identifier><dc:title>Combined tracer analysis for DESI 2024 BAO</dc:title><dc:creator>Valcin, D</dc:creator><dc:creator>Rashkovetskyi, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Beutler, F</dc:creator><dc:creator>McDonald, P</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Rosado-Marín, AJ</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Padmanabhan, N</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Dawson, KS</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Mena-Fernández, J</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Paillas, E</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Ruggeri, R</dc:creator><dc:creator>Samushia, L</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Saulder, C</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yu, J</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2026-04-01</dc:date><dc:description>This paper demonstrates how the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) and future baryon acoustic oscillations (BAO) analyses can optimally combine overlapping tracers (galaxies of distinct types) in the same redshift range. We make a unified catalog of Luminous Red Galaxies (LRGs) and Emission Line Galaxies (ELGs) in the redshift range 0.8 &amp;lt; z &amp;lt; 1.1 and investigate the impact on the BAO constraints. DESI DR1 contains ∼ 30% of the final DESI LRG sample and less than 25% of the final ELG sample, and the combination of LRGs and ELGs increases the number density and reduces the shot noise. We developed a pipeline to merge the overlapping tracers using galaxy bias as an approximately optimal weight and tested the pipeline on a suite of Abacus simulations, calibrated on the final version of the DESI Early Data Release. When applying our pipeline to the DESI DR1 catalog, we find an improvement in the BAO constraints of 11% for α iso and ∼ 7.0% for α AP consistent with our findings in mock catalogs. Our analysis was integrated into the DESI DR1 BAO analysis to produce the LRG+ELG result in the 0.8 &amp;lt; z &amp;lt; 1.1 redshift bin, which provided the most precise BAO measurement from DESI DR1 with a 0.86% constraint on the BAO distance scale and a 9.1σ detection of the isotropic BAO feature.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/90j6b8rn</dc:identifier><dc:identifier>https://escholarship.org/content/qt90j6b8rn/qt90j6b8rn.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2026/04/058</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2026, iss 04</dc:source><dc:coverage>058</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt87w3j5fv</identifier><datestamp>2026-09-16T06:16:37Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt87w3j5fv</dc:identifier><dc:title>Seismic Damage Assessment of a Full-Scale 10-Story Building Using UAV Vision-Based Sensing</dc:title><dc:creator>Ji, Ruipu</dc:creator><dc:creator>Lozano Bravo, Hilda</dc:creator><dc:creator>Lo, Eric</dc:creator><dc:creator>Norton, Tanner</dc:creator><dc:creator>Driscoll, John</dc:creator><dc:creator>Zhang, Jiachen</dc:creator><dc:creator>Kuester, Falko</dc:creator><dc:creator>Hutchinson, Tara</dc:creator><dc:date>2026-01-19</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/87w3j5fv</dc:identifier><dc:identifier>https://escholarship.org/content/qt87w3j5fv/qt87w3j5fv.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8s6427sc</identifier><datestamp>2026-09-16T06:16:16Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8s6427sc</dc:identifier><dc:title>System Identification of a 10-story Cold-Formed Steel Building: Systematic Study Considering Sensor Distribution and Changes in Ambient Conditions</dc:title><dc:creator>Sorosh, Shokrullah</dc:creator><dc:creator>Zhang, Jiachen</dc:creator><dc:creator>Saifullah, M Khalid</dc:creator><dc:creator>Skolnik, Derek</dc:creator><dc:creator>Hutchinson, Tara</dc:creator><dc:date>2026-01-19</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8s6427sc</dc:identifier><dc:identifier>https://escholarship.org/content/qt8s6427sc/qt8s6427sc.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3cq8m8w8</identifier><datestamp>2026-09-16T06:16:12Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3cq8m8w8</dc:identifier><dc:title>Modal Identification of Rooftop Mechanical Equipment with Different Attachment Designs on a Full-Scale Ten-Story Shake Table-Tested Building</dc:title><dc:creator>Zhang, Xianzhao</dc:creator><dc:creator>Zhang, Jiachen</dc:creator><dc:creator>Sorosh, Shokrullah</dc:creator><dc:creator>Hutchinson, Tara</dc:creator><dc:date>2026-01-19</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3cq8m8w8</dc:identifier><dc:identifier>https://escholarship.org/content/qt3cq8m8w8/qt3cq8m8w8.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1g79m654</identifier><datestamp>2026-09-16T06:16:09Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1g79m654</dc:identifier><dc:title>The DESI DR1 peculiar velocity survey: Growth rate measurements from the galaxy power spectrum</dc:title><dc:creator>Qin, F</dc:creator><dc:creator>Blake, C</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Turner, RJ</dc:creator><dc:creator>Lodha, K</dc:creator><dc:creator>Bautista, J</dc:creator><dc:creator>Lai, Y</dc:creator><dc:creator>Amsellem, AJ</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Carr, A</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Douglass, K</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Joyce, R</dc:creator><dc:creator>Kim, AG</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Lamman, C</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Ross, C</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Said, K</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2026-04-01</dc:date><dc:description>The large-scale structure of the Universe and its evolution encapsulate a wealth of cosmological information. A powerful means of unlocking this knowledge lies in measuring the auto-power spectrum and/or the cross-power spectrum of the galaxy density and momentum fields, followed by the estimation of cosmological parameters based on these spectrum measurements. In this study, we generalize the cross-power spectrum model to accommodate scenarios in which the density and momentum fields are derived from distinct galaxy surveys. The growth rate of the large-scale structures of the Universe, commonly represented as fσ 8 , was extracted by jointly fitting the monopole and quadrupole moments of the auto-density power spectrum, the monopole of the auto-momentum power spectrum, and the dipole of the cross-power spectrum. Our estimators, theoretical models, and parameter-fitting framework were tested using mocks, confirming their robustness and accuracy in retrieving the fiducial growth rate from simulation. These techniques were then applied to analyse the power spectrum of the DESI Bright Galaxy Survey and Peculiar Velocity Survey. The fit result of the growth rate is fσ 8 = 0.440 +0.080 −0.096 at effective redshift z eff = 0.07. By synthesizing the fitting outcomes from correlation functions, maximum likelihood estimation, and the power spectrum, a consensus value is yielded of fσ 8 ( z eff = 0.07) = 0.450 +0.055 −0.055 , and correspondingly we obtain γ = 0.580 +0.110 −0.110 , Ω m = 0.301 +0.011 −0.011 , and σ 8 = 0.834 +0.032 −0.032 . The measured fσ 8 and γ are consistent with the prediction of the Λ cold dark matter model and general relativity.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>cosmological parameters</dc:subject><dc:subject>large-scale structure of Universe</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1g79m654</dc:identifier><dc:identifier>https://escholarship.org/content/qt1g79m654/qt1g79m654.pdf</dc:identifier><dc:identifier>info:doi/10.1051/0004-6361/202558368</dc:identifier><dc:type>article</dc:type><dc:source>Astronomy &amp; Astrophysics, vol 708</dc:source><dc:coverage>a219</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt14z6f17s</identifier><datestamp>2026-09-16T06:15:59Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt14z6f17s</dc:identifier><dc:title>Design Strategies and Modeling Verification for Steel Stairs with Drift-Compatible Connections</dc:title><dc:creator>Sorosh, Shokrullah</dc:creator><dc:creator>Zhang, Jiachen</dc:creator><dc:creator>Kovac, Adam</dc:creator><dc:creator>Smith, Kevin</dc:creator><dc:creator>Hutchinson, Tara</dc:creator><dc:date>2025-09-03</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/14z6f17s</dc:identifier><dc:identifier>https://escholarship.org/content/qt14z6f17s/qt14z6f17s.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5n45t37j</identifier><datestamp>2026-09-16T06:15:56Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5n45t37j</dc:identifier><dc:title>Investigating Construction Methods in a Landmark 10-story Cold-Formed Steel Residential Building Shake Table Test Program</dc:title><dc:creator>Rivera, Daniel</dc:creator><dc:creator>Zhang, Jiachen</dc:creator><dc:creator>Singh, Amanpreet</dc:creator><dc:creator>Ji, Ruipu</dc:creator><dc:creator>Sorosh, Shokrullah</dc:creator><dc:creator>Eladly, Mohammed</dc:creator><dc:creator>Cyizere Rukundo, Fidence</dc:creator><dc:creator>Rivera, Diego</dc:creator><dc:creator>Ellis, Morgan</dc:creator><dc:creator>Padgett, Lynn</dc:creator><dc:creator>Jones, Harry</dc:creator><dc:creator>Karns, Jesse</dc:creator><dc:creator>Stewart, Daniel</dc:creator><dc:creator>Schafer, Benjamin</dc:creator><dc:creator>Hutchinson, Tara</dc:creator><dc:date>2026-03-18</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5n45t37j</dc:identifier><dc:identifier>https://escholarship.org/content/qt5n45t37j/qt5n45t37j.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1xr17512</identifier><datestamp>2026-09-16T06:15:53Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1xr17512</dc:identifier><dc:title>Weather Measurements During the CFS10 (10-Story Cold-Formed Steel Framed Building) Shake Table Test Program</dc:title><dc:creator>Blair, Daniel</dc:creator><dc:creator>Mueller, Tony</dc:creator><dc:creator>Zhang, Jiachen</dc:creator><dc:creator>Rivera, Daniel</dc:creator><dc:creator>Hutchinson, Tara</dc:creator><dc:date>2025-12-12</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1xr17512</dc:identifier><dc:identifier>https://escholarship.org/content/qt1xr17512/qt1xr17512.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8p68x1w1</identifier><datestamp>2026-09-16T06:15:50Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8p68x1w1</dc:identifier><dc:title>Advancing use of Cold-formed Steel Framing Systems for Mid-Rise Residential Construction in Seismic Zones via Full-Scale Shake Table Testing</dc:title><dc:creator>Hutchinson, Tara</dc:creator><dc:creator>Eladly, Mohammed</dc:creator><dc:creator>Ji, Ruipu</dc:creator><dc:creator>Rivera, Daniel</dc:creator><dc:creator>Cyizere Rukundo, Fidence</dc:creator><dc:creator>Singh, Amanpreet</dc:creator><dc:creator>Sorosh, Shokrullah</dc:creator><dc:creator>Zhang, Jiachen</dc:creator><dc:creator>Zhang, Xianzhao</dc:creator><dc:creator>Padgett, Lynn</dc:creator><dc:creator>Jones, Harry</dc:creator><dc:creator>Karns, Jesse</dc:creator><dc:creator>Schafer, Benjamin</dc:creator><dc:date>2026-03-18</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8p68x1w1</dc:identifier><dc:identifier>https://escholarship.org/content/qt8p68x1w1/qt8p68x1w1.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3386p4jq</identifier><datestamp>2026-09-16T06:13:01Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3386p4jq</dc:identifier><dc:title>Cryogenic light detectors with thermal signal amplification for 0νββ search experiments</dc:title><dc:creator>Armatol, A</dc:creator><dc:creator>Barabash, AS</dc:creator><dc:creator>Baudin, D</dc:creator><dc:creator>Berest, V</dc:creator><dc:creator>Beretta, M</dc:creator><dc:creator>Bergé, L</dc:creator><dc:creator>Buchynska, M</dc:creator><dc:creator>Calvo-Mozota, JM</dc:creator><dc:creator>Capelli, C</dc:creator><dc:creator>Carniti, P</dc:creator><dc:creator>Chapellier, M</dc:creator><dc:creator>Dafinei, I</dc:creator><dc:creator>Danevich, FA</dc:creator><dc:creator>Dixon, T</dc:creator><dc:creator>Drobizhev, A</dc:creator><dc:creator>Dumoulin, L</dc:creator><dc:creator>Ferri, F</dc:creator><dc:creator>Gallas, A</dc:creator><dc:creator>Giuliani, A</dc:creator><dc:creator>Gotti, C</dc:creator><dc:creator>Gras, Ph</dc:creator><dc:creator>Ianni, A</dc:creator><dc:creator>Imbert, L</dc:creator><dc:creator>Khalife, H</dc:creator><dc:creator>Kobychev, VV</dc:creator><dc:creator>Konovalov, SI</dc:creator><dc:creator>Loaiza, P</dc:creator><dc:creator>de Marcillac, P</dc:creator><dc:creator>Marnieros, S</dc:creator><dc:creator>Marrache-Kikuchi, CA</dc:creator><dc:creator>Martinez, M</dc:creator><dc:creator>Mazzucato, E</dc:creator><dc:creator>Nones, C</dc:creator><dc:creator>Olivieri, E</dc:creator><dc:creator>de Solórzano, A Ortiz</dc:creator><dc:creator>Pageot, M</dc:creator><dc:creator>Peinaud, Y</dc:creator><dc:creator>Pérez, V</dc:creator><dc:creator>Pessina, G</dc:creator><dc:creator>Poda, DV</dc:creator><dc:creator>Rosier, P</dc:creator><dc:creator>Scarpaci, JA</dc:creator><dc:creator>Schmidt, B</dc:creator><dc:creator>Tretyak, VI</dc:creator><dc:creator>Umatov, VI</dc:creator><dc:creator>Zarytskyy, MM</dc:creator><dc:creator>Zolotarova, A</dc:creator><dc:date>2026-01-01</dc:date><dc:description>As a step towards the realization of cryogenic-detector experiments to search for neutrinoless double-beta decay (such as CROSS, BINGO, and CUPID), we investigated a batch of 10 Ge light detectors (LDs) assisted by Neganov-Trofimov-Luke (NTL) signal amplification. Each LD was assembled with a large cubic light-emitting crystal (45 mm side) using the recently developed CROSS mechanical structure. The detector array was operated at milli-Kelvin temperatures in a pulse-tube cryostat at the Canfranc underground laboratory in Spain. We achieved good performance with scintillating bolometers from CROSS, made of Li2 100MoO4 crystals and used as reference detectors of the setup, and with all LDs tested (except for a single device that encountered an electronics issue). No leakage current was observed for 8 LDs with an electrode bias up to 100 V. Operating the LDs at an 80 V electrode bias applied in parallel, we obtained a gain of around 9 in the signal-to-noise ratio of these devices, allowing us to achieve a baseline noise RMS of O(10 eV). Thanks to the strong current polarization of the temperature sensors, the time response of the devices was reduced to around half a millisecond in rise time. The achieved performance of the LDs was extrapolated via simulations of pile-up rejection capability for several configurations of the CUPID detector structure. Despite the sub-optimal noise conditions of the LDs (particularly at high frequencies), we demonstrated that the NTL technology provides a viable solution for background reduction in CUPID.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Cryogenic detectors</dc:subject><dc:subject>Double-beta decay detectors</dc:subject><dc:subject>Photon detectors for UV</dc:subject><dc:subject>visible and IR photons (solid-state)</dc:subject><dc:subject>Scintillators</dc:subject><dc:subject>scintillation and light emission processes (solid</dc:subject><dc:subject>gas and liquid scintillators)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3386p4jq</dc:identifier><dc:identifier>https://escholarship.org/content/qt3386p4jq/qt3386p4jq.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1748-0221/21/01/p01035</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Instrumentation, vol 21, iss 01</dc:source><dc:coverage>p01035</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt13n1x48m</identifier><datestamp>2026-09-16T06:12:48Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt13n1x48m</dc:identifier><dc:title>DESI EDR: Calibrating the Tully–Fisher Relationship with the DESI Peculiar Velocity Survey</dc:title><dc:creator>Douglass, K</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Uberoi, N</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Saulder, C</dc:creator><dc:creator>Said, K</dc:creator><dc:creator>Demina, R</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Aldering, G</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Davis, TM</dc:creator><dc:creator>Dawson, KS</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Joyce, R</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Lucey, J</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2026-04-10</dc:date><dc:description>We calibrate the Tully–Fisher relation (TFR) with data from the DESI Peculiar Velocity (PV) Survey taken during the Survey Validation (SV) period of the DESI galaxy redshift survey. Placing spectroscopic fibers on the centers and major axes of spatially extended spiral galaxies identified in the 2020 Siena Galaxy Atlas using the DESI Legacy Surveys, we measure the rotational velocities at 0.33R26 for 1155 (1128 + 27 dwarf) spiral galaxies observed during SV. Using 39 spiral galaxies observed in the Coma cluster, we find a slope for the TFR of −8.32 ± 0.15 AB mag in the r band, with a scatter about the TFR of 1.12 ± 0.03 AB mag. We calibrate the zero-point of the TFR using galaxies with independent distances measured using type Ia supernovae (SNe Ia) via the cosmological distance ladder. From the SN Ia distances, we measure a zero-point of −19.21−0.31+0.30 AB mag in the r band. We produce a public catalog of the distances to these 1128 spiral galaxies observed during DESI SV as part of the DESI PV Survey with our calibrated TFR. This is, to our knowledge, the first catalog of TFR distances produced with velocities measured at a single point in the disk.</dc:description><dc:subject>5109 Space Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0306 Physical Chemistry (incl. Structural) (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/13n1x48m</dc:identifier><dc:identifier>https://escholarship.org/content/qt13n1x48m/qt13n1x48m.pdf</dc:identifier><dc:identifier>info:doi/10.3847/1538-4357/ae517b</dc:identifier><dc:type>article</dc:type><dc:source>The Astrophysical Journal, vol 1001, iss 1</dc:source><dc:coverage>20</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7gx3630p</identifier><datestamp>2026-09-16T06:12:42Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7gx3630p</dc:identifier><dc:title>H 0 without the sound horizon (or supernovae): A 2% measurement in DESI DR1</dc:title><dc:creator>Zaborowski, EA</dc:creator><dc:creator>Taylor, P</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Krolewski, A</dc:creator><dc:creator>Rashkovetskyi, M</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>To, C</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Anand, A</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Castander, FJ</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Della Costa, J</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Joyce, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Lamman, C</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Samushia, L</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2026-04-01</dc:date><dc:description>The sound horizon scale rs is a key source of information for measurements of H 0 from early-time data, and is therefore a common target of new physics proposed to solve the Hubble tension. We present a sub-2% measurement of the Hubble constant that is independent of this scale, using data from the first data release of the Dark Energy Spectroscopic Instrument (DESI DR1). Building on previous work, we remove dependency on the sound horizon size using a heuristic rescaling procedure at the power spectrum level. A key innovation is the inclusion of uncalibrated (agnostic to rs ) post-reconstruction BAO measurements from DESI DR1, as well as using the CMB acoustic scale θ * as a high-redshift anchor. Uncalibrated type-Ia supernovae are often included as an independent source of Ωm information; here we demonstrate the robustness of our results by additionally considering two supernova-independent alternative datasets. We find somewhat higher values of H 0 relative to our previous work: 69.2+1.3 -1.4, 70.3+1.4 -1.2, and 69.6+1.3 -1.8 km s-1 Mpc-1 respectively when including measurements from i) Planck/ACT CMB lensing × unWISE galaxies, ii) the DES Year 3 6×2pt analysis, and iii) Planck/ACT CMB lensing + the DES Year 5 supernova analysis. These remarkably consistent constraints achieve better than 2% precision; they are among the most stringent sound horizon-independent measurements from LSS to date, and provide a powerful avenue for probing the origin of the Hubble tension.</dc:description><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>5103 Classical Physics (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>physics of the early universe</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7gx3630p</dc:identifier><dc:identifier>https://escholarship.org/content/qt7gx3630p/qt7gx3630p.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2026/04/004</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2026, iss 04</dc:source><dc:coverage>004</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt87w3z5gj</identifier><datestamp>2026-09-16T06:12:17Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt87w3z5gj</dc:identifier><dc:title>The imprint of cosmic voids from the DESI Legacy Survey DR9 Luminous Red Galaxies in the Planck 2018 lensing map through spectroscopically calibrated mocks</dc:title><dc:creator>Sartori, S</dc:creator><dc:creator>Vielzeuf, P</dc:creator><dc:creator>Escoffier, S</dc:creator><dc:creator>Cousinou, MC</dc:creator><dc:creator>Kovács, A</dc:creator><dc:creator>DeRose, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Garcia-Bellido, J</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:date>2025-08-01</dc:date><dc:description>The cross-correlation of cosmic voids with the lensing convergence ( κ ) map of the Cosmic Microwave Background (CMB) fluctuations provides a powerful tool to refine our understanding of the current cosmological model. However, several studies have reported a moderate tension (up to ∼2 σ ) between the lensing imprint of cosmic voids on the observed CMB and the ΛCDM signal predicted by simulations. To address this “lensing-is-low” tension and to obtain new, precise measurements of the signal, we exploit the large DESI Legacy Survey Luminous Red Galaxy (LRG) data set, covering approximately 19 500 deg 2 of the sky and including about 10 million LRGs at z &amp;lt; 1.05. Our ΛCDM template was created using the Buzzard mocks, which we specifically calibrated to match the clustering properties of the observed galaxy sample by exploiting more than one million DESI spectra. We identified our catalogs of 3D voids in the range 0.35 &amp;lt; z &amp;lt; 0.95 and cross-correlated them through a stacking methodology, dividing the sample into bins according to the redshift and λ v values of the voids. For the full void sample, we report a 14 σ detection of the lensing signal, with A  κ  = 1.016 ± 0.054, which increases to 17 σ when considering the void-in-void ( A  κ  = 0.944 ± 0.064) and the void-in-cloud ( A  κ  = 0.975 ± 0.060) populations individually, the highest detection significance for studies of this kind. We observe a full agreement between observations and ΛCDM mocks across all redshift bins, sky regions, and void populations considered. In addition to these findings, our analysis highlights the importance of accurately matching sparseness and redshift error distributions between mocks and observations, as well as the role of λ v in enhancing the signal-to-noise ratio through void population discrimination.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/87w3z5gj</dc:identifier><dc:identifier>https://escholarship.org/content/qt87w3z5gj/qt87w3z5gj.pdf</dc:identifier><dc:identifier>info:doi/10.1051/0004-6361/202453562</dc:identifier><dc:type>article</dc:type><dc:source>Astronomy &amp; Astrophysics, vol 700</dc:source><dc:coverage>a17</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2kz3s03g</identifier><datestamp>2026-09-16T06:12:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2kz3s03g</dc:identifier><dc:title>Analytical and EZmock covariance validation for the DESI 2024 results</dc:title><dc:creator>Forero-Sánchez, D</dc:creator><dc:creator>Rashkovetskyi, M</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Padmanabhan, N</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Yu, J</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Mena-Fernández, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Enriquez-Vargas, M</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-04-01</dc:date><dc:description>The estimation of uncertainties in cosmological parameters is an important challenge in Large-Scale-Structure (LSS) analyses. For standard analyses such as Baryon Acoustic Oscillations (BAO) and Full-Shape two approaches are usually considered. First: analytical estimates of the covariance matrix use Gaussian approximations and (nonlinear) clustering measurements to estimate the matrix, which allows a relatively fast and computationally cheap way to generate matrices that adapt to an arbitrary clustering measurement. On the other hand, sample covariances are an empirical estimate of the matrix based on an ensemble of clustering measurements from fast and approximate simulations. While more computationally expensive due to the large amount of simulations and volume required, these allow us to take into account systematics that are impossible to model analytically. In this work we compare these two approaches in order to enable DESI's key analyses. We find that the configuration space analytical estimate performs satisfactorily in BAO analyses and its flexibility in terms of input clustering makes it the fiducial choice for DESI's 2024 BAO analysis. On the contrary, the analytical computation of the covariance matrix in Fourier space does not reproduce the expected measurements in terms of Full-Shape analyses, which motivates the use of a corrected mock covariance for DESI's 2024 Full Shape analysis.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2kz3s03g</dc:identifier><dc:identifier>https://escholarship.org/content/qt2kz3s03g/qt2kz3s03g.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/04/055</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 04</dc:source><dc:coverage>055</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2vr3w4nz</identifier><datestamp>2026-09-16T06:11:49Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2vr3w4nz</dc:identifier><dc:title>Lowering and Runtime Support for Fortran’s Multi-Image Parallel Features using LLVM Flang, PRIF, and Caffeine</dc:title><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Rasmussen, Katherine</dc:creator><dc:creator>Rouson, Damian</dc:creator><dc:creator>Pailleux, Jean-Didier</dc:creator><dc:creator>Renault, Etienne</dc:creator><dc:creator>Richardson, Brad</dc:creator><dc:date>2025-11-17</dc:date><dc:description>This paper provides an overview of the multi-image parallel features in Fortran 2023 and their implementation in the LLVM flang compiler and the Caffeine parallel runtime library. The features of interest support a Single-Program, Multiple-Data (SPMD) programming model based on executing multiple “images”, each of which is a program instance. The features also support a Partitioned Global Address Space (PGAS) in the form of “coarray” distributed data structures. The paper discusses the lowering of multi-image features to the Parallel Runtime Interface for Fortran (PRIF) and the implementation of PRIF in the Caffeine parallel runtime library. This paper also provides an early view into the design of a new multi-image dialect of the LLVM Multi-Level Intermediate Representation (MLIR). We describe validation and testing of the resulting software stack, and demonstrate that performance compares favorably to another open-source compiler and runtime library: GNU Compiler Collection (GCC) gfortran and OpenCoarrays, respectively.</dc:description><dc:subject>46 Information and Computing Sciences (for-2020)</dc:subject><dc:subject>4601 Applied Computing (for-2020)</dc:subject><dc:subject>Fortran</dc:subject><dc:subject>Parallel programming</dc:subject><dc:subject>HPC</dc:subject><dc:subject>PGAS</dc:subject><dc:subject>RMA</dc:subject><dc:subject>LLVM Flang</dc:subject><dc:subject>Exascale Computing</dc:subject><dc:subject>Runtime Libraries</dc:subject><dc:subject>Caffeine</dc:subject><dc:subject>GASNet-EX</dc:subject><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2vr3w4nz</dc:identifier><dc:identifier>https://escholarship.org/content/qt2vr3w4nz/qt2vr3w4nz.pdf</dc:identifier><dc:identifier>info:doi/10.1145/3731599.3767480</dc:identifier><dc:type>article</dc:type><dc:source>PROCEEDINGS OF 2025 WORKSHOPS OF THE INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING, NETWORK, STORAGE, AND ANALYSIS, SC25 WORKSHOPS, vol 00</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8c83v3dv</identifier><datestamp>2026-09-16T06:11:12Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8c83v3dv</dc:identifier><dc:title>Clustering analysis of medium-band selected high-redshift galaxies</dc:title><dc:creator>Ebina, H</dc:creator><dc:creator>White, M</dc:creator><dc:creator>Raichoor, A</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Lang, D</dc:creator><dc:creator>Luo, Y</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Anand, A</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Castander, FJ</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Dawson, KS</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Joyce, R</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Magneville, C</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yèche, C</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2026-03-01</dc:date><dc:description>Next-generation large-scale structure spectroscopic surveys will probe cosmology at high redshifts (2.3 &amp;lt; z &amp;lt; 3.5), relying on abundant galaxy tracers such as Lyα emitters (LAEs) and Lyman break galaxies (LBGs). Medium-band photometry has emerged as a potential technique for efficiently selecting these high-redshift galaxies. In this work, we present clustering analysis of medium-band selected galaxies at high redshift, utilizing photometric data from the Intermediate Band Imaging Survey (IBIS) and spectroscopic data from the Dark Energy Spectroscopic Instrument (DESI). We interpret the clustering of such samples using both Halo Occupation Distribution (HOD) modeling and a perturbation theory description of large-scale structure. Our modeling indicates that the current target sample is composed from an overlapping mixture of LAEs and LBGs with emission lines. Despite differences in target selection, we find that the clustering properties are consistent with previous studies, with correlation lengths r 0 ≃ 3-4 h -1Mpc and a linear bias of b ∼ 1.8-2.5. Finally, we discuss the simulation requirements implied by these measurements and demonstrate that the properties of the samples would make them excellent targets to enhance our understanding of the high-z universe.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8c83v3dv</dc:identifier><dc:identifier>https://escholarship.org/content/qt8c83v3dv/qt8c83v3dv.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2026/03/019</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2026, iss 03</dc:source><dc:coverage>019</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1k88d64c</identifier><datestamp>2026-09-16T06:08:02Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1k88d64c</dc:identifier><dc:title>Cosmological neutrino mass: a frequentist overview in light of DESI</dc:title><dc:creator>Chebat, D</dc:creator><dc:creator>Yèche, C</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Schöneberg, N</dc:creator><dc:creator>Walther, M</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Rohlf, J</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Jimenez, J</dc:creator><dc:creator>Joyce, R</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Magneville, C</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2026-01-01</dc:date><dc:description>We derive constraints on the neutrino mass using a variety of recent cosmological datasets, including DESI BAO, the full-shape analysis of the DESI matter power spectrum and the one-dimensional power spectrum of the Lyman-α forest (P1D) from eBOSS quasars as well as the cosmic microwave background (CMB). The constraints are obtained in the frequentist formalism by constructing profile likelihoods and applying the Feldman-Cousins prescription to compute confidence intervals. This method avoids potential prior and volume effects that may arise in a comparable Bayesian analysis. Parabolic fits to the profiles allow one to distinguish changes in the upper limits from variations in the constraining power σ of the different data combinations. We find that all profiles in the ΛCDM model are cut off by the ∑mν ≥ 0 bound, meaning that the corresponding parabolas reach their minimum in the unphysical sector. The most stringent 95% C.L. upper limit is obtained by the combination of DESI DR2 BAO, Planck PR4 and CMB lensing at 53 meV, below the minimum of 59 meV set by the normal ordering. The corresponding constraining power σ is 43 meV, which highlights the importance of the cut-off by negative values in the determination of the upper limit. Extending ΛCDM to non-zero curvature and w 0 wa CDM relaxes the constraints past 59 meV again, but only w 0 wa CDM exhibits profiles with a minimum at a positive value. Additionally, we extend the formalism to constrain the lightest neutrino mass. For DESI DR2 BAO, Planck PR4 and CMB lensing, we find confidence limits at 20 and 19 meV for normal and inverted ordering, respectively. Using a combination of DESI DR1 full-shape, BBN and eBOSS Lyman-α P1D, we successfully constrain the neutrino mass independently of the CMB. This combination yields m l ≤ 97 and 98 meV in the normal and inverted orderings, and total neutrino mass ∑mν ≤ 285 meV (95% C.L.). The addition of DESI full-shape or Lyman-α P1D to CMB and DESI BAO results in small but noticeable improvement of the constraining power of the data. Lyman-α free-streaming measurements especially improve the constraint. Since they are based on eBOSS data, this sets a promising precedent for upcoming DESI data.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>Frequentist statistics</dc:subject><dc:subject>neutrino masses from cosmology</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1k88d64c</dc:identifier><dc:identifier>https://escholarship.org/content/qt1k88d64c/qt1k88d64c.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2026/01/041</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2026, iss 01</dc:source><dc:coverage>041</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9003s15v</identifier><datestamp>2026-09-16T06:07:54Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9003s15v</dc:identifier><dc:title>Analysis of Defect Irrelevancy in a Non-Insulated REBCO Pancake Coil Using an Electric Network Model</dc:title><dc:creator>Webb-Mack, Zo</dc:creator><dc:creator>Ji, Qing</dc:creator><dc:creator>Wang, Xiaorong</dc:creator><dc:date>2022-09-01</dc:date><dc:description>High-temperature superconducting REBCO coated conductor is one of the main candidates for next-generation high field magnets in fusion reactors and particle accelerators owing to their high current-carrying capability. Although these materials can operate at higher temperatures and generate higher magnetic fields than their counterparts with lower critical temperatures, protecting the REBCO magnet against quench is challenging. A variety of candidate technologies that may be able to enable self-protection, including no-insulation technology and insulative coatings with temperature-dependent resistance, are in development. In order to understand current sharing and thermal processes during a quench, we model a REBCO pancake coil as an electrical circuit, considering power generation and heat transfer along conductor turns, and study the current distribution around a local defect with lower critical current. The magnetic field and coil terminal voltage predicted by the simulation was compared to published experimental results. Our results provide useful insights into how current sharing occurs around defects.</dc:description><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>4008 Electrical Engineering (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>Superconducting magnets</dc:subject><dc:subject>Magnetic fields</dc:subject><dc:subject>High-temperature superconductors</dc:subject><dc:subject>Integrated circuit modeling</dc:subject><dc:subject>Voltage</dc:subject><dc:subject>Resistors</dc:subject><dc:subject>Resistance heating</dc:subject><dc:subject>Circuit simulation</dc:subject><dc:subject>high-temperature superconductors</dc:subject><dc:subject>superconducting magnets</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>4008 Electrical engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9003s15v</dc:identifier><dc:identifier>https://escholarship.org/content/qt9003s15v/qt9003s15v.pdf</dc:identifier><dc:identifier>info:doi/10.1109/tasc.2022.3171164</dc:identifier><dc:type>article</dc:type><dc:source>IEEE Transactions on Applied Superconductivity, vol 32, iss 6</dc:source><dc:coverage>1 - 5</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt03p619qt</identifier><datestamp>2026-09-16T06:07:08Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt03p619qt</dc:identifier><dc:title>Influence of overhead HVAC and aerosol control strategies on coarse mode particle dispersion and exposure in a full-scale room experiment</dc:title><dc:creator>Um, Chai Yoon</dc:creator><dc:creator>Preble, Chelsea V</dc:creator><dc:creator>Zhao, Haoran</dc:creator><dc:creator>Delp, William W</dc:creator><dc:creator>Kirchstetter, Thomas W</dc:creator><dc:creator>Li, Jiayu</dc:creator><dc:creator>Schiavon, Stefano</dc:creator><dc:creator>Singer, Brett C</dc:creator><dc:date>2026-04-01</dc:date><dc:description>Coarse mode respiratory aerosols can carry viral loads over long distances and have very different dynamics than submicron particles, but experimental studies under realistic conditions remain limited. To study the differential impacts on exposure under different mixing conditions, we co-released 7–10 µm particles and carbon dioxide (CO2)—which served as an indicator of gas and submicron particle dynamics—in a 158 m3 room at LBNL’s FLEXLAB facility with an overhead heating, ventilation, and air conditioning (HVAC) system. The room was arranged as a distanced meeting then a classroom with eight heated manikins and a researcher. Spatial variability was measured using 16 particle counters and 22–26 CO2 sensors throughout the space. Conditions included: HVAC off or supply air at 1000-1060 m3 h-1 at neutral, cooling, or heating temperatures; with and without 20% outdoor air; and added HVAC filtration, portable air cleaners (PACs), or a physical barrier between the speaker and occupants. We found that good mixing via neutral or cooling supply air or use of PACs under heating lowered coarse particle exposure at some locations, but increased exposure for one-quarter to two-thirds of manikins compared to poor mixing under heating. A physical barrier reduced direct transfer of coarse particles during heating, but less during cooling. High spatial variability shows that a single measurement cannot represent occupant exposure. Instantaneous air mixing assumptions overstate the effectiveness of ventilation, HVAC filtration, and upper-room germicidal ultraviolet disinfection for coarse particles, as relatively few particles reach the return grille or upper room under most conditions.</dc:description><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>33 Built Environment and Design (for-2020)</dc:subject><dc:subject>Airborne transmission</dc:subject><dc:subject>Ventilation effectiveness</dc:subject><dc:subject>Air mixing</dc:subject><dc:subject>Particle dispersion</dc:subject><dc:subject>Particle deposition</dc:subject><dc:subject>Pollutant transport</dc:subject><dc:subject>0502 Environmental Science and Management (for)</dc:subject><dc:subject>1201 Architecture (for)</dc:subject><dc:subject>1202 Building (for)</dc:subject><dc:subject>Building &amp; Construction (science-metrix)</dc:subject><dc:subject>33 Built environment and design (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/03p619qt</dc:identifier><dc:identifier>https://escholarship.org/content/qt03p619qt/qt03p619qt.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.buildenv.2026.114333</dc:identifier><dc:type>article</dc:type><dc:source>Building and Environment, vol 293</dc:source><dc:coverage>114333</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt90j444fn</identifier><datestamp>2026-09-16T06:03:42Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt90j444fn</dc:identifier><dc:title>Galaxy-multiplet clustering from DESI DR2</dc:title><dc:creator>Wang, Hanyue</dc:creator><dc:creator>Eisenstein, Daniel J</dc:creator><dc:creator>Aguilar, Jessica Nicole</dc:creator><dc:creator>Ahlen, Steven</dc:creator><dc:creator>Bianchi, Davide</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>Claybaugh, Todd</dc:creator><dc:creator>de la Macorra, Axel</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Doel, Peter</dc:creator><dc:creator>Ferraro, Simone</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>Forero-Romero, Jaime E</dc:creator><dc:creator>Gaztañaga, Enrique</dc:creator><dc:creator>Gutierrez, Gaston</dc:creator><dc:creator>Honscheid, Klaus</dc:creator><dc:creator>Ishak, Mustapha</dc:creator><dc:creator>Joyce, Richard</dc:creator><dc:creator>Juneau, Stephanie</dc:creator><dc:creator>Kirkby, David</dc:creator><dc:creator>Kisner, Theodore</dc:creator><dc:creator>Kremin, Anthony</dc:creator><dc:creator>Lahav, Ofer</dc:creator><dc:creator>Lamman, Claire</dc:creator><dc:creator>Landriau, Martin</dc:creator><dc:creator>Manera, Marc</dc:creator><dc:creator>Meisner, Aaron</dc:creator><dc:creator>Miquel, Ramon</dc:creator><dc:creator>Mueller, Eva-Maria</dc:creator><dc:creator>Nadathur, Seshadri</dc:creator><dc:creator>Niz, Gustavo</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Percival, Will J</dc:creator><dc:creator>Prada, Francisco</dc:creator><dc:creator>Pérez-Ràfols, Ignasi</dc:creator><dc:creator>Ross, Ashley J</dc:creator><dc:creator>Rossi, Graziano</dc:creator><dc:creator>Sanchez, Eusebio</dc:creator><dc:creator>Schlegel, David</dc:creator><dc:creator>Schubnell, Michael</dc:creator><dc:creator>Silber, Joseph Harry</dc:creator><dc:creator>Sprayberry, David</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Weaver, Benjamin Alan</dc:creator><dc:creator>Zhou, Rongpu</dc:creator><dc:creator>Zou, Hu</dc:creator><dc:date>2026-01-05</dc:date><dc:description>ABSTRACT We present an efficient estimator for higher order galaxy clustering using small groups of nearby galaxies, or multiplets. Using the Luminous Red Galaxy sample from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2, we identify galaxy multiplets as discrete objects and measure their cross-correlations with the general galaxy field. Our results show that the multiplets exhibit stronger clustering bias as they trace more massive dark matter haloes than individual galaxies. When comparing the observed clustering statistics with the mock catalogues generated from the N-body simulation AbacusSummit, we find that the mocks underpredict multiplet clustering despite reproducing the galaxy two-point autocorrelation reasonably well. This discrepancy indicates that the standard Halo Occupation Distribution (HOD) model is insufficient to describe the properties of galaxy multiplets, revealing the greater constraining power of this higher order statistic on galaxy–halo connection and the possibility that multiplets are specific to additional assembly bias. We demonstrate that incorporating secondary biases into the HOD model improves agreement with the observed multiplet statistics, specifically by allowing galaxies to preferentially occupy haloes in denser environments. Our results highlight the potential of utilizing multiplet clustering, beyond traditional two-point correlation measurements, to break degeneracies in models describing the galaxy–dark matter connection.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>methods: data analysis</dc:subject><dc:subject>large-scale structure of Universe</dc:subject><dc:subject>cosmology: observations</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/90j444fn</dc:identifier><dc:identifier>https://escholarship.org/content/qt90j444fn/qt90j444fn.pdf</dc:identifier><dc:identifier>info:doi/10.1093/mnras/staf2069</dc:identifier><dc:type>article</dc:type><dc:source>Monthly Notices of the Royal Astronomical Society, vol 545, iss 4</dc:source><dc:coverage>staf2069</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4849h0w9</identifier><datestamp>2026-09-16T06:03:19Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4849h0w9</dc:identifier><dc:title>DESI DR1 Lyα 1D power spectrum: the Fast Fourier Transform estimator measurement</dc:title><dc:creator>Ravoux, Corentin</dc:creator><dc:creator>Abdul-Karim, Marie-Lynn</dc:creator><dc:creator>Le Goff, Jean-Marc</dc:creator><dc:creator>Armengaud, Eric</dc:creator><dc:creator>Aguilar, Jessica N</dc:creator><dc:creator>Ahlen, Steven</dc:creator><dc:creator>Bailey, Stephen</dc:creator><dc:creator>Bianchi, Davide</dc:creator><dc:creator>Brodzeller, Allyson</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>Chaves-Montero, Jonás</dc:creator><dc:creator>Claybaugh, Todd</dc:creator><dc:creator>Cuceu, Andrei</dc:creator><dc:creator>de Belsunce, Roger</dc:creator><dc:creator>de la Macorra, Axel</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Ding, Zhejie</dc:creator><dc:creator>Doel, Peter</dc:creator><dc:creator>Ferraro, Simone</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>Forero-Romero, Jaime E</dc:creator><dc:creator>Gaztañaga, Enrique</dc:creator><dc:creator>Karaçaylı, Naim Göksel</dc:creator><dc:creator>Gontcho, Satya Gontcho A</dc:creator><dc:creator>Gutierrez, Gaston</dc:creator><dc:creator>Guy, Julien</dc:creator><dc:creator>Herrera-Alcantar, Hiram K</dc:creator><dc:creator>Ishak, Mustapha</dc:creator><dc:creator>Kehoe, Robert</dc:creator><dc:creator>Kirkby, David</dc:creator><dc:creator>Kisner, Theodore</dc:creator><dc:creator>Kremin, Anthony</dc:creator><dc:creator>Landriau, Martin</dc:creator><dc:creator>Le Guillou, Laurent</dc:creator><dc:creator>Levi, Michael E</dc:creator><dc:creator>Manera, Marc</dc:creator><dc:creator>Martini, Paul</dc:creator><dc:creator>Meisner, Aaron</dc:creator><dc:creator>Miquel, Ramon</dc:creator><dc:creator>Montero-Camacho, Paulo</dc:creator><dc:creator>Muñoz-Gutiérrez, Andrea</dc:creator><dc:creator>Nadathur, Seshadri</dc:creator><dc:creator>Niz, Gustavo</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Pan, Zhiwei</dc:creator><dc:creator>Percival, Will J</dc:creator><dc:creator>Pérez-Ràfols, Ignasi</dc:creator><dc:creator>Pieri, Matthew M</dc:creator><dc:creator>Prada, Francisco</dc:creator><dc:creator>Rossi, Graziano</dc:creator><dc:creator>Sanchez, Eusebio</dc:creator><dc:creator>Saulder, Christoph</dc:creator><dc:creator>Schlegel, David</dc:creator><dc:creator>Schubnell, Michael</dc:creator><dc:creator>Seo, Hee-Jong</dc:creator><dc:creator>Silber, Joseph H</dc:creator><dc:creator>Siudek, Małgorzata</dc:creator><dc:creator>Sprayberry, David</dc:creator><dc:creator>Tan, Ting</dc:creator><dc:creator>Tang, Ji-Jia</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Walther, Michael</dc:creator><dc:creator>Weaver, Benjamin A</dc:creator><dc:creator>Yèche, Christophe</dc:creator><dc:creator>Yu, Jiaxi</dc:creator><dc:creator>Zhou, Rongpu</dc:creator><dc:creator>Zou, Hu</dc:creator><dc:date>2025-11-01</dc:date><dc:description>We present the one-dimensional Lyman-α forest power spectrum measurement derived from the data release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI). The measurement of the Lyman-α forest power spectrum along the line of sight from high-redshift quasar spectra provides information on the shape of the linear matter power spectrum, neutrino masses, and the properties of dark matter. In this work, we use a Fast Fourier Transform (FFT)-based estimator, which is validated on synthetic data in a companion paper. Compared to the FFT measurement performed on the DESI early data release, we improve the noise characterization with a cross-exposure estimator and test the robustness of our measurement using various data splits. We also refine the estimation of the uncertainties and now present an estimator for the covariance matrix of the measurement. Furthermore, we compare our results to previous high-resolution and eBOSS measurements. In another companion paper, we present the same DR1 measurement using the Quadratic Maximum Likelihood Estimator (QMLE). These two measurements are consistent with each other and constitute the most precise one-dimensional power spectrum measurement to date, while being in good agreement with results from the DESI early data release.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>intergalactic media</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4849h0w9</dc:identifier><dc:identifier>https://escholarship.org/content/qt4849h0w9/qt4849h0w9.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/11/079</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 11</dc:source><dc:coverage>079</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt03q290h9</identifier><datestamp>2026-09-16T06:02:28Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt03q290h9</dc:identifier><dc:title>The Compilation and Validation of the Spectroscopic Redshift Catalogs for the DESI-COSMOS and DESI-XMM-LSS Fields</dc:title><dc:creator>Ratajczak, J</dc:creator><dc:creator>Dawson, KS</dc:creator><dc:creator>Weaverdyck, N</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Blanco, D</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Castander, FJ</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hagen, T</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Jimenez, J</dc:creator><dc:creator>Joyce, R</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Koposov, SE</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Lamman, C</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Leauthaud, A</dc:creator><dc:creator>Lee, J</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Li, Q</dc:creator><dc:creator>Longhurst, I</dc:creator><dc:creator>Luo, Y</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>McCullough, J</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Raichoor, A</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Hernandez, Y Salcedo</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Saulder, C</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Wechsler, RH</dc:creator><dc:creator>White, M</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2026-02-02</dc:date><dc:description>Over several dedicated programs that include targets beyond the main cosmological samples, the Dark Energy Spectroscopic Instrument collected spectra for 304,970 unique objects in two fields centered on the COSMOS and XMM-LSS fields. In this work, we develop spectroscopic redshift robustness criteria for those spectra, validate these criteria using visual inspection, and provide two custom value-added catalogs with our redshift characterizations. With these criteria, we reliably classify 212,935 galaxies below z &amp;lt; 1.6, 9713 quasars, and 35,222 stars. The resulting catalogs achieve a redshift purity exceeding 99.4% across all galaxy samples. As a critical element in characterizing the selection function, we provide the description of 70 different algorithms that were used to select these targets from imaging data. To facilitate joint imaging/spectroscopic analyses, we provide row-matched photometry from the Dark Energy Camera, Hyper-Suprime Cam, and public COSMOS2020 photometric catalogs. Finally, we demonstrate example applications of these large catalogs to photometric redshift estimation, cluster finding, and completeness studies.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/03q290h9</dc:identifier><dc:identifier>https://escholarship.org/content/qt03q290h9/qt03q290h9.pdf</dc:identifier><dc:identifier>info:doi/10.3847/1538-3881/ae1fde</dc:identifier><dc:type>article</dc:type><dc:source>The Astronomical Journal, vol 171, iss 2</dc:source><dc:coverage>71</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0zd8109d</identifier><datestamp>2026-09-16T05:57:36Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0zd8109d</dc:identifier><dc:title>Design of a Structure for Assembly and Cooling the Magnet of the Next-Generation 45 GHz ECR Ion Source MARS-D</dc:title><dc:creator>Xu, Lianrong</dc:creator><dc:creator>Benitez, Janilee</dc:creator><dc:creator>Duran, Jaime Cruz</dc:creator><dc:creator>Ferracin, Paolo</dc:creator><dc:creator>Juchno, Mariusz</dc:creator><dc:creator>Phair, Larry</dc:creator><dc:creator>Todd, Damon</dc:creator><dc:creator>Wang, Li</dc:creator><dc:creator>Yang, Ye</dc:creator><dc:date>2026-05-01</dc:date><dc:description>The current Electron Cyclotron Resonance Ion Sources (ECRISs), constructed with Nb-Ti wires and the conventional racetrack-and-solenoid structure, have achieved operating frequencies up to 28 GHz and utilized about 90% of the critical current of the Nb-Ti wire. A Mixed Axial and Radial field System Demonstrator (MARS-D) is being developed at Lawrence Berkeley National Laboratory (LBNL). This system, which consists of an innovative hexagonal Closed-Loop Coil (CLC) and a set of solenoids, can generate higher magnetic fields (up to 150% ) while requiring only about 50% of the superconducting wire, enabling Nb-Ti wires to be used in the next-generation 45 GHz ECRIS. However, the assembly and cooling of such an efficient and compact magnet are particularly challenging due to the small radial gap between the CLC and solenoids, as well as the tight operating temperature margin. To address these challenges, a structure was developed that combines a three-section radially split solenoid mandrel with a series of shrink-fit reinforcement rings and cooling channels. This paper presents the detailed structure, manufacturing method, assembly procedure, impregnation method, mechanical Finite Element Analysis (FEA) comparison, and thermal FEA comparison.</dc:description><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Superconducting magnets</dc:subject><dc:subject>Solenoids</dc:subject><dc:subject>Cooling</dc:subject><dc:subject>Helium</dc:subject><dc:subject>Assembly</dc:subject><dc:subject>Ion sources</dc:subject><dc:subject>Magnetomechanical effects</dc:subject><dc:subject>Clamps</dc:subject><dc:subject>Magnetic liquids</dc:subject><dc:subject>Cyclotrons</dc:subject><dc:subject>ECR ion sources</dc:subject><dc:subject>magnet structure</dc:subject><dc:subject>superconducting magnets</dc:subject><dc:subject>NSD-88-Inch Cyclotron (c-lbnl-label)</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>4008 Electrical engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0zd8109d</dc:identifier><dc:identifier>https://escholarship.org/content/qt0zd8109d/qt0zd8109d.pdf</dc:identifier><dc:identifier>info:doi/10.1109/tasc.2025.3641911</dc:identifier><dc:type>article</dc:type><dc:source>IEEE Transactions on Applied Superconductivity, vol 36, iss 3</dc:source><dc:coverage>1 - 5</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9475h74w</identifier><datestamp>2026-09-16T05:57:23Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9475h74w</dc:identifier><dc:title>Rotational bands in Md249</dc:title><dc:creator>Appleton, CJ</dc:creator><dc:creator>Clark, RM</dc:creator><dc:creator>Morse, C</dc:creator><dc:creator>Seweryniak, D</dc:creator><dc:creator>Armstrong, M</dc:creator><dc:creator>Bequet, J</dc:creator><dc:creator>Burns, C</dc:creator><dc:creator>Campbell, CM</dc:creator><dc:creator>Chemey, AT</dc:creator><dc:creator>Chowdhury, P</dc:creator><dc:creator>Crawford, HL</dc:creator><dc:creator>Cromaz, M</dc:creator><dc:creator>Fallon, P</dc:creator><dc:creator>Garcia-Jiménez, G</dc:creator><dc:creator>Herzberg, RD</dc:creator><dc:creator>Hrabar, Y</dc:creator><dc:creator>Huang, T</dc:creator><dc:creator>Karayonchev, V</dc:creator><dc:creator>Kondev, FG</dc:creator><dc:creator>Korichi, A</dc:creator><dc:creator>Lauritsen, T</dc:creator><dc:creator>McGovern, P</dc:creator><dc:creator>Müller-Gatermann, C</dc:creator><dc:creator>Porzio, C</dc:creator><dc:creator>Potterveld, DH</dc:creator><dc:creator>Reviol, W</dc:creator><dc:creator>Rice, E</dc:creator><dc:creator>Rudolph, D</dc:creator><dc:creator>Sarmiento, LG</dc:creator><dc:creator>Siciliano, M</dc:creator><dc:creator>Sidhu, RS</dc:creator><dc:creator>Wahid, SG</dc:creator><dc:date>2025-12-01</dc:date><dc:description>Rotational structures in Md249 have been observed for the first time. One set of states forms a pair of strongly coupled bands with relatively strong E2 transitions and no identifiable M1 transitions between the two signature partners. Another set of states suggests a decoupled sequence of E2 transitions. These bands are assigned as based on the 7/2−[514] and on the favored signature of the 1/2−[521] Nilsson level, respectively. Based on previous decay studies, these levels are thought to be the ground state and first excited state of Md249, which also agrees with theoretical predictions.</dc:description><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>NSD-Low Energy Nuclear Physics (c-lbnl-label)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9475h74w</dc:identifier><dc:identifier>https://escholarship.org/content/qt9475h74w/qt9475h74w.pdf</dc:identifier><dc:identifier>info:doi/10.1103/c5zn-xn9j</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review C, vol 112, iss 6</dc:source><dc:coverage>064314</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt45j7r1v1</identifier><datestamp>2026-09-16T05:53:20Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt45j7r1v1</dc:identifier><dc:title>Fyn–Saracatinib Complex Structure Reveals an Active State-like Conformation</dc:title><dc:creator>Ta, Hai Minh</dc:creator><dc:creator>Sankaran, Banumathi</dc:creator><dc:creator>Roush, Eric D</dc:creator><dc:creator>Ferreon, Josephine C</dc:creator><dc:creator>Ferreon, Allan Chris M</dc:creator><dc:creator>Kim, Choel</dc:creator><dc:date>2026-01-01</dc:date><dc:description>Fyn is a Src-family tyrosine kinase implicated in synaptic dysfunction and neuroinflammation across multiple neurodegenerative disorders, including Alzheimer's disease (AD) and Parkinson's disease (PD). Saracatinib (AZD0530) is a potent Src-family inhibitor that has been explored as a repurposed therapeutic; however, its clinical utility is limited by poor kinase selectivity caused by high sequence conservation within Src-family ATP-binding sites. Here, we combine surface plasmon resonance (SPR) and X-ray crystallography to define saracatinib recognition by the Fyn kinase domain (KD). SPR single-cycle kinetics shows that saracatinib binds the isolated Fyn KD and full-length Fyn with low-nanomolar affinity, whereas dasatinib binds with subnanomolar affinity and markedly slower dissociation. We determined the crystal structure of the Fyn KD-saracatinib complex at 2.22 Å resolution. The kinase adopts an active-like conformation with the DFG motif and αC-helix in the 'in' state and a conserved β3 αC Lys-Glu salt bridge. Saracatinib occupies the adenine and ribose pockets, and engages the hinge through direct and water-mediated hydrogen bonding while complementing a hydrophobic back pocket by van der Waals contacts. Comparison with reported saracatinib-bound structures of other kinases suggests that the active-state geometry observed for Fyn creates a pocket not observed in inactive-like complexes, providing a structural handle for designing Fyn-selective inhibitors. Comparison with all saracatinib-bound kinase co-structures currently available in the PDB (ALK2 and PKMYT1) indicates a conserved monodentate hinge binding mode but kinase-dependent αC-helix conformations, providing a structural rationale for designing Fyn-selective analogues.</dc:description><dc:subject>3101 Biochemistry and Cell Biology (for-2020)</dc:subject><dc:subject>34 Chemical Sciences (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>Aging (rcdc)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>Neurodegenerative (rcdc)</dc:subject><dc:subject>Brain Disorders (rcdc)</dc:subject><dc:subject>Proto-Oncogene Proteins c-fyn (mesh)</dc:subject><dc:subject>Benzodioxoles (mesh)</dc:subject><dc:subject>Quinazolines (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Crystallography</dc:subject><dc:subject>X-Ray (mesh)</dc:subject><dc:subject>Protein Binding (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Molecular (mesh)</dc:subject><dc:subject>Protein Kinase Inhibitors (mesh)</dc:subject><dc:subject>Binding Sites (mesh)</dc:subject><dc:subject>Surface Plasmon Resonance (mesh)</dc:subject><dc:subject>Protein Conformation (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Quinazolines (mesh)</dc:subject><dc:subject>Protein Kinase Inhibitors (mesh)</dc:subject><dc:subject>Crystallography</dc:subject><dc:subject>X-Ray (mesh)</dc:subject><dc:subject>Surface Plasmon Resonance (mesh)</dc:subject><dc:subject>Binding Sites (mesh)</dc:subject><dc:subject>Protein Conformation (mesh)</dc:subject><dc:subject>Protein Binding (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Molecular (mesh)</dc:subject><dc:subject>Proto-Oncogene Proteins c-fyn (mesh)</dc:subject><dc:subject>Benzodioxoles (mesh)</dc:subject><dc:subject>AZD0530</dc:subject><dc:subject>Fyn</dc:subject><dc:subject>Src-family kinase</dc:subject><dc:subject>Tau</dc:subject><dc:subject>Tauopathy</dc:subject><dc:subject>X-ray crystallography</dc:subject><dc:subject>dasatinib</dc:subject><dc:subject>kinase inhibitor selectivity</dc:subject><dc:subject>neurodegeneration</dc:subject><dc:subject>saracatinib</dc:subject><dc:subject>surface plasmon resonance</dc:subject><dc:subject>Proto-Oncogene Proteins c-fyn (mesh)</dc:subject><dc:subject>Benzodioxoles (mesh)</dc:subject><dc:subject>Quinazolines (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Crystallography</dc:subject><dc:subject>X-Ray (mesh)</dc:subject><dc:subject>Protein Binding (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Molecular (mesh)</dc:subject><dc:subject>Protein Kinase Inhibitors (mesh)</dc:subject><dc:subject>Binding Sites (mesh)</dc:subject><dc:subject>Surface Plasmon Resonance (mesh)</dc:subject><dc:subject>Protein Conformation (mesh)</dc:subject><dc:subject>0399 Other Chemical Sciences (for)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>0699 Other Biological Sciences (for)</dc:subject><dc:subject>Chemical Physics (science-metrix)</dc:subject><dc:subject>3101 Biochemistry and cell biology (for-2020)</dc:subject><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>3404 Medicinal and biomolecular chemistry (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/45j7r1v1</dc:identifier><dc:identifier>https://escholarship.org/content/qt45j7r1v1/qt45j7r1v1.pdf</dc:identifier><dc:identifier>info:doi/10.3390/ijms27031143</dc:identifier><dc:type>article</dc:type><dc:source>International Journal of Molecular Sciences, vol 27, iss 3</dc:source><dc:coverage>1143</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0z2063j6</identifier><datestamp>2026-09-16T05:53:05Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0z2063j6</dc:identifier><dc:title>A joint analysis of 3D clustering and galaxy × CMB-lensing cross-correlations with DESI DR1 galaxies</dc:title><dc:creator>Maus, M</dc:creator><dc:creator>White, M</dc:creator><dc:creator>Sailer, N</dc:creator><dc:creator>Lizancos, A Baleato</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>DeRose, J</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Castander, FJ</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Lamman, C</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Samushia, L</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-11-01</dc:date><dc:description>The spectroscopic data from DESI Data Release 1 (DR1) galaxies enables the analysis of 3D clustering by fitting galaxy power spectra and reconstructed correlation functions in redshift space. Given low measurements of the amplitude of structure from cosmic shear at z ∼ 1, redshift space distortions (RSD) + Baryon Acoustic Oscillation (BAO) signals from DESI galaxies combined with weak lensing can break degeneracies and provide a tight alternative constraint on the z ∼ 1 amplitude of structure. In this paper we perform joint analyses that combine full-shape + post-reconstruction information from the DESI DR1 BGS and LRG samples along with angular cross-correlations with Planck PR4 and ACT DR6 CMB lensing maps. We show that adding galaxy-lensing cross-correlations tightens clustering amplitude constraints, improving σ 8 uncertainties by 30% over RSD+BAO alone. We also include angular galaxy-galaxy and galaxy-lensing spectra using photometric samples from the DESI Legacy Survey to further improve constraints. Our headline results are σ 8 = 0.803 ± 0.017, Ωm = 0.3037 ± 0.0069, and S 8 = 0.808 ± 0.017. Given DESI's preference for higher σ 8 compared to lower values from BOSS, we perform a catalog-level comparison of LRG samples from both surveys. We test sensitivity to dark energy assumptions by relaxing our ΛCDM prior and allowing for evolving dark energy via the w 0 - wa parameterization. We find our S 8 constraints to be relatively unchanged despite a 3.5σ tension with the cosmological constant model when combining with the Union3 supernova likelihood. Finally we test general relativity (GR) by allowing the gravitational slip parameter (γ) to vary, and find γ = 1.17 ± 0.11 in mild (∼ 1.5σ) tension with the GR value of 1.0.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>gravitational lensing</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0z2063j6</dc:identifier><dc:identifier>https://escholarship.org/content/qt0z2063j6/qt0z2063j6.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/11/077</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 11</dc:source><dc:coverage>077</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt99p3s3nz</identifier><datestamp>2026-09-16T05:52:27Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt99p3s3nz</dc:identifier><dc:title>Coordination Characteristics of Uranyl BBP Complexes: Insights from an Electronic Structure Analysis</dc:title><dc:creator>Pemmaraju, Chaitanya Das</dc:creator><dc:creator>Copping, Roy</dc:creator><dc:creator>Smiles, Danil E</dc:creator><dc:creator>Shuh, David K</dc:creator><dc:creator>Grønbech-Jensen, Niels</dc:creator><dc:creator>Prendergast, David</dc:creator><dc:creator>Canning, Andrew</dc:creator><dc:date>2017-03-31</dc:date><dc:description>Organic ligand complexes of lanthanide/actinide ions have been studied extensively for applications in nuclear fuel storage and recycling. Several complexes of 2,6-bis(2-benzimidazyl)pyridine (H2BBP) featuring the uranyl moiety have been reported recently, and the present study investigates the coordination characteristics of these complexes using density functional theory-based electronic structure analysis. In particular, with the aid of several computational models, the nonplanar equatorial coordination about uranyl, observed in some of the compounds, is studied and its origin traced to steric effects.</dc:description><dc:subject>3402 Inorganic Chemistry (for-2020)</dc:subject><dc:subject>34 Chemical Sciences (for-2020)</dc:subject><dc:subject>0904 Chemical Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>3403 Macromolecular and materials chemistry (for-2020)</dc:subject><dc:subject>3406 Physical chemistry (for-2020)</dc:subject><dc:subject>4004 Chemical engineering (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/99p3s3nz</dc:identifier><dc:identifier>https://escholarship.org/content/qt99p3s3nz/qt99p3s3nz.pdf</dc:identifier><dc:identifier>info:doi/10.1021/acsomega.6b00459</dc:identifier><dc:type>article</dc:type><dc:source>ACS Omega, vol 2, iss 3</dc:source><dc:coverage>1055 - 1062</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt47h152kk</identifier><datestamp>2026-09-16T05:52:09Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt47h152kk</dc:identifier><dc:title>Identification of Site Response Features Using Microtremor HVSR</dc:title><dc:creator>Ornelas, Francisco Javier G</dc:creator><dc:creator>de la Torre, Christopher A</dc:creator><dc:creator>Buckreis, Tristan E</dc:creator><dc:creator>Nweke, Chukwuebuka C</dc:creator><dc:creator>Brandenberg, Scott J</dc:creator><dc:creator>Stewart, Jonathan P</dc:creator><dc:date>2025-10-30</dc:date><dc:description>Frequency-dependent horizontal-to-vertical spectral ratios (HVSR) of three-component recordings provide information on-site resonant frequencies, which are potentially useful for predicting site response. We compute microtremor-derived HVSR (mHVSR) from Fourier amplitude spectra (FAS) using a relational database for site data, mainly in California. Using these data, we identify sites with peaks, sites with no peaks, and characteristics of peaks for sites that have them. Using a separate relational database for earthquake ground motion studies, we identify period-dependent response-spectra site terms, which reflect the mean offsets of site-specific ground motions from predictions of a ground motion model (GMM). Those site terms may have peaks, no peaks, or transitions from low-to-high values (with or without peaks) over some period range. This paper evaluates the degree to which features of site terms can be mapped to features of mHVSR at the same site. This is an important step towards the eventual development of an mHVSR-conditioned site response model to capture such features.</dc:description><dc:subject>4005 Civil Engineering (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>Geological &amp; Geomatics Engineering (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/47h152kk</dc:identifier><dc:identifier>https://escholarship.org/content/qt47h152kk/qt47h152kk.pdf</dc:identifier><dc:identifier>info:doi/10.1061/9780784486504.025</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3zz855b4</identifier><datestamp>2026-09-16T05:52:06Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3zz855b4</dc:identifier><dc:title>US04/DIN1: Edits for Asynchronous and Team Collective Subroutines</dc:title><dc:creator>Cook, Brandon</dc:creator><dc:creator>Rouson, Damian</dc:creator><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Budiardja, Reuben</dc:creator><dc:date>2025-11-12</dc:date><dc:description>This paper contains Fortran 202Y specification edits for work items US-04 and DIN1, Asynchronous and Team Collective Subroutines.
It passed by unanimous consent at the Nov 2025 meeting #237 of the INCITS/US Fortran Programming Language Standards Technical Committee.</dc:description><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:subject>incits-fortran</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3zz855b4</dc:identifier><dc:identifier/><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4ms0s74m</identifier><datestamp>2026-09-16T05:48:11Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4ms0s74m</dc:identifier><dc:title>Specifications and Syntax for Local Prefix Operation Intrinsics (sum)</dc:title><dc:creator>Cook, Brandon</dc:creator><dc:creator>Bonachea, Dan</dc:creator><dc:date>2025-10-13</dc:date><dc:description>This paper contains formal specifications and syntax for Fortran 202Y work item US-20, intrinsic subroutines for prefix sum operations.
It passed by unanimous consent at the Oct 2025 meeting #237 of the INCITS/US Fortran Programming Language Standards Technical Committee.</dc:description><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:subject>incits-fortran</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4ms0s74m</dc:identifier><dc:identifier/><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2147n686</identifier><datestamp>2026-09-16T05:48:08Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2147n686</dc:identifier><dc:title>US04: Requirements for Asynchronous Collective Subroutines</dc:title><dc:creator>Cook, Brandon</dc:creator><dc:creator>Rouson, Damian</dc:creator><dc:creator>Bonachea, Dan</dc:creator><dc:date>2025-10-14</dc:date><dc:description>This paper contains formal requirements for Fortran 202Y work item US-04, Asynchronous Collective Subroutines.
It passed by unanimous consent at the Oct 2025 meeting #237 of the INCITS/US Fortran Programming Language Standards Technical Committee.</dc:description><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:subject>incits-fortran</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2147n686</dc:identifier><dc:identifier/><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7b28f5hr</identifier><datestamp>2026-09-16T05:47:34Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7b28f5hr</dc:identifier><dc:title>Clustering of DESI galaxies split by thermal Sunyaev-Zeldovich effect</dc:title><dc:creator>Rashkovetskyi, Michael</dc:creator><dc:creator>Eisenstein, Daniel J</dc:creator><dc:creator>Aguilar, Jessica Nicole</dc:creator><dc:creator>Ahlen, Steven</dc:creator><dc:creator>Anand, Abhijeet</dc:creator><dc:creator>Bianchi, Davide</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>Castander, Francisco Javier</dc:creator><dc:creator>Claybaugh, Todd</dc:creator><dc:creator>Cuceu, Andrei</dc:creator><dc:creator>Dawson, Kyle S</dc:creator><dc:creator>de la Macorra, Axel</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Doel, Peter</dc:creator><dc:creator>Ferraro, Simone</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>Forero-Romero, Jaime E</dc:creator><dc:creator>Gaztañaga, Enrique</dc:creator><dc:creator>Gutierrez, Gaston</dc:creator><dc:creator>Herrera-Alcantar, Hiram K</dc:creator><dc:creator>Honscheid, Klaus</dc:creator><dc:creator>Howlett, Cullan</dc:creator><dc:creator>Ishak, Mustapha</dc:creator><dc:creator>Joyce, Richard</dc:creator><dc:creator>Kehoe, Robert</dc:creator><dc:creator>Kisner, Theodore</dc:creator><dc:creator>Kremin, Anthony</dc:creator><dc:creator>Lahav, Ofer</dc:creator><dc:creator>Lambert, Andrew</dc:creator><dc:creator>Landriau, Martin</dc:creator><dc:creator>Manera, Marc</dc:creator><dc:creator>Miquel, Ramon</dc:creator><dc:creator>Mueller, Eva-Maria</dc:creator><dc:creator>Nadathur, Seshadri</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Percival, Will J</dc:creator><dc:creator>Prada, Francisco</dc:creator><dc:creator>Pérez-Ràfols, Ignasi</dc:creator><dc:creator>Ross, Ashley J</dc:creator><dc:creator>Rossi, Graziano</dc:creator><dc:creator>Sanchez, Eusebio</dc:creator><dc:creator>Schlegel, David</dc:creator><dc:creator>Schubnell, Michael</dc:creator><dc:creator>Silber, Joseph Harry</dc:creator><dc:creator>Sprayberry, David</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Weaver, Benjamin Alan</dc:creator><dc:creator>Zhou, Rongpu</dc:creator><dc:creator>Zou, Hu</dc:creator><dc:date>2025-01-01</dc:date><dc:description>The thermal Sunyaev-Zeldovich (tSZ) effect is associated with galaxy clusters - extremely large and dense structures tracing the dark matter with a higher bias than isolated galaxies. We propose to use the tSZ data to separate galaxies from redshift surveys into distinct subpopulations corresponding to different densities and biases independently of the redshift survey systematics. Leveraging the information from different environments, as in density-split and density-marked clustering, is known to tighten the constraints on cosmological parameters, like  ,  and neutrino mass. We use data from the Dark Energy Spectroscopic Instrument (DESI) and the Atacama Cosmology Telescope (ACT) in their region of overlap to demonstrate informative tSZ splitting of Luminous Red Galaxies (LRGs). We discover a significant increase in the large-scale clustering of DESI LRGs corresponding to detections starting from 1-2 sigma in the ACT DR6 + Planck tSZ Compton-  map, below the cluster candidate threshold (4 sigma). We also find that such galaxies have higher line-of-sight coordinate (and velocity) dispersions and a higher number of close neighbors than both the full sample and near-zero tSZ regions. We produce simple simulations of tSZ maps that are intrinsically consistent with galaxy catalogs and do not include systematic effects, and find a similar pattern of large-scale clustering enhancement with tSZ effect significance. Moreover, we observe that this relative bias pattern remains largely unchanged with variations in the galaxy-halo connection model in our simulations. This is promising for future cosmological inference from tSZ-split clustering with semi-analytical models. Thus, we demonstrate that valuable cosmological information is present in the lower signal-to-noise regions of the thermal Sunyaev-Zeldovich map, extending far beyond the individual cluster candidates.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7b28f5hr</dc:identifier><dc:identifier>https://escholarship.org/content/qt7b28f5hr/qt7b28f5hr.pdf</dc:identifier><dc:identifier>info:doi/10.33232/001c.146033</dc:identifier><dc:type>article</dc:type><dc:source>The Open Journal of Astrophysics, vol 8</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0h61r8f2</identifier><datestamp>2026-09-16T05:47:19Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0h61r8f2</dc:identifier><dc:title>Cosmology from Planck CMB lensing and DESI DR1 quasar tomography</dc:title><dc:creator>de Belsunce, R</dc:creator><dc:creator>Krolewski, A</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Farren, G</dc:creator><dc:creator>Hadzhiyska, B</dc:creator><dc:creator>Tamone, A</dc:creator><dc:creator>Chiarenza, S</dc:creator><dc:creator>Sailer, N</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Della Costa, J</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Joyce, R</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Lamman, C</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-10-01</dc:date><dc:description>We present a measurement of the amplitude of matter fluctuations over the redshift range 0.8 ≤ z ≤ 3.5 from the cross correlation of over 1.2 million spectroscopic quasars selected by the Dark Energy Spectroscopic Instrument (DESI) across 7,200 deg2 (∼ 170 quasars/deg2) and Planck PR4 (NPIPE) cosmic microwave background (CMB) lensing maps. We perform a tomographic measurement in three bins centered at effective redshifts z=1.44, 2.27 and 2.75, which have ample overlap with the CMB lensing kernel. From a joint fit using the angular clustering of all three redshift bins (auto and cross-spectra), and including an prior from DESI DR1 baryon acoustic oscillations to break the degeneracy, we constrain the amplitude of matter fluctuations in the matter-dominated regime to be and . We provide a growth of structure measurement with the largest spectroscopic quasar sample to date at high redshift, which is ∼ 1.5σ higher than predictions from ΛCDM fits to measurements of the primary CMB from Planck PR4. The cross-correlation between PR4 lensing maps and DESI DR1 quasars is detected with a signal-to-noise ratio of 21.7 and the quasar auto-correlation at 27.2 for the joint analysis of all redshift bins. We combine our measurement with the CMB lensing auto-spectrum from the ground-based Atacama Cosmology Telescope (ACT DR6) and Planck PR4 to perform a sound-horizon-free measurement of the Hubble constant, yielding through its sensitivity to the matter-radiation equality scale.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>gravitational lensing</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0h61r8f2</dc:identifier><dc:identifier>https://escholarship.org/content/qt0h61r8f2/qt0h61r8f2.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/10/077</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 10</dc:source><dc:coverage>077</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9v10m4rv</identifier><datestamp>2026-09-16T05:47:04Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9v10m4rv</dc:identifier><dc:title>Constraining primordial non-Gaussianity from the large scale structure two-point and three-point correlation functions</dc:title><dc:creator>Brown, Z</dc:creator><dc:creator>Demina, R</dc:creator><dc:creator>Adame, AG</dc:creator><dc:creator>Avila, S</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Yuan, S</dc:creator><dc:creator>Gonzalez-Perez, V</dc:creator><dc:creator>García-Bellido, J</dc:creator><dc:creator>Levi, B</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Blum, R</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Muñoz-Gutièrrez, A</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlafly, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Silber, JH</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zhou, Z</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-10-06</dc:date><dc:description>ABSTRACT Surveys of cosmological large-scale structure (LSS) are sensitive to the presence of local primordial non-Gaussianity (PNG), and may be used to constrain models of inflation. Local PNG, characterized by $f_{\mathrm{NL}}$, the amplitude of the quadratic correction to the potential of a Gaussian random field, is traditionally measured from LSS two-point and three-point clustering via the power spectrum and bi-spectrum. We propose a framework to measure $f_{\mathrm{NL}}$ using the configuration space two-point correlation function (2pcf) monopole and three-point correlation function (3pcf) monopole of survey tracers. Our model estimates the effect of the scale-dependent bias induced by the presence of PNG on the 2pcf and 3pcf from the clustering of simulated dark matter haloes. We describe how this effect may be scaled to an arbitrary tracer of the cosmological matter density. The 2pcf and 3pcf of this tracer are measured to constrain the value of $f_{\mathrm{NL}}$. In LSS surveys, the effect of imaging systematics on two-point statistics is often degenerate with the PNG signal. Our proposed model employs three-point statistics primarily to break this degeneracy. Using simulations of luminous red galaxies observed by the Dark Energy Spectroscopic Instrument (DESI), we demonstrate the accuracy and constraining power of our method. Our forecast indicates the ability to constrain $f_{\mathrm{NL}}$ to a precision of $\sigma _{f_{\mathrm{NL}}} \approx 22$ with one year of DESI survey data, as well as the ability to constrain the imaging systematic weights in situ.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>early Universe</dc:subject><dc:subject>inflation</dc:subject><dc:subject>large-scale structure of Universe</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9v10m4rv</dc:identifier><dc:identifier>https://escholarship.org/content/qt9v10m4rv/qt9v10m4rv.pdf</dc:identifier><dc:identifier>info:doi/10.1093/mnras/staf1411</dc:identifier><dc:type>article</dc:type><dc:source>Monthly Notices of the Royal Astronomical Society, vol 543, iss 3</dc:source><dc:coverage>2078 - 2092</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5hn839qm</identifier><datestamp>2026-09-16T05:47:00Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5hn839qm</dc:identifier><dc:title>Silicon wafer fracture stress for tracking sensors in particle physics experiments</dc:title><dc:creator>Abidi, Haider</dc:creator><dc:creator>Fadeyev, Vitaliy</dc:creator><dc:creator>Jones, Tim</dc:creator><dc:creator>Kumar, Akhil</dc:creator><dc:creator>Lee, Tom</dc:creator><dc:creator>Poley, Luise</dc:creator><dc:creator>Sawyer, Craig</dc:creator><dc:creator>Vallone, Giorgio</dc:creator><dc:creator>Wonsak, Sven</dc:creator><dc:date>2025-10-01</dc:date><dc:description>For the construction of the ATLAS Inner Tracker strip detector, silicon strip sensor modules are glued directly onto carbon fibre support structures using a soft silicone gel. During tests at temperatures below -35°C, several of the sensors were found to crack due to a mismatch in coefficients of thermal expansion between polyimide circuit boards with copper metal layers (glued onto the sensor) and the silicon sensor itself. While module assembly procedures were developed to minimise variations between modules, cold tests showed a wide range of temperatures at which supposedly comparable modules failed. The observed variance (fracture temperatures between -35°C and -70°C) for supposedly comparable modules suggests an undetected variation between modules suspected to be intrinsic to the silicon wafer itself. Therefore, a test programme was developed to investigate the fracture stress of representative sensor wafer cutoffs. This paper presents results for the fracture stress of silicon sensors used in detector modules.</dc:description><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>4016 Materials Engineering (for-2020)</dc:subject><dc:subject>4009 Electronics</dc:subject><dc:subject>Sensors and Digital Hardware (for-2020)</dc:subject><dc:subject>Materials for solid-state detectors</dc:subject><dc:subject>Detector design and construction technologies and materials</dc:subject><dc:subject>Si microstrip and pad detectors</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5hn839qm</dc:identifier><dc:identifier>https://escholarship.org/content/qt5hn839qm/qt5hn839qm.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1748-0221/20/10/p10020</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Instrumentation, vol 20, iss 10</dc:source><dc:coverage>p10020</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt67q6j3gf</identifier><datestamp>2026-09-16T05:46:47Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt67q6j3gf</dc:identifier><dc:title>Cosmological implications of DESI DR2 BAO measurements in light of the latest ACT DR6 CMB data</dc:title><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Noriega, HE</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Lodha, K</dc:creator><dc:creator>Chebat, D</dc:creator><dc:creator>Rohlf, J</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Elbers, W</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Calderon, R</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Carrilho, P</dc:creator><dc:creator>Castander, FJ</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>de Belsunce, R</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Deiosso, N</dc:creator><dc:creator>Della Costa, J</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Lamman, C</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Leauthaud, A</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Li, Q</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Matthewson, WL</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Mena-Fernández, J</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Paillas, E</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Pan, J</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Rashkovetskyi, M</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Shafieloo, A</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Taylor, P</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Walther, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yèche, C</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Zhai, Z</dc:creator><dc:creator>Zhao, C</dc:creator><dc:creator>Zhou, R</dc:creator><dc:date>2025-10-15</dc:date><dc:description>We report cosmological results from the Dark Energy Spectroscopic Instrument (DESI) measurements of baryon acoustic oscillations (BAO) when combined with recent data from the Atacama Cosmology Telescope (ACT). By jointly analyzing ACT and data and applying conservative cuts to overlapping multipole ranges, we assess how different  dataset combinations affect consistency with DESI. While ACT alone exhibits a tension with DESI exceeding  within the  model, this discrepancy is reduced when ACT is analyzed in combination with . For our baseline DESI DR2   likelihood combination, the preference for evolving dark energy over a cosmological constant is about  , increasing to over  with the inclusion of type Ia supernova data. While the dark energy results remain quite consistent across various combinations of and ACT likelihoods with those obtained by the DESI collaboration, the constraints on neutrino mass are more sensitive, ranging from  in our baseline analysis, to  (95%&amp;nbsp;confidence level) in the CMB likelihood combination chosen by ACT when imposing the physical prior  .</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>4902 Mathematical Physics (for-2020)</dc:subject><dc:subject>49 Mathematical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/67q6j3gf</dc:identifier><dc:identifier>https://escholarship.org/content/qt67q6j3gf/qt67q6j3gf.pdf</dc:identifier><dc:identifier>info:doi/10.1103/d6yc-xpqb</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 112, iss 8</dc:source><dc:coverage>083529</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3142s836</identifier><datestamp>2026-09-16T05:43:40Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3142s836</dc:identifier><dc:title>The National Microbiome Data Collaborative Data Portal: an integrated multi-omics microbiome data resource</dc:title><dc:creator>Eloe-Fadrosh, Emiley A</dc:creator><dc:creator>Ahmed, Faiza</dc:creator><dc:creator>Anubhav</dc:creator><dc:creator>Babinski, Michal</dc:creator><dc:creator>Baumes, Jeffrey</dc:creator><dc:creator>Borkum, Mark</dc:creator><dc:creator>Bramer, Lisa</dc:creator><dc:creator>Canon, Shane</dc:creator><dc:creator>Christianson, Danielle S</dc:creator><dc:creator>Corilo, Yuri E</dc:creator><dc:creator>Davenport, Karen W</dc:creator><dc:creator>Davis, Brandon</dc:creator><dc:creator>Drake, Meghan</dc:creator><dc:creator>Duncan, William D</dc:creator><dc:creator>Flynn, Mark C</dc:creator><dc:creator>Hays, David</dc:creator><dc:creator>Hu, Bin</dc:creator><dc:creator>Huntemann, Marcel</dc:creator><dc:creator>Kelliher, Julia</dc:creator><dc:creator>Lebedeva, Sofya</dc:creator><dc:creator>Li, Po-E</dc:creator><dc:creator>Lipton, Mary</dc:creator><dc:creator>Lo, Chien-Chi</dc:creator><dc:creator>Martin, Stanton</dc:creator><dc:creator>Millard, David</dc:creator><dc:creator>Miller, Kayd</dc:creator><dc:creator>Miller, Mark A</dc:creator><dc:creator>Piehowski, Paul</dc:creator><dc:creator>Jackson, Elais Player</dc:creator><dc:creator>Purvine, Samuel</dc:creator><dc:creator>Reddy, TBK</dc:creator><dc:creator>Richardson, Rachel</dc:creator><dc:creator>Rudolph, Marisa</dc:creator><dc:creator>Sarrafan, Setareh</dc:creator><dc:creator>Shakya, Migun</dc:creator><dc:creator>Smith, Montana</dc:creator><dc:creator>Stratton, Kelly</dc:creator><dc:creator>Sundaramurthi, Jagadish Chandrabose</dc:creator><dc:creator>Vangay, Pajau</dc:creator><dc:creator>Winston, Donald</dc:creator><dc:creator>Wood-Charlson, Elisha M</dc:creator><dc:creator>Xu, Yan</dc:creator><dc:creator>Chain, Patrick SG</dc:creator><dc:creator>McCue, Lee Ann</dc:creator><dc:creator>Mans, Douglas</dc:creator><dc:creator>Mungall, Christopher J</dc:creator><dc:creator>Mouncey, Nigel J</dc:creator><dc:creator>Fagnan, Kjiersten</dc:creator><dc:date>2022-01-07</dc:date><dc:description>The National Microbiome Data Collaborative (NMDC) Data Portal (https://data.microbiomedata.org) supports microbiome multi-omics data exploration and access through an integrated, distributed data framework aligned with the FAIR (Findable, Accessible, Interoperable and Reusable) data principles (1). The NMDC Data Portal currently hosts 10.2 terabytes of multi-omics microbiome data, spanning five data types (metagenomes, metatranscriptomes, metaproteomes, metabolomes, and natural organic matter characterizations), generated at two Department of Energy User Facilities, the Joint Genome Institute (JGI) at Lawrence Berkeley National Laboratory (LBNL) and the Environmental Molecular Systems Laboratory (EMSL) at Pacific Northwest National Laboratory (PNNL). A flexible data schema (https://github.com/microbiomedata/nmdc-schema) leveraging community-driven standards underpins how data is managed and integrated. Annotated multi-omic data products are produced by the NMDC workflows and linked through common biosamples to enable search capabilities based on environmental context, instrumentation, and functional attributes. As a pilot system, the NMDC Data Portal offers download capabilities and several search components, including interactive geographic visualization of samples; environmental classification distribution visualized through an interactive Sankey diagram; time-series slider to select longitudinal samples of interest; and an upset plot displaying the number of multi-omics data generated from the same biosample within a study.</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Microbiome (rcdc)</dc:subject><dc:subject>Data Science (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>05 Environmental Sciences (for)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>08 Information and Computing Sciences (for)</dc:subject><dc:subject>Developmental Biology (science-metrix)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>34 Chemical sciences (for-2020)</dc:subject><dc:subject>41 Environmental sciences (for-2020)</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3142s836</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1093/nar/gkab990</dc:identifier><dc:type>article</dc:type><dc:source>Nucleic Acids Research, vol 50, iss D1</dc:source><dc:coverage>d828 - d836</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt07d6532s</identifier><datestamp>2026-09-16T05:43:17Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt07d6532s</dc:identifier><dc:title>Construction of the damped Lyα absorber catalog for DESI DR2 Lyα BAO</dc:title><dc:creator>Brodzeller, A</dc:creator><dc:creator>Wolfson, M</dc:creator><dc:creator>Santos, DM</dc:creator><dc:creator>Ho, M</dc:creator><dc:creator>Tan, T</dc:creator><dc:creator>Pieri, MM</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Abdul-Karim, M</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Anand, A</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Bault, A</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Casas, L</dc:creator><dc:creator>Charles, M</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Chebat, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Dawson, KS</dc:creator><dc:creator>de Belsunce, R</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Doshi, M</dc:creator><dc:creator>Elbers, W</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Garrison, LH</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gonzalez-Morales, AX</dc:creator><dc:creator>Green, D</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Herbold, M</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Lamman, C</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Goff, JM</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Leauthaud, A</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Li, Q</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Mena-Fernández, J</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Napolitano, L</dc:creator><dc:creator>Noriega, HE</dc:creator><dc:creator>Paillas, E</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Ramírez-Pérez, C</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Rohlf, J</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Sinigaglia, F</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Taylor, P</dc:creator><dc:creator>Turner, W</dc:creator><dc:creator>Walther, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yèche, C</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:creator>Zou, S</dc:creator><dc:date>2025-10-15</dc:date><dc:description>We present the Damped  Toolkit for automated detection and characterization of damped  absorbers (DLAs) in quasar spectra. Our method uses quasar spectral templates with and without absorption from intervening DLAs to reconstruct observed quasar forest regions. The best-fitting model determines whether a DLA is present while estimating the redshift and column density. With an optimized quality cut on detection significance (  ), the technique achieves an estimated 80% purity and 79% completeness when evaluated on simulated spectra with  that are free of broad absorption lines (BALs). We provide a catalog containing candidate DLAs from the DLA Toolkit detected in DESI DR1 quasar spectra, of which 21 719 were found in  spectra with predicted  and detection significance  . We compare the Damped  Toolkit to two alternative DLA finders based on a convolutional neural network and Gaussian process models. We present a strategy for combining these three techniques to produce a high-fidelity DLA catalog from DESI DR2 for the  forest baryon acoustic oscillation measurement. The combined catalog contains 41 152 candidate DLAs with  from quasar spectra with  . We estimate this sample to be approximately 85% pure and 79% complete when BAL quasars are excluded.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>4902 Mathematical Physics (for-2020)</dc:subject><dc:subject>49 Mathematical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/07d6532s</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1103/wxyv-46kb</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 112, iss 8</dc:source><dc:coverage>083510</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3655d6bp</identifier><datestamp>2026-09-16T05:43:10Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3655d6bp</dc:identifier><dc:title>DESI DR1 Lyα 1D power spectrum: the optimal estimator measurement</dc:title><dc:creator>Karaçaylı, Naim Göksel</dc:creator><dc:creator>Martini, Paul</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Bault, A</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Goff, JM</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Montero-Camacho, P</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Pan, Z</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Pieri, Matthew M</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Saulder, C</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Siudek, M</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tan, T</dc:creator><dc:creator>Tang, Ji-Jia</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Walther, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yu, J</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-10-01</dc:date><dc:description>The one-dimensional power spectrum P 1D of Lyα forest offers rich insights into cosmological and astrophysical parameters, including constraints on the sum of neutrino masses, warm dark matter models, and the thermal state of the intergalactic medium. We present the measurement of P 1D using the optimal quadratic maximum likelihood estimator applied to over 300,000 Lyα quasars from Data Release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI) survey. This sample represents the largest to date for P 1D measurements and is larger than the Extended Baryon Oscillation Spectroscopic Survey (eBOSS) by a factor of 1.7. We conduct a meticulous investigation of instrumental and analysis systematics and quantify their impact on P 1D. This includes the development of a cross-exposure estimator that eliminates the need to model the pipeline noise and has strong potential for future P 1D measurements. We also present new insights into metal contamination through the 1D correlation function. Using a fitting function we measure the evolution of the Lyα forest bias with high precision: bF (z) = (-0.218 ± 0.002) × ((1 + z)/4)2.96±0.06. In a companion validation paper, we substantially extend our previous suite of CCD image simulations to quantify the pipeline's exquisite performance accurately. In another companion paper, we present DR1 P 1D measurements using the Fast Fourier Transform (FFT) approach to power spectrum estimation. These two measurements produce a forest bias parameter that differs by 2.2 sigma. However, our model is simplistic, so this disagreement will be investigated in future work.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3655d6bp</dc:identifier><dc:identifier>https://escholarship.org/content/qt3655d6bp/qt3655d6bp.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/10/004</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 10</dc:source><dc:coverage>004</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt46b0d4cc</identifier><datestamp>2026-09-16T05:43:04Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt46b0d4cc</dc:identifier><dc:title>Validation of the DESI DR2 measurements of baryon acoustic oscillations from galaxies and quasars</dc:title><dc:creator>Andrade, U</dc:creator><dc:creator>Paillas, E</dc:creator><dc:creator>Mena-Fernández, J</dc:creator><dc:creator>Li, Q</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Rashkovetskyi, M</dc:creator><dc:creator>Pérez-Fernández, A</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sanders, N</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Deiosso, N</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>White, M</dc:creator><dc:creator>Karim, M Abdul</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Bansal, P</dc:creator><dc:creator>Behera, J</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Calderon, R</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Casas, L</dc:creator><dc:creator>Castander, FJ</dc:creator><dc:creator>Charles, M</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Cooper, AP</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Dawson, KS</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Della Costa, J</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Eisenstein, DJ</dc:creator><dc:creator>Elbers, W</dc:creator><dc:creator>Fernández-García, E</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Garrison, LH</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gonzalez-Morales, AX</dc:creator><dc:creator>Gordon, C</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>He, S</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Lamman, C</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Leauthaud, A</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Magneville, C</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Matthewson, WL</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Muñoz-Santos, D</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Napolitano, L</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Noriega, HE</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Pan, J</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Raichoor, A</dc:creator><dc:creator>Ramírez-Pérez, C</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:date>2025-10-15</dc:date><dc:description>The Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) galaxy and quasar clustering data represents a significant expansion of data from Data Release 1 (DR1), providing improved statistical precision in baryon acoustic oscillation (BAO) constraints across multiple tracers, including bright galaxies, luminous red galaxies, emission line galaxies, and quasars. In this paper, we validate the BAO analysis of DR2. We present the results of robustness tests on the blinded DR2 data and, after unblinding, consistency checks on the unblinded DR2 data. All results are compared with those obtained from a suite of mock catalogs that replicate the selection and clustering properties of the DR2 sample. We confirm the consistency of DR2 BAO measurements with DR1 while achieving a reduction in statistical uncertainties due to the increased survey volume and completeness. The combined BAO precision, including both statistical and systematic errors, improves from  in DR1 to 0.30% in DR2—a factor of 1.7 gain. We assess the impact of analysis choices, including different data vectors (correlation function vs power spectrum), modeling approaches and systematics treatments, and an assumption of the Gaussian likelihood, finding that our BAO constraints are stable across these variations and assumptions with a few minor refinements to the baseline setup of the DR1 BAO analysis. We summarize a series of pre-unblinding tests that confirmed the readiness of our analysis pipeline, the final systematic errors, and the DR2 BAO analysis baseline. The successful completion of these tests led to the unblinding of the DR2 BAO measurements, ultimately leading to the DESI DR2 cosmological analysis, with their implications for the expansion history of the Universe and the nature of dark energy presented in the DESI key paper (companion paper).</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/46b0d4cc</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1103/kdys-w8vl</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 112, iss 8</dc:source><dc:coverage>083512</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8vw655q0</identifier><datestamp>2026-09-16T05:42:51Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8vw655q0</dc:identifier><dc:title>Idiomatic Correctness-Checking via Julienne in Fortran 2023</dc:title><dc:creator>Rouson, Damian</dc:creator><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Rasmussen, Katherine</dc:creator><dc:date>2025-10-03</dc:date><dc:description>This paper presents a unified approach to unit testing and runtime assertion checking using Fortran 2023.  The paper describes the support for our approach in the Julienne framework.  Julienne leverages recent Fortran standards to implement object-oriented design patterns, support testing parallel programs, and implement functional programming patterns in order to craft idioms inspired by natural-language expressions. The presented idioms employ novel operators to write expressions that evaluate to a test-diagnosis object encapsulating two components: (1) the test outcome or assertion outcome and (2) an automatically generated diagnostic string.  Two other novel aspects of the approach include (1) the ability to enforce assertions inside pure procedures and (2) the ability to output rich diagnostic information inside pure procedures during error termination when assertions fail.  The latter capability mitigates against a reason that Fortran programmers commonly cite for not writing pure procedures: difficulty obtaining useful program output inside pure procedures when debugging code.  This paper demonstrates how the adoption of the proposed idioms leads naturally to a unifying theme across two otherwise disparate technologies: unit testing and runtime assertion checking.  Finally, this paper describes the usage of the Julienne testing framework for writing unit tests and assertions in the Matcha high-performance computing application and the Fiats deep learning library.</dc:description><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8vw655q0</dc:identifier><dc:identifier>https://escholarship.org/content/qt8vw655q0/qt8vw655q0.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S4BG65</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0569n02q</identifier><datestamp>2026-09-16T05:39:12Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0569n02q</dc:identifier><dc:title>Noise limits for dc SQUID readout of high-Q resonators below 300 MHz</dc:title><dc:creator>Ankel, V</dc:creator><dc:creator>Bartram, C</dc:creator><dc:creator>Begin, J</dc:creator><dc:creator>Bell, C</dc:creator><dc:creator>Brouwer, L</dc:creator><dc:creator>Chaudhuri, S</dc:creator><dc:creator>Clarke, John</dc:creator><dc:creator>Cho, H-M</dc:creator><dc:creator>Corbin, J</dc:creator><dc:creator>Craddock, W</dc:creator><dc:creator>Cuadra, S</dc:creator><dc:creator>Droster, A</dc:creator><dc:creator>Durkin, M</dc:creator><dc:creator>Echevers, J</dc:creator><dc:creator>Fry, JT</dc:creator><dc:creator>Hilton, G</dc:creator><dc:creator>Irwin, KD</dc:creator><dc:creator>Keller, A</dc:creator><dc:creator>Kolevatov, R</dc:creator><dc:creator>Kunder, A</dc:creator><dc:creator>Li, D</dc:creator><dc:creator>Otto, N</dc:creator><dc:creator>Pappas, KMW</dc:creator><dc:creator>Rapidis, NM</dc:creator><dc:creator>Salemi, CP</dc:creator><dc:creator>Schmidt, D</dc:creator><dc:creator>Simanovskaia, M</dc:creator><dc:creator>Singh, J</dc:creator><dc:creator>Stark, P</dc:creator><dc:creator>Tesche, CD</dc:creator><dc:creator>Ullom, J</dc:creator><dc:creator>Vale, L</dc:creator><dc:creator>van Assendelft, EC</dc:creator><dc:creator>van Bibber, K</dc:creator><dc:creator>Vissers, M</dc:creator><dc:creator>Wells, K</dc:creator><dc:creator>Wiedemann, J</dc:creator><dc:creator>Winslow, L</dc:creator><dc:creator>Wright, D</dc:creator><dc:creator>Yi, AK</dc:creator><dc:creator>Young, BA</dc:creator><dc:date>2025-09-07</dc:date><dc:description>We present the limits on noise for the readout of cryogenic high-Q resonators using dc Superconducting Quantum Interference Devices (SQUIDs) below 300 MHz. This analysis uses realized first-stage SQUIDs (previously published), whose performance is well described by Tesche–Clarke (TC) theory, coupled directly to the resonators. We also present data from a prototype second-stage dc SQUID array designed to couple to this first-stage SQUID as a follow-on amplifier with high system bandwidth. This analysis is the first full consideration of dc SQUID noise performance referred to a high-Q resonator over this frequency range and is presented relative to the standard quantum limit. We include imprecision, backaction, and backaction–imprecision noise correlations from TC theory, the noise contributed by the second-stage SQUIDs, wiring, and preamplifiers, and optimizations for both on-resonance measurements and off-resonance scan sensitivity. This architecture has modern relevance due to the increased interest in axion searches and the requirements of the DMRadio-m3 axion search, which uses dc SQUIDs in this frequency range.</dc:description><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>5104 Condensed Matter Physics (for-2020)</dc:subject><dc:subject>ATAP-GENERAL (c-lbnl-label)</dc:subject><dc:subject>ATAP-2025 (c-lbnl-label)</dc:subject><dc:subject>ATAP-SMP (c-lbnl-label)</dc:subject><dc:subject>01 Mathematical Sciences (for)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Applied Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0569n02q</dc:identifier><dc:identifier>https://escholarship.org/content/qt0569n02q/qt0569n02q.pdf</dc:identifier><dc:identifier>info:doi/10.1063/5.0280831</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Applied Physics, vol 138, iss 9</dc:source><dc:coverage>094505</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0034c8tp</identifier><datestamp>2026-09-16T05:38:32Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0034c8tp</dc:identifier><dc:title>Synthetic Accessibility and Sodium Ion Conductivity of the Na8–x A x P2O9 (NAP) High-Temperature Sodium Superionic Conductor Framework</dc:title><dc:creator>Walters, Lauren N</dc:creator><dc:creator>Fei, Yuxing</dc:creator><dc:creator>Rendy, Bernardus</dc:creator><dc:creator>Yang, Xiaochen</dc:creator><dc:creator>Diallo, Mouhamad</dc:creator><dc:creator>Jun, KyuJung</dc:creator><dc:creator>Wei, Grace</dc:creator><dc:creator>McDermott, Matthew J</dc:creator><dc:creator>Giunto, Andrea</dc:creator><dc:creator>Mishra, Tara</dc:creator><dc:creator>Shen, Fengyu</dc:creator><dc:creator>Milsted, David</dc:creator><dc:creator>Oo, May Sabai</dc:creator><dc:creator>Kim, Haegyeom</dc:creator><dc:creator>Tucker, Michael C</dc:creator><dc:creator>Ceder, Gerbrand</dc:creator><dc:date>2025-09-09</dc:date><dc:description>Advancement of solid-state electrolytes (SSEs) for all solid-state batteries typically focuses on modification of a known structural framework to improve conductivity, e.g., cation substitution for an immobile ion or varying the concentration of the mobile ions. Novel frameworks can be disruptive by enabling fast ion conduction aided by different structure and diffusion mechanisms, thereby unlocking optimal conductors with different properties. Herein, we perform a high-throughput survey of a structural framework for sodium ion conduction, Na8–x A x P2O9 (NAP), to understand the family’s thermodynamic stability, synthesizability, and ionic conduction. We show that the parent phase Na4TiP2O9 (NTP) undergoes a structural distortion (with accompanying conductivity transition) due to unstable phonons arising from pseudo-Jahn–Teller mode in the 1D titanium chains. Screening compounds in which Ti is substituted by other metals computationally reveal a number of candidates that are predicted to be low in formation energy and have high predicted ionic conductivities. High-throughput experimental and subsequent methodology optimization trials deliver one new compound, Na4SnP2O9 (NSP). X-ray diffraction (XRD), microscopy, and spectroscopy characterization indicate that the room-temperature structure of NSP is similar to the high-temperature, orthorhombic NTP phase but with some small unresolved structural differences. These uncharacterized structural details are speculated to limit the ion conductivity. Temperature-dependent XRD and electrochemical impedance spectroscopy indicate multiple coupled conductivity–structure transitions at a high temperature. We demonstrate the challenges with synthesis development and a priori identification of promising SSE phases as a major bottleneck in new (energy) materials development.</dc:description><dc:subject>3402 Inorganic Chemistry (for-2020)</dc:subject><dc:subject>34 Chemical Sciences (for-2020)</dc:subject><dc:subject>3406 Physical Chemistry (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>03 Chemical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Materials (science-metrix)</dc:subject><dc:subject>34 Chemical sciences (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0034c8tp</dc:identifier><dc:identifier>https://escholarship.org/content/qt0034c8tp/qt0034c8tp.pdf</dc:identifier><dc:identifier>info:doi/10.1021/acs.chemmater.5c01573</dc:identifier><dc:type>article</dc:type><dc:source>Chemistry of Materials, vol 37, iss 17</dc:source><dc:coverage>6807 - 6822</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2mc5x08w</identifier><datestamp>2026-09-16T05:38:19Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2mc5x08w</dc:identifier><dc:title>Observed declines in leaf nitrogen explained by photosynthetic acclimation to CO2</dc:title><dc:creator>Bassiouni, Maoya</dc:creator><dc:creator>Smith, Nicholas G</dc:creator><dc:creator>Reu, Jacqueline C</dc:creator><dc:creator>Peñuelas, Josep</dc:creator><dc:creator>Keenan, Trevor F</dc:creator><dc:date>2025-08-19</dc:date><dc:description>Widespread evidence of decreasing leaf nutrients has raised concerns about ecosystem productivity under global change. Interpreting trends in leaf nutrients has important implications for the fate of ecosystem services, particularly the role of forests in mitigating climate change and sustaining quality food sources. Here, we challenge the common interpretation that decreasing leaf nitrogen concentration (LNC) is evidence of increasing nutrient limitations on ecosystem primary productivity. Instead, we show that declines in LNC (4% decrease per 50 ppm CO2 increase), observed across 409 European forest plots over 22 y, can be explained by reduced photosynthetic nitrogen demand. This regional trend is consistent with leaf acclimation to increasing atmospheric CO2 according to optimality theory. This finding suggests that enhanced photosynthetic nitrogen use efficiency due to CO2 fertilization may lead to less nitrogen uptake and/or reallocation of nitrogen for plant growth and other functions. Our results have large implications for understanding and simulating interactions between ecosystem nitrogen and carbon cycles and suggest nitrogen requirements for terrestrial carbon uptake under elevated CO2 may be lower than previously thought.</dc:description><dc:subject>3108 Plant Biology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>Nitrogen (mesh)</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Photosynthesis (mesh)</dc:subject><dc:subject>Acclimatization (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Forests (mesh)</dc:subject><dc:subject>climate change</dc:subject><dc:subject>ecoevolutionarytheory</dc:subject><dc:subject>photosynthesis</dc:subject><dc:subject>CO2fertilization</dc:subject><dc:subject>nutrient limitation</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>Nitrogen (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Acclimatization (mesh)</dc:subject><dc:subject>Photosynthesis (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>Forests (mesh)</dc:subject><dc:subject>CO2 fertilization</dc:subject><dc:subject>climate change</dc:subject><dc:subject>ecoevolutionary theory</dc:subject><dc:subject>nutrient limitation</dc:subject><dc:subject>photosynthesis</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>Nitrogen (mesh)</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Photosynthesis (mesh)</dc:subject><dc:subject>Acclimatization (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Forests (mesh)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2mc5x08w</dc:identifier><dc:identifier>https://escholarship.org/content/qt2mc5x08w/qt2mc5x08w.pdf</dc:identifier><dc:identifier>info:doi/10.1073/pnas.2501958122</dc:identifier><dc:type>article</dc:type><dc:source>Proceedings of the National Academy of Sciences of the United States of America, vol 122, iss 33</dc:source><dc:coverage>e2501958122</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8sr171mx</identifier><datestamp>2026-09-16T05:34:08Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8sr171mx</dc:identifier><dc:title>Synthetic Scientific Image Generation with VAE, GAN, and Diffusion Model Architectures</dc:title><dc:creator>Sordo, Zineb</dc:creator><dc:creator>Chagnon, Eric</dc:creator><dc:creator>Hu, Zixi</dc:creator><dc:creator>Donatelli, Jeffrey J</dc:creator><dc:creator>Andeer, Peter</dc:creator><dc:creator>Nico, Peter S</dc:creator><dc:creator>Northen, Trent</dc:creator><dc:creator>Ushizima, Daniela</dc:creator><dc:date>2025-07-26</dc:date><dc:description>Generative AI (genAI) has emerged as a powerful tool for synthesizing diverse and complex image data, offering new possibilities for scientific imaging applications. This review presents a comprehensive comparative analysis of leading generative architectures, ranging from Variational Autoencoders (VAEs) to Generative Adversarial Networks (GANs) on through to Diffusion Models, in the context of scientific image synthesis. We examine each model's foundational principles, recent architectural advancements, and practical trade-offs. Our evaluation, conducted on domain-specific datasets including microCT scans of rocks and composite fibers, as well as high-resolution images of plant roots, integrates both quantitative metrics (SSIM, LPIPS, FID, CLIPScore) and expert-driven qualitative assessments. Results show that GANs, particularly StyleGAN, produce images with high perceptual quality and structural coherence. Diffusion-based models for inpainting and image variation, such as DALL-E 2, delivered high realism and semantic alignment but generally struggled in balancing visual fidelity with scientific accuracy. Importantly, our findings reveal limitations of standard quantitative metrics in capturing scientific relevance, underscoring the need for domain-expert validation. We conclude by discussing key challenges such as model interpretability, computational cost, and verification protocols, and discuss future directions where generative AI can drive innovation in data augmentation, simulation, and hypothesis generation in scientific research.</dc:description><dc:subject>46 Information and Computing Sciences (for-2020)</dc:subject><dc:subject>4603 Computer Vision and Multimedia Computation (for-2020)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>Biomedical Imaging (rcdc)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>Networking and Information Technology R&amp;D (NITRD) (rcdc)</dc:subject><dc:subject>Generic health relevance (hrcs-hc)</dc:subject><dc:subject>image generation</dc:subject><dc:subject>generative AI</dc:subject><dc:subject>Generative Adversarial Networks</dc:subject><dc:subject>diffusion</dc:subject><dc:subject>synthetic data</dc:subject><dc:subject>Generative Adversarial Networks</dc:subject><dc:subject>diffusion</dc:subject><dc:subject>generative AI</dc:subject><dc:subject>image generation</dc:subject><dc:subject>synthetic data</dc:subject><dc:subject>4003 Biomedical engineering (for-2020)</dc:subject><dc:subject>4603 Computer vision and multimedia computation (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8sr171mx</dc:identifier><dc:identifier>https://escholarship.org/content/qt8sr171mx/qt8sr171mx.pdf</dc:identifier><dc:identifier>info:doi/10.3390/jimaging11080252</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Imaging, vol 11, iss 8</dc:source><dc:coverage>252</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt48n6r0zt</identifier><datestamp>2026-09-16T05:33:25Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt48n6r0zt</dc:identifier><dc:title>Requirements for US20 collective subroutines for prefix operations</dc:title><dc:creator>Cook, Brandon</dc:creator><dc:creator>Bonachea, Dan</dc:creator><dc:date>2025-06-23</dc:date><dc:description>This paper contains formal requirements for Fortran 202Y work item US-20, collective subroutines for prefix operations.
It passed by unanimous consent at the Jun 2025 meeting #236 of the INCITS/US Fortran Programming Language Standards Technical Committee.</dc:description><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:subject>incits-fortran</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/48n6r0zt</dc:identifier><dc:identifier/><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5p71z3p7</identifier><datestamp>2026-09-16T05:14:51Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5p71z3p7</dc:identifier><dc:title>Rethinking α-RuCl3: Parameters, models, and phase diagram</dc:title><dc:creator>Möller, Marius</dc:creator><dc:creator>Maksimov, PA</dc:creator><dc:creator>Jiang, Shengtao</dc:creator><dc:creator>蒋晟韬</dc:creator><dc:creator>White, Steven R</dc:creator><dc:creator>Valentí, Roser</dc:creator><dc:creator>Chernyshev, AL</dc:creator><dc:date>2025-09-01</dc:date><dc:description>RuCl3 was likely the first ever deliberately synthesized ruthenium compound, following the discovery of the Ru44 element in 1844. For a long time it was known as an oxidation catalyst, with its physical properties being discrepant and confusing, until a decade ago when its allotropic form α-RuCl3 rose to exceptional prominence. This “rediscovery” of α-RuCl3 has not only reshaped the hunt for a material manifestation of the Kitaev spin liquid, but it has opened the floodgates of theoretical and experimental research in the many unusual phases and excitations that the anisotropic-exchange magnets as a class of compounds have to offer. Given its importance for the field of Kitaev materials, it is astonishing that the low-energy spin model that describes this compound and its possible proximity to the much-desired spin-liquid state is still a subject of significant debate ten years later. In the present study, we argue that the existing key phenomenological observations put strong natural constraints on the effective microscopic spin model of α-RuCl3, and specifically on its spin-orbit-induced anisotropic-exchange parameters that are responsible for the nontrivial physical properties of this material. These constraints allow one to focus on the relevant region of the multidimensional phase diagram of the α-RuCl3 model, suggest an intuitive description of it via a different parametrization of the exchange matrix, offer a unifying view on the earlier assessments of its parameters, and bring closer together several approaches to the derivation of anisotropic-exchange models. We explore extended phase diagrams relevant to the α-RuCl3 parameter space using quasiclassical, Luttinger-Tisza, exact diagonalization, and density-matrix renormalization-group methods, demonstrating a remarkably close quantitative accord between them on the general structure and hierarchy of the phases, with the zigzag, ferromagnetic, and incommensurate phases that are proximate to each other. One of the highlights is the detailed agreement on the nature of the incommensurate phases that realize two distinct counterrotating helical states.</dc:description><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>34 Chemical Sciences (for-2020)</dc:subject><dc:subject>5103 Classical Physics (for-2020)</dc:subject><dc:subject>34 Chemical sciences (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5p71z3p7</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1103/hflp-41lj</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review B, vol 112, iss 10</dc:source><dc:coverage>104403</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1qx8n794</identifier><datestamp>2026-09-16T05:14:33Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1qx8n794</dc:identifier><dc:title>Constraints on primordial non-Gaussianity from the cross-correlation of DESI luminous red galaxies and Planck CMB lensing</dc:title><dc:creator>Bermejo-Climent, JR</dc:creator><dc:creator>Demina, R</dc:creator><dc:creator>Krolewski, A</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Farren, G</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Rabinowitz, D</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>White, M</dc:creator><dc:creator>Yèche, C</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:date>2025-06-01</dc:date><dc:description>Aims. We use the angular cross-correlation between a luminous red galaxy (LRG) sample from the Dark Energy Spectroscopic Instrument (DESI) Legacy Survey data release DR9 and the Planck cosmic microwave background (CMB) lensing maps to constrain the local primordial non-Gaussianity parameter, f NL , using the scale-dependent galaxy bias effect. The galaxy sample covers approximately 40% of the sky, contains galaxies up to redshift z ∼ 1.4, and is calibrated with the LRG spectra that have been observed for DESI Year 1 (Y1).   Methods. We apply a nonlinear imaging systematics treatment based on neural networks to remove observational effects that could potentially bias the f NL measurement. Our measurement is performed without blinding, but the full analysis pipeline is tested with simulations including systematics.   Results. Using the two-point angular cross-correlation between LRG and CMB lensing only, we find f NL = 39 −38 +40 at the 68% confidence level, and our result is robust in terms of systematics and cosmological assumptions. If we combine this information with the autocorrelation of LRG, applying a scale cut to limit the impact of systematics, we find f NL = 24 −21 +20 at the 68% confidence level. Our results motivate the use of CMB lensing cross-correlations to measure f NL with future datasets, given its stability in terms of observational systematics compared to the angular autocorrelation. Furthermore, performing accurate systematics mitigation is crucially important in order to achieve competitive constraints on f NL from CMB lensing cross-correlation in combination with the tracers’ autocorrelation.</dc:description><dc:subject>5109 Space Sciences (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>cosmic background radiation</dc:subject><dc:subject>cosmology: observations</dc:subject><dc:subject>early Universe</dc:subject><dc:subject>large-scale structure of Universe</dc:subject><dc:subject>inflation</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1qx8n794</dc:identifier><dc:identifier>https://escholarship.org/content/qt1qx8n794/qt1qx8n794.pdf</dc:identifier><dc:identifier>info:doi/10.1051/0004-6361/202453446</dc:identifier><dc:type>article</dc:type><dc:source>Astronomy &amp; Astrophysics, vol 698</dc:source><dc:coverage>a177</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9fh0c1z8</identifier><datestamp>2026-09-16T05:14:20Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9fh0c1z8</dc:identifier><dc:title>Nonconservation of Lepton Numbers in the Neutrino Sector Could Change the Prospects for Core Collapse Supernova Explosions</dc:title><dc:creator>Suliga, Anna M</dc:creator><dc:creator>Cheong, Patrick Chi-Kit</dc:creator><dc:creator>張志杰</dc:creator><dc:creator>Froustey, Julien</dc:creator><dc:creator>Fuller, George M</dc:creator><dc:creator>Gráf, Lukáš</dc:creator><dc:creator>Kehrer, Kyle</dc:creator><dc:creator>Scholer, Oliver</dc:creator><dc:creator>Shalgar, Shashank</dc:creator><dc:date>2025-06-20</dc:date><dc:description>We show that interactions violating the conservation of lepton numbers in the neutrino sector could significantly alter the standard low entropy picture for the presupernova collapsing core of a massive star. A rapid neutrino-antineutrino equilibration leads to entropy generation and enhanced electron capture and, hence, a lower electron fraction than in the standard model. This would affect the downstream core evolution, the prospects for a supernova explosion, and the emergent neutrino signal. If realized by lepton-number-violating neutrino self-interactions (LNV νSI), the relevant mediator mass and coupling ranges can be probed by future accelerator-based experiments.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>01 Mathematical Sciences (for)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9fh0c1z8</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1103/gnp5-4y8k</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review Letters, vol 134, iss 24</dc:source><dc:coverage>241002</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt68r3w98f</identifier><datestamp>2026-09-16T05:10:33Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt68r3w98f</dc:identifier><dc:title>Long-Range Transverse-Momentum Correlations and Radial Flow in Pb-Pb Collisions at the LHC</dc:title><dc:creator>Acharya, S</dc:creator><dc:creator>Rinella, G Aglieri</dc:creator><dc:creator>Aglietta, L</dc:creator><dc:creator>Agnello, M</dc:creator><dc:creator>Agrawal, N</dc:creator><dc:creator>Ahammed, Z</dc:creator><dc:creator>Ahmad, S</dc:creator><dc:creator>Ahn, SU</dc:creator><dc:creator>Ahuja, I</dc:creator><dc:creator>Akbar, Z</dc:creator><dc:creator>Akindinov, A</dc:creator><dc:creator>Akishina, V</dc:creator><dc:creator>Al-Turany, M</dc:creator><dc:creator>Aleksandrov, D</dc:creator><dc:creator>Alessandro, B</dc:creator><dc:creator>Alfanda, HM</dc:creator><dc:creator>Molina, R Alfaro</dc:creator><dc:creator>Ali, B</dc:creator><dc:creator>Alici, A</dc:creator><dc:creator>Alizadehvandchali, N</dc:creator><dc:creator>Alkin, A</dc:creator><dc:creator>Alme, J</dc:creator><dc:creator>Alocco, G</dc:creator><dc:creator>Alt, T</dc:creator><dc:creator>Altamura, AR</dc:creator><dc:creator>Altsybeev, I</dc:creator><dc:creator>Anaam, MN</dc:creator><dc:creator>Andrei, C</dc:creator><dc:creator>Andreou, N</dc:creator><dc:creator>Andronic, A</dc:creator><dc:creator>Andronov, E</dc:creator><dc:creator>Anguelov, V</dc:creator><dc:creator>Antinori, F</dc:creator><dc:creator>Antonioli, P</dc:creator><dc:creator>Apadula, N</dc:creator><dc:creator>Appelshäuser, H</dc:creator><dc:creator>Arata, C</dc:creator><dc:creator>Arcelli, S</dc:creator><dc:creator>Arnaldi, R</dc:creator><dc:creator>Arneiro, JGMCA</dc:creator><dc:creator>Arsene, IC</dc:creator><dc:creator>Arslandok, M</dc:creator><dc:creator>Augustinus, A</dc:creator><dc:creator>Averbeck, R</dc:creator><dc:creator>Averyanov, D</dc:creator><dc:creator>Azmi, MD</dc:creator><dc:creator>Baba, H</dc:creator><dc:creator>Badalà, A</dc:creator><dc:creator>Bae, J</dc:creator><dc:creator>Bae, Y</dc:creator><dc:creator>Baek, YW</dc:creator><dc:creator>Bai, X</dc:creator><dc:creator>Bailhache, R</dc:creator><dc:creator>Bailung, Y</dc:creator><dc:creator>Bala, R</dc:creator><dc:creator>Baldisseri, A</dc:creator><dc:creator>Balis, B</dc:creator><dc:creator>Bangalia, S</dc:creator><dc:creator>Banoo, Z</dc:creator><dc:creator>Barbasova, V</dc:creator><dc:creator>Barile, F</dc:creator><dc:creator>Barioglio, L</dc:creator><dc:creator>Barlou, M</dc:creator><dc:creator>Barman, B</dc:creator><dc:creator>Barnaföldi, GG</dc:creator><dc:creator>Barnby, LS</dc:creator><dc:creator>Barreau, E</dc:creator><dc:creator>Barret, V</dc:creator><dc:creator>Barreto, L</dc:creator><dc:creator>Barth, K</dc:creator><dc:creator>Bartsch, E</dc:creator><dc:creator>Bastid, N</dc:creator><dc:creator>Basu, S</dc:creator><dc:creator>Batigne, G</dc:creator><dc:creator>Battistini, D</dc:creator><dc:creator>Batyunya, B</dc:creator><dc:creator>Bauri, D</dc:creator><dc:creator>Alba, JL Bazo</dc:creator><dc:creator>Bearden, IG</dc:creator><dc:creator>Becht, P</dc:creator><dc:creator>Behera, D</dc:creator><dc:creator>Belikov, I</dc:creator><dc:creator>Hechavarria, ADC Bell</dc:creator><dc:creator>Bellini, F</dc:creator><dc:creator>Bellwied, R</dc:creator><dc:creator>Belokurova, S</dc:creator><dc:creator>Beltran, LGE</dc:creator><dc:creator>Beltran, YAV</dc:creator><dc:creator>Bencedi, G</dc:creator><dc:creator>Bensaoula, A</dc:creator><dc:creator>Beole, S</dc:creator><dc:creator>Berdnikov, Y</dc:creator><dc:creator>Berdnikova, A</dc:creator><dc:creator>Bergmann, L</dc:creator><dc:creator>Bernardinis, L</dc:creator><dc:creator>Betev, L</dc:creator><dc:creator>Bhaduri, PP</dc:creator><dc:creator>Bhalla, T</dc:creator><dc:creator>Bhasin, A</dc:creator><dc:creator>Bhattacharjee, B</dc:creator><dc:date>2026-01-23</dc:date><dc:description>This Letter presents measurements of long-range transverse-momentum correlations using a new observable, v_{0}(p_{T}), serving as a probe of event-by-event radial-flow fluctuations, the underlying radial expansion, and the medium's properties in heavy-ion collisions. Results are reported for inclusive charged particles, pions, kaons, and protons across various centrality intervals in Pb-Pb collisions at sqrt[s_{NN}]=5.02  TeV, recorded by the ALICE detector. A pseudorapidity-gap technique, similar to that used in anisotropic-flow studies, is employed to suppress short-range correlations. At low p_{T}, a characteristic mass ordering consistent with hydrodynamic collective flow is observed. At higher p_{T} (&amp;gt;3  GeV/c), protons exhibit larger v_{0}(p_{T}) than pions and kaons, in agreement with expectations from quark-recombination models. Comparisons to viscous hydrodynamic calculations with varying bulk viscosity and equation of state demonstrate the sensitivity of the v_{0}(p_{T}) observable to these key medium properties. The findings establish v_{0}(p_{T}) as a valuable addition to the set of observables used in Bayesian analyses for extracting the transport properties and constraining the equation of state of strongly interacting matter, while also helping to systematically explore its sensitivity and impact within such global studies.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>ALICE Collaboration</dc:subject><dc:subject>01 Mathematical Sciences (for)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/68r3w98f</dc:identifier><dc:identifier>https://escholarship.org/content/qt68r3w98f/qt68r3w98f.pdf</dc:identifier><dc:identifier>info:doi/10.1103/l36g-6f46</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review Letters, vol 136, iss 3</dc:source><dc:coverage>032302</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9ng999qt</identifier><datestamp>2026-09-16T05:10:19Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9ng999qt</dc:identifier><dc:title>Measurement of the Higgs boson mass and width using the four-lepton final state in proton-proton collisions at s=13 TeV</dc:title><dc:creator>Hayrapetyan, A</dc:creator><dc:creator>Tumasyan, A</dc:creator><dc:creator>Adam, W</dc:creator><dc:creator>Andrejkovic, JW</dc:creator><dc:creator>Bergauer, T</dc:creator><dc:creator>Chatterjee, S</dc:creator><dc:creator>Damanakis, K</dc:creator><dc:creator>Dragicevic, M</dc:creator><dc:creator>Hussain, PS</dc:creator><dc:creator>Jeitler, M</dc:creator><dc:creator>Krammer, N</dc:creator><dc:creator>Li, A</dc:creator><dc:creator>Liko, D</dc:creator><dc:creator>Mikulec, I</dc:creator><dc:creator>Schieck, J</dc:creator><dc:creator>Schöfbeck, R</dc:creator><dc:creator>Schwarz, D</dc:creator><dc:creator>Sonawane, M</dc:creator><dc:creator>Templ, S</dc:creator><dc:creator>Waltenberger, W</dc:creator><dc:creator>Wulz, C-E</dc:creator><dc:creator>Darwish, MR</dc:creator><dc:creator>Janssen, T</dc:creator><dc:creator>Van Laer, T</dc:creator><dc:creator>Van Mechelen, P</dc:creator><dc:creator>Breugelmans, N</dc:creator><dc:creator>D’Hondt, J</dc:creator><dc:creator>Dansana, S</dc:creator><dc:creator>De Moor, A</dc:creator><dc:creator>Delcourt, M</dc:creator><dc:creator>Heyen, F</dc:creator><dc:creator>Lowette, S</dc:creator><dc:creator>Makarenko, I</dc:creator><dc:creator>Müller, D</dc:creator><dc:creator>Tavernier, S</dc:creator><dc:creator>Tytgat, M</dc:creator><dc:creator>Van Onsem, GP</dc:creator><dc:creator>Van Putte, S</dc:creator><dc:creator>Vannerom, D</dc:creator><dc:creator>Bilin, B</dc:creator><dc:creator>Clerbaux, B</dc:creator><dc:creator>Das, AK</dc:creator><dc:creator>De Lentdecker, G</dc:creator><dc:creator>Evard, H</dc:creator><dc:creator>Favart, L</dc:creator><dc:creator>Gianneios, P</dc:creator><dc:creator>Jaramillo, J</dc:creator><dc:creator>Khalilzadeh, A</dc:creator><dc:creator>Khan, FA</dc:creator><dc:creator>Lee, K</dc:creator><dc:creator>Mahdavikhorrami, M</dc:creator><dc:creator>Malara, A</dc:creator><dc:creator>Paredes, S</dc:creator><dc:creator>Shahzad, MA</dc:creator><dc:creator>Thomas, L</dc:creator><dc:creator>Bemden, M Vanden</dc:creator><dc:creator>Vander Velde, C</dc:creator><dc:creator>Vanlaer, P</dc:creator><dc:creator>De Coen, M</dc:creator><dc:creator>Dobur, D</dc:creator><dc:creator>Gokbulut, G</dc:creator><dc:creator>Hong, Y</dc:creator><dc:creator>Knolle, J</dc:creator><dc:creator>Lambrecht, L</dc:creator><dc:creator>Marckx, D</dc:creator><dc:creator>Amarilo, K Mota</dc:creator><dc:creator>Samalan, A</dc:creator><dc:creator>Skovpen, K</dc:creator><dc:creator>Van Den Bossche, N</dc:creator><dc:creator>van der Linden, J</dc:creator><dc:creator>Wezenbeek, L</dc:creator><dc:creator>Benecke, A</dc:creator><dc:creator>Bethani, A</dc:creator><dc:creator>Bruno, G</dc:creator><dc:creator>Caputo, C</dc:creator><dc:creator>De Jeneret, J De Favereau</dc:creator><dc:creator>Delaere, C</dc:creator><dc:creator>Donertas, IS</dc:creator><dc:creator>Giammanco, A</dc:creator><dc:creator>Guzel, AO</dc:creator><dc:creator>Jain</dc:creator><dc:creator>Lemaitre, V</dc:creator><dc:creator>Lidrych, J</dc:creator><dc:creator>Mastrapasqua, P</dc:creator><dc:creator>Tran, TT</dc:creator><dc:creator>Wertz, S</dc:creator><dc:creator>Alves, GA</dc:creator><dc:creator>Pereira, M Alves Gallo</dc:creator><dc:creator>Coelho, E</dc:creator><dc:creator>Silva, G Correia</dc:creator><dc:creator>Hensel, C</dc:creator><dc:creator>De Oliveira, T Menezes</dc:creator><dc:creator>Herrera, C Mora</dc:creator><dc:creator>Moraes, A</dc:creator><dc:creator>Teles, P Rebello</dc:creator><dc:creator>Soeiro, M</dc:creator><dc:creator>Pereira, A Vilela</dc:creator><dc:creator>Júnior, WL Aldá</dc:creator><dc:creator>Filho, M Barroso Ferreira</dc:creator><dc:creator>Malbouisson, H Brandao</dc:creator><dc:date>2025-05-01</dc:date><dc:description>A measurement of the Higgs boson mass and width via its decay to two  bosons is presented. Proton-proton collision data collected by the CMS experiment, corresponding to an integrated luminosity of  at a center-of-mass energy of 13&amp;nbsp;TeV, is used. The invariant mass distribution of four leptons in the on-shell Higgs boson decay is used to measure its mass and constrain its width. This yields the most precise single measurement of the Higgs boson mass to date,  , and an upper limit on the width  at 95%&amp;nbsp;confidence level. A combination of the on- and off-shell Higgs boson production decaying to four leptons is used to determine the Higgs boson width, assuming that no new virtual particles affect the production, a premise that is tested by adding new heavy particles in the gluon fusion loop model. This result is combined with a previous CMS analysis of the off-shell Higgs boson production with decay to two leptons and two neutrinos, giving a measured Higgs boson width of  , in agreement with the standard model prediction of 4.1&amp;nbsp;MeV. The strength of the off-shell Higgs boson production is also reported. The scenario of no off-shell Higgs boson production is excluded at a confidence level corresponding to 3.8 standard deviations.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9ng999qt</dc:identifier><dc:identifier>https://escholarship.org/content/qt9ng999qt/qt9ng999qt.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevd.111.092014</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 111, iss 9</dc:source><dc:coverage>092014</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3068f1p0</identifier><datestamp>2026-09-16T05:06:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3068f1p0</dc:identifier><dc:title>Selection of high-redshift Lyman-Break Galaxies from broadband and wide photometric surveys</dc:title><dc:creator>Payerne, Constantin</dc:creator><dc:creator>Doumerg, William d'Assignies</dc:creator><dc:creator>Yèche, Christophe</dc:creator><dc:creator>Ruhlmann-Kleider, Vanina</dc:creator><dc:creator>Raichoor, Anand</dc:creator><dc:creator>Lang, Dusting</dc:creator><dc:creator>Aguilar, Jessica Nicole</dc:creator><dc:creator>Ahlen, Steven</dc:creator><dc:creator>Arnouts, Stéphane</dc:creator><dc:creator>Bianchi, Davide</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>Claybaugh, Todd</dc:creator><dc:creator>Cole, Shaun</dc:creator><dc:creator>de la Macorra, Axel</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Doel, Peter</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>Forero-Romero, Jaime E</dc:creator><dc:creator>Gontcho, Satya Gontcho A</dc:creator><dc:creator>Gutierrez, Gaston</dc:creator><dc:creator>Gwyn, Stephen</dc:creator><dc:creator>Honscheid, Klaus</dc:creator><dc:creator>Juneau, Stephanie</dc:creator><dc:creator>Lambert, Andrew</dc:creator><dc:creator>Landriau, Martin</dc:creator><dc:creator>Le Guillou, Laurent</dc:creator><dc:creator>Levi, Michael E</dc:creator><dc:creator>Magneville, Christophe</dc:creator><dc:creator>Manera, Marc</dc:creator><dc:creator>Meisner, Aaron</dc:creator><dc:creator>Miquel, Ramon</dc:creator><dc:creator>Moustakas, John</dc:creator><dc:creator>Newman, Jeffrey A</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Percival, Will</dc:creator><dc:creator>Picouet, Vincent</dc:creator><dc:creator>Prada, Francisco</dc:creator><dc:creator>Pérez-Ràfols, Ignasi</dc:creator><dc:creator>Rossi, Graziano</dc:creator><dc:creator>Sanchez, Eusebio</dc:creator><dc:creator>Sawicki, Marcin</dc:creator><dc:creator>Schlegel, David</dc:creator><dc:creator>Schubnell, Michael</dc:creator><dc:creator>Sprayberry, David</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Weaver, Benjamin A</dc:creator><dc:creator>Zou, Hu</dc:creator><dc:date>2025-05-01</dc:date><dc:description>In this paper, we investigate the possibility of selecting high-redshift Lyman-Break Galaxies (LBG) using current and future broadband wide photometric surveys, such as the Ultraviolet Near Infrared Optical Northern Survey (UNIONS) or the Vera C. Rubin Legacy Survey of Space and Time (LSST), using a Random Forest algorithm. This work is conducted in the context of future large-scale structure spectroscopic surveys like DESI-II, the next phase of the Dark Energy Spectroscopic Instrument (DESI), which will start around 2029. We use deep imaging data from the Hyper Suprime Camera (HSC) and the Canada-France-Hawaii Telescope Large Area U-band Deep Survey (CLAUDS) on the COSMOS and XMM-LSS fields. To predict the selection performance of LBGs with image quality similar to UNIONS, we degrade the u,g,r,i and z bands to UNIONS depth. The Random Forest algorithm is trained with the u,g,r,i and z bands to classify LBGs in the 2.5 &amp;lt; z &amp;lt; 3.5 range. We find that fixing a target density budget of 1,100 deg-2, the Random Forest approach gives a density of z &amp;gt; 2 targets of 873 deg-2, and a density of 493 deg-2 of confirmed LBGs after spectroscopic confirmation with DESI. This UNIONS-like selection was tested in a dedicated spectroscopic observation campaign of 1,000 targets with DESI on the COSMOS field, providing a safe spectroscopic sample with a mean redshift of 3. This sample is used to derive forecasts for DESI-II, assuming a sky coverage of 5,000 deg2. We predict uncertainties on Alcock-Paczynski parameters α ⊥ and α ∥ to be 0.7% and 1% for 2.6 &amp;lt; z &amp;lt; 3.2, resulting in a potential 2% measurement of the dark energy fraction at high redshift. Additionally, we estimate the uncertainty in local non-Gaussianity and predict σ f NL ≈ 7, which would be comparable to the current best precision achieved by Planck. The latter forecast suggests that achieving the precision required to place stringent constraints on inflationary models (σ f NL ≈ 1) using spectroscopic galaxy surveys necessitates the development of a next-generation (Stage V) spectroscopic survey.</dc:description><dc:subject>5109 Space Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>galaxy surveys</dc:subject><dc:subject>high redshift galaxies</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3068f1p0</dc:identifier><dc:identifier>https://escholarship.org/content/qt3068f1p0/qt3068f1p0.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/05/031</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 05</dc:source><dc:coverage>031</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9nz787fw</identifier><datestamp>2026-09-16T05:03:59Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9nz787fw</dc:identifier><dc:title>Imaging Quantum Materials under Extreme Conditions</dc:title><dc:creator>Lee-Wong, Eric Jia Shiu</dc:creator><dc:contributor>Maple, M. Brian</dc:contributor><dc:date>2024-01-01</dc:date><dc:description>The goal of this dissertation is to study strongly correlated f–electron materials under extreme conditions using various novel imaging techniques. Strongly correlated electron materials exhibit complex physics, and when modified by a control parameter such as pressure, chemical composition, magnetic field, or temperature, can lead to novel quantum phases of matter. The underlying physics of these novel quantum phases of matter and phenomena are not completely understood and their properties, and potential applications in technology, are still being explored.In this dissertation I will review three selected works involving the application of a new optical magnetic resonance spectroscopy (ODMR) method on ferrimagnetic thin films and in-elastic x-ray spectroscopy at the Advanced Photon Source (APS) that was used to study the correlated f-electron superconductor UTe2 at large hydrostatic pressure up to 52 GPa. This dissertation will then describe the on-going projects to extend NV ODMR spectroscopy to high pressure experiments in search of emergent phases and phenomena such as superconductivity, magnetism, topological insulating states, valence fluctuations, heavy fermion phenomena, and quantum criticality in f-electron materials.
First, I will describe research conducted using a new type of ODMR method using nitrogen vacancies (NV) defects in diamond to detect thermal magnons in ferrimagnetic thin films and thin film disks of yttrium iron garnet (YIG). This research demonstrated the detection sensitivity of NVs to a broad range of magnon wavevectors (k) in YIG, up to 5.1 × 107 m-1, as well as observation of parametrically excited magnons and quantized magnon wave modes in patterned disks with radius of 5 μm of 100 nm thin film YIG. 
A second follow up study used single NV centers to probe changes in the perpendicular magnetic anisotropy (PMA) in thin film YIG. By detecting variations in the single NV relaxation rate, Γ, we were able to extract the effective magnetization 4πM_eff in 8 nm and 12 nm YIG to be -442±7 Oe and -1470±12  Oe, which matches results gathered by traditional ferromagnetic resonance spectroscopy techniques. The spinwave stiffness constant D_s was found to be 8.458×10^(-40)  J m^2. 
This study was followed by research into the structural and electronic properties of UTe2, a novel f- electron superconductor involving resonant x-ray emission spectroscopy (RXES), partial fluorescence yield x-ray absorption spectroscopy (PFY-XAS), and x-ray diffraction experiments (XRD) on UTe2 at high pressure using diamond anvil cells (DACs), at the Argonne National Laboratory’s’ Advanced Photon Source, in search of quantum phase transitions in UTe2 under hydrostatic pressure. High pressure XRD measurements on single crystal UTe2 at room temperature resulted in the discovery of a crystal phase transition in UTe2 from an orthorhombic Immm ordered phase to a tetragonal I4/mmm ordered phase at ~ 7 GPa. Additionally, through a combination of RXES and PFY-XAS we were able to detect a pressure induced change in the U valence from U 3+ to U 4+ at low pressure which then stabilized towards a valence of U 3+ up to 52 GPa. 
</dc:description><dc:subject>Physics</dc:subject><dc:language>en</dc:language><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9nz787fw</dc:identifier><dc:identifier>https://escholarship.org/content/qt9nz787fw/qt9nz787fw.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt98b4k7nt</identifier><datestamp>2026-09-16T05:03:53Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt98b4k7nt</dc:identifier><dc:title>Task-specific programming of optical diffraction using deep learning-designed surfaces</dc:title><dc:creator>Rahman, Md Sadman Sakib</dc:creator><dc:contributor>Ozcan, Aydogan</dc:contributor><dc:date>2024-01-01</dc:date><dc:description>In recent years, the perceived stagnation in the growth of electronic computing has fueled the search for alternative computing platforms. At the same time, the rise and success of deep neural networks have sparked renewed interest in neuromorphic computing for machine learning. Among these emerging platforms, optics stands out as a promising candidate for energy-efficient and low-latency computing. While much of the focus in optical computing has been on integrated optics, the recent success of diffractive deep neural networks or diffractive networks has also revived interest in diffraction-based free-space computing. Diffractive networks exploit programmed diffraction of light by spatially engineered surfaces for passive all-optical information processing at the speed of light propagation. These surfaces are digitally optimized through deep learning, enabling the input wave's diffraction to be tailored for a specific task by leveraging data that encapsulates the input-output relationship. Once the digital optimization is complete, these surfaces are fabricated and integrated into an all-optical ‘computer’, driven by passive light-matter interactions. Diffractive networks enable all-optical classification of input objects and support a diverse range of computational imaging tasks. This thesis presents methods to enhance the inference capabilities of diffractive networks and explores novel applications of this optical computing framework. First, the accuracy of diffractive systems for object classification is improved through ensemble learning, which involves combining the outputs of multiple diffractive networks. Novel strategies to diversify and assort the ensemble members are introduced, leading to significant performance gains. Then, time-lapse image classification is explored to improve the accuracy of standalone diffractive networks. By leveraging the natural jitter of the input object relative to the diffractive network, this method achieves, with a single diffractive network, accuracy comparable to that of an ensemble of 30 time-static networks. Next, the application of diffractive networks for all-optical hologram processing is demonstrated. This approach bypasses high-latency and power-intensive digital processing for removing twin-image artifacts, enabling passive inline hologram reconstruction at the speed of light propagation. Finally, a novel optical communication scheme is introduced, which utilizes electronic encoding and diffractive decoding to transfer images around arbitrarily shaped opaque occlusions of zero light transmittance. The joint training of the electronic encoder and the diffractive decoder allows efficient encoding of information in the transmitted wavefront, enabling the joint system to evade occlusions and transfer images even when the direct rays between the transmitter and the receiver are blocked. In summary, this thesis makes significant progress in the application of diffractive networks, while also laying the groundwork for future advancements in this field.</dc:description><dc:subject>Optics</dc:subject><dc:subject>Electrical engineering</dc:subject><dc:subject>Electromagnetics</dc:subject><dc:subject>Deep learning</dc:subject><dc:subject>DIffractive optics</dc:subject><dc:subject>Optical information processing</dc:subject><dc:subject>Programmed diffraction</dc:subject><dc:language>en</dc:language><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/98b4k7nt</dc:identifier><dc:identifier>https://escholarship.org/content/qt98b4k7nt/qt98b4k7nt.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt94p2r6j9</identifier><datestamp>2026-09-16T05:03:48Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt94p2r6j9</dc:identifier><dc:title>Philological Encounters and the Making of Cultural Geographies of South Asia, 1750-1950</dc:title><dc:creator>Krishna, Vipin</dc:creator><dc:contributor>Lal, Vinay</dc:contributor><dc:date>2024-01-01</dc:date><dc:description>The present cultural geographies of South Asia were first forged in the crucibles of South Asian nationalisms of India and Pakistan in the early 20th century. Roughly from 1900 to 1950, South Asian intellectuals began using vernacular languages to create cultural and political geographies and spatial imaginaries within South Asia. This dissertation specifically asks three questions, namely what made it necessary to draw such cultural geographies in South Asia in the nationalist period in the early 20th century, what these cultural geographies meant, and finally, why languages were at the center of such considerations of cultural geographies. In asking these questions, this dissertation titled Philological Encounters and the Making of Cultural Geographies of South Asia, 1750-1950 examines the encounter between a North Indian textual ecumene, and 19th-century colonial liberalism within the realm of discourses about language. I examine the ways in which this encounter shaped the cultural geographies and spatial imaginations of North India. In examining these discourses, this dissertation details the accretion of ideas about North Indian languages that resulted from the South Asian encounter with colonialism in the late 18th and 19th-centuries.
First, this dissertation argues that late 18th and early 19th centuries colonial encounter concertedly added discourses regarding cartography and liberalism and utilitarianism to North Indian languages. In addition to this cartographic specification, 19th-century liberalism presented a different way of conceiving the relationship between language, people, land, and space than had previously existed, thereby connecting land to language through customary usage. It was through this ‘micro’, and ‘macro’ mapping that discourses regarding language began to mirror discourses regarding ethnicity and territory. The mapping of language through the sciences of cartography and through the politics of liberalism had a profound effect on the ways in which North Indian intellectuals conceived of their space and place in North India during the nationalist period.
Second, this dissertation argues that in addition to the idea of cartography, languages throughout the 19th century were rendered as having familial relations. The metaphor of family concertedly entered discourses regarding languages in North India. Discourses regarding ethnic unions and families began to shape the discourse of native scholars during the nationalist period.
Finally, this dissertation argues that the 19th century colonial encounter made these philological transformations and cultural geographies part of state sciences. It was these transformations—from linguistic geography to cartography, and from ecumenical disputations to ethnic discourse, and the governmentalization of such discourses as part of state sciences—that laid the conditions for North Indian intellectuals in the early 20th century to conceive of cultural geographies of language in the Nationalist period. It is also because cultural geographies of language became part of administrative discourses that early 20th century North Indian intellectuals began to contend with administrative geographies of language by pitting their own ideas of cultural geography against administrative ideas of language.
</dc:description><dc:subject>History</dc:subject><dc:subject>Culture</dc:subject><dc:subject>Language</dc:subject><dc:subject>South Asia</dc:subject><dc:language>en</dc:language><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/94p2r6j9</dc:identifier><dc:identifier>https://escholarship.org/content/qt94p2r6j9/qt94p2r6j9.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7sz9k14p</identifier><datestamp>2026-09-16T05:03:35Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7sz9k14p</dc:identifier><dc:title>Electrochemical Control for Extracellular Microenvironments with High Spatiotemporal Resolutions</dc:title><dc:creator>Wang, Jingyu</dc:creator><dc:contributor>Liu, Chong</dc:contributor><dc:date>2024-01-01</dc:date><dc:description>Microorganisms often exist in complex assemblages, where chemical gradients play a crucial role in influencing their metabolic processes. These gradients, resulting from endogenous microbial activities, involve a dynamic transfer of nutrients, signaling molecules, and metabolic waste. Understanding the effects of such gradients on microbial physiology is important for advancing our knowledge of microbial systems. Traditional methods for creating artificial microenvironments to study these interactions, such as chamber systems, pipette injection, hydrogels, and microfluidic devices, have provided significant insights in the physiological heterogeneity in the microbial systems. However, existing platforms are limited by their spatial resolution and temporal response times. My research aims to improve the spatiotemporal resolution of artificial microenvironments by developing a novel biocompatible electrochemical platform for the generation and regulation of chemical gradients. Leveraging the fast and controllable kinetics of electrochemistry, this platform will allow for higher resolution and quicker response times compared to conventional methods. Through meticulous electrochemical design and advanced simulation guidance, I have established and optimized the electrochemical platforms for controllable gradients of oxygen (O2), hydrogen peroxide (H2O2) and pH.My first research project focused on the electrochemical control of O2 and H2O2 gradients (Chapter 2). O2 and H2O2 as one of reactive oxygen species (ROS) are two critical biologically relevant species in extracellular microenvironment. To artificially creating O2 and H2O2 gradients, I performed electrochemical oxygen reduction catalyzed by Au and Pt deposition layer on Si microwire arrays. Microwire electrodes allowed for customized morphology, facilitating the exploration of the relationship between the electrode morphology and the gradient profiles. However, the inverse design of the desired gradients is still challenging considering the large variations of extracellular O2 and H2O2 gradients in different microbial systems. To address this challenge, a machine learned based inverse design strategy was developed to quickly program a desired concentration profile at the microscopic level. Finite element method (FEM) models and machine learning algorithms were integrated to corelated the electrochemical parameters with the gradient profiles, and the targeted microenvironments of O2 and H2O2 generated through inverse design was experimentally validated. The concept of the inverse design assisted by artificial intelligence was demonstrated on both O2 and H2O2 gradients, enhancing our ability to understand and control extracellular spaces with precise spatiotemporal resolution.
With the success in O2 and H2O2 gradients, my research was extended to the investigation of pH microenvironment (Chapter 3). pH, which reflects the local proton availability, is a critical factor in biological metabolism and physiology. To achieve a controllable pH gradient through electrochemical strategy, a proton-coupled electron transfer reaction (PCET) was meticulously designed and evaluated. Instead of using microwire electrodes, interdigitated electrodes consisting of a pair of microelectrode array strips was used to provide more flexibility in tuning the range and slope of the pH gradients. Key parameters, including oxidation and reduction potential, the gap between electrodes, and the electrolyte concentration, were systematically optimized to achieve the desired pH differential, guided by a comprehensive simulation model. The pH gradients generated by electrochemical reactions were mapped using confocal microscopy, revealing a high spatial resolution of ~100 μm and a rapid response time of ~101 s. Additionally, the biocompatibility of this electrochemical platform was evaluated, confirming its suitability for further applications in microbial systems.
During my graduate career, I have demonstrated that electrochemistry represents a highly promising approach for constructing controllable microenvironments within microbial systems, advancing the spatiotemporal resolution of the artificial gradients. This strategy can be extended to the regulation of various small molecules that play crucial roles in cellular physiology across diverse assemblages. The development of this platform provides a novel toolkit for investigating microbial behavior in heterogenous microenvironments, thereby contributing to the broader field of microbial physiology and ecology.
</dc:description><dc:subject>Materials Science</dc:subject><dc:subject>Biochemistry</dc:subject><dc:subject>Confocal microscopy</dc:subject><dc:subject>Electrochemistry</dc:subject><dc:subject>Microenvironments</dc:subject><dc:subject>Spatiotemporal control</dc:subject><dc:language>en</dc:language><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7sz9k14p</dc:identifier><dc:identifier>https://escholarship.org/content/qt7sz9k14p/qt7sz9k14p.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7jd9r0wr</identifier><datestamp>2026-09-16T05:03:32Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7jd9r0wr</dc:identifier><dc:title>Specters of the Influencer Ecosystem: Labor and/as Infrastructure on and beyond Digital Platforms</dc:title><dc:creator>Li, Zizi</dc:creator><dc:contributor>Anderson, Steven F</dc:contributor><dc:date>2024-01-01</dc:date><dc:description>Social media influencers are key drivers in today’s complex culture of consuming media, goods, and identities. The majority of research on influencers has focused on individual creators, with extremely limited attention on the broader context of social media industries and the workers who support it. I argue that our current understanding of influencer work has displaced our ability to recognize the full spectrum of labor that goes into the industrial workflow of influencer media production. My research elucidates how the influencer ecosystem mobilizes racial, gendered, and classed labor from both its media and commodity supply chains. This ecosystem contains the entangled operations of waged and non-waged labor extraction from the chains of precarious workers in influencer media production, home management, e-commerce marketing, and retail logistics. By looking at an expanded notion of influencer industrial and infrastructural labor, this project rethinks labor value, forms and circuits of labor, and sites of production in digital culture as they relate to race, gender, sexuality, and class. This research further employs the concept of spectrality to reconsider how we engage with ubiquitous influencer media and confronts the social and cultural forces that made some labor spectral and certain laboring bodies into spectacle. In doing so, this dissertation accomplishes three goals: 1) to draw much-needed attention to obscured but resonant forms of labor; 2) to articulate the crucial roles of women and people of color, in the production of digital culture and economy; 3) to understand the logic behind the production, circulation, and management of influencer media. The organization of this dissertation roughly traces the consumption cycle of (im)material commodity production, circulation, and discard in influencer cultural production and e-commerce operation: from the process of constructing virtual influencers as digital beings and strategic marketing tools, to mobilizing influencers and logistic workers in selling and delivering physical goods, to the post-consumption stage of managing and tidying up overflowing items. Juxtaposing these three sites of value production and labor extraction carves out a relational space to excavate and assemble different forms of undervalued labor and infrastructure. </dc:description><dc:subject>Communication</dc:subject><dc:subject>Multimedia communications</dc:subject><dc:subject>Women's studies</dc:subject><dc:subject>Digital Media</dc:subject><dc:subject>Gender</dc:subject><dc:subject>Influencer Culture</dc:subject><dc:subject>Labor</dc:subject><dc:subject>Race</dc:subject><dc:subject>Social Media</dc:subject><dc:language>en</dc:language><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7jd9r0wr</dc:identifier><dc:identifier>https://escholarship.org/content/qt7jd9r0wr/qt7jd9r0wr.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5925c7vb</identifier><datestamp>2026-09-16T05:02:57Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5925c7vb</dc:identifier><dc:title>The Role of Store-Operated Calcium Entry in Skeletal Muscle for Sustained Force Production During Exercise: A Computational Study</dc:title><dc:creator>Kumar, Anusha</dc:creator><dc:contributor>Rangamani, Padmini</dc:contributor><dc:date>2024-01-01</dc:date><dc:description>Ca2+ signaling within myofibers is fundamental for muscle contraction facilitating activities from everyday tasks to high-intensity exercise. Stimulation at the neuromuscular junction induces an action potential that propagates along and throughout the myofiber, leading to release of Ca2+ from the sarcoplasmic reticulum (SR). Ca2+ then binds to troponin, enabling muscle contraction. Recent research highlights the role of store-operated calcium entry (SOCE) in maintaining intracellular Ca2+ stores during muscle activation. Upon SR Ca2+ depletion, stromal interaction molecule 1 in the SR membrane forms assemblies with ORAI1 channels in the sarcolemma, facilitating Ca2+ influx into myoplasm that can then be transported back into the SR. In this thesis, we develop a multi-compartment model to capture the role of SOCE in myoplasmic Ca2+ dynamics and force production during exercise. This model builds on previous models in the literature, integrating features of Ca2+ signaling and APs by including a novel combination of relevant ion channels and pumps, as well as Ca2+ buffers, and SOCE. Model parameters were calibrated against experimental data to ensure physiological relevance and model robustness. The model was simulated at various frequencies and durations of stimuli relevant to endurance vs resistance exercises. The model predicted reductions in both the maximum and average myoplasmic Ca2+ in the absence of SOCE flux, implying a diminished ability to sustain high force. The strength of this effect varied according to the frequency and exercise type. This study offers insights into muscle performance, endurance, and recovery, relevant to athletic training, physical therapy, and medical research.</dc:description><dc:subject>Mechanical engineering</dc:subject><dc:subject>Calcium signaling</dc:subject><dc:subject>Computational modeling</dc:subject><dc:subject>fast twitch fiber</dc:subject><dc:subject>SOCE</dc:subject><dc:language>en</dc:language><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5925c7vb</dc:identifier><dc:identifier>https://escholarship.org/content/qt5925c7vb/qt5925c7vb.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3534h9td</identifier><datestamp>2026-09-16T05:02:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3534h9td</dc:identifier><dc:title>Diversionary Diplomacy: Executive Appeals to Historical Memory in Nationalist Standoffs</dc:title><dc:creator>Sterbenz, Ciara</dc:creator><dc:contributor>Hazlett, Chad J</dc:contributor><dc:date>2024-01-01</dc:date><dc:description>In this dissertation, I ask: when and why do leaders invoke histories of international rivalry and collective memory centering national suffering inflicted by foreign adversaries to emphasize foreign threats and disrupt bilateral relations? A large literature in international relations has debated the veracity of diversionary war theory wherein leaders attempt to distract from acute domestic crises by inciting conflict abroad. In so doing, they exploit the psychology of out-group threat to unite the public in opposition to a foreign adversary, sparking a patriotic “rally-round-the-flag” effect which provides a much needed boost in support for government. Yet, an extensive body of research in psychology on prejudice and racism demonstrates strong out-group aversion also when threats are much less overt, involving conflict over values, beliefs, or abstract feelings of power and control. With a substantive focus on East Asia, my dissertation therefore extends inquiry on diversionary behavior beyond the narrow purview of outright conflict, examining a number of historical disputes which rile strong domestic reactions but fall far short of escalation into militarized confrontation. Concisely stated, I argue that, in these disputes, vulnerable leaders instrumentally leverage historical memory centering collective national suffering at the hands of an international rival to amplify perceptions of external threat and distract from internal problems. Due to their deep symbolic importance in national narratives of collective trauma and foreign antagonism, these historical disputes draw widespread domestic attention and generate strong nationalistic sentiment, even while remaining non-militarized. I offer support for this argument through an analysis the relations between South Korea and Japan where historical grievances remain highly salient in the public domain but enter state-to-state dialogues inconsistently. Specifically, I examine periods of high and low domestic political insecurity, tracking where and how leaders draw attention to historical disputes, raising the salience of external threats and long-standing legacies of conflict to stir strong anti-foreign, nationalist sentiment and disrupt bilateral relations.</dc:description><dc:subject>International relations</dc:subject><dc:subject>collective memory</dc:subject><dc:subject>diversion</dc:subject><dc:subject>East Asia</dc:subject><dc:subject>historical memory</dc:subject><dc:subject>nationalism</dc:subject><dc:subject>rivalry</dc:subject><dc:language>en</dc:language><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3534h9td</dc:identifier><dc:identifier>https://escholarship.org/content/qt3534h9td/qt3534h9td.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1k0253pf</identifier><datestamp>2026-09-16T05:01:36Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1k0253pf</dc:identifier><dc:title>Neighborhood Organizational Resources and Spatial Inequality in Urban and Suburban America</dc:title><dc:creator>DiRago, Nicholas Vincent</dc:creator><dc:contributor>Walker, Edward T</dc:contributor><dc:date>2024-01-01</dc:date><dc:description>While it is widely recognized that urban organizations can influence neighborhood effects and spatial inequality in the United States, it often remains unclear how and how much organizations matter. This dissertation advances a flexible approach to analyzing organizational determinants of urban inequality. Applicable upstream and downstream, this approach can clarify how organizations broker goods, services, and social ties within communities and how organizations govern communities and allocate resources across places. The dissertation’s foundation is a suite of metrics for neighborhood organizational resources (NORs) that reflects the porous nature of neighborhood boundaries, captures contact between residents and organizations, and distinguishes between organizational quantity and size. Seven novel measures are introduced, compared to conventional metrics, and applied empirically to organizational action at multiple levels. One set of analyses uses smartphone mobility data to capture how routine organizations facilitate micro-level interactions and transactions, including the case of grocery stores and disparities in food access. A second set of analyses turns to macro-level organizational action in the housing and community development sector, testing whether nonprofit housing developers influence the spatial distribution of new low-income housing subsidized by the Low-Income Housing Tax Credit. Estimating spatial models on a novel dataset spanning 30 American metropolitan areas over 14 years, at most weak evidence emerges of a causal link between NORs and subsidy allocations. This dissertation brings organizational determinants of urban inequality into sharper focus through attention to spatial boundaries, the relationships that connect organizations to individuals, and dynamics of dependence among organizations.</dc:description><dc:subject>Sociology</dc:subject><dc:subject>housing</dc:subject><dc:subject>inequality</dc:subject><dc:subject>neighborhood</dc:subject><dc:subject>organizations</dc:subject><dc:subject>spatial</dc:subject><dc:subject>urban</dc:subject><dc:language>en</dc:language><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1k0253pf</dc:identifier><dc:identifier>https://escholarship.org/content/qt1k0253pf/qt1k0253pf.pdf</dc:identifier><dc:type>etd</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7849z8p9</identifier><datestamp>2026-09-16T05:01:06Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7849z8p9</dc:identifier><dc:title>Validation of the DESI DR2 Lyα BAO analysis using synthetic datasets</dc:title><dc:creator>Casas, L</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Lokken, M</dc:creator><dc:creator>Abdul-Karim, M</dc:creator><dc:creator>Ramírez-Pérez, C</dc:creator><dc:creator>Alonso, D</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Charles, M</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Dawson, KS</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Eisenstein, DJ</dc:creator><dc:creator>Elbers, W</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Garrison, Lehman H</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gonzalez-Morales, AX</dc:creator><dc:creator>Gordon, C</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Herbold, M</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Goff, JM</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Leauthaud, A</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Li, Q</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Mena-Fernández, J</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Santos, D Muñoz</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Napolitano, L</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Noriega, HE</dc:creator><dc:creator>Paillas, E</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Pieri, Matthew M</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sinigaglia, F</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tan, T</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Taylor, P</dc:creator><dc:creator>Turner, W</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Walther, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Wolfson, M</dc:creator><dc:creator>Yèche, C</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Zhou, R</dc:creator><dc:date>2026-01-15</dc:date><dc:description>The second data release (DR2) of the Dark Energy Spectroscopic Instrument (DESI), containing data from the first three years of observations, doubles the number of Lyman-α (Lyα) forest spectra in DR1 and it provides the largest dataset of its kind. To ensure a robust validation of the baryonic acoustic oscillation (BAO) analysis using Lyα forests, we have made significant updates compared to DR1 to both the mocks and the analysis framework used in the validation. In particular, we present CoLoRe-QL, a new set of Lyα mocks that use a quasilinear input power spectrum to incorporate the nonlinear broadening of the BAO peak. We have also increased the number of realizations used in the validation to 400, compared to the 150 realizations used in DR1. Finally, we present a detailed study of the impact of quasar redshift errors on the BAO measurement, and we compare different strategies to mask damped Lyman-α absorbers in our spectra. The BAO measurement from the Lyα dataset of DESI DR2 is presented in a companion publication.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>dark energy experiments</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7849z8p9</dc:identifier><dc:identifier>https://escholarship.org/content/qt7849z8p9/qt7849z8p9.pdf</dc:identifier><dc:identifier>info:doi/10.1103/fvgh-kswf</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 113, iss 2</dc:source><dc:coverage>023520</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt66c429fj</identifier><datestamp>2026-09-16T04:56:59Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt66c429fj</dc:identifier><dc:title>Trade‐offs among restored ecosystem functions are context‐dependent in Mediterranean‐type regions</dc:title><dc:creator>Fiedler, Sebastian</dc:creator><dc:creator>Perring, Michael P</dc:creator><dc:creator>Monteiro, José A</dc:creator><dc:creator>Branquinho, Cristina</dc:creator><dc:creator>Buzhdygan, Oksana</dc:creator><dc:creator>Cavieres, Lohengrin A</dc:creator><dc:creator>Cleland, Elsa E</dc:creator><dc:creator>Cortina‐Segarra, Jordi</dc:creator><dc:creator>Grünzweig, José M</dc:creator><dc:creator>Holm, Jennifer A</dc:creator><dc:creator>Irob, Katja</dc:creator><dc:creator>Keenan, Trevor F</dc:creator><dc:creator>Köbel, Melanie</dc:creator><dc:creator>Maestre, Fernando T</dc:creator><dc:creator>Pagel, Jörn</dc:creator><dc:creator>Rodríguez‐Ramírez, Natalia</dc:creator><dc:creator>Ruiz‐Benito, Paloma</dc:creator><dc:creator>Schurr, Frank M</dc:creator><dc:creator>Sheffer, Efrat</dc:creator><dc:creator>Valencia, Enrique</dc:creator><dc:creator>Tietjen, Britta</dc:creator><dc:date>2025-08-01</dc:date><dc:description>Global biodiversity hotspots, including Mediterranean‐type ecosystems worldwide, are highly threatened by global change that alters biodiversity, ecosystem functions, and services. Some restoration activities enhance ecosystem functions by reintroducing plant species based on known relationships between plant traits and ecosystem processes. Achieving multiple functions across different site conditions, however, requires understanding how abiotic factors like climate and soil, along with plant assemblages, influence ecosystem functions, including their trade‐offs and synergies. We used the ModEST ecosystem simulation model, which integrates carbon, water, and nutrient processes with plant traits, to assess the relationships between restored plant assemblages and ecosystem functions in Mediterranean‐type climates and soils. We investigated whether maximised carbon increment, water use efficiency, and nitrogen use efficiency, along with their trade‐offs and synergies, varied across different abiotic contexts. Further, we asked whether assemblages that maximised functions varied across environments and among these functions. We found that maximised ecosystem carbon increment and nitrogen use efficiency occurred under moist, warm conditions, while water use efficiency peaked under drier conditions. Generally, the assemblage that maximised one function differed from those for other maximised functions. Synergies were rare, except between water and nitrogen use efficiencies in loam soils across most climates. Trade‐offs among maximised functions were common, varying in strength with abiotic context and plant assemblages, and were more pronounced in sandy loam soils compared to clay‐rich soils. Our findings suggest that due to variation in abiotic conditions within and across Mediterranean‐type regions at the global scale, site‐specific plant assemblages are required to maximise ecosystem functions. Thus, lessons from a single site cannot be transferred to another site, even where the same plant functional types are available for restoration. Our simulation results offer valuable insights into potential ecosystem performance under specific abiotic conditions following restoration with particular plant functional types, thereby informing local restoration efforts.</dc:description><dc:subject>4101 Climate Change Impacts and Adaptation (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>15 Life on Land (sdg)</dc:subject><dc:subject>biotic and abiotic context</dc:subject><dc:subject>ecosystem functioning</dc:subject><dc:subject>ecosystem restoration</dc:subject><dc:subject>Mediterranean-type ecosystems (MTEs)</dc:subject><dc:subject>process-based simulation modelling</dc:subject><dc:subject>trade-offs and synergies</dc:subject><dc:subject>0501 Ecological Applications (for)</dc:subject><dc:subject>0502 Environmental Science and Management (for)</dc:subject><dc:subject>0602 Ecology (for)</dc:subject><dc:subject>Ecology (science-metrix)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>4102 Ecological applications (for-2020)</dc:subject><dc:subject>4104 Environmental management (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/66c429fj</dc:identifier><dc:identifier>https://escholarship.org/content/qt66c429fj/qt66c429fj.pdf</dc:identifier><dc:identifier>info:doi/10.1002/ecog.07609</dc:identifier><dc:type>article</dc:type><dc:source>Ecography, vol 2025, iss 8</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8hc2d6fp</identifier><datestamp>2026-09-16T04:56:54Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8hc2d6fp</dc:identifier><dc:title>Assessing land use change trajectories following food insecurity shocks in 25 low- and middle-income countries</dc:title><dc:creator>Patrick, Evan</dc:creator><dc:creator>Butsic, Van</dc:creator><dc:creator>Potts, Matthew D</dc:creator><dc:date>2025-07-01</dc:date><dc:description>Food insecurity is a perennial problem in much of the developing world, with gains against hunger backsliding in recent years and climate change predicted to accelerate this trend. Food insecurity is highly disruptive to rural livelihoods and can lead to dramatic shifts in food production strategies and resultant land use. However, studies to date have yet to outline the overarching patterns of land use change that can result from food insecurity. We elucidate the impact of food insecurity events between 2013 and 2020 in 25 low- and middle-income countries on resulting land use change and demographics. Using propensity score matching, we create a counterfactual and assess changes in forest cover, crop cover, population and nighttime luminosity between regions that experience food insecurity and comparable food-secure regions. Land use change theory, specifically the classical trajectories of agricultural intensification, land rent theory, and regime shifts help to explain observed land use trajectories. We find that food insecurity events lead to around a 4&amp;nbsp;% decline in population and a 3&amp;nbsp;% decline in cropped areas, alongside a 4&amp;nbsp;% increase in forest cover compared to control regions. Additionally, we show that drought-driven food insecurity drives impacts on land use and conflict-driven food insecurity shows greater impacts on population and nighttime luminosity. Food insecurity shocks result in an increase in population and crop cover in urban areas despite losses in adjoining rural land, suggesting that food insecurity drives local rural to urban migration. Furthermore, by assessing the impacts of discrete food insecurity events in three countries, we find that regional contexts mediate impacts by producing variable land use change trajectories.</dc:description><dc:subject>4406 Human Geography (for-2020)</dc:subject><dc:subject>44 Human Society (for-2020)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Nutrition (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Generic health relevance (hrcs-hc)</dc:subject><dc:subject>2 Zero Hunger (sdg)</dc:subject><dc:subject>15 Life on Land (sdg)</dc:subject><dc:subject>Land use change</dc:subject><dc:subject>Food insecurity</dc:subject><dc:subject>Smallholder agriculture</dc:subject><dc:subject>Vulnerability</dc:subject><dc:subject>Drought</dc:subject><dc:subject>Conflict</dc:subject><dc:subject>Environmental Sciences (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8hc2d6fp</dc:identifier><dc:identifier>https://escholarship.org/content/qt8hc2d6fp/qt8hc2d6fp.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.gloenvcha.2025.102999</dc:identifier><dc:type>article</dc:type><dc:source>Global Environmental Change, vol 92</dc:source><dc:coverage>102999</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt07d801t4</identifier><datestamp>2026-09-16T04:53:09Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt07d801t4</dc:identifier><dc:title>DESI 2024 III: baryon acoustic oscillations from galaxies and quasars</dc:title><dc:creator>Adame, AG</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alam, S</dc:creator><dc:creator>Alexander, DM</dc:creator><dc:creator>Alvarez, M</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Anand, A</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Avila, S</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Awan, H</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Baltay, C</dc:creator><dc:creator>Bault, A</dc:creator><dc:creator>Behera, J</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Beutler, F</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Blake, C</dc:creator><dc:creator>Blum, R</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Buckley-Geer, E</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Calderon, R</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Cereskaite, R</dc:creator><dc:creator>Cervantes-Cota, JL</dc:creator><dc:creator>Chabanier, S</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Davis, TM</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Deiosso, N</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Edelstein, J</dc:creator><dc:creator>Eftekharzadeh, S</dc:creator><dc:creator>Eisenstein, DJ</dc:creator><dc:creator>Elliott, A</dc:creator><dc:creator>Fagrelius, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Ereza, J</dc:creator><dc:creator>Findlay, N</dc:creator><dc:creator>Flaugher, B</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Sánchez, D</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gonzalez-Morales, AX</dc:creator><dc:creator>Gonzalez-Perez, V</dc:creator><dc:creator>Gordon, C</dc:creator><dc:creator>Green, D</dc:creator><dc:creator>Gruen, D</dc:creator><dc:creator>Gsponer, R</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hadzhiyska, B</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Hanif, MMS</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Iršič, V</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Karaçaylı, NG</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kent, S</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kong, H</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Krolewski, A</dc:creator><dc:creator>Lai, Y</dc:creator><dc:creator>Lan, T-W</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Lang, D</dc:creator><dc:creator>Lasker, J</dc:creator><dc:creator>Le Goff, JM</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Leauthaud, A</dc:creator><dc:creator>Levi, ME</dc:creator><dc:date>2025-04-01</dc:date><dc:description>We present the DESI 2024 galaxy and quasar baryon acoustic oscillations (BAO) measurements using over 5.7 million unique galaxy and quasar redshifts in the range 0.1 &amp;lt; z &amp;lt; 2.1. Divided by tracer type, we utilize 300,017 galaxies from the magnitude-limited Bright Galaxy Survey with 0.1 &amp;lt; z &amp;lt; 0.4, 2,138,600 Luminous Red Galaxies with 0.4 &amp;lt; z &amp;lt; 1.1, 2,432,022 Emission Line Galaxies with 0.8 &amp;lt; z &amp;lt; 1.6, and 856,652 quasars with 0.8 &amp;lt; z &amp;lt; 2.1, over a ∼ 7,500 square degree footprint. The analysis was blinded at the catalog-level to avoid confirmation bias. All fiducial choices of the BAO fitting and reconstruction methodology, as well as the size of the systematic errors, were determined on the basis of the tests with mock catalogs and the blinded data catalogs. We present several improvements to the BAO analysis pipeline, including enhancing the BAO fitting and reconstruction methods in a more physically-motivated direction, and also present results using combinations of tracers. We employ a unified BAO analysis method across all tracers. We present a re-analysis of SDSS BOSS and eBOSS results applying the improved DESI methodology and find scatter consistent with the level of the quoted SDSS theoretical systematic uncertainties. With the total effective survey volume of ∼ 18 Gpc3, the combined precision of the BAO measurements across the six different redshift bins is ∼0.52%, marking a 1.2-fold improvement over the previous state-of-the-art results using only first-year data. We detect the BAO in all of these six redshift bins. The highest significance of BAO detection is 9.1σ at the effective redshift of 0.93, with a constraint of 0.86% placed on the BAO scale. We find that our observed BAO scales are systematically larger than the prediction of the Planck 2018-ΛCDM at z &amp;lt; 0.8. We translate the results into transverse comoving distance and radial Hubble distance measurements, which are used to constrain cosmological models in our companion paper.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/07d801t4</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1088/1475-7516/2025/04/012</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 04</dc:source><dc:coverage>012 - 012</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1z06d8p5</identifier><datestamp>2026-09-16T04:49:09Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1z06d8p5</dc:identifier><dc:title>Spatial turnover of soil viral populations and genotypes overlain by cohesive responses to moisture in grasslands</dc:title><dc:creator>Santos-Medellín, Christian</dc:creator><dc:creator>Estera-Molina, Katerina</dc:creator><dc:creator>Yuan, Mengting</dc:creator><dc:creator>Pett-Ridge, Jennifer</dc:creator><dc:creator>Firestone, Mary K</dc:creator><dc:creator>Emerson, Joanne B</dc:creator><dc:date>2022-11-08</dc:date><dc:description>Viruses shape microbial communities, food web dynamics, and carbon and nutrient cycling in diverse ecosystems. However, little is known about the patterns and drivers of viral community composition, particularly in soil, precluding a predictive understanding of viral impacts on terrestrial habitats. To investigate soil viral community assembly processes, here we analyzed 43 soil viromes from a rainfall manipulation experiment in a Mediterranean grassland in California. We identified 5,315 viral populations (viral operational taxonomic units [vOTUs] with a representative sequence ≥10 kbp) and found that viral community composition exhibited a highly significant distance-decay relationship within the 200-m2 field site. This pattern was recapitulated by the intrapopulation microheterogeneity trends of prevalent vOTUs (detected in ≥90% of the viromes), which tended to exhibit negative correlations between spatial distance and the genomic similarity of their predominant allelic variants. Although significant spatial structuring was also observed in the bacterial and archaeal communities, the signal was dampened relative to the viromes, suggesting differences in local assembly drivers for viruses and prokaryotes and/or differences in the temporal scales captured by viromes and total DNA. Despite the overwhelming spatial signal, evidence for environmental filtering was revealed in a protein-sharing network analysis, wherein a group of related vOTUs predicted to infect actinobacteria was shown to be significantly enriched in low-moisture samples distributed throughout the field. Overall, our results indicate a highly diverse, dynamic, active, and spatially structured soil virosphere capable of rapid responses to changing environmental conditions.</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Infectious Diseases (rcdc)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Grassland (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Viruses (mesh)</dc:subject><dc:subject>Genotype (mesh)</dc:subject><dc:subject>soil virome</dc:subject><dc:subject>soil microbiome</dc:subject><dc:subject>distance-decay relationship</dc:subject><dc:subject>relic DNA</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Viruses (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Genotype (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Grassland (mesh)</dc:subject><dc:subject>distance–decay relationship</dc:subject><dc:subject>relic DNA</dc:subject><dc:subject>soil microbiome</dc:subject><dc:subject>soil virome</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Grassland (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Viruses (mesh)</dc:subject><dc:subject>Genotype (mesh)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1z06d8p5</dc:identifier><dc:identifier>https://escholarship.org/content/qt1z06d8p5/qt1z06d8p5.pdf</dc:identifier><dc:identifier>info:doi/10.1073/pnas.2209132119</dc:identifier><dc:type>article</dc:type><dc:source>Proceedings of the National Academy of Sciences of the United States of America, vol 119, iss 45</dc:source><dc:coverage>e2209132119</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt39k0r8nk</identifier><datestamp>2026-09-16T04:48:49Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt39k0r8nk</dc:identifier><dc:title>Two-color ionization injection using a plasma beatwave accelerator</dc:title><dc:creator>Schroeder, CB</dc:creator><dc:creator>Benedetti, C</dc:creator><dc:creator>Esarey, E</dc:creator><dc:creator>Chen, M</dc:creator><dc:creator>Leemans, WP</dc:creator><dc:date>2018-11-01</dc:date><dc:description>Two-color laser ionization injection is a method to generate ultra-low emittance (sub-100 nm transverse normalized emittance) beams in a laser-driven plasma accelerator. A plasma beatwave accelerator is proposed to drive the plasma wave for ionization injection, where the beating of the lasers effectively produces a train of long-wavelength pulses. The plasma beatwave accelerator excites a large amplitude plasma wave with low peak laser electric fields, leaving atomically-bound electrons with low ionization potential. A short-wavelength, low-amplitude ionization injection laser pulse (with a small ponderomotive force and large peak electric field) is used to ionize the remaining bound electrons at a wake phase suitable for trapping, generating an ultra-low emittance electron beam that is accelerated in the plasma wave. Using a plasma beatwave accelerator for wakefield excitation, compared to short-pulse wakefield excitation, allows for a lower amplitude injection laser pulse and, hence, a lower emittance beam may be generated.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Laser-plasma accelerator</dc:subject><dc:subject>Plasma beatwave accelerator</dc:subject><dc:subject>High-brightness electron beams</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0299 Other Physical Sciences (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/39k0r8nk</dc:identifier><dc:identifier>https://escholarship.org/content/qt39k0r8nk/qt39k0r8nk.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.nima.2018.01.008</dc:identifier><dc:type>article</dc:type><dc:source>Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, vol 909</dc:source><dc:coverage>149 - 152</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4p99x21k</identifier><datestamp>2026-09-16T04:48:26Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4p99x21k</dc:identifier><dc:title>JAX‐CanVeg: A Differentiable Land Surface Model</dc:title><dc:creator>Jiang, Peishi</dc:creator><dc:creator>Kidger, Patrick</dc:creator><dc:creator>Bandai, Toshiyuki</dc:creator><dc:creator>Baldocchi, Dennis</dc:creator><dc:creator>Liu, Heping</dc:creator><dc:creator>Xiao, Yi</dc:creator><dc:creator>Zhang, Qianyu</dc:creator><dc:creator>Wang, Carlos Tianxin</dc:creator><dc:creator>Steefel, Carl</dc:creator><dc:creator>Chen, Xingyuan</dc:creator><dc:date>2025-03-01</dc:date><dc:description>Abstract Land surface models consider the exchange of water, energy, and carbon along the soil‐canopy‐atmosphere continuum, which is challenging to model due to their complex interdependency and associated challenges in representing and parameterizing them. Differentiable modeling provides a new opportunity to capture these complex interactions by seamlessly hybridizing process‐based models with deep neural networks (DNNs), benefiting both worlds, that is, the physical interpretation of process‐based models and the learning power of DNNs. Here, we developed a differentiable land model, JAX‐CanVeg. The new model builds on the legacy CanVeg by incorporating advanced functionalities through JAX in the graphic processing unit support, automatic differentiation, and integration with DNNs. We demonstrated JAX‐CanVeg's hybrid modeling capability by applying the model at four flux tower sites with varying aridity. To this end, we developed a hybrid version of the Ball‐Berry equation that emulates the water stress impact on stomatal closure to explore the capability of the hybrid model in (a) improving the simulations of latent heat fluxes and net ecosystem exchange , (b) improving the optimization trade‐off when learning observations of both and , and (c) benefiting a multi‐layer canopy model setup. Our results show that the proposed hybrid model improved the simulations of and at all sites, with an improved optimization trade‐off over the process‐based model. Additionally, the multi‐layer canopy set benefited hybrid modeling at some sites. Anchored in differentiable modeling, our study provides a new avenue for modeling land‐atmosphere interactions by leveraging the benefits of both data‐driven learning and process‐based modeling.
Plain Language Summary Land‐atmosphere interactions involve flux exchanges of carbon, water, and energy. They are important terrestrial ecosystem components that are being gradually modified by the warming climate. Despite the progress in the land surface model development, accurately modeling these interactions still remains a challenge owing to multiple complicated processes going from the canopy top to the soil system. In this paper, we developed a new land surface model that uses a novel modeling approach called differentiable programming to seamlessly integrate process‐based models and deep neural networks. The new model, JAX‐CanVeg, is consistent with the known ecohydrological processes while flexible to be coupled with neural networks to improve the simulations of water and carbon fluxes. We demonstrated the hybrid modeling capability of JAX‐CanVeg by coupling the equation to calculate stomatal conductance with a neural network that quantifies the water stress impact through soil moisture observations. As a proof of concept, applying the hybrid JAX‐CanVeg in four different ecosystems improves simulations of latent heat fluxes and net ecosystem exchanges. The improvement shows promise in using the new model to enhance the simulations of terrestrial water and carbon cycling and better facilitate answering research questions related to climate change.
Key Points    We developed a differentiable land surface model using a high‐performance machine learning package JAX   We proposed a hybrid Ball‐Berry model that accounts for the influence of water stress on stomatal conductance through a deep neural network   We showed that the hybrid JAX‐CanVeg improved the simulations of water and carbon fluxes at four ecosystems with varying aridity</dc:description><dc:subject>4013 Geomatic Engineering (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>Networking and Information Technology R&amp;D (NITRD) (rcdc)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>differentiable land surface modeling</dc:subject><dc:subject>hybrid modeling</dc:subject><dc:subject>stomatal conductance</dc:subject><dc:subject>water stress</dc:subject><dc:subject>optimization trade-off</dc:subject><dc:subject>0406 Physical Geography and Environmental Geoscience (for)</dc:subject><dc:subject>0905 Civil Engineering (for)</dc:subject><dc:subject>0907 Environmental Engineering (for)</dc:subject><dc:subject>Environmental Engineering (science-metrix)</dc:subject><dc:subject>3707 Hydrology (for-2020)</dc:subject><dc:subject>4005 Civil engineering (for-2020)</dc:subject><dc:subject>4011 Environmental engineering (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4p99x21k</dc:identifier><dc:identifier>https://escholarship.org/content/qt4p99x21k/qt4p99x21k.pdf</dc:identifier><dc:identifier>info:doi/10.1029/2024wr038116</dc:identifier><dc:type>article</dc:type><dc:source>Water Resources Research, vol 61, iss 3</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt19m4w50f</identifier><datestamp>2026-09-16T04:47:53Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt19m4w50f</dc:identifier><dc:title>Nonmonotonic Energy Dependence of Net-Proton Number Fluctuations</dc:title><dc:creator>Adam, J</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, JR</dc:creator><dc:creator>Adkins, JK</dc:creator><dc:creator>Agakishiev, G</dc:creator><dc:creator>Aggarwal, MM</dc:creator><dc:creator>Ahammed, Z</dc:creator><dc:creator>Alekseev, I</dc:creator><dc:creator>Anderson, DM</dc:creator><dc:creator>Aparin, A</dc:creator><dc:creator>Aschenauer, EC</dc:creator><dc:creator>Ashraf, MU</dc:creator><dc:creator>Atetalla, FG</dc:creator><dc:creator>Attri, A</dc:creator><dc:creator>Averichev, GS</dc:creator><dc:creator>Bairathi, V</dc:creator><dc:creator>Barish, K</dc:creator><dc:creator>Behera, A</dc:creator><dc:creator>Bellwied, R</dc:creator><dc:creator>Bhasin, A</dc:creator><dc:creator>Bielcik, J</dc:creator><dc:creator>Bielcikova, J</dc:creator><dc:creator>Bland, LC</dc:creator><dc:creator>Bordyuzhin, IG</dc:creator><dc:creator>Brandenburg, JD</dc:creator><dc:creator>Brandin, AV</dc:creator><dc:creator>Butterworth, J</dc:creator><dc:creator>Caines, H</dc:creator><dc:creator>de la Barca Sánchez, M Calderón</dc:creator><dc:creator>Cebra, D</dc:creator><dc:creator>Chakaberia, I</dc:creator><dc:creator>Chaloupka, P</dc:creator><dc:creator>Chan, BK</dc:creator><dc:creator>Chang, F-H</dc:creator><dc:creator>Chang, Z</dc:creator><dc:creator>Chankova-Bunzarova, N</dc:creator><dc:creator>Chatterjee, A</dc:creator><dc:creator>Chen, D</dc:creator><dc:creator>Chen, J</dc:creator><dc:creator>Chen, JH</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Chen, Z</dc:creator><dc:creator>Cheng, J</dc:creator><dc:creator>Cherney, M</dc:creator><dc:creator>Chevalier, M</dc:creator><dc:creator>Choudhury, S</dc:creator><dc:creator>Christie, W</dc:creator><dc:creator>Chu, X</dc:creator><dc:creator>Crawford, HJ</dc:creator><dc:creator>Csanád, M</dc:creator><dc:creator>Daugherity, M</dc:creator><dc:creator>Dedovich, TG</dc:creator><dc:creator>Deppner, IM</dc:creator><dc:creator>Derevschikov, AA</dc:creator><dc:creator>Didenko, L</dc:creator><dc:creator>Dong, X</dc:creator><dc:creator>Drachenberg, JL</dc:creator><dc:creator>Dunlop, JC</dc:creator><dc:creator>Edmonds, T</dc:creator><dc:creator>Elsey, N</dc:creator><dc:creator>Engelage, J</dc:creator><dc:creator>Eppley, G</dc:creator><dc:creator>Esumi, S</dc:creator><dc:creator>Evdokimov, O</dc:creator><dc:creator>Ewigleben, A</dc:creator><dc:creator>Eyser, O</dc:creator><dc:creator>Fatemi, R</dc:creator><dc:creator>Fazio, S</dc:creator><dc:creator>Federic, P</dc:creator><dc:creator>Fedorisin, J</dc:creator><dc:creator>Feng, CJ</dc:creator><dc:creator>Feng, Y</dc:creator><dc:creator>Filip, P</dc:creator><dc:creator>Finch, E</dc:creator><dc:creator>Fisyak, Y</dc:creator><dc:creator>Francisco, A</dc:creator><dc:creator>Fulek, L</dc:creator><dc:creator>Gagliardi, CA</dc:creator><dc:creator>Galatyuk, T</dc:creator><dc:creator>Geurts, F</dc:creator><dc:creator>Gibson, A</dc:creator><dc:creator>Gopal, K</dc:creator><dc:creator>Gou, X</dc:creator><dc:creator>Grosnick, D</dc:creator><dc:creator>Guryn, W</dc:creator><dc:creator>Hamad, AI</dc:creator><dc:creator>Hamed, A</dc:creator><dc:creator>Harabasz, S</dc:creator><dc:creator>Harris, JW</dc:creator><dc:creator>He, S</dc:creator><dc:creator>He, W</dc:creator><dc:creator>He, XH</dc:creator><dc:creator>He, Y</dc:creator><dc:creator>Heppelmann, S</dc:creator><dc:creator>Heppelmann, S</dc:creator><dc:creator>Herrmann, N</dc:creator><dc:creator>Hoffman, E</dc:creator><dc:creator>Holub, L</dc:creator><dc:creator>Hong, Y</dc:creator><dc:creator>Horvat, S</dc:creator><dc:date>2021-03-05</dc:date><dc:description>Nonmonotonic variation with collision energy (sqrt[s_{NN}]) of the moments of the net-baryon number distribution in heavy-ion collisions, related to the correlation length and the susceptibilities of the system, is suggested as a signature for the quantum chromodynamics critical point. We report the first evidence of a nonmonotonic variation in the kurtosis times variance of the net-proton number (proxy for net-baryon number) distribution as a function of sqrt[s_{NN}] with 3.1  σ significance for head-on (central) gold-on-gold (Au+Au) collisions measured solenoidal tracker at Relativistic Heavy Ion Collider. Data in noncentral Au+Au collisions and models of heavy-ion collisions without a critical point show a monotonic variation as a function of sqrt[s_{NN}].</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>STAR Collaboration</dc:subject><dc:subject>NSD-Relativistic Nuclear Collisions (c-lbnl-label)</dc:subject><dc:subject>01 Mathematical Sciences (for)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/19m4w50f</dc:identifier><dc:identifier>https://escholarship.org/content/qt19m4w50f/qt19m4w50f.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevlett.126.092301</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review Letters, vol 126, iss 9</dc:source><dc:coverage>092301</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0w86d72g</identifier><datestamp>2026-09-16T04:43:55Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0w86d72g</dc:identifier><dc:title>Modeling and design of compact, permanent-magnet transport systems for highly divergent, broad energy spread laser-driven proton beams</dc:title><dc:creator>De Chant, J</dc:creator><dc:creator>Nakamura, K</dc:creator><dc:creator>Ji, Q</dc:creator><dc:creator>Obst-Huebl, L</dc:creator><dc:creator>Barber, S</dc:creator><dc:creator>Snijders, AM</dc:creator><dc:creator>Geddes, CGR</dc:creator><dc:creator>van Tilborg, J</dc:creator><dc:creator>Gonsalves, AJ</dc:creator><dc:creator>Schroeder, CB</dc:creator><dc:creator>Esarey, E</dc:creator><dc:date>2025-03-01</dc:date><dc:description>Laser-driven (LD) ion acceleration has been explored in a newly constructed short focal length laser beamline at the BELLA petawatt facility (interaction point 2, iP2). For applications utilizing such LD ion beams, a beam transport system is required, which for reasons of compactness be ideally contained within 3&amp;nbsp;m. While they are generated from a micron-scale source, large divergence and energy spread of LD ion beams present a unique challenge to transporting them compared to beams from conventional accelerators. This study gives an overview of proposed compact transport designs using permanent magnets satisfying different requirements depending on the application for the iP2 laser beamline such as radiation biology, material science, and high-energy density science. These designs are optimized for different parameters such as energy spread and peak proton density according to the application’s need. The various designs consist solely of permanent magnet elements, which can provide high magnetic field gradients on a small footprint. While the field strengths are fixed, we have shown that the beam size is able to be tuned effectively by varying the placement of the magnets. The performance of each design was evaluated based on high-order particle tracking simulations of typical LD proton beams. We also examine the ability of certain configurations to tune and select beam energies, critical for specific applications. A more detailed investigation was carried out for a design to deliver 10&amp;nbsp;MeV LD accelerated ions for radiation biology applications. With these transport system designs, the iP2 laser beamline is ready to house various application experiments.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0w86d72g</dc:identifier><dc:identifier>https://escholarship.org/content/qt0w86d72g/qt0w86d72g.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevaccelbeams.28.033501</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review Accelerators and Beams, vol 28, iss 3</dc:source><dc:coverage>033501</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9n46h42z</identifier><datestamp>2026-09-16T04:43:51Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9n46h42z</dc:identifier><dc:title>Measuring σ 8 using DESI Legacy Imaging Surveys Emission-Line galaxies and Planck CMB lensing, and the impact of dust on parameter inference</dc:title><dc:creator>Karim, Tanveer</dc:creator><dc:creator>Singh, Sukhdeep</dc:creator><dc:creator>Rezaie, Mehdi</dc:creator><dc:creator>Eisenstein, Daniel</dc:creator><dc:creator>Hadzhiyska, Boryana</dc:creator><dc:creator>Speagle, Joshua S</dc:creator><dc:creator>Aguilar, Jessica Nicole</dc:creator><dc:creator>Ahlen, Steven</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>Claybaugh, Todd</dc:creator><dc:creator>de la Macorra, Axel</dc:creator><dc:creator>Ferraro, Simone</dc:creator><dc:creator>Forero-Romero, Jaime E</dc:creator><dc:creator>Gaztañaga, Enrique</dc:creator><dc:creator>Gontcho, Satya Gontcho A</dc:creator><dc:creator>Gutierrez, Gaston</dc:creator><dc:creator>Guy, Julien</dc:creator><dc:creator>Honscheid, Klaus</dc:creator><dc:creator>Juneau, Stephanie</dc:creator><dc:creator>Kirkby, David</dc:creator><dc:creator>Krolewski, Alex</dc:creator><dc:creator>Lambert, Andrew</dc:creator><dc:creator>Landriau, Martin</dc:creator><dc:creator>Levi, Michael</dc:creator><dc:creator>Meisner, Aaron</dc:creator><dc:creator>Miquel, Ramon</dc:creator><dc:creator>Moustakas, John</dc:creator><dc:creator>Muñoz-Gutiérrez, Andrea</dc:creator><dc:creator>Myers, Adam</dc:creator><dc:creator>Niz, Gustavo</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Percival, Will</dc:creator><dc:creator>Prada, Francisco</dc:creator><dc:creator>Rossi, Graziano</dc:creator><dc:creator>Sanchez, Eusebio</dc:creator><dc:creator>Schlafly, Edward</dc:creator><dc:creator>Schlegel, David</dc:creator><dc:creator>Schubnell, Michael</dc:creator><dc:creator>Sprayberry, David</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Weaver, Benjamin Alan</dc:creator><dc:creator>Zou, Hu</dc:creator><dc:date>2025-02-01</dc:date><dc:description>Measuring the growth of structure is a powerful probe for studying the dark sector, especially in light of the σ 8 tension between primary CMB anisotropy and low-redshift surveys. This paper provides a new measurement of the amplitude of the matter power spectrum, σ 8, using galaxy-galaxy and galaxy-CMB lensing power spectra of Dark Energy Spectroscopic Instrument Legacy Imaging Surveys Emission-Line Galaxies and the Planck 2018 CMB lensing map. We create an ELG catalog composed of 24 million galaxies and with a purity of 85%, covering a redshift range 0 &amp;lt; z &amp;lt; 3, with z mean = 1.09. We implement several novel systematic corrections, such as jointly modeling the contribution of imaging systematics and photometric redshift uncertainties to the covariance matrix. We also study the impacts of various dust maps on cosmological parameter inference. We measure the cross-power spectra over f sky = 0.25 with a signal-to-background ratio of up to 30σ. We find that the choice of dust maps to account for imaging systematics in estimating the ELG overdensity field has a significant impact on the final estimated values of σ 8 and ΩM, with far-infrared emission-based dust maps preferring σ 8 to be as low as 0.702 ± 0.030, and stellar-reddening-based dust maps preferring as high as 0.719 ± 0.030. The highest preferred value is at ∼ 3 σ tension with the Planck primary anisotropy results. These findings indicate a need for tomographic analyses at high redshifts and joint modeling of systematics.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>gravitational lensing</dc:subject><dc:subject>weak gravitational lensing</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9n46h42z</dc:identifier><dc:identifier>https://escholarship.org/content/qt9n46h42z/qt9n46h42z.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/02/045</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 02</dc:source><dc:coverage>045</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3441w1cr</identifier><datestamp>2026-09-16T04:40:11Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3441w1cr</dc:identifier><dc:title>Generative machine learning for detector response modeling with a conditional normalizing flow</dc:title><dc:creator>Xu, Allison</dc:creator><dc:creator>Han, Shuo</dc:creator><dc:creator>Ju, Xiangyang</dc:creator><dc:creator>Wang, Haichen</dc:creator><dc:date>2024-02-01</dc:date><dc:description>In this paper, we explore the potential of generative machine learning models as an alternative to the computationally expensive Monte Carlo (MC) simulations commonly used by the Large Hadron Collider (LHC) experiments. Our objective is to develop a generative model capable of efficiently simulating detector responses for specific particle observables, focusing on the correlations between detector responses of different particles in the same event and accommodating asymmetric detector responses. We present a conditional normalizing flow model (??ℱ) based on a chain of Masked Autoregressive Flows, which effectively incorporates conditional variables and models high-dimensional density distributions. We assess the performance of the ??ℱ model using a simulated sample of Higgs boson decaying to diphoton events at the LHC. We create reconstruction-level observables using a smearing technique. We show that conditional normalizing flows can accurately model complex detector responses and their correlation. This method can potentially reduce the computational burden associated with generating large numbers of simulated events while ensuring that the generated events meet the requirements for data analyses. We make our code available at https://github.com/allixu/normalizing_flow_for_detector_response.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Networking and Information Technology R&amp;D (NITRD) (rcdc)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>Analysis and statistical methods</dc:subject><dc:subject>Simulation methods and programs</dc:subject><dc:subject>Performance of High Energy Physics Detectors</dc:subject><dc:subject>Pattern recognition</dc:subject><dc:subject>cluster finding</dc:subject><dc:subject>calibration and fitting methods</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3441w1cr</dc:identifier><dc:identifier>https://escholarship.org/content/qt3441w1cr/qt3441w1cr.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1748-0221/19/02/p02003</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Instrumentation, vol 19, iss 02</dc:source><dc:coverage>p02003</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0fg0h624</identifier><datestamp>2026-09-16T04:40:00Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0fg0h624</dc:identifier><dc:title>Configuration, Performance, and Commissioning of the ATLAS b-jet Triggers for the 2022 and 2023 LHC data-taking periods</dc:title><dc:creator>Aad, G</dc:creator><dc:creator>Aakvaag, E</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdelhameed, S</dc:creator><dc:creator>Abeling, K</dc:creator><dc:creator>Abicht, NJ</dc:creator><dc:creator>Abidi, SH</dc:creator><dc:creator>Aboelela, M</dc:creator><dc:creator>Aboulhorma, A</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Ackermann, A</dc:creator><dc:creator>Bourdarios, C Adam</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Addepalli, SV</dc:creator><dc:creator>Addison, MJ</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adiguzel, A</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Afik, Y</dc:creator><dc:creator>Agaras, MN</dc:creator><dc:creator>Aggarwal, A</dc:creator><dc:creator>Agheorghiesei, C</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Ahuja, S</dc:creator><dc:creator>Ai, X</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Aikot, A</dc:creator><dc:creator>Tamlihat, M Ait</dc:creator><dc:creator>Aitbenchikh, B</dc:creator><dc:creator>Akbiyik, M</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Akiyama, D</dc:creator><dc:creator>Akolkar, NN</dc:creator><dc:creator>Aktas, S</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Albicocco, P</dc:creator><dc:creator>Albouy, GL</dc:creator><dc:creator>Alderweireldt, S</dc:creator><dc:creator>Alegria, ZL</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alfonsi, F</dc:creator><dc:creator>Algren, M</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Ali, B</dc:creator><dc:creator>Ali, HMJ</dc:creator><dc:creator>Ali, S</dc:creator><dc:creator>Alibocus, SW</dc:creator><dc:creator>Aliev, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alkakhi, W</dc:creator><dc:creator>Allaire, C</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allen, JS</dc:creator><dc:creator>Allen, JF</dc:creator><dc:creator>Flores, CA Allendes</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Alsolami, ZMK</dc:creator><dc:creator>Fernandez, A Alvarez</dc:creator><dc:creator>Cardoso, M Alves</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Aly, M</dc:creator><dc:creator>Coutinho, Y Amaral</dc:creator><dc:creator>Ambler, A</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amerl, M</dc:creator><dc:creator>Ames, CG</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Amini, B</dc:creator><dc:creator>Amirie, KJ</dc:creator><dc:creator>Amirkhanov, A</dc:creator><dc:creator>Dos Santos, SP Amor</dc:creator><dc:creator>Amos, KR</dc:creator><dc:creator>Amperiadou, D</dc:creator><dc:creator>An, S</dc:creator><dc:creator>Ananiev, V</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Anderson, AC</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antel, C</dc:creator><dc:creator>Antipov, E</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:date>2025-03-01</dc:date><dc:description>In 2022 and 2023, the Large Hadron Collider produced approximately two billion hadronic interactions each second from bunches of protons that collide at a rate of 40 MHz. The ATLAS trigger system is used to reduce this rate to a few kHz for recording. Selections based on hadronic jets, their energy, and event topology reduce the rate to ?(10) kHz while maintaining high efficiencies for important signatures resulting in b-quarks, but to reach the desired recording rate of hundreds of Hz, additional real-time selections based on the identification of jets containing b-hadrons (b-jets) are employed to achieve low thresholds on the jet transverse momentum at the High-Level Trigger. The configuration, commissioning, and performance of the real-time ATLAS b-jet identification algorithms for the early LHC Run 3 collision data are presented. These recent developments provide substantial gains in signal efficiency for critical signatures; for the Standard Model production of Higgs boson pairs, a 50% improvement in selection efficiency is observed in final states with four b-quarks or two b-quarks and two hadronically decaying τ-leptons.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Particle identification methods</dc:subject><dc:subject>Trigger detectors</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0fg0h624</dc:identifier><dc:identifier>https://escholarship.org/content/qt0fg0h624/qt0fg0h624.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1748-0221/20/03/p03002</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Instrumentation, vol 20, iss 03</dc:source><dc:coverage>p03002</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2120s0wq</identifier><datestamp>2026-09-16T04:39:50Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2120s0wq</dc:identifier><dc:title>ICRF wave propagation and absorption modelling via machine learning</dc:title><dc:creator>Sánchez-Villar</dc:creator><dc:creator>Bai, Z</dc:creator><dc:creator>Bertelli, N</dc:creator><dc:creator>Bethel, EW</dc:creator><dc:creator>Perciano, T</dc:creator><dc:creator>Shiraiwa, S</dc:creator><dc:creator>Wallace, G</dc:creator><dc:creator>Wright, JC</dc:creator><dc:date>2023-01-01</dc:date><dc:description>A surrogate model of the wave absorption in the ion cyclotron range of frequencies is presented. The model is trained to capture the physics of 1D electron and ion power absorption profiles for both the high harmonic fast wave scheme in NSTX, and the minority heating scheme in WEST. The surrogate models, based on both the random forest regressor and the multilayer perceptron algorithms, reduce inference time of 1D power absorption profiles from 1-5 minutes required by TORIC to ∼50 µs with high accuracy (i.e. R2 = 0.71−0.96).</dc:description><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2120s0wq</dc:identifier><dc:identifier>https://escholarship.org/content/qt2120s0wq/qt2120s0wq.pdf</dc:identifier><dc:type>article</dc:type><dc:source>49th Eps Conference on Plasma Physics Eps 2023</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2x11h667</identifier><datestamp>2026-09-16T04:39:46Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2x11h667</dc:identifier><dc:title>Critical current and stability tests of Nb3Sn for LBNL CCT magnet project</dc:title><dc:creator>Lu, Jun</dc:creator><dc:creator>Croteau, Jean-Francois</dc:creator><dc:creator>Arbelaez, Diego</dc:creator><dc:date>2023-03-21</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2x11h667</dc:identifier><dc:identifier>https://escholarship.org/content/qt2x11h667/qt2x11h667.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5vz3h9b5</identifier><datestamp>2026-09-16T04:39:40Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5vz3h9b5</dc:identifier><dc:title>Distributed fiber-optic sensing in a subscale high-temperature superconducting dipole magnet</dc:title><dc:creator>Luo, Linqing</dc:creator><dc:creator>Ferracin, Paolo</dc:creator><dc:creator>Higley, Hugh</dc:creator><dc:creator>Marchevsky, Maxim</dc:creator><dc:creator>Prestemon, Soren</dc:creator><dc:creator>Fernandez, Jose Luis Rudeiros</dc:creator><dc:creator>Teyber, Reed</dc:creator><dc:creator>Turqueti, Marcos</dc:creator><dc:creator>Vallone, Giorgio</dc:creator><dc:creator>Wang, Xiaorong</dc:creator><dc:creator>Wu, Yuxin</dc:creator><dc:date>2025-03-01</dc:date><dc:description>High-temperature superconductors, such as REBa2Cu3O7−x (REBCO, RE = rare earth), are becoming pivotal for high-field magnet technology for future circular colliders and compact fusion reactors. The U.S. Magnet Development Program, in collaboration with industry, is developing REBCO magnet technology using round conductors consisting of multiple REBCO tapes. For these multi-tape cables, traditional instrumentation, such as voltage taps and resistive strain gauges, become insufficient to help measure and understand the performance-limiting factors in these model magnets. Distributed fiber-optic sensing (DFOS) is a potential solution to address this challenge. Although DFOS is well established for various applications, measuring temperature and strain in high-temperature superconducting magnets is in its infancy. Here we report the detailed implementation and test results of DFOS based on Rayleigh scattering in a subscale canted cosθ (CCT) dipole magnet using high-temperature superconducting CORC® wires. We co-wound optical fibers in each layer of the CCT magnet and compared different types of commercial fibers and mold-release agents to reduce the power attenuation in the fibers. The DFOS allowed us to measure mechanical deformation and temperature along the conductor during tests at 77 and 4.2 K. The measured strain agreed quantitively with a finite-element mechanical model of the subscale magnet. Our results indicate that DFOS can effectively identify locations of strain and temperature changes, offering unique insight into magnet performance that can advance our understanding and development of the REBCO magnet technology for high-energy physics and fusion applications.</dc:description><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>4016 Materials Engineering (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>distributed optical fiber sensing</dc:subject><dc:subject>superconducting magnet</dc:subject><dc:subject>REBCO cable</dc:subject><dc:subject>ATAP-2025 (c-lbnl-label)</dc:subject><dc:subject>ATAP-GENERAL (c-lbnl-label)</dc:subject><dc:subject>ATAP-SMP (c-lbnl-label)</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>4016 Materials engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5vz3h9b5</dc:identifier><dc:identifier>https://escholarship.org/content/qt5vz3h9b5/qt5vz3h9b5.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1361-6668/adba98</dc:identifier><dc:type>article</dc:type><dc:source>Superconductor Science and Technology, vol 38, iss 3</dc:source><dc:coverage>035029</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt22s9879f</identifier><datestamp>2026-09-16T04:39:32Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt22s9879f</dc:identifier><dc:title>Parallel Runtime Interface for Fortran (PRIF) Specification, Revision 0.5</dc:title><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Rasmussen, Katherine</dc:creator><dc:creator>Richardson, Brad</dc:creator><dc:creator>Rouson, Damian</dc:creator><dc:date>2024-12-19</dc:date><dc:description>This document specifies an interface to support the parallel features of Fortran, named the Parallel Runtime Interface for Fortran (PRIF). PRIF is a proposed solution in which the runtime library is primarily responsible for implementing coarray allocation, deallocation and accesses, image synchronization, atomic operations, events, teams and collective subroutines. In this interface, the compiler is responsible for transforming the invocation of Fortran-level parallel features into procedure calls to the necessary PRIF subroutines. The interface is designed for portability across shared- and distributed-memory machines, different operating systems, and multiple architectures. Implementations of this interface are intended as an augmentation for the compiler's own runtime library. With an implementation-agnostic interface, alternative parallel runtime libraries may be developed that support the same interface. One benefit of this approach is the ability to vary the communication substrate. A central aim of this document is to define a parallel runtime interface in standard Fortran syntax, which enables us to leverage Fortran to succinctly express various properties of the procedure interfaces, including argument attributes.</dc:description><dc:subject>Caffeine</dc:subject><dc:subject>Coarray</dc:subject><dc:subject>Compilers</dc:subject><dc:subject>Fortran</dc:subject><dc:subject>Library specification</dc:subject><dc:subject>Parallel programming</dc:subject><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/22s9879f</dc:identifier><dc:identifier>https://escholarship.org/content/qt22s9879f/qt22s9879f.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S4CG6G</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0887f7qc</identifier><datestamp>2026-09-16T04:39:26Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0887f7qc</dc:identifier><dc:title>Identifying Missing Quasars from the DESI Bright Galaxy Survey</dc:title><dc:creator>Juneau, S</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Alexander, DM</dc:creator><dc:creator>Pucha, R</dc:creator><dc:creator>Fawcett, VA</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Ruiz-Macias, O</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Pan, Z</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alam, S</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Circosta, C</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Davis, TM</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlafly, EF</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Siudek, M</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tan, T</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Yèche, C</dc:creator><dc:creator>Zhou, Z</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-03-03</dc:date><dc:description>The Dark Energy Spectroscopic Instrument (DESI) cosmology survey includes a Bright Galaxy Survey (BGS), which will yield spectra for over 10 million bright galaxies (r &amp;lt; 20.2 AB mag). The resulting sample will be valuable for both cosmological and astrophysical studies. However, the star/galaxy separation criterion implemented in the nominal BGS target selection algorithm excludes quasar host galaxies in addition to bona fide stars. While this excluded population is comparatively rare (∼3–4 per square degrees), it may hold interesting clues regarding galaxy and quasar physics. Therefore, we present a target selection strategy that was implemented to recover these missing active galactic nuclei (AGN) from the BGS sample. The design of the selection criteria was both motivated and confirmed using spectroscopy. The resulting BGS-AGN sample is uniformly distributed over the entire DESI footprint. According to DESI survey validation data, the sample comprises 93% quasi-stellar objects (QSOs), 3% narrow-line AGN or blazars with a galaxy contamination rate of 2%, and a stellar contamination rate of 2%. Peaking around redshift z = 0.5, the BGS-AGN sample is intermediary between quasars from the rest of the BGS and those from the DESI QSO sample in terms of redshifts and AGN luminosities. The stacked spectrum is nearly identical to that of the DESI QSO targets, confirming that the sample is dominated by quasars. We highlight interesting small populations reaching z &amp;gt; 2, which are either faint quasars with nearby projected companions or very bright quasars with strong absorption features including the Lyα forest, metal absorbers, and/or broad absorption lines.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0887f7qc</dc:identifier><dc:identifier>https://escholarship.org/content/qt0887f7qc/qt0887f7qc.pdf</dc:identifier><dc:identifier>info:doi/10.3847/1538-3881/adabc9</dc:identifier><dc:type>article</dc:type><dc:source>The Astronomical Journal, vol 169, iss 3</dc:source><dc:coverage>157</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4dc7x4tz</identifier><datestamp>2026-09-16T04:38:36Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4dc7x4tz</dc:identifier><dc:title>Impact of systematic redshift errors on the cross-correlation of the Lyman-α forest with quasars at small scales using DESI Early Data</dc:title><dc:creator>Bault, Abby</dc:creator><dc:creator>Kirkby, David</dc:creator><dc:creator>Guy, Julien</dc:creator><dc:creator>Brodzeller, Allyson</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Cabayol-Garcia, L</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Cruz, R</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Filbert, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gordon, C</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Iršič, V</dc:creator><dc:creator>Karaçaylı, NG</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Montero-Camacho, P</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Ramírez-Pérez, C</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlafly, EF</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Tan, T</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Walther, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zhou, Z</dc:creator><dc:date>2025-01-01</dc:date><dc:description>The Dark Energy Spectroscopic Instrument (DESI) will measure millions of quasar spectra by the end of its 5 year survey. Quasar redshift errors impact the shape of the Lyman-α forest correlation functions, which can affect cosmological analyses and therefore cosmological interpretations. Using data from the DESI Early Data Release and the first two months of the main survey, we measure the systematic redshift error from an offset in the cross-correlation of the Lyman-α forest with quasars. We find evidence for a redshift dependent bias causing redshifts to be underestimated with increasing redshift, stemming from improper modeling of the Lyman-α optical depth in the templates used for redshift estimation. New templates were derived for the DESI Year 1 quasar sample at z &amp;gt; 1.6 and we found the redshift dependent bias, Δr ∥, increased from -1.94 ± 0.15 h -1 Mpc to -0.08 ± 0.04 h -1 Mpc (-205 ± 15 km s-1 to -9.0 ± 4.0 km s-1). These new templates will be used to provide redshifts for the DESI Year 1 quasar sample.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>dark energy experiments</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>dark energy experiments</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4dc7x4tz</dc:identifier><dc:identifier>https://escholarship.org/content/qt4dc7x4tz/qt4dc7x4tz.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/130</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>130</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0zq3b9jr</identifier><datestamp>2026-09-16T04:35:14Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0zq3b9jr</dc:identifier><dc:title>Vertical canopy gradients of respiration drive plant carbon budgets and leaf area index</dc:title><dc:creator>Needham, Jessica F</dc:creator><dc:creator>Dey, Sharmila</dc:creator><dc:creator>Koven, Charles D</dc:creator><dc:creator>Fisher, Rosie A</dc:creator><dc:creator>Knox, Ryan G</dc:creator><dc:creator>Lamour, Julien</dc:creator><dc:creator>Lemieux, Gregory</dc:creator><dc:creator>Longo, Marcos</dc:creator><dc:creator>Rogers, Alistair</dc:creator><dc:creator>Holm, Jennifer</dc:creator><dc:date>2025-04-01</dc:date><dc:description>Despite its importance for determining global carbon fluxes, leaf respiration remains poorly constrained in land surface models (LSMs). We tested the sensitivity of the Energy Exascale Earth System Model Land Model - Functionally Assembled Terrestrial Ecosystem Simulator (ELM-FATES) to variation in the canopy gradients of leaf maintenance respiration (Rdark). We ran global and point simulations varying the canopy gradient of Rdark to explore the impacts on forest structure, composition, and carbon cycling. In global simulations, steeper canopy gradients of Rdark lead to increased understory survival and leaf biomass. Leaf area index (LAI) increased up to 77% in tropical regions compared with the default parameterization, improving alignment with remotely sensed benchmarks. Global vegetation carbon varied from 308 Pg C to 449 Pg C across the ensemble. In tropical forest simulations, steeper gradients of Rdark had a large impact on successional dynamics. Results show the importance of canopy gradients in leaf traits and fluxes for determining plant carbon budgets and emergent ecosystem properties such as competitive dynamics, LAI, and vegetation carbon. The high-model sensitivity to canopy gradients in Rdark highlights the need for more observations of how leaf traits and fluxes vary along light micro-environments to inform critical dynamics in LSMs.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Carbon (mesh)</dc:subject><dc:subject>Cell Respiration (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Biological (mesh)</dc:subject><dc:subject>Carbon Cycle (mesh)</dc:subject><dc:subject>Biomass (mesh)</dc:subject><dc:subject>Forests (mesh)</dc:subject><dc:subject>Computer Simulation (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>carbon sequestration</dc:subject><dc:subject>land surface models</dc:subject><dc:subject>leaf area index</dc:subject><dc:subject>leaf respiration</dc:subject><dc:subject>vegetation demography models</dc:subject><dc:subject>carbon sequestration</dc:subject><dc:subject>land surface models</dc:subject><dc:subject>leaf area index</dc:subject><dc:subject>leaf respiration</dc:subject><dc:subject>vegetation demography models</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Carbon (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Biomass (mesh)</dc:subject><dc:subject>Cell Respiration (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Biological (mesh)</dc:subject><dc:subject>Computer Simulation (mesh)</dc:subject><dc:subject>Carbon Cycle (mesh)</dc:subject><dc:subject>Forests (mesh)</dc:subject><dc:subject>carbon sequestration</dc:subject><dc:subject>land surface models</dc:subject><dc:subject>leaf area index</dc:subject><dc:subject>leaf respiration</dc:subject><dc:subject>vegetation demography models</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Carbon (mesh)</dc:subject><dc:subject>Cell Respiration (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Biological (mesh)</dc:subject><dc:subject>Carbon Cycle (mesh)</dc:subject><dc:subject>Biomass (mesh)</dc:subject><dc:subject>Forests (mesh)</dc:subject><dc:subject>Computer Simulation (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>07 Agricultural and Veterinary Sciences (for)</dc:subject><dc:subject>Plant Biology &amp; Botany (science-metrix)</dc:subject><dc:subject>3108 Plant biology (for-2020)</dc:subject><dc:subject>4101 Climate change impacts and adaptation (for-2020)</dc:subject><dc:subject>4102 Ecological applications (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0zq3b9jr</dc:identifier><dc:identifier>https://escholarship.org/content/qt0zq3b9jr/qt0zq3b9jr.pdf</dc:identifier><dc:identifier>info:doi/10.1111/nph.20423</dc:identifier><dc:type>article</dc:type><dc:source>New Phytologist, vol 246, iss 1</dc:source><dc:coverage>144 - 157</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5z01m0wp</identifier><datestamp>2026-09-16T04:35:05Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5z01m0wp</dc:identifier><dc:title>Candidate strongly lensed type Ia supernovae in the Zwicky Transient Facility archive</dc:title><dc:creator>Townsend, A</dc:creator><dc:creator>Nordin, J</dc:creator><dc:creator>Carracedo, A Sagués</dc:creator><dc:creator>Kowalski, M</dc:creator><dc:creator>Arendse, N</dc:creator><dc:creator>Dhawan, S</dc:creator><dc:creator>Goobar, A</dc:creator><dc:creator>Johansson, J</dc:creator><dc:creator>Mörtsell, E</dc:creator><dc:creator>Schulze, S</dc:creator><dc:creator>Andreoni, I</dc:creator><dc:creator>Fernández, E</dc:creator><dc:creator>Kim, AG</dc:creator><dc:creator>Nugent, PE</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Rigault, M</dc:creator><dc:creator>Sarin, N</dc:creator><dc:creator>Sharma, D</dc:creator><dc:creator>Bellm, EC</dc:creator><dc:creator>Coughlin, MW</dc:creator><dc:creator>Dekany, R</dc:creator><dc:creator>Groom, SL</dc:creator><dc:creator>Lacroix, L</dc:creator><dc:creator>Laher, RR</dc:creator><dc:creator>Riddle, R</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-02-01</dc:date><dc:description>Context. Gravitationally lensed type Ia supernovae (glSNe Ia) are unique astronomical tools that can be used to study cosmological parameters, distributions of dark matter, the astrophysics of the supernovae, and the intervening lensing galaxies themselves. A small number of highly magnified glSNe Ia have been discovered by ground-based telescopes such as the Zwicky Transient Facility (ZTF), but simulations predict that a fainter, undetected population may also exist.   Aims. We present a systematic search for glSNe Ia in the ZTF archive of alerts distributed from June 1 2019 to September 1 2022.   Methods. Using the AMPEL platform, we developed a pipeline that distinguishes candidate glSNe Ia from other variable sources. Initial cuts were applied to the ZTF alert photometry (with constraints on the peak absolute magnitude and the distance to a catalogue-matched galaxy, as examples) before forced photometry was obtained for the remaining candidates. Additional cuts were applied to refine the candidates based on their light curve colours, lens galaxy colours, and the resulting parameters from fits to the SALT2 SN Ia template. The candidates were also cross-matched with the DESI spectroscopic catalogue.   Results. Seven transients were identified that passed all the cuts and had an associated galaxy DESI redshift, which we present as glSN Ia candidates. Although superluminous supernovae (SLSNe) cannot be fully rejected as contaminants, two events, ZTF19abpjicm and ZTF22aahmovu, are significantly different from typical SLSNe and their light curves can be modelled as two-image glSN Ia systems. From this two-image modelling, we estimate time delays of 22 ± 3 and 34 ± 1 days for the two events, respectively, which suggests that we have uncovered a population of glSNe Ia with longer time delays.   Conclusions. The pipeline is efficient and sensitive enough to parse full alert streams. It is currently being applied to the live ZTF alert stream to identify and follow-up future candidates while active. This pipeline could be the foundation for glSNe Ia searches in future surveys, such as the Rubin Observatory Legacy Survey of Space and Time.</dc:description><dc:subject>5109 Space Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>gravitational lensing: strong</dc:subject><dc:subject>methods: observational</dc:subject><dc:subject>techniques: photometric</dc:subject><dc:subject>supernovae: general</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5z01m0wp</dc:identifier><dc:identifier>https://escholarship.org/content/qt5z01m0wp/qt5z01m0wp.pdf</dc:identifier><dc:identifier>info:doi/10.1051/0004-6361/202451082</dc:identifier><dc:type>article</dc:type><dc:source>Astronomy &amp; Astrophysics, vol 694</dc:source><dc:coverage>a146</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2zq475m8</identifier><datestamp>2026-09-16T04:34:25Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2zq475m8</dc:identifier><dc:title>Consumption After a Diet Violation</dc:title><dc:creator>Tomiyama, A Janet</dc:creator><dc:creator>Moskovich, Ashley</dc:creator><dc:creator>Haltom, Kate Byrne</dc:creator><dc:creator>Ju, Tiffany</dc:creator><dc:creator>Mann, Traci</dc:creator><dc:date>2009-10-01</dc:date><dc:description>Previous research, restricted to the laboratory, has found that restrained eaters overeat after they violate their diet. However, there has been no evidence showing that this same process occurs outside the lab. We hypothesized that outside of this artificial setting, restrained eaters would be able to control their eating. In Study 1, 127 participants reported hourly on their diet violations and eating over 2 days. In Study 2, 89 participants tracked their intake for 8 days, and 50 of these participants consumed a milk shake (a diet violation) on Day 7, as part of an ostensibly unrelated study. As hypothesized, dieters did not overeat following violations of their diet in either study. These findings are in contrast with those of previous lab studies and dispel the widely held belief that diet violations lead to overeating in everyday life.</dc:description><dc:subject>52 Psychology (for-2020)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Nutrition (rcdc)</dc:subject><dc:subject>16 Peace</dc:subject><dc:subject>Justice and Strong Institutions (sdg)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Diet Records (mesh)</dc:subject><dc:subject>Diet</dc:subject><dc:subject>Reducing (mesh)</dc:subject><dc:subject>Eating (mesh)</dc:subject><dc:subject>Feeding Behavior (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Inhibition</dc:subject><dc:subject>Psychological (mesh)</dc:subject><dc:subject>Internal-External Control (mesh)</dc:subject><dc:subject>Students (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Diet</dc:subject><dc:subject>Reducing (mesh)</dc:subject><dc:subject>Feeding Behavior (mesh)</dc:subject><dc:subject>Internal-External Control (mesh)</dc:subject><dc:subject>Eating (mesh)</dc:subject><dc:subject>Students (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Diet Records (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:subject>Inhibition</dc:subject><dc:subject>Psychological (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Diet Records (mesh)</dc:subject><dc:subject>Diet</dc:subject><dc:subject>Reducing (mesh)</dc:subject><dc:subject>Eating (mesh)</dc:subject><dc:subject>Feeding Behavior (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Inhibition</dc:subject><dc:subject>Psychological (mesh)</dc:subject><dc:subject>Internal-External Control (mesh)</dc:subject><dc:subject>Students (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:subject>1701 Psychology (for)</dc:subject><dc:subject>1702 Cognitive Sciences (for)</dc:subject><dc:subject>Experimental Psychology (science-metrix)</dc:subject><dc:subject>52 Psychology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2zq475m8</dc:identifier><dc:identifier>https://escholarship.org/content/qt2zq475m8/qt2zq475m8.pdf</dc:identifier><dc:identifier>info:doi/10.1111/j.1467-9280.2009.02436.x</dc:identifier><dc:type>article</dc:type><dc:source>Psychological Science, vol 20, iss 10</dc:source><dc:coverage>1275 - 1281</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7298g7m9</identifier><datestamp>2026-09-16T04:34:11Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7298g7m9</dc:identifier><dc:title>A Guide to Using GitHub for Developing and Versioning Data Standards and Reporting Formats</dc:title><dc:creator>Crystal‐Ornelas, Robert</dc:creator><dc:creator>Varadharajan, Charuleka</dc:creator><dc:creator>Bond‐Lamberty, Ben</dc:creator><dc:creator>Boye, Kristin</dc:creator><dc:creator>Burrus, Madison</dc:creator><dc:creator>Cholia, Shreyas</dc:creator><dc:creator>Crow, Michael</dc:creator><dc:creator>Damerow, Joan</dc:creator><dc:creator>Devarakonda, Ranjeet</dc:creator><dc:creator>Ely, Kim S</dc:creator><dc:creator>Goldman, Amy</dc:creator><dc:creator>Heinz, Susan</dc:creator><dc:creator>Hendrix, Valerie</dc:creator><dc:creator>Kakalia, Zarine</dc:creator><dc:creator>Pennington, Stephanie C</dc:creator><dc:creator>Robles, Emily</dc:creator><dc:creator>Rogers, Alistair</dc:creator><dc:creator>Simmonds, Maegen</dc:creator><dc:creator>Velliquette, Terri</dc:creator><dc:creator>Weierbach, Helen</dc:creator><dc:creator>Weisenhorn, Pamela</dc:creator><dc:creator>Welch, Jessica N</dc:creator><dc:creator>Agarwal, Deborah A</dc:creator><dc:date>2021-08-01</dc:date><dc:description>Abstract Data standardization combined with descriptive metadata facilitate data reuse, which is the ultimate goal of the Findable, Accessible, Interoperable, and Reusable (FAIR) principles. Community data or metadata standards are increasingly created through an approach that emphasizes collaboration between various stakeholders. Such an approach requires platforms for collaboration on the development process that centers on sharing information and receiving feedback. Our objective in this study was to conduct a systematic review to identify data standards and reporting formats that use version control for developing data standards and to summarize common practices, particularly in earth and environmental sciences. Out of 108 data standards and reporting formats identified in our review, 32 used GitHub as the version control platform, and no other platforms were used. We found no universally accepted methodology for developing and publishing data standards. Many GitHub repositories did not use key features that could help developers to gather user feedback, or to create and revise standards that build on previous work. We provide guidance for community‐driven standard development and associated documentation on GitHub based on a systematic review of existing practices.
Key Points    Developing data standards on Version Control System platforms like GitHub enables collaboration and transparency   Many standards do not use tools for collaboration: issue tracking, licensing, and automated website hosting (GitBook or GitHub Pages)   We make recommendations and provide templates for creating descriptive version‐controlled data standard documentation on GitHub</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Networking and Information Technology R&amp;D (NITRD) (rcdc)</dc:subject><dc:subject>Data Science (rcdc)</dc:subject><dc:subject>FAIR data</dc:subject><dc:subject>TRUST principles</dc:subject><dc:subject>open science</dc:subject><dc:subject>metadata</dc:subject><dc:subject>data repositories</dc:subject><dc:subject>37 Earth sciences (for-2020)</dc:subject><dc:subject>41 Environmental sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7298g7m9</dc:identifier><dc:identifier>https://escholarship.org/content/qt7298g7m9/qt7298g7m9.pdf</dc:identifier><dc:identifier>info:doi/10.1029/2021ea001797</dc:identifier><dc:type>article</dc:type><dc:source>Earth and Space Science, vol 8, iss 8</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2dt5w83t</identifier><datestamp>2026-09-16T04:33:58Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2dt5w83t</dc:identifier><dc:title>DESI 2024 VI: cosmological constraints from the measurements of baryon acoustic oscillations</dc:title><dc:creator>Adame, AG</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alam, S</dc:creator><dc:creator>Alexander, DM</dc:creator><dc:creator>Alvarez, M</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Anand, A</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Avila, S</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Awan, H</dc:creator><dc:creator>Bahr-Kalus, B</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Baltay, C</dc:creator><dc:creator>Bault, A</dc:creator><dc:creator>Behera, J</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Bera, A</dc:creator><dc:creator>Beutler, F</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Blake, C</dc:creator><dc:creator>Blum, R</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Buckley-Geer, E</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Calderon, R</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Cereskaite, R</dc:creator><dc:creator>Cervantes-Cota, JL</dc:creator><dc:creator>Chabanier, S</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Davis, TM</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Deiosso, N</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Edelstein, J</dc:creator><dc:creator>Eftekharzadeh, S</dc:creator><dc:creator>Eisenstein, DJ</dc:creator><dc:creator>Elliott, A</dc:creator><dc:creator>Fagrelius, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Ereza, J</dc:creator><dc:creator>Findlay, N</dc:creator><dc:creator>Flaugher, B</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Sánchez, D</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Frenk, CS</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gonzalez-Morales, AX</dc:creator><dc:creator>Gonzalez-Perez, V</dc:creator><dc:creator>Gordon, C</dc:creator><dc:creator>Green, D</dc:creator><dc:creator>Gruen, D</dc:creator><dc:creator>Gsponer, R</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hadzhiyska, B</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Hanif, MMS</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Iršič, V</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Karaçaylı, NG</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kent, S</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Krolewski, A</dc:creator><dc:creator>Lai, Y</dc:creator><dc:creator>Lan, T-W</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Lang, D</dc:creator><dc:creator>Lasker, J</dc:creator><dc:creator>Le Goff, JM</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:date>2025-02-01</dc:date><dc:description>We present cosmological results from the measurement of baryon acoustic oscillations (BAO) in galaxy, quasar and Lyman-α forest tracers from the first year of observations from the Dark Energy Spectroscopic Instrument (DESI), to be released in the DESI Data Release 1. DESI BAO provide robust measurements of the transverse comoving distance and Hubble rate, or their combination, relative to the sound horizon, in seven redshift bins from over 6 million extragalactic objects in the redshift range 0.1 &amp;lt; z &amp;lt; 4.2. To mitigate confirmation bias, a blind analysis was implemented to measure the BAO scales. DESI BAO data alone are consistent with the standard flat ΛCDM cosmological model with a matter density Ωm=0.295±0.015. Paired with a baryon density prior from Big Bang Nucleosynthesis and the robustly measured acoustic angular scale from the cosmic microwave background (CMB), DESI requires H 0=(68.52±0.62) km s-1 Mpc-1. In conjunction with CMB anisotropies from Planck and CMB lensing data from Planck and ACT, we find Ωm=0.307± 0.005 and H 0=(67.97±0.38) km s-1 Mpc-1. Extending the baseline model with a constant dark energy equation of state parameter w, DESI BAO alone require w=-0.99+0.15 -0.13. In models with a time-varying dark energy equation of state parametrised by w 0 and wa , combinations of DESI with CMB or with type Ia supernovae (SN Ia) individually prefer w 0 &amp;gt; -1 and wa &amp;lt; 0. This preference is 2.6σ for the DESI+CMB combination, and persists or grows when SN Ia are added in, giving results discrepant with the ΛCDM model at the 2.5σ, 3.5σ or 3.9σ levels for the addition of the Pantheon+, Union3, or DES-SN5YR supernova datasets respectively. For the flat ΛCDM model with the sum of neutrino mass ∑ mν free, combining the DESI and CMB data yields an upper limit ∑ mν &amp;lt; 0.072 (0.113) eV at 95% confidence for a ∑ mν &amp;gt; 0 (∑ mν &amp;gt; 0.059) eV prior. These neutrino-mass constraints are substantially relaxed if the background dynamics are allowed to deviate from flat ΛCDM.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>dark energy experiments</dc:subject><dc:subject>neutrino masses from cosmology</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2dt5w83t</dc:identifier><dc:identifier>https://escholarship.org/content/qt2dt5w83t/qt2dt5w83t.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/02/021</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 02</dc:source><dc:coverage>021</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0tc9r96f</identifier><datestamp>2026-09-16T04:30:39Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0tc9r96f</dc:identifier><dc:title>Enhanced Isomer Population via Direct Irradiation of Solid-Density Targets Using a Compact Laser-Plasma Accelerator</dc:title><dc:creator>Jacob, Robert E</dc:creator><dc:creator>Tannous, Speero M</dc:creator><dc:creator>Bernstein, Lee A</dc:creator><dc:creator>Brown, Joshua</dc:creator><dc:creator>Ostermayr, Tobias</dc:creator><dc:creator>Chen, Qiang</dc:creator><dc:creator>Schneider, Dieter HG</dc:creator><dc:creator>Schroeder, Carl B</dc:creator><dc:creator>van Tilborg, Jeroen</dc:creator><dc:creator>Esarey, Eric H</dc:creator><dc:creator>Geddes, Cameron GR</dc:creator><dc:date>2025-02-07</dc:date><dc:description>Excitation of long-lived states in bromine nuclei using a tabletop laser-plasma accelerator providing pulsed (&amp;lt;100  fs) electron beams provided a sensitive probe of γ strength and level densities in the nuclear quasicontinuum and may indicate angular momentum coupling through electron-nuclear interactions. Solid-density active LaBr_{3} targets absorb real and virtual photons up to 35±2.5  MeV and deexcite through γ cascade into different states. A factor of 4.354±0.932 enhancement of the ^{80}Br^{m}/^{80}Br^{g} isomeric ratio was observed following electron irradiation, as compared to bremsstrahlung. Additional angular momentum transfer could possibly occur through nuclear-plasma or electron-nuclear interactions enabled by the ultrashort electron beam. Further investigation of these mechanisms could have far-reaching impact including decreased storage of long-term nuclear waste and an improved understanding of heavy element formation in astrophysical settings.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>ATAP-GENERAL (c-lbnl-label)</dc:subject><dc:subject>ATAP-2025 (c-lbnl-label)</dc:subject><dc:subject>ATAP-BELLA Center (c-lbnl-label)</dc:subject><dc:subject>01 Mathematical Sciences (for)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0tc9r96f</dc:identifier><dc:identifier>https://escholarship.org/content/qt0tc9r96f/qt0tc9r96f.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevlett.134.052504</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review Letters, vol 134, iss 5</dc:source><dc:coverage>052504</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2dp6h4zr</identifier><datestamp>2026-09-16T04:29:48Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2dp6h4zr</dc:identifier><dc:title>Model organism development and evaluation for late‐onset Alzheimer's disease: MODEL‐AD</dc:title><dc:creator>Oblak, Adrian L</dc:creator><dc:creator>Forner, Stefania</dc:creator><dc:creator>Territo, Paul R</dc:creator><dc:creator>Sasner, Michael</dc:creator><dc:creator>Carter, Gregory W</dc:creator><dc:creator>Howell, Gareth R</dc:creator><dc:creator>Sukoff‐Rizzo, Stacey J</dc:creator><dc:creator>Logsdon, Benjamin A</dc:creator><dc:creator>Mangravite, Lara M</dc:creator><dc:creator>Mortazavi, Ali</dc:creator><dc:creator>Baglietto‐Vargas, David</dc:creator><dc:creator>Green, Kim N</dc:creator><dc:creator>MacGregor, Grant R</dc:creator><dc:creator>Wood, Marcelo A</dc:creator><dc:creator>Tenner, Andrea J</dc:creator><dc:creator>LaFerla, Frank M</dc:creator><dc:creator>Lamb, Bruce T</dc:creator><dc:creator>and The MODEL‐AD</dc:creator><dc:creator>Consortium</dc:creator><dc:date>2020-01-01</dc:date><dc:description>Alzheimer's disease (AD) is a major cause of dementia, disability, and death in the elderly. Despite recent advances in our understanding of the basic biological mechanisms underlying AD, we do not know how to prevent it, nor do we have an approved disease-modifying intervention. Both are essential to slow or stop the growth in dementia prevalence. While our current animal models of AD have provided novel insights into AD disease mechanisms, thus far, they have not been successfully used to predict the effectiveness of therapies that have moved into AD clinical trials. The Model Organism Development and Evaluation for Late-onset Alzheimer's Disease (MODEL-AD; www.model-ad.org) Consortium was established to maximize human datasets to identify putative variants, genes, and biomarkers for AD; to generate, characterize, and validate the next generation of mouse models of AD; and to develop a preclinical testing pipeline. MODEL-AD is a collaboration among Indiana University (IU); The Jackson Laboratory (JAX); University of Pittsburgh School of Medicine (Pitt); Sage BioNetworks (Sage); and the University of California, Irvine (UCI) that will generate new AD modeling processes and pipelines, data resources, research results, standardized protocols, and models that will be shared through JAX's and Sage's proven dissemination pipelines with the National Institute on Aging-supported AD Centers, academic and medical research centers, research institutions, and the pharmaceutical industry worldwide.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>5202 Biological Psychology (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:subject>52 Psychology (for-2020)</dc:subject><dc:subject>Acquired Cognitive Impairment (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Aging (rcdc)</dc:subject><dc:subject>Dementia (rcdc)</dc:subject><dc:subject>Brain Disorders (rcdc)</dc:subject><dc:subject>Alzheimer's Disease (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) (rcdc)</dc:subject><dc:subject>Neurodegenerative (rcdc)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>Neurological (hrcs-hc)</dc:subject><dc:subject>Alzheimer's disease</dc:subject><dc:subject>animal models</dc:subject><dc:subject>LOAD</dc:subject><dc:subject>MRI</dc:subject><dc:subject>Open Science</dc:subject><dc:subject>PET</dc:subject><dc:subject>preclinical</dc:subject><dc:subject>and The MODEL‐AD</dc:subject><dc:subject>Consortium</dc:subject><dc:subject>Alzheimer's disease</dc:subject><dc:subject>LOAD</dc:subject><dc:subject>MRI</dc:subject><dc:subject>Open Science</dc:subject><dc:subject>PET</dc:subject><dc:subject>animal models</dc:subject><dc:subject>preclinical</dc:subject><dc:subject>3202 Clinical sciences (for-2020)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:subject>5202 Biological psychology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2dp6h4zr</dc:identifier><dc:identifier>https://escholarship.org/content/qt2dp6h4zr/qt2dp6h4zr.pdf</dc:identifier><dc:identifier>info:doi/10.1002/trc2.12110</dc:identifier><dc:type>article</dc:type><dc:source>Alzheimer's &amp; Dementia: Translational Research &amp; Clinical Interventions, vol 6, iss 1</dc:source><dc:coverage>e12110</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2g9006xh</identifier><datestamp>2026-09-16T04:29:36Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2g9006xh</dc:identifier><dc:title>Experimental Soil Warming Impacts Soil Moisture and Plant Water Stress and Thereby Ecosystem Carbon Dynamics</dc:title><dc:creator>Riley, WJ</dc:creator><dc:creator>Tao, J</dc:creator><dc:creator>Mekonnen, ZA</dc:creator><dc:creator>Grant, RF</dc:creator><dc:creator>Brodie, EL</dc:creator><dc:creator>Pegoraro, E</dc:creator><dc:creator>Torn, MS</dc:creator><dc:date>2025-02-01</dc:date><dc:description>Abstract  Experimental soil heating experiments have found a consistent increase in soil‐surface CO 2 emissions ( F  s  ), but inconsistent soil organic carbon (SOC) responses. Interpretation of heating effects is complicated by spatial heterogeneity and soil moisture, nitrogen availability, and microbial and plant responses. Here we applied a mechanistic ecosystem model to interpret heating impacts on a California forest subjected to 1&amp;nbsp;m deep, 4°C heating. The model accurately simulated control‐plot CO 2 fluxes, SOC stocks, fine root biomass, soil moisture, and soil temperature, and the observed increases in F  s  and decreases in fine root biomass. We show that a complex suite of interactions can lead to a consistent increase in F  s  (∼17%) over the 5‐year study period, with very small changes in SOC stocks (&amp;lt;1%). Modeled increases in leaf water stress from soil drying reduced GPP and NPP. The resulting reduction in leaf and fine root allocation increased fine root litter inputs to the soil and reduced root exudation. Soil heating led to about a 50% larger increase in root autotrophic respiration than in heterotrophic respiration, with the heating effect on both these fluxes decreasing over the simulation period. Increased heterotrophic respiration led to increased soil N availability and plant N uptake. These heating responses are mechanistically linked, of magnitudes that can affect ecosystem dynamics, and long‐term observations of them are rarely made. Therefore, we conclude that a coupled observational and mechanistic modeling framework is needed to interpret manipulation experiments, and to improve projections of climate change impacts on terrestrial ecosystem carbon dynamics. 
Plain Language Summary  We used observations and a mechanistic ecosystem model, ecosys , to study how experimental soil warming affects the carbon cycle in a Californian forest. Soil warming is an important response to climate change and can strongly affect ecosystem carbon storage. The model reasonably captured observed surface CO 2 fluxes and vertically resolved soil moisture, temperature, carbon stocks, and fine root biomass. The model also accurately captured the effects of the imposed 4°C soil heating on surface CO 2 fluxes and decreases in fine root biomass. Soil heating dried the soil, particularly near the soil surface, leading to modeled plant water stress and reduced photosynthesis and above‐ and belowground plant growth. This study demonstrates how difficult it is to get a full picture of how warming affects forests from experiments alone—they do not cover sufficiently large areas, last long enough, or capture all the important details about plant and soil interactions. Our modeling work demonstrates the need for more detailed measurements and better models to understand and predict how climate change might alter belowground biogeochemical and plant processes, the carbon cycle, and ecosystem carbon storage. 
Key Points     Modeling of a soil heating experiment showed increased CO 2 emissions consistent with observations, but minimal soil carbon changes     Accurate simulation of observed CO 2 fluxes, soil carbon, roots, and soil moisture explained heating impacts on plant water stress    Emphasizes the need to combine observational data with modeling to understand heating effects on ecosystem carbon dynamics</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>3701 Atmospheric Sciences (for-2020)</dc:subject><dc:subject>3704 Geoinformatics (for-2020)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>soil heating</dc:subject><dc:subject>carbon cycle</dc:subject><dc:subject>ecosystem carbon</dc:subject><dc:subject>soil moisture</dc:subject><dc:subject>plant water stress</dc:subject><dc:subject>ecosystem modeling</dc:subject><dc:subject>0401 Atmospheric Sciences (for)</dc:subject><dc:subject>3701 Atmospheric sciences (for-2020)</dc:subject><dc:subject>3704 Geoinformatics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2g9006xh</dc:identifier><dc:identifier>https://escholarship.org/content/qt2g9006xh/qt2g9006xh.pdf</dc:identifier><dc:identifier>info:doi/10.1029/2024ms004714</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Advances in Modeling Earth Systems, vol 17, iss 2</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8jx4m6t8</identifier><datestamp>2026-09-16T04:29:25Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8jx4m6t8</dc:identifier><dc:title>Blinding scheme for the scale-dependence bias signature of local primordial non-Gaussianity for DESI 2024</dc:title><dc:creator>Chaussidon, E</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Yèche, C</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>The next generation of spectroscopic surveys is expected to achieve an unprecedented level of accuracy in the measurement of cosmological parameters. To avoid confirmation bias and thereby improve the reliability of these results, blinding procedures become a standard practice in the cosmological analyses of such surveys. Blinding is especially crucial when the impact of observational systematics is important relative to the cosmological signal, and a detection of that signal would have significant implications. This is the case for local primordial non-gaussianity, as probed by the scale-dependent bias of the galaxy power spectrum at large scales that are heavily sensitive to the dependence of the target selection on the imaging quality, known as imaging systematics. We propose a blinding method for the scale-dependent bias signature of local primordial non-gaussianity at the density field level which consists in generating a set of weights for the data that replicate the scale-dependent bias. The applied blinding is predictable, and can be straightforwardly combined with other catalog-level blinding procedures that have been designed for the baryon acoustic oscillation and redshift space distortion signals. The procedure is validated through simulations that replicate data from the first year of observation of the Dark Energy Spectroscopic Instrument, but may find applications to other upcoming spectroscopic surveys.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Biomedical Imaging (rcdc)</dc:subject><dc:subject>galaxy clustering</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>galaxy surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8jx4m6t8</dc:identifier><dc:identifier>https://escholarship.org/content/qt8jx4m6t8/qt8jx4m6t8.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/135</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>135</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt13045467</identifier><datestamp>2026-09-16T04:29:21Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt13045467</dc:identifier><dc:title>Validating the galaxy and quasar catalog-level blinding scheme for the DESI 2024 analysis</dc:title><dc:creator>Andrade, U</dc:creator><dc:creator>Mena-Fernández, J</dc:creator><dc:creator>Awan, H</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Pan, J</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Buckley-Geer, E</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Hanif, MMS</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Paillas, E</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Pinon, M</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Fernández, A</dc:creator><dc:creator>Rashkovetskyi, M</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Verde, L</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:date>2025-01-01</dc:date><dc:description>In the era of precision cosmology, ensuring the integrity of data analysis through blinding techniques is paramount — a challenge particularly relevant for the Dark Energy Spectroscopic Instrument (DESI). DESI represents a monumental effort to map the cosmic web, with the goal to measure the redshifts of tens of millions of galaxies and quasars. Given the data volume and the impact of the findings, the potential for confirmation bias poses a significant challenge. To address this, we implement and validate a comprehensive blind analysis strategy for DESI Data Release 1 (DR1), tailored to the specific observables DESI is most sensitive to: Baryonic Acoustic Oscillations (BAO), Redshift-Space Distortion (RSD) and primordial non-Gaussianities (PNG). We carry out the blinding at the catalog level, implementing shifts in the redshifts of the observed galaxies to blind for BAO and RSD signals and weights to blind for PNG through a scale-dependent bias. We validate the blinding technique on mocks as well as on data by applying a second blinding layer to perform a series of sanity checks; the latter allows probing complexities in real data not captured in mocks. We find that the blinding strategy alters the data vector in a controlled way, and the BAO and RSD analysis choices are robust to blinding. The successful validation of the blinding strategy paves the way for the unblinded DESI DR1 analysis, alongside future blind analyses with DESI and other surveys.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>cosmological</dc:subject><dc:subject>parameters from LSS</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/13045467</dc:identifier><dc:identifier>https://escholarship.org/content/qt13045467/qt13045467.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/128</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>128</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5f17p68c</identifier><datestamp>2026-09-16T04:29:17Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5f17p68c</dc:identifier><dc:title>Optimal reconstruction of baryon acoustic oscillations for DESI 2024</dc:title><dc:creator>Paillas, E</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Padmanabhan, N</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Buckley-Geer, E</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Hanif, MMS</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Medina-Varela, L</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Mena-Fernández, J</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Fernández, A</dc:creator><dc:creator>Rashkovetskyi, M</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rosado-Marin, A</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Ruggeri, R</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Saulder, C</dc:creator><dc:creator>Schlafly, EF</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Valcin, D</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Yu, J</dc:creator><dc:creator>Yuan, S</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>Baryon acoustic oscillations (BAO) provide a robust standard ruler to measure the expansion history of the Universe through galaxy clustering. Density-field reconstruction is now a widely adopted procedure for increasing the precision and accuracy of the BAO detection. With the goal of finding the optimal reconstruction settings to be used in the DESI 2024 galaxy BAO analysis, we assess the sensitivity of the post-reconstruction BAO constraints to different choices in our analysis configuration, performing tests on blinded data from the first year of DESI observations (DR1), as well as on mocks that mimic the expected clustering and selection properties of the DESI DR1 target samples. Overall, we find that BAO constraints remain robust against multiple aspects in the reconstruction process, including the choice of smoothing scale, treatment of redshift-space distortions, fiber assignment incompleteness, and parameterizations of the BAO model. We also present a series of tests that DESI followed in order to assess the maturity of the end-to-end galaxy BAO pipeline before the unblinding of the large-scale structure catalogs.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5f17p68c</dc:identifier><dc:identifier>https://escholarship.org/content/qt5f17p68c/qt5f17p68c.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/142</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>142</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9zb2d29s</identifier><datestamp>2026-09-16T04:26:26Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9zb2d29s</dc:identifier><dc:title>Mitigation of DESI fiber assignment incompleteness effect on two-point clustering with small angular scale truncated estimators</dc:title><dc:creator>Pinon, M</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>McDonald, P</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Ruhlmann-Kleider, V</dc:creator><dc:creator>White, M</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Cahn, RN</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Lasker, J</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>We present a method to mitigate the effects of fiber assignment incompleteness in two-point power spectrum and correlation function measurements from galaxy spectroscopic surveys, by truncating small angular scales from estimators. We derive the corresponding modified correlation function and power spectrum windows to account for the small angular scale truncation in the theory prediction. We validate this approach on simulations reproducing the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) with and without fiber assignment. We show that we recover unbiased cosmological constraints using small angular scale truncated estimators from simulations with fiber assignment incompleteness, with respect to standard estimators from complete simulations. Additionally, we present an approach to remove the sensitivity of the fits to high k modes in the theoretical power spectrum, by applying a transformation to the data vector and window matrix. We find that our method efficiently mitigates the effect of fiber assignment incompleteness in two-point correlation function and power spectrum measurements, at low computational cost and with little statistical loss.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9zb2d29s</dc:identifier><dc:identifier>https://escholarship.org/content/qt9zb2d29s/qt9zb2d29s.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/131</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>131</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8k53z0rn</identifier><datestamp>2026-09-16T04:26:21Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8k53z0rn</dc:identifier><dc:title>Impact and mitigation of spectroscopic systematics on DESI DR1 clustering measurements</dc:title><dc:creator>Krolewski, A</dc:creator><dc:creator>Yu, J</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Penmetsa, S</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Wilson, MJ</dc:creator><dc:creator>Hou, J</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlafly, EF</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zhao, C</dc:creator><dc:date>2025-01-01</dc:date><dc:description>The large scale structure catalogs within DESI Data Release 1 (DR1) use nearly 6 million galaxies and quasars as tracers of the large-scale structure of the universe to measure the expansion history with baryon acoustic oscillations and the growth of structure with redshift-space distortions. In order to take advantage of DESI's unprecedented statistical power, we must ensure that the galaxy clustering measurements are unaffected by non-cosmological density fluctuations. One source of spurious fluctuations comes from variation in galaxy density with spectroscopic observing conditions, lowering the redshift efficiency (and thus galaxy density) in certain areas of the sky. We measure the uniformity of the redshift success rate for DESI luminous red galaxies (LRG), bright galaxies (BGS) and quasars (QSO), complementing the detailed discussion of emission line galaxy (ELG) systematics in a companion paper [1]. We find small but significant fluctuations of up to 3% in redshift success rate with the effective spectroscopic signal-to-noise, and create and describe weights that remove these fluctuations. We also describe the process to identify and remove data from certain poorly performing fibers from DESI DR1, and measure the stability of the redshift success rate with time. Finally, we find small but significant correlations of redshift success rate with position on the focal plane, survey speed, and number of exposures required, and show the impact of weights correcting these trends on the power spectrum multipoles and on cosmological parameters from BAO and RSD fits. These corrections change the best-fit parameters by &amp;lt;15% of their statistical errors, and thus contribute negligibly to the overall DESI error budget.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8k53z0rn</dc:identifier><dc:identifier>https://escholarship.org/content/qt8k53z0rn/qt8k53z0rn.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/147</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>147</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt978149tj</identifier><datestamp>2026-09-16T04:26:16Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt978149tj</dc:identifier><dc:title>Validation of the DESI 2024 Lyα forest BAO analysis using synthetic datasets</dc:title><dc:creator>Cuceu, Andrei</dc:creator><dc:creator>Herrera-Alcantar, Hiram K</dc:creator><dc:creator>Gordon, Calum</dc:creator><dc:creator>Martini, Paul</dc:creator><dc:creator>Guy, Julien</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>Gonzalez-Morales, Alma X</dc:creator><dc:creator>Karim, M Abdul</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Bault, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Karaçaylı, NG</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Goff, JM</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Ramírez-Pérez, C</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tan, T</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Walther, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>The first year of data from the Dark Energy Spectroscopic Instrument (DESI) contains the largest set of Lyman-α (Lyα) forest spectra ever observed. This data, collected in the DESI Data Release 1 (DR1) sample, has been used to measure the Baryon Acoustic Oscillation (BAO) feature at redshift z = 2.33. In this work, we use a set of 150 synthetic realizations of DESI DR1 to validate the DESI 2024 Lyα forest BAO measurement presented in [1]. The synthetic data sets are based on Gaussian random fields using the log-normal approximation. We produce realistic synthetic DESI spectra that include all major contaminants affecting the Lyα forest. The synthetic data sets span a redshift range 1.8 &amp;lt; z &amp;lt; 3.8, and are analysed using the same framework and pipeline used for the DESI 2024 Lyα forest BAO measurement. To measure BAO, we use both the Lyα auto-correlation and its cross-correlation with quasar positions. We use the mean of correlation functions from the set of DESI DR1 realizations to show that our model is able to recover unbiased measurements of the BAO position. We also fit each mock individually and study the population of BAO fits in order to validate BAO uncertainties and test our method for estimating the covariance matrix of the Lyα forest correlation functions. Finally, we discuss the implications of our results and identify the needs for the next generation of Lyα forest synthetic data sets, with the top priority being to simulate the effect of BAO broadening due to non-linear evolution.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>dark energy experiments</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/978149tj</dc:identifier><dc:identifier>https://escholarship.org/content/qt978149tj/qt978149tj.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/148</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>148</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5502f0rk</identifier><datestamp>2026-09-16T04:26:09Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5502f0rk</dc:identifier><dc:title>A comparison between ShapeFit compression and Full-Modelling method with PyBird for DESI 2024 and beyond</dc:title><dc:creator>Lai, Y</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Maus, M</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Noriega, HE</dc:creator><dc:creator>Ramírez-Solano, S</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Davis, TM</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, W</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Verde, L</dc:creator><dc:creator>Yuan, S</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>DESI aims to provide one of the tightest constraints on cosmological parameters by analysing the clustering of more than thirty million galaxies. However, obtaining such constraints requires special care in validating the methodology and efforts to reduce the computational time required through data compression and emulation techniques. In this work, we perform a rigorous validation of the PyBird power spectrum modelling code with both a traditional emulated Full-Modelling approach and the model-independent ShapeFit compression approach. By using cubic box simulations that accurately reproduce the clustering and precision of the DESI survey, we find that the cosmological constraints from ShapeFit and Full-Modelling are consistent with each other at the ∼ 0.5σ level for the ΛCDM model. Both ShapeFit and Full-Modelling are also consistent with the true ΛCDM simulation cosmology down to a scale of k max = 0.20 hMpc-1 even after including the hexadecapole. For extended models such as the wCDM and the oCDM models, we find that including the hexadecapole can significantly improve the constraints and reduce the modelling errors with the same k max. While their discrepancies between the constraints from ShapeFit and Full-Modelling are more significant than ΛCDM, they remain consistent within 0.7σ. Lastly, we also show that the constraints on cosmological parameters with the correlation function evaluated from PyBird down to s min = 30h -1Mpc are unbiased and consistent with the constraints from the power spectrum.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5502f0rk</dc:identifier><dc:identifier>https://escholarship.org/content/qt5502f0rk/qt5502f0rk.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/139</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>139</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6fc35504</identifier><datestamp>2026-09-16T04:26:05Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6fc35504</dc:identifier><dc:title>ELG spectroscopic systematics analysis of the DESI Data Release 1</dc:title><dc:creator>Yu, J</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Rocher, A</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Forero-Sánchez, D</dc:creator><dc:creator>Kneib, J</dc:creator><dc:creator>Krolewski, A</dc:creator><dc:creator>Lan, T-W</dc:creator><dc:creator>Rashkovetskyi, M</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlafly, EF</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Zhao, C</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>Dark Energy Spectroscopic Instrument (DESI) uses more than 2.4 million Emission Line Galaxies (ELGs) for 3D large-scale structure (LSS) analyses in its Data Release 1 (DR1). Such large statistics enable thorough research on systematic uncertainties. In this study, we focus on spectroscopic systematics of ELGs. The redshift success rate (f goodz) is the relative fraction of secure redshifts among all measurements. It depends on observing conditions, thus introduces non-cosmological variations to the LSS. We, therefore, develop the redshift failure weight (w zfail) and a per-fibre correction (η zfail) to mitigate these dependences. They have minor influences on the galaxy clustering. For ELGs with a secure redshift, there are two subtypes of systematics: 1) catastrophics (large) that only occur in a few samples; 2) redshift uncertainty (small) that exists for all samples. The catastrophics represent 0.26% of the total DR1 ELGs, composed of the confusion between [O ii] and sky residuals, double objects, total catastrophics and others. We simulate the realistic 0.26% catastrophics of DR1 ELGs, the hypothetical 1% catastrophics, and the truncation of the contaminated 1.31 &amp;lt; z &amp;lt; 1.33 in the AbacusSummit ELG mocks. Their P ℓ show non-negligible bias from the uncontaminated mocks. But their influences on the redshift space distortions (RSD) parameters are smaller than 0.2σ. The redshift uncertainty of DR1 ELGs is 8.5km s-1 with a Lorentzian profile. The code for implementing the catastrophics and redshift uncertainty on mocks can be found in https://github.com/Jiaxi-Yu/modelling_spectro_sys.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>galaxy clustering</dc:subject><dc:subject>galaxy surveys</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6fc35504</dc:identifier><dc:identifier>https://escholarship.org/content/qt6fc35504/qt6fc35504.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/126</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>126</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt746597bw</identifier><datestamp>2026-09-16T04:26:00Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt746597bw</dc:identifier><dc:title>Comparing Compressed and Full-Modeling analyses with FOLPS: implications for DESI 2024 and beyond</dc:title><dc:creator>Noriega, HE</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Ramirez-Solano, S</dc:creator><dc:creator>Fromenteau, S</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Cervantes-Cota, JL</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Findlay, N</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Hou, J</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Lai, Y</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Maus, M</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Morales-Navarrete, G</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rocher, A</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Verde, L</dc:creator><dc:creator>Yuan, S</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>The Dark Energy Spectroscopic Instrument (DESI) will provide unprecedented information about the large-scale structure of our Universe. In this work, we study the robustness of the theoretical modelling of the power spectrum of Folps, a novel effective field theory-based package for evaluating the redshift space power spectrum in the presence of massive neutrinos. We perform this validation by fitting the AbacusSummit high-accuracy N-body simulations for Luminous Red Galaxies, Emission Line Galaxies and Quasar tracers, calibrated to describe DESI observations. We quantify the potential systematic error budget of Folps finding that the modelling errors are fully sub-dominant for the DESI statistical precision within the studied range of scales. Additionally, we study two complementary approaches to fit and analyse the power spectrum data, one based on direct Full-Modelling fits and the other on the ShapeFit compression variables, both resulting in very good agreement in precision and accuracy. In each of these approaches, we study a set of potential systematic errors induced by several assumptions, such as the choice of template cosmology, the effect of prior choice in the nuisance parameters of the model, or the range of scales used in the analysis. Furthermore, we show how opening up the parameter space beyond the vanilla ΛCDM model affects the DESI observables. These studies include the addition of massive neutrinos, spatial curvature, and dark energy equation of state. We also examine how relaxing the usual Cosmic Microwave Background and Big Bang Nucleosynthesis priors on the primordial spectral index and the baryonic matter abundance, respectively, impacts the inference on the rest of the parameters of interest. This paper pathways towards performing a robust and reliable analysis of the shape of the power spectrum of DESI galaxy and quasar clustering using Folps.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>galaxy clusters</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/746597bw</dc:identifier><dc:identifier>https://escholarship.org/content/qt746597bw/qt746597bw.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/136</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>136</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0z21p7rc</identifier><datestamp>2026-09-16T04:25:56Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0z21p7rc</dc:identifier><dc:title>Characterization of contaminants in the Lyman-alpha forest auto-correlation with DESI</dc:title><dc:creator>Guy, J</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Karaçaylı, NG</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Pieri, MM</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Ramírez-Pérez, C</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Rich, J</dc:creator><dc:creator>Walther, M</dc:creator><dc:creator>Karim, M Abdul</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bault, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>de la Cruz, R</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gonzalez-Morales, AX</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Montero-Camacho, P</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tan, T</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>Baryon Acoustic Oscillations can be measured with sub-percent precision above redshift two with the Lyman-α (Lyα) forest auto-correlation and its cross-correlation with quasar positions. This is one of the key goals of the Dark Energy Spectroscopic Instrument (DESI) which started its main survey in May 2021. We present in this paper a study of the contaminants to the Lyα forest which are mainly caused by correlated signals introduced by the spectroscopic data processing pipeline as well as astrophysical contaminants due to foreground absorption in the intergalactic medium. Notably, an excess signal caused by the sky background subtraction noise is present in the Lyα auto-correlation in the first line-of-sight separation bin. We use synthetic data to isolate this contribution, we also characterize the effect of spectro-photometric calibration noise, and propose a simple model to account for both effects in the analysis of the Lyα forest. We then measure the auto-correlation of the quasar flux transmission fraction of low redshift quasars, where there is no Lyα forest absorption but only its contaminants. We demonstrate that we can interpret the data with a two-component model: data processing noise and triply ionized Silicon and Carbon auto-correlations. This result can be used to improve the modeling of the Lyα auto-correlation function measured with DESI.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>dark energy experiments</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0z21p7rc</dc:identifier><dc:identifier>https://escholarship.org/content/qt0z21p7rc/qt0z21p7rc.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/140</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>140</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0z89g4qv</identifier><datestamp>2026-09-16T04:25:51Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0z89g4qv</dc:identifier><dc:title>Fiducial-cosmology-dependent systematics for the DESI 2024 BAO analysis</dc:title><dc:creator>Pérez-Fernández, A</dc:creator><dc:creator>Medina-Varela, L</dc:creator><dc:creator>Ruggeri, R</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Padmanabhan, N</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alam, S</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Lasker, J</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Mena-Fernández, J</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Paillas, E</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Rashkovetskyi, M</dc:creator><dc:creator>Rocher, A</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, A</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Valcin, D</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yu, J</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>When measuring the Baryon Acoustic Oscillations (BAO) scale from galaxy surveys, one typically assumes a fiducial cosmology when converting redshift measurements into comoving distances and also when defining input parameters for the reconstruction algorithm. A parameterised template for the model to be fitted is also created based on a (possibly different) fiducial cosmology. This model reliance can be considered a form of data compression, and the data is then analysed allowing that the true answer is different from the fiducial cosmology assumed. In this study, we evaluate the impact of the fiducial cosmology assumed in the BAO analysis of the Dark Energy Spectroscopic Instrument (DESI) survey Data Release 1 (DR1) on the final measurements in DESI 2024 III. We utilise a suite of mock galaxy catalogues with survey realism that mirrors the DESI DR1 tracers: the bright galaxy sample (BGS), the luminous red galaxies (LRG), the emission line galaxies (ELG) and the quasars (QSO), spanning a redshift range from 0.1 to 2.1. We compare the four secondary AbacusSummit cosmologies against DESI's fiducial cosmology (Planck 2018). The secondary cosmologies explored include a lower cold dark matter density, a thawing dark energy universe, a higher number of effective species, and a lower amplitude of matter clustering. The mocks are processed through the BAO pipeline by consistently iterating the grid, template, and reconstruction reference cosmologies. We determine a conservative systematic contribution to the error of 0.1% for both the isotropic and anisotropic dilation parameters α iso and α AP. We then directly test the impact of the fiducial cosmology on DESI DR1 data.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0z89g4qv</dc:identifier><dc:identifier>https://escholarship.org/content/qt0z89g4qv/qt0z89g4qv.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/144</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>144</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5mz2b76f</identifier><datestamp>2026-09-16T04:25:44Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5mz2b76f</dc:identifier><dc:title>HOD-dependent systematics for luminous red galaxies in the DESI 2024 BAO analysis</dc:title><dc:creator>Mena-Fernández, J</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Yuan, S</dc:creator><dc:creator>Hadzhiyska, B</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Rashkovetskyi, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Padmanabhan, N</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Alam, S</dc:creator><dc:creator>Rocher, A</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Medina-Varela, L</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Paillas, E</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Pérez-Fernández, A</dc:creator><dc:creator>Rosado-Marin, A</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Ruggeri, R</dc:creator><dc:creator>Saulder, C</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yu, J</dc:creator><dc:creator>Zhang, H</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>In this paper, we present the estimation of systematics related to the halo occupation distribution (HOD) modeling in the baryon acoustic oscillations (BAO) distance measurement of the Dark Energy Spectroscopic Instrument (DESI) 2024 analysis. This paper focuses on the study of HOD systematics for luminous red galaxies (LRG). We consider three different HOD models for LRGs, including the base 5-parameter vanilla model and two extensions to it, that we refer to as baseline and extended models. The baseline model is described by the 5 vanilla HOD parameters, an incompleteness factor and a velocity bias parameter, whereas the extended one also includes a galaxy assembly bias and a satellite profile parameter. We utilize the 25 dark matter simulations available in the AbacusSummit simulation suite at z=0.8 and generate mock catalogs for our different HOD models. To test the impact of the HOD modeling in the position of the BAO peak, we run BAO fits for all these sets of simulations and compare the best-fit BAO-scaling parameters α iso and α AP between every pair of HOD models. We do this for both Fourier and configuration spaces independently, using post-reconstruction measurements. We find a 3.3σ detection of HOD systematic for α AP in configuration space with an amplitude of 0.19%. For the other cases, we did not find a 3σ detection, and we decided to compute a conservative estimation of the systematic using the ensemble of shifts between all pairs of HOD models. By doing this, we quote a systematic with an amplitude of 0.07% in α iso for both Fourier and configuration spaces; and of 0.09% in α AP for Fourier space.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>galaxy clustering</dc:subject><dc:subject>galaxy surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5mz2b76f</dc:identifier><dc:identifier>https://escholarship.org/content/qt5mz2b76f/qt5mz2b76f.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/133</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>133</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt20f4w28b</identifier><datestamp>2026-09-16T04:25:39Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt20f4w28b</dc:identifier><dc:title>Validation of the DESI 2024 Lyman alpha forest BAL masking strategy</dc:title><dc:creator>Martini, P</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Ennesser, L</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>de Belsunce, R</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Karaçaylı, NG</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Montero-Camacho, P</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tan, T</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Walther, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>Broad absorption line quasars (BALs) exhibit blueshifted absorption relative to a number of their prominent broad emission features. These absorption features can contribute to quasar redshift errors and add absorption to the Lyman-α (Lyα) forest that is unrelated to large-scale structure. We present a detailed analysis of the impact of BALs on the Baryon Acoustic Oscillation (BAO) results with the Lyα forest from the first year of data from the Dark Energy Spectroscopic Instrument (DESI). The baseline strategy for the first year analysis is to mask all pixels associated with all BAL absorption features that fall within the wavelength region used to measure the forest. We explore a range of alternate masking strategies and demonstrate that these changes have minimal impact on the BAO measurements with both DESI data and synthetic data. This includes when we mask the BAL features associated with emission lines outside of the forest region to minimize their contribution to redshift errors. We identify differences in the properties of BALs in the synthetic datasets relative to the observational data, as well as use the synthetic observations to characterize the completeness of the BAL identification algorithm, and demonstrate that incompleteness and differences in the BALs between real and synthetic data also do not impact the BAO results for the Lyα forest.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>dark energy experiments</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/20f4w28b</dc:identifier><dc:identifier>https://escholarship.org/content/qt20f4w28b/qt20f4w28b.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/137</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>137</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt442129hp</identifier><datestamp>2026-09-16T04:25:35Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt442129hp</dc:identifier><dc:title>Synthetic spectra for Lyman-α forest analysis in the Dark Energy Spectroscopic Instrument</dc:title><dc:creator>Herrera-Alcantar, Hiram K</dc:creator><dc:creator>Muñoz-Gutiérrez, Andrea</dc:creator><dc:creator>Tan, Ting</dc:creator><dc:creator>González-Morales, Alma X</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>Guy, Julien</dc:creator><dc:creator>Moustakas, John</dc:creator><dc:creator>Kirkby, David</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Bault, A</dc:creator><dc:creator>Cabayol-Garcia, L</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>de la Cruz, R</dc:creator><dc:creator>García, LÁ</dc:creator><dc:creator>Gordon, C</dc:creator><dc:creator>Iršič, V</dc:creator><dc:creator>Karaçaylı, NG</dc:creator><dc:creator>Le Goff, JM</dc:creator><dc:creator>Montero-Camacho, P</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Ramírez-Pérez, C</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Walther, M</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Levi, Michael E</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zhou, Z</dc:creator><dc:date>2025-01-01</dc:date><dc:description>Synthetic data sets are used in cosmology to test analysis procedures, to verify that systematic errors are well understood and to demonstrate that measurements are unbiased. In this work we describe the methods used to generate synthetic datasets of Lyman-α quasar spectra aimed for studies with the Dark Energy Spectroscopic Instrument (DESI). In particular, we focus on demonstrating that our simulations reproduces important features of real samples, making them suitable to test the analysis methods to be used in DESI and to place limits on systematic effects on measurements of Baryon Acoustic Oscillations (BAO). We present a set of mocks that reproduce the statistical properties of the DESI early data set with good agreement. Additionally, we use a synthetic dataset to forecast the BAO scale constraining power of the completed DESI survey through the Lyman-α forest.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>cosmological simulations</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/442129hp</dc:identifier><dc:identifier>https://escholarship.org/content/qt442129hp/qt442129hp.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/141</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>141 - 141</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6jn2057t</identifier><datestamp>2026-09-16T04:25:30Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6jn2057t</dc:identifier><dc:title>An analysis of parameter compression and Full-Modeling techniques with Velocileptors for DESI 2024 and beyond</dc:title><dc:creator>Maus, M</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>White, M</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Findlay, N</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lai, Y</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Noriega, HE</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Ramirez-Solano, S</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rocher, A</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yuan, S</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Zhang, H</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>In anticipation of forthcoming data releases of current and future spectroscopic surveys, we present the validation tests and analysis of systematic effects within velocileptors modeling pipeline when fitting mock data from the AbacusSummit N-body simulations. We compare the constraints obtained from parameter compression methods to the direct fitting (Full-Modeling) approaches of modeling the galaxy power spectra, and show that the ShapeFit extension to the traditional template method is consistent with the Full-Modeling method within the standard ΛCDM parameter space. We show the dependence on scale cuts when fitting the different redshift bins using the ShapeFit and Full-Modeling methods. We test the ability to jointly fit data from multiple redshift bins as well as joint analysis of the pre-reconstruction power spectrum with the post-reconstruction BAO correlation function signal. We further demonstrate the behavior of the model when opening up the parameter space beyond ΛCDM and also when combining likelihoods with external datasets, namely the Planck CMB priors. Finally, we describe different parametrization options for the galaxy bias, counterterm, and stochastic parameters, and employ the halo model in order to physically motivate suitable priors that are necessary to ensure the stability of the perturbation theory.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6jn2057t</dc:identifier><dc:identifier>https://escholarship.org/content/qt6jn2057t/qt6jn2057t.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/138</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>138</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9c75z2jn</identifier><datestamp>2026-09-16T04:25:15Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9c75z2jn</dc:identifier><dc:title>DESI 2024 IV: Baryon Acoustic Oscillations from the Lyman alpha forest</dc:title><dc:creator>Adame, AG</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alam, S</dc:creator><dc:creator>Alexander, DM</dc:creator><dc:creator>Alvarez, M</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Anand, A</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Avila, S</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Awan, H</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Baltay, C</dc:creator><dc:creator>Bault, A</dc:creator><dc:creator>Bautista, J</dc:creator><dc:creator>Behera, J</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Beutler, F</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Blake, C</dc:creator><dc:creator>Blum, R</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Buckley-Geer, E</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Calderon, R</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Cereskaite, R</dc:creator><dc:creator>Cervantes-Cota, JL</dc:creator><dc:creator>Chabanier, S</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Davis, TM</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Cruz, R</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Deiosso, N</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Ding, J</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Edelstein, J</dc:creator><dc:creator>Eftekharzadeh, S</dc:creator><dc:creator>Eisenstein, DJ</dc:creator><dc:creator>Elliott, A</dc:creator><dc:creator>Fagrelius, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Ereza, J</dc:creator><dc:creator>Findlay, N</dc:creator><dc:creator>Flaugher, B</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Sánchez, D</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gonzalez-Morales, AX</dc:creator><dc:creator>Gonzalez-Perez, V</dc:creator><dc:creator>Gordon, C</dc:creator><dc:creator>Green, D</dc:creator><dc:creator>Gruen, D</dc:creator><dc:creator>Gsponer, R</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hadzhiyska, B</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Hanif, MMS</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Iršič, V</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Karaçaylı, NG</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kent, S</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Krolewski, A</dc:creator><dc:creator>Lai, Y</dc:creator><dc:creator>Lan, T-W</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Lang, D</dc:creator><dc:creator>Lasker, J</dc:creator><dc:creator>Le Goff, JM</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:date>2025-01-01</dc:date><dc:description>We present the measurement of Baryon Acoustic Oscillations (BAO) from the Lyman-α (Lyα) forest of high-redshift quasars with the first-year dataset of the Dark Energy Spectroscopic Instrument (DESI). Our analysis uses over 420 000 Lyα forest spectra and their correlation with the spatial distribution of more than 700 000 quasars. An essential facet of this work is the development of a new analysis methodology on a blinded dataset. We conducted rigorous tests using synthetic data to ensure the reliability of our methodology and findings before unblinding. Additionally, we conducted multiple data splits to assess the consistency of the results and scrutinized various analysis approaches to confirm their robustness. For a given value of the sound horizon (rd ), we measure the expansion at z eff = 2.33 with 2% precision, H(z eff) = ( 239.2 ± 4.8 ) (147.09 Mpc /rd ) km/s/Mpc. Similarly, we present a 2.4% measurement of the transverse comoving distance to the same redshift, DM (z eff) = ( 5.84 ± 0.14 ) (rd /147.09 Mpc) Gpc. Together with other DESI BAO measurements at lower redshifts, these results are used in a companion paper to constrain cosmological parameters.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9c75z2jn</dc:identifier><dc:identifier>https://escholarship.org/content/qt9c75z2jn/qt9c75z2jn.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/124</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>124</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9gm8j3mb</identifier><datestamp>2026-09-16T04:25:09Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9gm8j3mb</dc:identifier><dc:title>The construction of large-scale structure catalogs for the Dark Energy Spectroscopic Instrument</dc:title><dc:creator>Ross, AJ</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alam, S</dc:creator><dc:creator>Anand, A</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Ereza, J</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gonzalez-Morales, AX</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Heydenreich, S</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Karim, T</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kong, H</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Krolewski, A</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Lasker, J</dc:creator><dc:creator>Guillou, LL</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>McDonald, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moon, J</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Napolitano, L</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Raichoor, A</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rosado-Marin, A</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Samushia, L</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlafly, EF</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Smith, A</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Valcin, D</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Wilson, MJ</dc:creator><dc:creator>Yu, J</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Zhao, C</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>We present the technical details on how large-scale structure (LSS) catalogs are constructed from redshifts measured from spectra observed by the Dark Energy Spectroscopic Instrument (DESI). The LSS catalogs provide the information needed to determine the relative number density of DESI tracers as a function of redshift and celestial coordinates and, e.g., determine clustering statistics. We produce catalogs that are weighted subsamples of the observed data, each matched to a weighted `random' catalog that forms an unclustered sampling of the probability density that DESI could have observed those data at each location. Precise knowledge of the DESI observing history and associated hardware performance allows for a determination of the DESI footprint and the number of times DESI has covered it at sub-arcsecond level precision. This enables the completeness of any DESI sample to be modeled at this same resolution. The pipeline developed to create LSS catalogs has been designed to easily allow robustness tests and enable future improvements. We describe how it allows ongoing work improving the match between galaxy and random catalogs, such as including further information when assigning redshifts to randoms, accounting for fluctuations in target density, accounting for variation in the redshift success rate, and accommodating blinding schemes.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9gm8j3mb</dc:identifier><dc:identifier>https://escholarship.org/content/qt9gm8j3mb/qt9gm8j3mb.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/125</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>125</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5q93c7nq</identifier><datestamp>2026-09-16T04:24:58Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5q93c7nq</dc:identifier><dc:title>Real-world clinical impact of plasma cell-free DNA metagenomic next-generation sequencing assay</dc:title><dc:creator>Kaur, Ishminder</dc:creator><dc:creator>Shaw, Bennett</dc:creator><dc:creator>Multani, Ashrit</dc:creator><dc:creator>Pham, Christine</dc:creator><dc:creator>Malhotra, Sanchi</dc:creator><dc:creator>Smith, Ethan</dc:creator><dc:creator>Adachi, Kristina</dc:creator><dc:creator>Allyn, Paul</dc:creator><dc:creator>Bango, Zackary</dc:creator><dc:creator>Beaird, Omer Eugene</dc:creator><dc:creator>Caldera</dc:creator><dc:creator>Chandrasekaran, Sukantha</dc:creator><dc:creator>Chan, Lynn</dc:creator><dc:creator>Cheema, Rabia</dc:creator><dc:creator>Daouk, Sarah</dc:creator><dc:creator>Deville, Jaime</dc:creator><dc:creator>Dong, Huan Vinh</dc:creator><dc:creator>Fan, Austin</dc:creator><dc:creator>Garner, Omai</dc:creator><dc:creator>Gaynor, Pryce</dc:creator><dc:creator>Gray, Hannah</dc:creator><dc:creator>Gorin, Aleksandr</dc:creator><dc:creator>Kalava, Sowmya</dc:creator><dc:creator>Kanatani, Meganne</dc:creator><dc:creator>Karnaze, Andrew</dc:creator><dc:creator>Saleh, Tawny</dc:creator><dc:creator>Sharma, Yamini</dc:creator><dc:creator>Stauber, Stacey</dc:creator><dc:creator>Vargas, Moises</dc:creator><dc:creator>Veral, Monette</dc:creator><dc:creator>Winston, Drew</dc:creator><dc:creator>Yanagimoto-Ogawa, Lauren</dc:creator><dc:creator>Aldrovandi, Grace</dc:creator><dc:creator>Nielsen-Saines, Karin</dc:creator><dc:creator>Fuller, Trevon</dc:creator><dc:creator>Jackson, Nicholas</dc:creator><dc:creator>Uslan, Daniel</dc:creator><dc:creator>Schaenman, Joanna</dc:creator><dc:creator>Vijayan, Tara</dc:creator><dc:creator>Sakona, Ashlyn</dc:creator><dc:creator>Yang, Shangxin</dc:creator><dc:date>2025-05-01</dc:date><dc:description>OBJECTIVE: To describe the real-world clinical impact of a commercially available plasma cell-free DNA metagenomic next-generation sequencing assay, the Karius test (KT).
METHODS: We retrospectively evaluated the clinical impact of KT by clinical panel adjudication. Descriptive statistics were used to study associations of diagnostic indications, host characteristics, and KT-generated microbiologic patterns with the clinical impact of KT. Multivariable logistic regression modeling was used to further characterize predictors of higher positive clinical impact.
RESULTS: We evaluated 1000 unique clinical cases of KT from 941 patients between January 1, 2017-August 31, 2023. The cohort included adult (70%) and pediatric (30%) patients. The overall clinical impact of KT was positive in 16%, negative in 2%, and no clinical impact in 82% of the cases. Among adult patients, multivariable logistic regression modeling showed that culture-negative endocarditis (OR 2.3; 95% CI, 1.11-4.53; P .022) and concern for fastidious/zoonotic/vector-borne pathogens (OR 2.1; 95% CI, 1.11-3.76; P .019) were associated with positive clinical impact of KT. Host immunocompromised status was not reliably associated with a positive clinical impact of KT (OR 1.03; 95% CI, 0.83-1.29; P .7806). No significant predictors of KT clinical impact were found in pediatric patients. Microbiologic result pattern was also a significant predictor of impact.
CONCLUSIONS: Our study highlights that despite the positive clinical impact of KT in select situations, most testing results had no clinical impact. We also confirm diagnostic indications where KT may have the highest yield, thereby generating tools for diagnostic stewardship.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>Biodefense (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Infection (hrcs-hc)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Retrospective Studies (mesh)</dc:subject><dc:subject>High-Throughput Nucleotide Sequencing (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Metagenomics (mesh)</dc:subject><dc:subject>Cell-Free Nucleic Acids (mesh)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Child</dc:subject><dc:subject>Preschool (mesh)</dc:subject><dc:subject>Adolescent (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:subject>Infant (mesh)</dc:subject><dc:subject>Aged</dc:subject><dc:subject>80 and over (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Retrospective Studies (mesh)</dc:subject><dc:subject>Adolescent (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Aged</dc:subject><dc:subject>80 and over (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Child</dc:subject><dc:subject>Preschool (mesh)</dc:subject><dc:subject>Infant (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:subject>Metagenomics (mesh)</dc:subject><dc:subject>High-Throughput Nucleotide Sequencing (mesh)</dc:subject><dc:subject>Cell-Free Nucleic Acids (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Retrospective Studies (mesh)</dc:subject><dc:subject>High-Throughput Nucleotide Sequencing (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Metagenomics (mesh)</dc:subject><dc:subject>Cell-Free Nucleic Acids (mesh)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Child</dc:subject><dc:subject>Preschool (mesh)</dc:subject><dc:subject>Adolescent (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:subject>Infant (mesh)</dc:subject><dc:subject>Aged</dc:subject><dc:subject>80 and over (mesh)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>Epidemiology (science-metrix)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:subject>42 Health sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5q93c7nq</dc:identifier><dc:identifier>https://escholarship.org/content/qt5q93c7nq/qt5q93c7nq.pdf</dc:identifier><dc:identifier>info:doi/10.1017/ice.2024.242</dc:identifier><dc:type>article</dc:type><dc:source>Infection Control and Hospital Epidemiology, vol 46, iss 5</dc:source><dc:coverage>504 - 511</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8ks5b73d</identifier><datestamp>2026-09-16T04:24:50Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8ks5b73d</dc:identifier><dc:title>Search for charged-lepton flavor violation in the production and decay of top quarks using trilepton final states in proton-proton collisions at s=13 TeV</dc:title><dc:creator>Hayrapetyan, A</dc:creator><dc:creator>Tumasyan, A</dc:creator><dc:creator>Adam, W</dc:creator><dc:creator>Andrejkovic, JW</dc:creator><dc:creator>Bergauer, T</dc:creator><dc:creator>Chatterjee, S</dc:creator><dc:creator>Damanakis, K</dc:creator><dc:creator>Dragicevic, M</dc:creator><dc:creator>Del Valle, A Escalante</dc:creator><dc:creator>Hussain, PS</dc:creator><dc:creator>Jeitler, M</dc:creator><dc:creator>Krammer, N</dc:creator><dc:creator>Liko, D</dc:creator><dc:creator>Mikulec, I</dc:creator><dc:creator>Schieck, J</dc:creator><dc:creator>Schöfbeck, R</dc:creator><dc:creator>Schwarz, D</dc:creator><dc:creator>Sonawane, M</dc:creator><dc:creator>Templ, S</dc:creator><dc:creator>Waltenberger, W</dc:creator><dc:creator>Wulz, C-E</dc:creator><dc:creator>Darwish, MR</dc:creator><dc:creator>Janssen, T</dc:creator><dc:creator>Van Mechelen, P</dc:creator><dc:creator>Bols, ES</dc:creator><dc:creator>D’Hondt, J</dc:creator><dc:creator>Dansana, S</dc:creator><dc:creator>De Moor, A</dc:creator><dc:creator>Delcourt, M</dc:creator><dc:creator>Faham, H El</dc:creator><dc:creator>Lowette, S</dc:creator><dc:creator>Makarenko, I</dc:creator><dc:creator>Müller, D</dc:creator><dc:creator>Sahasransu, AR</dc:creator><dc:creator>Tavernier, S</dc:creator><dc:creator>Tytgat, M</dc:creator><dc:creator>Van Putte, S</dc:creator><dc:creator>Vannerom, D</dc:creator><dc:creator>Clerbaux, B</dc:creator><dc:creator>De Lentdecker, G</dc:creator><dc:creator>Favart, L</dc:creator><dc:creator>Hohov, D</dc:creator><dc:creator>Jaramillo, J</dc:creator><dc:creator>Khalilzadeh, A</dc:creator><dc:creator>Lee, K</dc:creator><dc:creator>Mahdavikhorrami, M</dc:creator><dc:creator>Malara, A</dc:creator><dc:creator>Paredes, S</dc:creator><dc:creator>Pétré, L</dc:creator><dc:creator>Postiau, N</dc:creator><dc:creator>Thomas, L</dc:creator><dc:creator>Bemden, M Vanden</dc:creator><dc:creator>Vander Velde, C</dc:creator><dc:creator>Vanlaer, P</dc:creator><dc:creator>De Coen, M</dc:creator><dc:creator>Dobur, D</dc:creator><dc:creator>Hong, Y</dc:creator><dc:creator>Knolle, J</dc:creator><dc:creator>Lambrecht, L</dc:creator><dc:creator>Mestdach, G</dc:creator><dc:creator>Rendón, C</dc:creator><dc:creator>Samalan, A</dc:creator><dc:creator>Skovpen, K</dc:creator><dc:creator>Van Den Bossche, N</dc:creator><dc:creator>Wezenbeek, L</dc:creator><dc:creator>Benecke, A</dc:creator><dc:creator>Bruno, G</dc:creator><dc:creator>Caputo, C</dc:creator><dc:creator>Delaere, C</dc:creator><dc:creator>Donertas, IS</dc:creator><dc:creator>Giammanco, A</dc:creator><dc:creator>Jaffel, K</dc:creator><dc:creator>Jain</dc:creator><dc:creator>Lemaitre, V</dc:creator><dc:creator>Lidrych, J</dc:creator><dc:creator>Mastrapasqua, P</dc:creator><dc:creator>Mondal, K</dc:creator><dc:creator>Tran, TT</dc:creator><dc:creator>Wertz, S</dc:creator><dc:creator>Alves, GA</dc:creator><dc:creator>Coelho, E</dc:creator><dc:creator>Hensel, C</dc:creator><dc:creator>De Oliveira, T Menezes</dc:creator><dc:creator>Moraes, A</dc:creator><dc:creator>Teles, P Rebello</dc:creator><dc:creator>Soeiro, M</dc:creator><dc:creator>Júnior, WL Aldá</dc:creator><dc:creator>Pereira, M Alves Gallo</dc:creator><dc:creator>Filho, M Barroso Ferreira</dc:creator><dc:creator>Malbouisson, H Brandao</dc:creator><dc:creator>Carvalho, W</dc:creator><dc:creator>Chinellato, J</dc:creator><dc:creator>Da Costa, EM</dc:creator><dc:creator>Da Silveira, GG</dc:creator><dc:creator>De Jesus Damiao, D</dc:creator><dc:creator>De Souza, S Fonseca</dc:creator><dc:creator>Martins, J</dc:creator><dc:creator>Herrera, C Mora</dc:creator><dc:creator>Amarilo, K Mota</dc:creator><dc:creator>Mundim, L</dc:creator><dc:date>2025-01-01</dc:date><dc:description>A search is performed for charged-lepton flavor violating processes in top quark (  ) production and decay. The data were collected by the CMS experiment from proton-proton collisions at a center-of-mass energy of 13&amp;nbsp;TeV and correspond to an integrated luminosity of  . The selected events are required to contain one opposite-sign electron-muon pair, a third charged lepton (electron or muon), and at least one jet of which no more than one is associated with a bottom quark. Boosted decision trees are used to distinguish signal from background, exploiting differences in the kinematics of the final states particles. The data are consistent with the standard model expectation. Upper limits at 95%&amp;nbsp;confidence level are placed in the context of effective field theory on the Wilson coefficients, which range between  depending on the flavor of the associated light quark and the Lorentz structure of the interaction. These limits are converted to upper limits on branching fractions involving up (charm) quarks,  (  ), of  ,  , and  for tensorlike, vectorlike, and scalarlike interactions, respectively.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>4902 Mathematical Physics (for-2020)</dc:subject><dc:subject>49 Mathematical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8ks5b73d</dc:identifier><dc:identifier>https://escholarship.org/content/qt8ks5b73d/qt8ks5b73d.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevd.111.012009</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 111, iss 1</dc:source><dc:coverage>012009</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5jq3z5r6</identifier><datestamp>2026-09-16T04:24:20Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5jq3z5r6</dc:identifier><dc:title>Integer points in arbitrary convex cones: the case of the PSD and SOC cones</dc:title><dc:creator>De Loera, Jesús A</dc:creator><dc:creator>Marsters, Brittney</dc:creator><dc:creator>Xu, Luze</dc:creator><dc:creator>Zhang, Shixuan</dc:creator><dc:date>2026-03-01</dc:date><dc:description>We investigate the semigroup of integer points inside a convex cone. We extend classical results in integer linear programming to integer conic programming. We show that the semigroup associated with nonpolyhedral cones can sometimes have a notion of finite generating set with the help of a group action. We show this is true for the cone of positive semidefinite matrices (PSD) and the second-order cone (SOC). Both cones have a finite generating set of integer points, similar in spirit to Hilbert bases, under the action of a finitely generated group. We also extend notions of total dual integrality, Gomory-Chvátal closure, and Carathéodory rank to integer points in arbitrary cones.</dc:description><dc:subject>4901 Applied Mathematics (for-2020)</dc:subject><dc:subject>4903 Numerical and Computational Mathematics (for-2020)</dc:subject><dc:subject>4904 Pure Mathematics (for-2020)</dc:subject><dc:subject>49 Mathematical Sciences (for-2020)</dc:subject><dc:subject>Integer points</dc:subject><dc:subject>Convex cones</dc:subject><dc:subject>Semigroups</dc:subject><dc:subject>Hilbert bases</dc:subject><dc:subject>Conic programming</dc:subject><dc:subject>Positive semidefinite Cone</dc:subject><dc:subject>Second-order cone</dc:subject><dc:subject>0102 Applied Mathematics (for)</dc:subject><dc:subject>0103 Numerical and Computational Mathematics (for)</dc:subject><dc:subject>0802 Computation Theory and Mathematics (for)</dc:subject><dc:subject>Operations Research (science-metrix)</dc:subject><dc:subject>4613 Theory of computation (for-2020)</dc:subject><dc:subject>4901 Applied mathematics (for-2020)</dc:subject><dc:subject>4903 Numerical and computational mathematics (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5jq3z5r6</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1007/s10107-024-02188-8</dc:identifier><dc:type>article</dc:type><dc:source>Mathematical Programming, vol 216, iss 1-2</dc:source><dc:coverage>3 - 27</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt35053859</identifier><datestamp>2026-09-16T04:11:19Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt35053859</dc:identifier><dc:title>Yrast structures of Nb98 and Mo99</dc:title><dc:creator>Fotiades, N</dc:creator><dc:creator>Cizewski, JA</dc:creator><dc:creator>Fallon, P</dc:creator><dc:creator>Kevrekidis, PG</dc:creator><dc:creator>Krücken, R</dc:creator><dc:creator>Lee, IY</dc:creator><dc:date>2025-01-01</dc:date><dc:description>Background: Neutron-rich nuclei in the A≈100 mass region are interesting due to a rapid shape transition, especially pronounced in the Zr isotopes, and more recently observed in Nb isotopes. Nb98, with only one proton and one neutron outside the subshell closure nucleus of Zr96, is amenable to shell model calculations. Purpose: To further examine the rapid shape transition, the yrast structure of Nb98 was established in this work. This was the only yrast structure missing from all immediate neighbors to Zr96. Method: The yrast structure of Nb98 was studied in the fission of the compound systems formed in three heavy-ion induced reactions, Mg24 (134.5 MeV) +Yb173, Na23 (129 MeV) +Yb176, and O18 (91 MeV) +Pb208. Prompt γ-ray spectroscopy was accomplished using the Gammasphere array. Results: Excitation energies up to 3 MeV were observed for the first time in Nb98. The yrast structure above the previously known (5)+ isomer was established. In the process of studying Nb98 the yrast structure of positive-parity states in Mo99 was extended to 3.7 MeV excitation energy, the previously known Nb99 level scheme was enriched, and two new levels were added in the level scheme of Zr97. Conclusions: The coupling of the odd proton occupying the g9/2 orbital to the yrast states in the core nucleus of Zr97 can account for all observed states in Nb98. The yrast structure for the positive-parity states of Mo99 is compared to the deformed ground-state bands of the Ru101 isotone and of Mo98,100.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>NSD-Low Energy Nuclear Physics (c-lbnl-label)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/35053859</dc:identifier><dc:identifier>https://escholarship.org/content/qt35053859/qt35053859.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevc.111.014316</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review C, vol 111, iss 1</dc:source><dc:coverage>014316</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt23n2s341</identifier><datestamp>2026-09-16T04:10:42Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt23n2s341</dc:identifier><dc:title>The projected background for the CUORE experiment</dc:title><dc:creator>Alduino, C</dc:creator><dc:creator>Alfonso, K</dc:creator><dc:creator>Artusa, DR</dc:creator><dc:creator>Avignone, FT</dc:creator><dc:creator>Azzolini, O</dc:creator><dc:creator>Banks, TI</dc:creator><dc:creator>Bari, G</dc:creator><dc:creator>Beeman, JW</dc:creator><dc:creator>Bellini, F</dc:creator><dc:creator>Benato, G</dc:creator><dc:creator>Bersani, A</dc:creator><dc:creator>Biassoni, M</dc:creator><dc:creator>Branca, A</dc:creator><dc:creator>Brofferio, C</dc:creator><dc:creator>Bucci, C</dc:creator><dc:creator>Camacho, A</dc:creator><dc:creator>Caminata, A</dc:creator><dc:creator>Canonica, L</dc:creator><dc:creator>Cao, XG</dc:creator><dc:creator>Capelli, S</dc:creator><dc:creator>Cappelli, L</dc:creator><dc:creator>Carbone, L</dc:creator><dc:creator>Cardani, L</dc:creator><dc:creator>Carniti, P</dc:creator><dc:creator>Casali, N</dc:creator><dc:creator>Cassina, L</dc:creator><dc:creator>Chiesa, D</dc:creator><dc:creator>Chott, N</dc:creator><dc:creator>Clemenza, M</dc:creator><dc:creator>Copello, S</dc:creator><dc:creator>Cosmelli, C</dc:creator><dc:creator>Cremonesi, O</dc:creator><dc:creator>Creswick, RJ</dc:creator><dc:creator>Cushman, JS</dc:creator><dc:creator>D’Addabbo, A</dc:creator><dc:creator>Dafinei, I</dc:creator><dc:creator>Davis, CJ</dc:creator><dc:creator>Dell’Oro, S</dc:creator><dc:creator>Deninno, MM</dc:creator><dc:creator>Di Domizio, S</dc:creator><dc:creator>Di Vacri, ML</dc:creator><dc:creator>Drobizhev, A</dc:creator><dc:creator>Fang, DQ</dc:creator><dc:creator>Faverzani, M</dc:creator><dc:creator>Fernandes, G</dc:creator><dc:creator>Ferri, E</dc:creator><dc:creator>Ferroni, F</dc:creator><dc:creator>Fiorini, E</dc:creator><dc:creator>Franceschi, MA</dc:creator><dc:creator>Freedman, SJ</dc:creator><dc:creator>Fujikawa, BK</dc:creator><dc:creator>Giachero, A</dc:creator><dc:creator>Gironi, L</dc:creator><dc:creator>Giuliani, A</dc:creator><dc:creator>Gladstone, L</dc:creator><dc:creator>Gorla, P</dc:creator><dc:creator>Gotti, C</dc:creator><dc:creator>Gutierrez, TD</dc:creator><dc:creator>Haller, EE</dc:creator><dc:creator>Han, K</dc:creator><dc:creator>Hansen, E</dc:creator><dc:creator>Heeger, KM</dc:creator><dc:creator>Hennings-Yeomans, R</dc:creator><dc:creator>Hickerson, KP</dc:creator><dc:creator>Huang, HZ</dc:creator><dc:creator>Kadel, R</dc:creator><dc:creator>Keppel, G</dc:creator><dc:creator>Kolomensky, Yu G</dc:creator><dc:creator>Leder, A</dc:creator><dc:creator>Ligi, C</dc:creator><dc:creator>Lim, KE</dc:creator><dc:creator>Ma, YG</dc:creator><dc:creator>Maino, M</dc:creator><dc:creator>Marini, L</dc:creator><dc:creator>Martinez, M</dc:creator><dc:creator>Maruyama, RH</dc:creator><dc:creator>Mei, Y</dc:creator><dc:creator>Moggi, N</dc:creator><dc:creator>Morganti, S</dc:creator><dc:creator>Mosteiro, PJ</dc:creator><dc:creator>Napolitano, T</dc:creator><dc:creator>Nastasi, M</dc:creator><dc:creator>Nones, C</dc:creator><dc:creator>Norman, EB</dc:creator><dc:creator>Novati, V</dc:creator><dc:creator>Nucciotti, A</dc:creator><dc:creator>O’Donnell, T</dc:creator><dc:creator>Ouellet, JL</dc:creator><dc:creator>Pagliarone, CE</dc:creator><dc:creator>Pallavicini, M</dc:creator><dc:creator>Palmieri, V</dc:creator><dc:creator>Pattavina, L</dc:creator><dc:creator>Pavan, M</dc:creator><dc:creator>Pessina, G</dc:creator><dc:creator>Pettinacci, V</dc:creator><dc:creator>Piperno, G</dc:creator><dc:creator>Pira, C</dc:creator><dc:creator>Pirro, S</dc:creator><dc:creator>Pozzi, S</dc:creator><dc:creator>Previtali, E</dc:creator><dc:date>2017-08-01</dc:date><dc:description>The Cryogenic Underground Observatory for Rare Events (CUORE) is designed to search for neutrinoless double beta decay of 130$$^{130}$$Te with an array of 988 TeO2$$_2$$&amp;nbsp;bolometers operating at temperatures around 10 mK. The experiment is currently being commissioned in Hall A of Laboratori Nazionali del Gran Sasso, Italy. The goal of CUORE is to reach a 90% C.L. exclusion sensitivity on the 130$$^{130}$$Te decay half-life of 9 ×$$\times $$ 1025$$^{25}$$ years after 5&amp;nbsp;years of data taking. The main issue to be addressed to accomplish this aim is the rate of background events in the region of interest, which must not be higher than 10-2$$^{-2}$$&amp;nbsp;counts/keV/kg/year. We developed a detailed Monte Carlo simulation, based on results from a campaign of material screening, radioassays, and bolometric measurements, to evaluate the expected background. This was used over the years to guide the construction strategies of the experiment and we use it here to project a background model for CUORE. In this paper we report the results of our study and our expectations for the background rate in the energy region where the peak signature of neutrinoless double beta decay of 130$$^{130}$$Te is expected.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>physics.ins-det</dc:subject><dc:subject>physics.ins-det</dc:subject><dc:subject>NSD-Neutrinos (c-lbnl-label)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5102 Atomic</dc:subject><dc:subject>molecular and optical physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/23n2s341</dc:identifier><dc:identifier>https://escholarship.org/content/qt23n2s341/qt23n2s341.pdf</dc:identifier><dc:identifier>info:doi/10.1140/epjc/s10052-017-5080-6</dc:identifier><dc:type>article</dc:type><dc:source>European Physical Journal C, vol 77, iss 8</dc:source><dc:coverage>543</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3cj6g8cd</identifier><datestamp>2026-09-16T04:07:06Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3cj6g8cd</dc:identifier><dc:title>Towards machine learning assisted TORIC-PetraM ICRF core-edge coupling</dc:title><dc:creator>Sánchez-Villar</dc:creator><dc:creator>Bai, Z</dc:creator><dc:creator>Bertelli, N</dc:creator><dc:creator>Bethel, EW</dc:creator><dc:creator>Hillairet, J</dc:creator><dc:creator>Perciano, T</dc:creator><dc:creator>Shiraiwa, S</dc:creator><dc:creator>Wallace, GM</dc:creator><dc:creator>Wright, JC</dc:creator><dc:date>2024-01-01</dc:date><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3cj6g8cd</dc:identifier><dc:identifier/><dc:type>article</dc:type><dc:source>50th Eps Conference on Plasma Physics Eps 2024</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2fd2j700</identifier><datestamp>2026-09-16T04:01:45Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2fd2j700</dc:identifier><dc:title>Associations of prenatal urinary melamine, melamine analogues, and aromatic amines with gestational duration and fetal growth in the ECHO Cohort</dc:title><dc:creator>Choi, Giehae</dc:creator><dc:creator>Xun, Xiaoshuang</dc:creator><dc:creator>Bennett, Deborah H</dc:creator><dc:creator>Meeker, John D</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Sathyanarayana, Sheela</dc:creator><dc:creator>Schantz, Susan L</dc:creator><dc:creator>Trasande, Leonardo</dc:creator><dc:creator>Watkins, Deborah</dc:creator><dc:creator>Pellizzari, Edo D</dc:creator><dc:creator>Li, Wenlong</dc:creator><dc:creator>Kannan, Kurunthachalam</dc:creator><dc:creator>Woodruff, Tracey J</dc:creator><dc:creator>Buckley, Jessie P</dc:creator><dc:creator>Consortium, for the ECHO Cohort</dc:creator><dc:date>2025-01-01</dc:date><dc:description>Melamine, its analogues, and aromatic amines (AAs) were commonly detected in a previous study of pregnant women in the Environmental influences on Child Health Outcomes (ECHO) Cohort. While these chemicals have identified toxicities, little is known about their influences on fetal development. We measured these chemicals in gestational urine samples in 3 ECHO cohort sites to assess associations with birth outcomes (n&amp;nbsp;=&amp;nbsp;1,231). We estimated beta coefficients and 95% confidence intervals (CIs) using adjusted linear mixed models with continuous dilution-standardized concentrations (log2 transformed and scaled by interquartile range, IQR) or binary indicators for detection. As secondary analyses, we repeated analyses using categorical outcomes. Forty-one of 45 analytes were detected in at least one sample, with&amp;nbsp;&amp;gt;&amp;nbsp;95&amp;nbsp;% detection of melamine, cyanuric acid, ammelide, and aniline. Higher melamine concentration was associated with longer gestational age (β^ per IQR increase of log2-transformed: 0.082 [95&amp;nbsp;% CI: -0.012, 0.177]; 2nd vs 1st tertile: 0.173 [-0.048, 0.394]; 3rd vs 1st tertile: 0.186 [-0.035, 0.407]). Similarly in secondary analyses using categorical outcomes, an IQR increase in log2(melamine) was associated with 1.22 [0.99, 1.50] higher odds of post-term (&amp;gt;40 &amp;amp; ≤42&amp;nbsp;weeks) as compared to full-term (≥38 &amp;amp; ≤40&amp;nbsp;weeks). Several AAs were associated with birthweight and gestational length, with the direction of associations varying by AA. Some stronger associations were observed in females. Our findings suggest melamine and its analogs and AAs may influence gestational length and birthweight.</dc:description><dc:subject>3215 Reproductive Medicine (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Pregnancy (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Infant Mortality (rcdc)</dc:subject><dc:subject>Perinatal Period - Conditions Originating in Perinatal Period (rcdc)</dc:subject><dc:subject>Conditions Affecting the Embryonic and Fetal Periods (rcdc)</dc:subject><dc:subject>Triazines (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Fetal Development (mesh)</dc:subject><dc:subject>Gestational Age (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Maternal Exposure (mesh)</dc:subject><dc:subject>Amines (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Melamine</dc:subject><dc:subject>Cyanuric acid</dc:subject><dc:subject>Aromatic amines</dc:subject><dc:subject>Gestational age</dc:subject><dc:subject>Birthweight</dc:subject><dc:subject>Preterm birth</dc:subject><dc:subject>Low birthweight</dc:subject><dc:subject>Large for gestational age</dc:subject><dc:subject>Small for gestational age</dc:subject><dc:subject>ECHO Cohort Consortium</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Amines (mesh)</dc:subject><dc:subject>Triazines (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Maternal Exposure (mesh)</dc:subject><dc:subject>Fetal Development (mesh)</dc:subject><dc:subject>Gestational Age (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Aromatic amines</dc:subject><dc:subject>Birthweight</dc:subject><dc:subject>Cyanuric acid</dc:subject><dc:subject>Gestational age</dc:subject><dc:subject>Large for gestational age</dc:subject><dc:subject>Low birthweight</dc:subject><dc:subject>Melamine</dc:subject><dc:subject>Preterm birth</dc:subject><dc:subject>Small for gestational age</dc:subject><dc:subject>Triazines (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Fetal Development (mesh)</dc:subject><dc:subject>Gestational Age (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Maternal Exposure (mesh)</dc:subject><dc:subject>Amines (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Environmental Sciences (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2fd2j700</dc:identifier><dc:identifier>https://escholarship.org/content/qt2fd2j700/qt2fd2j700.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.envint.2024.109227</dc:identifier><dc:type>article</dc:type><dc:source>Environment International, vol 195</dc:source><dc:coverage>109227</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt65r1f8q5</identifier><datestamp>2026-09-16T04:00:56Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt65r1f8q5</dc:identifier><dc:title>Girth and groomed radius of jets recoiling against isolated photons in lead-lead and proton-proton collisions at s NN = 5.02 &amp;nbsp;TeV</dc:title><dc:creator>Hayrapetyan, A</dc:creator><dc:creator>Tumasyan, A</dc:creator><dc:creator>Adam, W</dc:creator><dc:creator>Andrejkovic, JW</dc:creator><dc:creator>Bergauer, T</dc:creator><dc:creator>Chatterjee, S</dc:creator><dc:creator>Damanakis, K</dc:creator><dc:creator>Dragicevic, M</dc:creator><dc:creator>Hussain, PS</dc:creator><dc:creator>Jeitler, M</dc:creator><dc:creator>Krammer, N</dc:creator><dc:creator>Li, A</dc:creator><dc:creator>Liko, D</dc:creator><dc:creator>Mikulec, I</dc:creator><dc:creator>Schieck, J</dc:creator><dc:creator>Schöfbeck, R</dc:creator><dc:creator>Schwarz, D</dc:creator><dc:creator>Sonawane, M</dc:creator><dc:creator>Templ, S</dc:creator><dc:creator>Waltenberger, W</dc:creator><dc:creator>Wulz, C-E</dc:creator><dc:creator>Darwish, MR</dc:creator><dc:creator>Janssen, T</dc:creator><dc:creator>Van Mechelen, P</dc:creator><dc:creator>Bols, ES</dc:creator><dc:creator>D'Hondt, J</dc:creator><dc:creator>Dansana, S</dc:creator><dc:creator>De Moor, A</dc:creator><dc:creator>Delcourt, M</dc:creator><dc:creator>Lowette, S</dc:creator><dc:creator>Makarenko, I</dc:creator><dc:creator>Müller, D</dc:creator><dc:creator>Tavernier, S</dc:creator><dc:creator>Tytgat, M</dc:creator><dc:creator>Van Onsem, GP</dc:creator><dc:creator>Van Putte, S</dc:creator><dc:creator>Vannerom, D</dc:creator><dc:creator>Clerbaux, B</dc:creator><dc:creator>Das, AK</dc:creator><dc:creator>De Lentdecker, G</dc:creator><dc:creator>Evard, H</dc:creator><dc:creator>Favart, L</dc:creator><dc:creator>Gianneios, P</dc:creator><dc:creator>Hohov, D</dc:creator><dc:creator>Jaramillo, J</dc:creator><dc:creator>Khalilzadeh, A</dc:creator><dc:creator>Khan, FA</dc:creator><dc:creator>Lee, K</dc:creator><dc:creator>Mahdavikhorrami, M</dc:creator><dc:creator>Malara, A</dc:creator><dc:creator>Paredes, S</dc:creator><dc:creator>Thomas, L</dc:creator><dc:creator>Bemden, M Vanden</dc:creator><dc:creator>Vander Velde, C</dc:creator><dc:creator>Vanlaer, P</dc:creator><dc:creator>De Coen, M</dc:creator><dc:creator>Dobur, D</dc:creator><dc:creator>Hong, Y</dc:creator><dc:creator>Knolle, J</dc:creator><dc:creator>Lambrecht, L</dc:creator><dc:creator>Mestdach, G</dc:creator><dc:creator>Amarilo, K Mota</dc:creator><dc:creator>Rendón, C</dc:creator><dc:creator>Samalan, A</dc:creator><dc:creator>Skovpen, K</dc:creator><dc:creator>Van Den Bossche, N</dc:creator><dc:creator>van der Linden, J</dc:creator><dc:creator>Wezenbeek, L</dc:creator><dc:creator>Benecke, A</dc:creator><dc:creator>Bethani, A</dc:creator><dc:creator>Bruno, G</dc:creator><dc:creator>Caputo, C</dc:creator><dc:creator>Delaere, C</dc:creator><dc:creator>Donertas, IS</dc:creator><dc:creator>Giammanco, A</dc:creator><dc:creator>Jain</dc:creator><dc:creator>Lemaitre, V</dc:creator><dc:creator>Lidrych, J</dc:creator><dc:creator>Mastrapasqua, P</dc:creator><dc:creator>Tran, TT</dc:creator><dc:creator>Wertz, S</dc:creator><dc:creator>Alves, GA</dc:creator><dc:creator>Coelho, E</dc:creator><dc:creator>Hensel, C</dc:creator><dc:creator>De Oliveira, T Menezes</dc:creator><dc:creator>Moraes, A</dc:creator><dc:creator>Teles, P Rebello</dc:creator><dc:creator>Soeiro, M</dc:creator><dc:creator>Júnior, WL Aldá</dc:creator><dc:creator>Pereira, M Alves Gallo</dc:creator><dc:creator>Filho, M Barroso Ferreira</dc:creator><dc:creator>Malbouisson, H Brandao</dc:creator><dc:creator>Carvalho, W</dc:creator><dc:creator>Chinellato, J</dc:creator><dc:creator>Da Costa, EM</dc:creator><dc:creator>Da Silveira, GG</dc:creator><dc:creator>De Jesus Damiao, D</dc:creator><dc:creator>De Souza, S Fonseca</dc:creator><dc:creator>De Souza, R Gomes</dc:creator><dc:creator>Martins, J</dc:creator><dc:date>2025-02-01</dc:date><dc:description>This Letter presents the first measurements of the groomed jet radius R g and the jet girth g in events with an isolated photon recoiling against a jet in lead-lead (PbPb) and proton-proton (pp) collisions at the LHC at a nucleon-nucleon center-of-mass energy of 5.02 TeV. The observables R g and g provide a quantitative measure of how narrow or broad a jet is. The analysis uses PbPb and pp data samples with integrated luminosities of 1.7 &amp;nbsp;nb − 1 and 301 &amp;nbsp;pb − 1 , respectively, collected with the CMS experiment in 2018 and 2017. Events are required to have a photon with transverse momentum p T γ &amp;gt; 100 &amp;nbsp;GeV and at least one jet back-to-back in azimuth with respect to the photon and with transverse momentum p T jet such that p T jet / p T γ &amp;gt; 0.4 . The measured R g and g distributions are unfolded to the particle level, which facilitates the comparison between the PbPb and pp results and with theoretical predictions. It is found that jets with p T jet / p T γ &amp;gt; 0.8 , i.e., those that closely balance the photon p T γ , are narrower in PbPb than in pp collisions. Relaxing the selection to include jets with p T jet / p T γ &amp;gt; 0.4 reduces the narrowing of the angular structure of jets in PbPb relative to the pp reference. This shows that selection bias effects associated with jet energy loss play an important role in the interpretation of jet substructure measurements.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>CMS</dc:subject><dc:subject>Jet substructure</dc:subject><dc:subject>Gluons</dc:subject><dc:subject>Jets</dc:subject><dc:subject>Photon</dc:subject><dc:subject>Lead-lead</dc:subject><dc:subject>Proton-proton</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/65r1f8q5</dc:identifier><dc:identifier>https://escholarship.org/content/qt65r1f8q5/qt65r1f8q5.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.physletb.2024.139088</dc:identifier><dc:type>article</dc:type><dc:source>Physics Letters B, vol 861</dc:source><dc:coverage>139088</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt84w4k34d</identifier><datestamp>2026-09-16T04:00:44Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt84w4k34d</dc:identifier><dc:title>Constraints on the Higgs boson self-coupling from the combination of single and double Higgs boson production in proton-proton collisions at s = 13 TeV</dc:title><dc:creator>Hayrapetyan, A</dc:creator><dc:creator>Tumasyan, A</dc:creator><dc:creator>Adam, W</dc:creator><dc:creator>Andrejkovic, JW</dc:creator><dc:creator>Bergauer, T</dc:creator><dc:creator>Chatterjee, S</dc:creator><dc:creator>Damanakis, K</dc:creator><dc:creator>Dragicevic, M</dc:creator><dc:creator>Hussain, PS</dc:creator><dc:creator>Jeitler, M</dc:creator><dc:creator>Krammer, N</dc:creator><dc:creator>Li, A</dc:creator><dc:creator>Liko, D</dc:creator><dc:creator>Mikulec, I</dc:creator><dc:creator>Schieck, J</dc:creator><dc:creator>Schöfbeck, R</dc:creator><dc:creator>Schwarz, D</dc:creator><dc:creator>Sonawane, M</dc:creator><dc:creator>Templ, S</dc:creator><dc:creator>Waltenberger, W</dc:creator><dc:creator>Wulz, C-E</dc:creator><dc:creator>Darwish, MR</dc:creator><dc:creator>Janssen, T</dc:creator><dc:creator>Van Laer, T</dc:creator><dc:creator>Van Mechelen, P</dc:creator><dc:creator>Breugelmans, N</dc:creator><dc:creator>D'Hondt, J</dc:creator><dc:creator>Dansana, S</dc:creator><dc:creator>De Moor, A</dc:creator><dc:creator>Delcourt, M</dc:creator><dc:creator>Heyen, F</dc:creator><dc:creator>Lowette, S</dc:creator><dc:creator>Makarenko, I</dc:creator><dc:creator>Müller, D</dc:creator><dc:creator>Tavernier, S</dc:creator><dc:creator>Tytgat, M</dc:creator><dc:creator>Van Onsem, GP</dc:creator><dc:creator>Van Putte, S</dc:creator><dc:creator>Vannerom, D</dc:creator><dc:creator>Bilin, B</dc:creator><dc:creator>Clerbaux, B</dc:creator><dc:creator>Das, AK</dc:creator><dc:creator>De Lentdecker, G</dc:creator><dc:creator>Evard, H</dc:creator><dc:creator>Favart, L</dc:creator><dc:creator>Gianneios, P</dc:creator><dc:creator>Jaramillo, J</dc:creator><dc:creator>Khalilzadeh, A</dc:creator><dc:creator>Khan, FA</dc:creator><dc:creator>Lee, K</dc:creator><dc:creator>Mahdavikhorrami, M</dc:creator><dc:creator>Malara, A</dc:creator><dc:creator>Paredes, S</dc:creator><dc:creator>Shahzad, MA</dc:creator><dc:creator>Thomas, L</dc:creator><dc:creator>Bemden, M Vanden</dc:creator><dc:creator>Vander Velde, C</dc:creator><dc:creator>Vanlaer, P</dc:creator><dc:creator>De Coen, M</dc:creator><dc:creator>Dobur, D</dc:creator><dc:creator>Gokbulut, G</dc:creator><dc:creator>Hong, Y</dc:creator><dc:creator>Knolle, J</dc:creator><dc:creator>Lambrecht, L</dc:creator><dc:creator>Marckx, D</dc:creator><dc:creator>Amarilo, K Mota</dc:creator><dc:creator>Samalan, A</dc:creator><dc:creator>Skovpen, K</dc:creator><dc:creator>Van Den Bossche, N</dc:creator><dc:creator>van der Linden, J</dc:creator><dc:creator>Wezenbeek, L</dc:creator><dc:creator>Benecke, A</dc:creator><dc:creator>Bethani, A</dc:creator><dc:creator>Bruno, G</dc:creator><dc:creator>Caputo, C</dc:creator><dc:creator>De Jeneret, J De Favereau</dc:creator><dc:creator>Delaere, C</dc:creator><dc:creator>Donertas, IS</dc:creator><dc:creator>Giammanco, A</dc:creator><dc:creator>Guzel, AO</dc:creator><dc:creator>Jain</dc:creator><dc:creator>Lemaitre, V</dc:creator><dc:creator>Lidrych, J</dc:creator><dc:creator>Mastrapasqua, P</dc:creator><dc:creator>Tran, TT</dc:creator><dc:creator>Wertz, S</dc:creator><dc:creator>Alves, GA</dc:creator><dc:creator>Pereira, M Alves Gallo</dc:creator><dc:creator>Coelho, E</dc:creator><dc:creator>Silva, G Correia</dc:creator><dc:creator>Hensel, C</dc:creator><dc:creator>De Oliveira, T Menezes</dc:creator><dc:creator>Moraes, A</dc:creator><dc:creator>Teles, P Rebello</dc:creator><dc:creator>Soeiro, M</dc:creator><dc:creator>Pereira, A Vilela</dc:creator><dc:creator>Júnior, WL Aldá</dc:creator><dc:creator>Filho, M Barroso Ferreira</dc:creator><dc:creator>Malbouisson, H Brandao</dc:creator><dc:creator>Carvalho, W</dc:creator><dc:date>2025-02-01</dc:date><dc:description>The Higgs boson (H) trilinear self-coupling, λ 3 , is constrained via its measured properties and limits on the HH pair production using the proton-proton collision data collected by the CMS experiment at s = 13 TeV . The combination of event categories enriched in single-H and HH events is used to measure κ λ , defined as the value of λ 3 normalized to its standard model prediction, while simultaneously constraining the Higgs boson couplings to fermions and vector bosons. Values of κ λ outside the interval − 1.2 &amp;lt; κ λ &amp;lt; 7.5 are excluded at 2σ confidence level, which is compatible with the expected range of − 2.0 &amp;lt; κ λ &amp;lt; 7.7 under the assumption that all other Higgs boson couplings are equal to their standard model predicted values. Relaxing the assumption on the Higgs couplings to fermions and vector bosons the observed (expected) κ λ interval is constrained to be within − 1.4 &amp;lt; κ λ &amp;lt; 7.8 ( − 2.3 &amp;lt; κ λ &amp;lt; 7.8 ) at 2σ confidence level.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>CMS</dc:subject><dc:subject>Higgs</dc:subject><dc:subject>HH</dc:subject><dc:subject>Di-Higgs</dc:subject><dc:subject>Self-coupling</dc:subject><dc:subject>Combination</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/84w4k34d</dc:identifier><dc:identifier>https://escholarship.org/content/qt84w4k34d/qt84w4k34d.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.physletb.2024.139210</dc:identifier><dc:type>article</dc:type><dc:source>Physics Letters B, vol 861</dc:source><dc:coverage>139210</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1df7z10n</identifier><datestamp>2026-09-16T03:56:40Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1df7z10n</dc:identifier><dc:title>Crack Identification and Characterization in Deformed Nb3Sn Rutherford Cable Stacks Using Machine Learning</dc:title><dc:creator>Croteau, Jean-Francois</dc:creator><dc:creator>Vallone, Giorgio</dc:creator><dc:creator>Menon, Nandana</dc:creator><dc:creator>D'Addazio, Marika</dc:creator><dc:creator>Niccoli, Fabrizio</dc:creator><dc:creator>Pong, Ian</dc:creator><dc:creator>Ferracin, Paolo</dc:creator><dc:creator>Prestemon, Soren</dc:creator><dc:date>2025-08-01</dc:date><dc:description>An investigation of instance segmentation of cracks in Nb3Sn 4-stack 40-strand Rutherford cables using machine learning is presented. Three samples were uniaxially and biaxially loaded before metallographic inspections were performed. The Mask R-CNN model was used in the Detectron2 framework with pre-trained weights but fine-tuned to detect and segment cracks. The model detected cracks with bounding box and mask average precisions (AP) of 42.8 and 27.9, respectively, and was used for instance segmentation of all cracks in the three samples. More cracks were found in the sample pre-loaded along the z-axis (i.e., along the cable length). Pre-loading along the x-axis (i.e., on the cables edges) reduced the number of cracks and changed the crack orientation distribution, away from being highly aligned with the y-axis (i.e., normal to the cables broad faces), i.e., the direction with the highest applied load. Fine-tuning of the Segment Anything Model (SAM) was also studied but performed poorly without human-provided prompts. However, the zero-shot capability of SAM showed high promises to accelerate the image annotation process for applications beyond this study.</dc:description><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>4008 Electrical Engineering (for-2020)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>Training</dc:subject><dc:subject>Wires</dc:subject><dc:subject>Computational modeling</dc:subject><dc:subject>Machine learning</dc:subject><dc:subject>Analytical models</dc:subject><dc:subject>Feature extraction</dc:subject><dc:subject>Optical microscopy</dc:subject><dc:subject>Numerical models</dc:subject><dc:subject>Magnets</dc:subject><dc:subject>Instance segmentation</dc:subject><dc:subject>Cracks</dc:subject><dc:subject>image analysis</dc:subject><dc:subject>machine learning</dc:subject><dc:subject>Nb3Sn</dc:subject><dc:subject>superconducting magnets</dc:subject><dc:subject>ATAP-GENERAL (c-lbnl-label)</dc:subject><dc:subject>ATAP-2025 (c-lbnl-label)</dc:subject><dc:subject>ATAP-SMP (c-lbnl-label)</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>4008 Electrical engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1df7z10n</dc:identifier><dc:identifier>https://escholarship.org/content/qt1df7z10n/qt1df7z10n.pdf</dc:identifier><dc:identifier>info:doi/10.1109/tasc.2024.3513940</dc:identifier><dc:type>article</dc:type><dc:source>IEEE Transactions on Applied Superconductivity, vol 35, iss 5</dc:source><dc:coverage>1 - 7</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt88t8n8bq</identifier><datestamp>2026-09-16T03:56:25Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt88t8n8bq</dc:identifier><dc:title>Quasi-Lindblad pseudomode theory for open quantum systems</dc:title><dc:creator>Park, Gunhee</dc:creator><dc:creator>박건희</dc:creator><dc:creator>Huang, Zhen</dc:creator><dc:creator>Zhu, Yuanran</dc:creator><dc:creator>Yang, Chao</dc:creator><dc:creator>Chan, Garnet Kin-Lic</dc:creator><dc:creator>Lin, Lin</dc:creator><dc:date>2024-11-01</dc:date><dc:description>We introduce a new framework to study the dynamics of open quantum systems with linearly coupled Gaussian baths. Our approach replaces the continuous bath with an auxiliary discrete set of pseudomodes with dissipative dynamics, but we further relax the complete positivity requirement in the Lindblad master equation and formulate a quasi-Lindblad pseudomode theory. We show that this quasi-Lindblad pseudomode formulation directly leads to a representation of the bath correlation function in terms of a complex weighted sum of complex exponentials, an expansion that is known to be rapidly convergent in practice and thus leads to a compact set of pseudomodes. The pseudomode representation is not unique and can differ by a gauge choice. When the global dynamics can be simulated exactly, the system dynamics is unique and independent of the specific pseudomode representation. However, the gauge choice may affect the stability of the global dynamics, and we provide an analysis of why and when the global dynamics can retain stability despite losing positivity. We showcase the performance of this formulation across various spectral densities in both bosonic and fermionic problems, finding significant improvements over conventional pseudomode formulations.</dc:description><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>34 Chemical sciences (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/88t8n8bq</dc:identifier><dc:identifier>https://escholarship.org/content/qt88t8n8bq/qt88t8n8bq.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevb.110.195148</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review B, vol 110, iss 19</dc:source><dc:coverage>195148</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0v7133j4</identifier><datestamp>2026-09-16T03:56:12Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0v7133j4</dc:identifier><dc:title>Capturing structural intuition: Human-gated imitation learning for structural design with flow matching</dc:title><dc:creator>Sun, Tao</dc:creator><dc:creator>Wang, Shaoyi</dc:creator><dc:creator>Schleicher, Simon</dc:creator><dc:creator>Weber, Ramon</dc:creator><dc:date>2026-09-18</dc:date><dc:description>Structural design is deeply expertise-driven: engineers rely on intuition, experience, and both explicit
and tacit knowledge of load paths, structural typologies, first principles and in-depth calculations to
arrive at a design solution. Current computational workflows in structural design largely focus on
optimization, form-finding and dimensioning of members, where the design space is predefined and
algorithms iteratively refine a solution. Machine learning, however, opens the possibility to explore
broader design spaces in which geometry and topology are not fixed in advance. Imitation learning
(IL), a paradigm closely related to reinforcement learning, offers a pathway to integrate skills from
design examples, rather than explicit rulesets. Recently, flow matching, a generative framework that
learns a vector field transporting noise toward data over time, has emerged as a prominent method
for modeling complex, multimodal action distributions that standard one-shot predictors often fail to
capture. By learning from engineers’ demonstrations with a flow-based imitation policy, we transfer
structural intuition into a design agent without dense reward engineering or computationally expensive
finite element analysis at every decision step. To study this idea, we create a 2D structural testing
environment. Coupled with a finite element analysis solver to track and rank design outcomes, we create
a training ground for the IL algorithm. Using the environment we tested building of pin-jointed steel
truss bridges as graphs and trained an imitation policy to predict chunks of continuous placement actions
and capture longer-term design intent. Our results show that the flow-based policies can learn structural
intuition, generating diverse feasible bridge designs that reflect established engineering principles. The
work introduces a reproducible benchmark for assembly-constrained structural design and examines the
limitation and the potential of generative imitation learning as an alternative framework for structural
design exploration beyond top-down optimization.</dc:description><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0v7133j4</dc:identifier><dc:identifier>https://escholarship.org/content/qt0v7133j4/qt0v7133j4.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9913j7jj</identifier><datestamp>2026-09-16T03:56:08Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9913j7jj</dc:identifier><dc:title>Mechanics-Guided Member Grouping for Cross-Section Optimization with Heterogeneous Graphs</dc:title><dc:creator>Wang, Shaoyi</dc:creator><dc:creator>Sun, Tao</dc:creator><dc:creator>Weber, Ramon</dc:creator><dc:creator>Schleicher, Simon</dc:creator><dc:date>2026-09-18</dc:date><dc:description>Structural member sizing directly influences material consumption, embodied carbon, and overall
structural efficiency. Recent advances in graph representations have opened new possibilities for
structural optimization, with applications such as topology optimization and surrogate modeling. We
propose a graph-based representation learning and clustering pipeline that uses structural simulation
results to support member sizing and cross-section optimization. In this representation, connection
points and linear members in the structural system are modeled as two node types in a heterogeneous
graph. Mechanical responses, geometric properties, and topological information are encoded as features,
and structural context is propagated through message passing. We then train a Heterogeneous Graph
Attention Network (HeteroGAT) encoder with a contrastive objective constructed from mechanically
similar and topologically adjacent member pairs. Finally, we cluster the learned embeddings with
Gaussian Mixture Models (GMM). The resulting clusters provide a practical basis for structural
optimization. Specifically, we use the clustering results as grouping rules for cross-section optimization
in Karamba3D, such that members within the same cluster share a common profile. Using steel member
sizing as a case study, we evaluate the cross-section assignment strategies on a whole-building structural
system and demonstrate the method through multiple application examples. The results show that the
proposed method achieves a rationalized section system with significantly fewer cross-section types and
stable convergence, while maintaining structural performance comparable to the original design, making
it a practical tool for early-stage steel structural design.</dc:description><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9913j7jj</dc:identifier><dc:identifier>https://escholarship.org/content/qt9913j7jj/qt9913j7jj.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt42k112z2</identifier><datestamp>2026-09-16T03:55:59Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt42k112z2</dc:identifier><dc:title>A genomic catalog of Earth’s microbiomes</dc:title><dc:creator>Nayfach, Stephen</dc:creator><dc:creator>Roux, Simon</dc:creator><dc:creator>Seshadri, Rekha</dc:creator><dc:creator>Udwary, Daniel</dc:creator><dc:creator>Varghese, Neha</dc:creator><dc:creator>Schulz, Frederik</dc:creator><dc:creator>Wu, Dongying</dc:creator><dc:creator>Paez-Espino, David</dc:creator><dc:creator>Chen, I-Min</dc:creator><dc:creator>Huntemann, Marcel</dc:creator><dc:creator>Palaniappan, Krishna</dc:creator><dc:creator>Ladau, Joshua</dc:creator><dc:creator>Mukherjee, Supratim</dc:creator><dc:creator>Reddy, TBK</dc:creator><dc:creator>Nielsen, Torben</dc:creator><dc:creator>Kirton, Edward</dc:creator><dc:creator>Faria, José P</dc:creator><dc:creator>Edirisinghe, Janaka N</dc:creator><dc:creator>Henry, Christopher S</dc:creator><dc:creator>Jungbluth, Sean P</dc:creator><dc:creator>Chivian, Dylan</dc:creator><dc:creator>Dehal, Paramvir</dc:creator><dc:creator>Wood-Charlson, Elisha M</dc:creator><dc:creator>Arkin, Adam P</dc:creator><dc:creator>Tringe, Susannah G</dc:creator><dc:creator>Visel, Axel</dc:creator><dc:creator>Woyke, Tanja</dc:creator><dc:creator>Mouncey, Nigel J</dc:creator><dc:creator>Ivanova, Natalia N</dc:creator><dc:creator>Kyrpides, Nikos C</dc:creator><dc:creator>Eloe-Fadrosh, Emiley A</dc:creator><dc:date>2021-04-01</dc:date><dc:description>The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to &amp;gt;10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes.</dc:description><dc:subject>4101 Climate Change Impacts and Adaptation (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Biotechnology (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Air Microbiology (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Archaea (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Catalogs as Topic (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Metabolomics (mesh)</dc:subject><dc:subject>Metagenome (mesh)</dc:subject><dc:subject>Metagenomics (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Viruses (mesh)</dc:subject><dc:subject>Water Microbiology (mesh)</dc:subject><dc:subject>IMG/M Data Consortium</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Viruses (mesh)</dc:subject><dc:subject>Archaea (mesh)</dc:subject><dc:subject>Air Microbiology (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Water Microbiology (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Catalogs as Topic (mesh)</dc:subject><dc:subject>Metabolomics (mesh)</dc:subject><dc:subject>Metagenome (mesh)</dc:subject><dc:subject>Metagenomics (mesh)</dc:subject><dc:subject>Air Microbiology (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Archaea (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Catalogs as Topic (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Metabolomics (mesh)</dc:subject><dc:subject>Metagenome (mesh)</dc:subject><dc:subject>Metagenomics (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Viruses (mesh)</dc:subject><dc:subject>Water Microbiology (mesh)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/42k112z2</dc:identifier><dc:identifier>https://escholarship.org/content/qt42k112z2/qt42k112z2.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41587-020-0718-6</dc:identifier><dc:type>article</dc:type><dc:source>Nature Biotechnology, vol 39, iss 4</dc:source><dc:coverage>499 - 509</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2cm2c75g</identifier><datestamp>2026-09-16T03:51:28Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2cm2c75g</dc:identifier><dc:title>Photosynthetic responses to temperature across the tropics: a meta-analytic approach</dc:title><dc:creator>Carter, Kelsey R</dc:creator><dc:creator>Cavaleri, Molly A</dc:creator><dc:creator>Atkin, Owen K</dc:creator><dc:creator>Bahar, Nur HA</dc:creator><dc:creator>Cheesman, Alexander W</dc:creator><dc:creator>Choury, Zineb</dc:creator><dc:creator>Crous, Kristine Y</dc:creator><dc:creator>Doughty, Christopher E</dc:creator><dc:creator>Dusenge, Mirindi E</dc:creator><dc:creator>Ely, Kim S</dc:creator><dc:creator>Evans, John R</dc:creator><dc:creator>da Silva, Jéssica Fonseca</dc:creator><dc:creator>Mau, Alida C</dc:creator><dc:creator>Medlyn, Belinda E</dc:creator><dc:creator>Meir, Patrick</dc:creator><dc:creator>Norby, Richard J</dc:creator><dc:creator>Read, Jennifer</dc:creator><dc:creator>Reed, Sasha C</dc:creator><dc:creator>Reich, Peter B</dc:creator><dc:creator>Rogers, Alistair</dc:creator><dc:creator>Serbin, Shawn P</dc:creator><dc:creator>Slot, Martijn</dc:creator><dc:creator>Schwartz, Elsa C</dc:creator><dc:creator>Tribuzy, Edgard S</dc:creator><dc:creator>Uddling, Johan</dc:creator><dc:creator>Vårhammar, Angelica</dc:creator><dc:creator>Walker, Anthony P</dc:creator><dc:creator>Winter, Klaus</dc:creator><dc:creator>Wood, Tana E</dc:creator><dc:creator>Wu, Jin</dc:creator><dc:date>2025-08-16</dc:date><dc:description>BACKGROUND AND AIMS: Tropical forests exchange more carbon dioxide (CO2) with the atmosphere than any other terrestrial biome. Yet, uncertainty in the projected carbon balance over the next century is roughly three times greater for the tropics than other for ecosystems. Our limited knowledge of tropical plant physiological responses, including photosynthetic, to climate change is a substantial source of uncertainty in our ability to forecast the global terrestrial carbon sink.
METHODS: We used a meta-analytic approach, focusing on tropical photosynthetic temperature responses, to address this knowledge gap. Our dataset, gleaned from 18 independent studies, included leaf-level light-saturated photosynthetic (Asat) temperature responses from 108 woody species, with additional temperature parameters (35 species) and rates (250 species) of both maximum rates of electron transport (Jmax) and Rubisco carboxylation (Vcmax). We investigated how these parameters responded to mean annual temperature (MAT), temperature variability, aridity and elevation, as well as also how responses differed among successional strategy, leaf habit and light environment.
KEY RESULTS: Optimum temperatures for Asat (ToptA) and Jmax (ToptJ) increased with MAT but not for Vcmax (ToptV). Although photosynthetic rates were higher for 'light' than 'shaded' leaves, light conditions did not generate differences in temperature response parameters. ToptA did not differ with successional strategy, but early successional species had ~4 °C wider thermal niches than mid/late species. Semi-deciduous species had ~1 °C higher ToptA than broadleaf evergreen species. Most global modelling efforts consider all tropical forests as a single 'broadleaf evergreen' functional type, but our data show that tropical species with different leaf habits display distinct temperature responses that should be included in modelling efforts.
CONCLUSIONS: This novel research will inform modelling efforts to quantify tropical ecosystem carbon cycling and provide more accurate representations of how these key ecosystems will respond to altered temperature patterns in the face of climate warming.</dc:description><dc:subject>3108 Plant Biology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>Photosynthesis (mesh)</dc:subject><dc:subject>Tropical Climate (mesh)</dc:subject><dc:subject>Temperature (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>A-C-i curves</dc:subject><dc:subject>maximum rate of photosynthetic electron transport (J(max))</dc:subject><dc:subject>maximum rate of Rubisco carboxylation (V-cmax)</dc:subject><dc:subject>meta-analysis</dc:subject><dc:subject>photosynthesis</dc:subject><dc:subject>temperature response</dc:subject><dc:subject>tropics</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>Temperature (mesh)</dc:subject><dc:subject>Tropical Climate (mesh)</dc:subject><dc:subject>Photosynthesis (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>A–C i curves</dc:subject><dc:subject>maximum rate of Rubisco carboxylation (Vcmax)</dc:subject><dc:subject>maximum rate of photosynthetic electron transport (Jmax)</dc:subject><dc:subject>meta-analysis</dc:subject><dc:subject>photosynthesis</dc:subject><dc:subject>temperature response</dc:subject><dc:subject>tropics</dc:subject><dc:subject>Photosynthesis (mesh)</dc:subject><dc:subject>Tropical Climate (mesh)</dc:subject><dc:subject>Temperature (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>0602 Ecology (for)</dc:subject><dc:subject>0607 Plant Biology (for)</dc:subject><dc:subject>0705 Forestry Sciences (for)</dc:subject><dc:subject>Plant Biology &amp; Botany (science-metrix)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>3108 Plant biology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2cm2c75g</dc:identifier><dc:identifier>https://escholarship.org/content/qt2cm2c75g/qt2cm2c75g.pdf</dc:identifier><dc:identifier>info:doi/10.1093/aob/mcae206</dc:identifier><dc:type>article</dc:type><dc:source>Annals of Botany, vol 135, iss 7</dc:source><dc:coverage>1293 - 1310</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0sj1h6rn</identifier><datestamp>2026-09-16T03:51:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0sj1h6rn</dc:identifier><dc:title>Erratum: DESI 2024 V: Full-Shape Galaxy Clustering from Galaxies and Quasars</dc:title><dc:creator>Adame, AG</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alam, S</dc:creator><dc:creator>Alexander, DM</dc:creator><dc:creator>Alvarez, M</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Anand, A</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Avila, S</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Awan, H</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Baltay, C</dc:creator><dc:creator>Bault, A</dc:creator><dc:creator>Behera, J</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Beutler, F</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Blake, C</dc:creator><dc:creator>Blum, R</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Buckley-Geer, E</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Calderon, R</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Cereskaite, R</dc:creator><dc:creator>Cervantes-Cota, JL</dc:creator><dc:creator>Chabanier, S</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Davis, TM</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Deiosso, N</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Edelstein, J</dc:creator><dc:creator>Eftekharzadeh, S</dc:creator><dc:creator>Eisenstein, DJ</dc:creator><dc:creator>Elliott, A</dc:creator><dc:creator>Fagrelius, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Ereza, J</dc:creator><dc:creator>Findlay, N</dc:creator><dc:creator>Flaugher, B</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Sánchez, D</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Garrison, LH</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gonzalez-Morales, AX</dc:creator><dc:creator>Gonzalez-Perez, V</dc:creator><dc:creator>Gordon, C</dc:creator><dc:creator>Green, D</dc:creator><dc:creator>Gruen, D</dc:creator><dc:creator>Gsponer, R</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hadzhiyska, B</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Hanif, MMS</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Iršič, V</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Karaçaylı, NG</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kent, S</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kong, H</dc:creator><dc:creator>Koposov, SE</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Krolewski, A</dc:creator><dc:creator>Lai, Y</dc:creator><dc:creator>Lan, T-W</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Lang, D</dc:creator><dc:creator>Lasker, J</dc:creator><dc:creator>Le Goff, JM</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:date>2026-02-01</dc:date><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0sj1h6rn</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1088/1475-7516/2026/02/e02</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2026, iss 02</dc:source><dc:coverage>e02</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6rj2b2hd</identifier><datestamp>2026-09-16T03:51:06Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6rj2b2hd</dc:identifier><dc:title>How a Community-Academic-Government Partnership for Drinking Water Justice Strengthens the Rigor, Relevance, Reach, and Reflexivity of Science</dc:title><dc:creator>Karasaki, Seigi</dc:creator><dc:creator>Libenson, Arianna</dc:creator><dc:creator>Tran, Tien</dc:creator><dc:creator>Bangia, Komal</dc:creator><dc:creator>Cushing, Lara J</dc:creator><dc:creator>Rempel, Jenny L</dc:creator><dc:creator>August, Laura</dc:creator><dc:creator>Baehner, Lauren</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Pace, Clare</dc:creator><dc:date>2024-11-26</dc:date><dc:description>This practice brief presents lessons learned through the Water Equity Science Shop (WESS), a community-academic-government partnership seeking to address drinking water challenges in California through community-engaged research and knowledge dissemination. Formed in 2017, WESS is comprised of Community Water Center, a community-based organization (CBO) working towards realizing California’s Human Right to Water; researchers at the University of California (Berkeley and Los Angeles); and scientists at the California Environmental Protection Agency’s Office of Environmental Health Hazard Assessment. We describe the development of an online “Drinking Water Tool,” which presents data and maps on drinking water access, threats, and local decision-making processes. We discuss how features of the WESS collaboration have extended the “4 Rs”—the rigor, relevance, reach, and reflexivity—of our science and resulted in new approaches for assessing drinking water (in)justice that have both influenced and been influenced by complementary efforts by state agencies. Through our reflections, we elucidate how collaborations between communities, CBOs, academic institutions, and state agencies can generate actionable evidence and accessible data to support the incorporation of environmental justice goals into drinking water supply and management.</dc:description><dc:subject>4802 Environmental and Resources Law (for-2020)</dc:subject><dc:subject>48 Law and Legal Studies (for-2020)</dc:subject><dc:subject>44 Human Society (for-2020)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>environmental justice</dc:subject><dc:subject>environmental health</dc:subject><dc:subject>drinking water</dc:subject><dc:subject>Human Right to Water</dc:subject><dc:subject>collaborative research</dc:subject><dc:subject>community-engaged research</dc:subject><dc:subject>Human Right to Water</dc:subject><dc:subject>collaborative research</dc:subject><dc:subject>community-engaged research</dc:subject><dc:subject>drinking water</dc:subject><dc:subject>environmental health</dc:subject><dc:subject>environmental justice</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6rj2b2hd</dc:identifier><dc:identifier>https://escholarship.org/content/qt6rj2b2hd/qt6rj2b2hd.pdf</dc:identifier><dc:identifier>info:doi/10.1089/env.2024.0039</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Justice</dc:source><dc:coverage>10.1089/env.2024.0039</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt00f9n225</identifier><datestamp>2026-09-16T03:46:57Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt00f9n225</dc:identifier><dc:title>Performance of the CMS high-level trigger during LHC Run 2</dc:title><dc:creator>Hayrapetyan, A</dc:creator><dc:creator>Tumasyan, A</dc:creator><dc:creator>Adam, W</dc:creator><dc:creator>Andrejkovic, JW</dc:creator><dc:creator>Benato, L</dc:creator><dc:creator>Bergauer, T</dc:creator><dc:creator>Chatterjee, S</dc:creator><dc:creator>Damanakis, K</dc:creator><dc:creator>Dragicevic, M</dc:creator><dc:creator>Hussain, PS</dc:creator><dc:creator>Jeitler, M</dc:creator><dc:creator>Krammer, N</dc:creator><dc:creator>Li, A</dc:creator><dc:creator>Liko, D</dc:creator><dc:creator>Mikulec, I</dc:creator><dc:creator>Schieck, J</dc:creator><dc:creator>Schöfbeck, R</dc:creator><dc:creator>Schwarz, D</dc:creator><dc:creator>Sonawane, M</dc:creator><dc:creator>Waltenberger, W</dc:creator><dc:creator>Wulz, C-E</dc:creator><dc:creator>Janssen, T</dc:creator><dc:creator>Van Laer, T</dc:creator><dc:creator>Van Mechelen, P</dc:creator><dc:creator>Breugelmans, N</dc:creator><dc:creator>D'Hondt, J</dc:creator><dc:creator>Dansana, S</dc:creator><dc:creator>De Moor, A</dc:creator><dc:creator>Delcourt, M</dc:creator><dc:creator>Heyen, F</dc:creator><dc:creator>Lowette, S</dc:creator><dc:creator>Makarenko, I</dc:creator><dc:creator>Müller, D</dc:creator><dc:creator>Tavernier, S</dc:creator><dc:creator>Tytgat, M</dc:creator><dc:creator>Van Onsem, GP</dc:creator><dc:creator>Van Putte, S</dc:creator><dc:creator>Vannerom, D</dc:creator><dc:creator>Beghin, D</dc:creator><dc:creator>Bilin, B</dc:creator><dc:creator>Brun, H</dc:creator><dc:creator>Clerbaux, B</dc:creator><dc:creator>Das, AK</dc:creator><dc:creator>De Bruyn, I</dc:creator><dc:creator>De Lentdecker, G</dc:creator><dc:creator>Evard, H</dc:creator><dc:creator>Favart, L</dc:creator><dc:creator>Gianneios, P</dc:creator><dc:creator>Jaramillo, J</dc:creator><dc:creator>Khalilzadeh, A</dc:creator><dc:creator>Khan, FA</dc:creator><dc:creator>Lee, K</dc:creator><dc:creator>Malara, A</dc:creator><dc:creator>Paredes, S</dc:creator><dc:creator>Shahzad, MA</dc:creator><dc:creator>Thomas, L</dc:creator><dc:creator>Bemden, M Vanden</dc:creator><dc:creator>Vander Velde, C</dc:creator><dc:creator>Vanlaer, P</dc:creator><dc:creator>Cornelis, T</dc:creator><dc:creator>De Coen, M</dc:creator><dc:creator>Dobur, D</dc:creator><dc:creator>Gokbulut, G</dc:creator><dc:creator>Hong, Y</dc:creator><dc:creator>Knolle, J</dc:creator><dc:creator>Lambrecht, L</dc:creator><dc:creator>Marckx, D</dc:creator><dc:creator>Amarilo, K Mota</dc:creator><dc:creator>Skovpen, K</dc:creator><dc:creator>Van Den Bossche, N</dc:creator><dc:creator>van der Linden, J</dc:creator><dc:creator>Wezenbeek, L</dc:creator><dc:creator>Benecke, A</dc:creator><dc:creator>Bethani, A</dc:creator><dc:creator>Bruno, G</dc:creator><dc:creator>Caputo, C</dc:creator><dc:creator>De Jeneret, J De Favereau</dc:creator><dc:creator>Delaere, C</dc:creator><dc:creator>Donertas, IS</dc:creator><dc:creator>Giammanco, A</dc:creator><dc:creator>Guzel, AO</dc:creator><dc:creator>Jain</dc:creator><dc:creator>Lemaitre, V</dc:creator><dc:creator>Lidrych, J</dc:creator><dc:creator>Mastrapasqua, P</dc:creator><dc:creator>Tran, TT</dc:creator><dc:creator>Turkcapar, S</dc:creator><dc:creator>Alves, GA</dc:creator><dc:creator>Coelho, E</dc:creator><dc:creator>Silva, G Correia</dc:creator><dc:creator>Hensel, C</dc:creator><dc:creator>De Oliveira, T Menezes</dc:creator><dc:creator>Herrera, C Mora</dc:creator><dc:creator>Teles, P Rebello</dc:creator><dc:creator>Soeiro, M</dc:creator><dc:creator>Manganote, EJ Tonelli</dc:creator><dc:creator>Pereira, A Vilela</dc:creator><dc:creator>Júnior, WL Aldá</dc:creator><dc:creator>Filho, M Barroso Ferreira</dc:creator><dc:creator>Malbouisson, H Brandao</dc:creator><dc:date>2024-11-01</dc:date><dc:description>The CERN LHC provided proton and heavy ion collisions during its Run 2 operation period from 2015 to 2018. Proton-proton collisions reached a peak instantaneous luminosity of 2.1× 1034 cm-2s-1, twice the initial design value, at √(s)=13 TeV. The CMS experiment records a subset of the collisions for further processing as part of its online selection of data for physics analyses, using a two-level trigger system: the Level-1 trigger, implemented in custom-designed electronics, and the high-level trigger, a streamlined version of the offline reconstruction software running on a large computer farm. This paper presents the performance of the CMS high-level trigger system during LHC Run 2 for physics objects, such as leptons, jets, and missing transverse momentum, which meet the broad needs of the CMS physics program and the challenge of the evolving LHC and detector conditions. Sophisticated algorithms that were originally used in offline reconstruction were deployed online. Highlights include a machine-learning b tagging algorithm and a reconstruction algorithm for tau leptons that decay hadronically.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>Networking and Information Technology R&amp;D (NITRD) (rcdc)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>Large detector systems for particle and astroparticle physics</dc:subject><dc:subject>Trigger concepts and systems (hardware and software)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/00f9n225</dc:identifier><dc:identifier>https://escholarship.org/content/qt00f9n225/qt00f9n225.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1748-0221/19/11/p11021</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Instrumentation, vol 19, iss 11</dc:source><dc:coverage>p11021</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6x82z9st</identifier><datestamp>2026-09-16T03:42:30Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6x82z9st</dc:identifier><dc:title>The CMS Statistical Analysis and Combination Tool: Combine</dc:title><dc:creator>Hayrapetyan, A</dc:creator><dc:creator>Tumasyan, A</dc:creator><dc:creator>Adam, W</dc:creator><dc:creator>Andrejkovic, JW</dc:creator><dc:creator>Bergauer, T</dc:creator><dc:creator>Chatterjee, S</dc:creator><dc:creator>Damanakis, K</dc:creator><dc:creator>Dragicevic, M</dc:creator><dc:creator>Hussain, PS</dc:creator><dc:creator>Jeitler, M</dc:creator><dc:creator>Krammer, N</dc:creator><dc:creator>Li, A</dc:creator><dc:creator>Liko, D</dc:creator><dc:creator>Mikulec, I</dc:creator><dc:creator>Schieck, J</dc:creator><dc:creator>Schöfbeck, R</dc:creator><dc:creator>Schwarz, D</dc:creator><dc:creator>Sonawane, M</dc:creator><dc:creator>Templ, S</dc:creator><dc:creator>Waltenberger, W</dc:creator><dc:creator>Wulz, C-E</dc:creator><dc:creator>Darwish, MR</dc:creator><dc:creator>Janssen, T</dc:creator><dc:creator>Van Mechelen, P</dc:creator><dc:creator>Breugelmans, N</dc:creator><dc:creator>D’Hondt, J</dc:creator><dc:creator>Dansana, S</dc:creator><dc:creator>De Moor, A</dc:creator><dc:creator>Delcourt, M</dc:creator><dc:creator>Heyen, F</dc:creator><dc:creator>Lowette, S</dc:creator><dc:creator>Makarenko, I</dc:creator><dc:creator>Müller, D</dc:creator><dc:creator>Tavernier, S</dc:creator><dc:creator>Tytgat, M</dc:creator><dc:creator>Van Onsem, GP</dc:creator><dc:creator>Van Putte, S</dc:creator><dc:creator>Vannerom, D</dc:creator><dc:creator>Clerbaux, B</dc:creator><dc:creator>Das, AK</dc:creator><dc:creator>De Lentdecker, G</dc:creator><dc:creator>Evard, H</dc:creator><dc:creator>Favart, L</dc:creator><dc:creator>Gianneios, P</dc:creator><dc:creator>Hohov, D</dc:creator><dc:creator>Jaramillo, J</dc:creator><dc:creator>Khalilzadeh, A</dc:creator><dc:creator>Khan, FA</dc:creator><dc:creator>Lee, K</dc:creator><dc:creator>Mahdavikhorrami, M</dc:creator><dc:creator>Malara, A</dc:creator><dc:creator>Paredes, S</dc:creator><dc:creator>Shahzad, MA</dc:creator><dc:creator>Thomas, L</dc:creator><dc:creator>Bemden, M Vanden</dc:creator><dc:creator>Vander Velde, C</dc:creator><dc:creator>Vanlaer, P</dc:creator><dc:creator>De Coen, M</dc:creator><dc:creator>Dobur, D</dc:creator><dc:creator>Gokbulut, G</dc:creator><dc:creator>Hong, Y</dc:creator><dc:creator>Knolle, J</dc:creator><dc:creator>Lambrecht, L</dc:creator><dc:creator>Marckx, D</dc:creator><dc:creator>Mestdach, G</dc:creator><dc:creator>Amarilo, K Mota</dc:creator><dc:creator>Samalan, A</dc:creator><dc:creator>Skovpen, K</dc:creator><dc:creator>Van Den Bossche, N</dc:creator><dc:creator>van der Linden, J</dc:creator><dc:creator>Wezenbeek, L</dc:creator><dc:creator>Benecke, A</dc:creator><dc:creator>Bethani, A</dc:creator><dc:creator>Bruno, G</dc:creator><dc:creator>Caputo, C</dc:creator><dc:creator>De Jeneret, J De Favereau</dc:creator><dc:creator>Delaere, C</dc:creator><dc:creator>Donertas, IS</dc:creator><dc:creator>Giammanco, A</dc:creator><dc:creator>Guzel, AO</dc:creator><dc:creator>Jain</dc:creator><dc:creator>Lemaitre, V</dc:creator><dc:creator>Lidrych, J</dc:creator><dc:creator>Mastrapasqua, P</dc:creator><dc:creator>Tran, TT</dc:creator><dc:creator>Wertz, S</dc:creator><dc:creator>Alves, GA</dc:creator><dc:creator>Pereira, M Alves Gallo</dc:creator><dc:creator>Coelho, E</dc:creator><dc:creator>Silva, G Correia</dc:creator><dc:creator>Hensel, C</dc:creator><dc:creator>De Oliveira, T Menezes</dc:creator><dc:creator>Moraes, A</dc:creator><dc:creator>Teles, P Rebello</dc:creator><dc:creator>Soeiro, M</dc:creator><dc:creator>Pereira, A Vilela</dc:creator><dc:creator>Júnior, WL Aldá</dc:creator><dc:creator>Filho, M Barroso Ferreira</dc:creator><dc:creator>Malbouisson, H Brandao</dc:creator><dc:creator>Carvalho, W</dc:creator><dc:date>2024-12-01</dc:date><dc:description>This paper describes the Combine software package used for statistical analyses by the CMS Collaboration. The package, originally designed to perform searches for a Higgs boson and the combined analysis of those searches, has evolved to become the statistical analysis tool presently used in the majority of measurements and searches performed by the CMS Collaboration. It is not specific to the CMS experiment, and this paper is intended to serve as a reference for users outside of the CMS Collaboration, providing an outline of the most salient features and capabilities. Readers are provided with the possibility to run Combine and reproduce examples provided in this paper using a publicly available container image. Since the package is constantly evolving to meet the demands of ever-increasing data sets and analysis sophistication, this paper cannot cover all details of Combine. However, the online documentation referenced within this paper provides an up-to-date and complete user guide.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>46 Information and Computing Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6x82z9st</dc:identifier><dc:identifier>https://escholarship.org/content/qt6x82z9st/qt6x82z9st.pdf</dc:identifier><dc:identifier>info:doi/10.1007/s41781-024-00121-4</dc:identifier><dc:type>article</dc:type><dc:source>EPJ Research Infrastructures, vol 8, iss 1</dc:source><dc:coverage>19</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6zh078qk</identifier><datestamp>2026-09-16T03:41:41Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6zh078qk</dc:identifier><dc:title>The DESI Early Data Release white dwarf catalogue</dc:title><dc:creator>Manser, Christopher J</dc:creator><dc:creator>Izquierdo, Paula</dc:creator><dc:creator>Gänsicke, Boris T</dc:creator><dc:creator>Swan, Andrew</dc:creator><dc:creator>Koester, Detlev</dc:creator><dc:creator>Robert, Akshay</dc:creator><dc:creator>Xu, Siyi</dc:creator><dc:creator>Inight, Keith</dc:creator><dc:creator>Amroota, Ben</dc:creator><dc:creator>Fusillo, NP Gentile</dc:creator><dc:creator>Koposov, Sergey E</dc:creator><dc:creator>Kim, Bokyoung</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Prieto, Carlos Allende</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Blum, R</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cooper, AP</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, Michael E</dc:creator><dc:creator>Li, TS</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlafly, EF</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zhou, Z</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2024-10-25</dc:date><dc:description>ABSTRACT The Early Data Release (EDR) of the Dark Energy Spectroscopic Instrument (DESI) comprises spectroscopy obtained from 2020 December 14 to 2021 June 10. White dwarfs were targeted by DESI both as calibration sources and as science targets and were selected based on Gaia photometry and astrometry. Here, we present the DESI EDR white dwarf catalogue, which includes 2706 spectroscopically confirmed white dwarfs of which approximately 60 per cent have been spectroscopically observed for the first time, as well as 66 white dwarf binary systems. We provide spectral classifications for all white dwarfs, and discuss their distribution within the Gaia Hertzsprung–Russell diagram. We provide atmospheric parameters derived from spectroscopic and photometric fits for white dwarfs with pure hydrogen or helium photospheres, a mixture of those two, and white dwarfs displaying carbon features in their spectra. We also discuss the less abundant systems in the sample, such as those with magnetic fields, and cataclysmic variables. The DESI EDR white dwarf sample is significantly less biased than the sample observed by the Sloan Digital Sky Survey, which is skewed to bluer and therefore hotter white dwarfs, making DESI more complete and suitable for performing statistical studies of white dwarfs.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>techniques: spectroscopic</dc:subject><dc:subject>catalogues</dc:subject><dc:subject>surveys</dc:subject><dc:subject>white dwarfs</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6zh078qk</dc:identifier><dc:identifier>https://escholarship.org/content/qt6zh078qk/qt6zh078qk.pdf</dc:identifier><dc:identifier>info:doi/10.1093/mnras/stae2205</dc:identifier><dc:type>article</dc:type><dc:source>Monthly Notices of the Royal Astronomical Society, vol 535, iss 1</dc:source><dc:coverage>254 - 289</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6kp7s2b5</identifier><datestamp>2026-09-16T03:41:35Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6kp7s2b5</dc:identifier><dc:title>Observation of double J/ψ meson production in pPb collisions at sNN=8.16 TeV</dc:title><dc:creator>Hayrapetyan, A</dc:creator><dc:creator>Tumasyan, A</dc:creator><dc:creator>Adam, W</dc:creator><dc:creator>Andrejkovic, JW</dc:creator><dc:creator>Bergauer, T</dc:creator><dc:creator>Chatterjee, S</dc:creator><dc:creator>Damanakis, K</dc:creator><dc:creator>Dragicevic, M</dc:creator><dc:creator>Hussain, PS</dc:creator><dc:creator>Jeitler, M</dc:creator><dc:creator>Krammer, N</dc:creator><dc:creator>Li, A</dc:creator><dc:creator>Liko, D</dc:creator><dc:creator>Mikulec, I</dc:creator><dc:creator>Schieck, J</dc:creator><dc:creator>Schöfbeck, R</dc:creator><dc:creator>Schwarz, D</dc:creator><dc:creator>Sonawane, M</dc:creator><dc:creator>Templ, S</dc:creator><dc:creator>Waltenberger, W</dc:creator><dc:creator>Wulz, C-E</dc:creator><dc:creator>Darwish, MR</dc:creator><dc:creator>Janssen, T</dc:creator><dc:creator>Van Laer, T</dc:creator><dc:creator>Van Mechelen, P</dc:creator><dc:creator>Breugelmans, N</dc:creator><dc:creator>D’Hondt, J</dc:creator><dc:creator>Dansana, S</dc:creator><dc:creator>De Moor, A</dc:creator><dc:creator>Delcourt, M</dc:creator><dc:creator>Heyen, F</dc:creator><dc:creator>Lowette, S</dc:creator><dc:creator>Makarenko, I</dc:creator><dc:creator>Müller, D</dc:creator><dc:creator>Tavernier, S</dc:creator><dc:creator>Tytgat, M</dc:creator><dc:creator>Van Onsem, GP</dc:creator><dc:creator>Van Putte, S</dc:creator><dc:creator>Vannerom, D</dc:creator><dc:creator>Bilin, B</dc:creator><dc:creator>Clerbaux, B</dc:creator><dc:creator>Das, AK</dc:creator><dc:creator>De Lentdecker, G</dc:creator><dc:creator>Evard, H</dc:creator><dc:creator>Favart, L</dc:creator><dc:creator>Gianneios, P</dc:creator><dc:creator>Jaramillo, J</dc:creator><dc:creator>Khalilzadeh, A</dc:creator><dc:creator>Khan, FA</dc:creator><dc:creator>Lee, K</dc:creator><dc:creator>Mahdavikhorrami, M</dc:creator><dc:creator>Malara, A</dc:creator><dc:creator>Paredes, S</dc:creator><dc:creator>Shahzad, MA</dc:creator><dc:creator>Thomas, L</dc:creator><dc:creator>Bemden, M Vanden</dc:creator><dc:creator>Vander Velde, C</dc:creator><dc:creator>Vanlaer, P</dc:creator><dc:creator>De Coen, M</dc:creator><dc:creator>Dobur, D</dc:creator><dc:creator>Gokbulut, G</dc:creator><dc:creator>Hong, Y</dc:creator><dc:creator>Knolle, J</dc:creator><dc:creator>Lambrecht, L</dc:creator><dc:creator>Marckx, D</dc:creator><dc:creator>Amarilo, K Mota</dc:creator><dc:creator>Samalan, A</dc:creator><dc:creator>Skovpen, K</dc:creator><dc:creator>Van Den Bossche, N</dc:creator><dc:creator>van der Linden, J</dc:creator><dc:creator>Wezenbeek, L</dc:creator><dc:creator>Benecke, A</dc:creator><dc:creator>Bethani, A</dc:creator><dc:creator>Bruno, G</dc:creator><dc:creator>Caputo, C</dc:creator><dc:creator>De Jeneret, J De Favereau</dc:creator><dc:creator>Delaere, C</dc:creator><dc:creator>Donertas, IS</dc:creator><dc:creator>Giammanco, A</dc:creator><dc:creator>Guzel, AO</dc:creator><dc:creator>Jain</dc:creator><dc:creator>Lemaitre, V</dc:creator><dc:creator>Lidrych, J</dc:creator><dc:creator>Mastrapasqua, P</dc:creator><dc:creator>Tran, TT</dc:creator><dc:creator>Wertz, S</dc:creator><dc:creator>Alves, GA</dc:creator><dc:creator>Pereira, M Alves Gallo</dc:creator><dc:creator>Coelho, E</dc:creator><dc:creator>Silva, G Correia</dc:creator><dc:creator>Hensel, C</dc:creator><dc:creator>De Oliveira, T Menezes</dc:creator><dc:creator>Moraes, A</dc:creator><dc:creator>Teles, P Rebello</dc:creator><dc:creator>Soeiro, M</dc:creator><dc:creator>Pereira, A Vilela</dc:creator><dc:creator>Júnior, WL Aldá</dc:creator><dc:creator>Filho, M Barroso Ferreira</dc:creator><dc:creator>Malbouisson, H Brandao</dc:creator><dc:creator>Carvalho, W</dc:creator><dc:date>2024-11-01</dc:date><dc:description>The first observation of the concurrent production of two  mesons in proton-nucleus collisions is presented. The analysis is based on a proton-lead (  ) data sample recorded at a nucleon-nucleon center-of-mass energy of 8.16&amp;nbsp;TeV by the CMS experiment at the CERN LHC and corresponding to an integrated luminosity of  . The two  mesons are reconstructed in their  decay channels with transverse momenta  and rapidity  . Events where one of the  mesons is reconstructed in the dielectron channel are also considered in the search. The  process is observed with a significance of 5.3 standard deviations. The measured inclusive fiducial cross section, using the four-muon channel alone, is  . A fit of the data to the expected rapidity separation for pairs of  mesons produced in single (SPS) and double (DPS) parton scatterings yields  and  , respectively. This latter result can be transformed into a lower bound on the effective DPS cross section, closely related to the squared average interparton transverse separation in the collision, of  at 95%&amp;nbsp;confidence level.      © 2024 CERN, for the CMS Collaboration 2024 CERN</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6kp7s2b5</dc:identifier><dc:identifier>https://escholarship.org/content/qt6kp7s2b5/qt6kp7s2b5.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevd.110.092002</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 110, iss 9</dc:source><dc:coverage>092002</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5mm917mq</identifier><datestamp>2026-09-16T03:38:05Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5mm917mq</dc:identifier><dc:title>Spontaneous fission of the odd-Z isotope Db255</dc:title><dc:creator>Pore, JL</dc:creator><dc:creator>Younes, W</dc:creator><dc:creator>Gates, JM</dc:creator><dc:creator>Robledo, LM</dc:creator><dc:creator>Garcia, FH</dc:creator><dc:creator>Orford, R</dc:creator><dc:creator>Crawford, HL</dc:creator><dc:creator>Fallon, P</dc:creator><dc:creator>Gooding, JA</dc:creator><dc:creator>Covo, M Kireeff</dc:creator><dc:creator>McCarthy, M</dc:creator><dc:creator>Stoyer, MA</dc:creator><dc:date>2024-10-01</dc:date><dc:description>Experiments conducted at Lawrence Berkeley National Laboratory's 88-Inch Cyclotron Facility aimed to produce and study the decay of the previously unobserved isotope Db255. This isotope was produced in the Pb206(V51, 2n)Db255 reaction, separated from unreacted beam material and reaction by-products with the Berkeley Gas-filled Separator, and then implanted into a double-sided silicon-strip detector at the BGS focal plane. Decay properties of Db255 were determined from the analysis of evaporation residue (EVR) fission and EVR-α-α correlations. The properties of this new isotope of dubnium differ dramatically from those of its neighboring Db isotopes. Db255 was found to decay primarily by spontaneous fission (SF) with a small α-decay branch, where the average half-life of the observed decays was t1/2=2.6−0.3+0.4 ms. Theoretical calculations were performed using the Wentzel-Kramers-Brillouin approximation, with parameters calculated within a self-consistent microscopic approach, to see if these unique properties could be reproduced. A SF half-life estimate is obtained that closely matches the measured value, while simultaneously pointing out the sensitivities that need to be further constrained in future work.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>CSD-05-HEC-B (c-lbnl-label)</dc:subject><dc:subject>NSD-Low Energy Nuclear Physics (c-lbnl-label)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5mm917mq</dc:identifier><dc:identifier>https://escholarship.org/content/qt5mm917mq/qt5mm917mq.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevc.110.l041301</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review C, vol 110, iss 4</dc:source><dc:coverage>l041301</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0p92q5md</identifier><datestamp>2026-09-16T03:37:45Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0p92q5md</dc:identifier><dc:title>Toward the Discovery of New Elements: Production of Livermorium (Z=116) with Ti50</dc:title><dc:creator>Gates, JM</dc:creator><dc:creator>Orford, R</dc:creator><dc:creator>Rudolph, D</dc:creator><dc:creator>Appleton, C</dc:creator><dc:creator>Barrios, BM</dc:creator><dc:creator>Benitez, JY</dc:creator><dc:creator>Bordeau, M</dc:creator><dc:creator>Botha, W</dc:creator><dc:creator>Campbell, CM</dc:creator><dc:creator>Chadderton, J</dc:creator><dc:creator>Chemey, AT</dc:creator><dc:creator>Clark, RM</dc:creator><dc:creator>Crawford, HL</dc:creator><dc:creator>Despotopulos, JD</dc:creator><dc:creator>Dorvaux, O</dc:creator><dc:creator>Esker, NE</dc:creator><dc:creator>Fallon, P</dc:creator><dc:creator>Folden, CM</dc:creator><dc:creator>Gall, BJP</dc:creator><dc:creator>Garcia, FH</dc:creator><dc:creator>Golubev, P</dc:creator><dc:creator>Gooding, JA</dc:creator><dc:creator>Grebo, M</dc:creator><dc:creator>Gregorich, KE</dc:creator><dc:creator>Guerrero, M</dc:creator><dc:creator>Henderson, RA</dc:creator><dc:creator>Herzberg, R-D</dc:creator><dc:creator>Hrabar, Y</dc:creator><dc:creator>King, TT</dc:creator><dc:creator>Covo, M Kireeff</dc:creator><dc:creator>Kirkland, AS</dc:creator><dc:creator>Krücken, R</dc:creator><dc:creator>Leistenschneider, E</dc:creator><dc:creator>Lykiardopoulou, EM</dc:creator><dc:creator>McCarthy, M</dc:creator><dc:creator>Mildon, JA</dc:creator><dc:creator>Müller-Gatermann, C</dc:creator><dc:creator>Phair, L</dc:creator><dc:creator>Pore, JL</dc:creator><dc:creator>Rice, E</dc:creator><dc:creator>Rykaczewski, KP</dc:creator><dc:creator>Sammis, BN</dc:creator><dc:creator>Sarmiento, LG</dc:creator><dc:creator>Seweryniak, D</dc:creator><dc:creator>Sharp, DK</dc:creator><dc:creator>Sinjari, A</dc:creator><dc:creator>Steinegger, P</dc:creator><dc:creator>Stoyer, MA</dc:creator><dc:creator>Szornel, JM</dc:creator><dc:creator>Thomas, K</dc:creator><dc:creator>Todd, DS</dc:creator><dc:creator>Vo, P</dc:creator><dc:creator>Watson, V</dc:creator><dc:creator>Wooddy, PT</dc:creator><dc:date>2024-10-25</dc:date><dc:description>The ^{244}Pu(^{50}Ti,xn)^{294-x}Lv reaction was investigated at Lawrence Berkeley National Laboratory's 88-Inch Cyclotron. The experiment was aimed at the production of a superheavy element with Z≥114 by irradiating an actinide target with a beam heavier than ^{48}Ca. Produced Lv ions were separated from the unwanted beam and nuclear reaction products using the Berkeley Gas-filled Separator and implanted into a newly commissioned focal-plane detector system. Two decay chains were observed and assigned to the decay of ^{290}Lv. The production cross section was measured to be σ_{prod}=0.44(_{-0.28}^{+0.58})  pb at a center-of-target center-of-mass energy of 220(3)&amp;nbsp;MeV. This represents the first published measurement of the production of a superheavy element near the "island of stability," with a beam of ^{50}Ti and is an essential precursor in the pursuit of searching for new elements beyond Z=118.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>CSD-05-HEC-B (c-lbnl-label)</dc:subject><dc:subject>NSD-88-Inch Cyclotron (c-lbnl-label)</dc:subject><dc:subject>NSD-Applied Nuclear Physics (c-lbnl-label)</dc:subject><dc:subject>NSD-Featured (c-lbnl-label)</dc:subject><dc:subject>NSD-Low Energy Nuclear Physics (c-lbnl-label)</dc:subject><dc:subject>01 Mathematical Sciences (for)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0p92q5md</dc:identifier><dc:identifier>https://escholarship.org/content/qt0p92q5md/qt0p92q5md.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevlett.133.172502</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review Letters, vol 133, iss 17</dc:source><dc:coverage>172502</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt53r2t6qh</identifier><datestamp>2026-09-16T03:37:41Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt53r2t6qh</dc:identifier><dc:title>Speciation Genomics in the Tiger Whiptail Lizards (Aspidoscelis tigris Complex)</dc:title><dc:creator>Barley, Anthony J</dc:creator><dc:creator>Ho, David V</dc:creator><dc:creator>Baumann, Peter</dc:creator><dc:creator>Wang, Ian J</dc:creator><dc:creator>Shaffer, H Bradley</dc:creator><dc:creator>Fisher, Robert N</dc:creator><dc:creator>Gray, Levi N</dc:creator><dc:creator>Krabbenhoft, Trevor J</dc:creator><dc:creator>Espinoza, Robert E</dc:creator><dc:creator>Escalona, Merly</dc:creator><dc:creator>Toffelmier, Erin</dc:creator><dc:creator>Sahasrabudhe, Ruta</dc:creator><dc:creator>Nguyen, Oanh</dc:creator><dc:creator>Fairbairn, Colin W</dc:creator><dc:creator>Beraut, Eric</dc:creator><dc:creator>Thomson, Robert C</dc:creator><dc:contributor>Mugal, Carina</dc:contributor><dc:date>2025-11-28</dc:date><dc:description>The transition from small genetic to genome-scale datasets for studying biodiversity has revealed that genetic exchange through introgressive hybridization is a widespread phenomenon in nature. Despite this, a lack of high-quality reference genomes for most non-model species limits our understanding of the impact of this process for many taxonomic groups. This restricts the range of insights that genomic tools can provide for conservation biologists, who often hope to employ genomic datasets to accurately identify historically isolated lineages to protect and to predict their evolutionary fate in the face of environmental change. Tiger whiptail lizards (Aspidoscelis tigris complex) are an abundant and important ecological component of ecosystems across the southwestern United States. In this study, we assembled and annotated a chromosome-level reference genome for A. t. stejnegeri from coastal California. We then used this reference genome to reconstruct patterns of speciation and admixture within the larger species complex, finding evidence that gene flow is widespread both geographically and across the genome.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>3104 Evolutionary Biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Biotechnology (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Generic health relevance (hrcs-hc)</dc:subject><dc:subject>15 Life on Land (sdg)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Lizards (mesh)</dc:subject><dc:subject>Genetic Speciation (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>Gene Flow (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>California Conservation Genomics Project</dc:subject><dc:subject>CCGP</dc:subject><dc:subject>introgression</dc:subject><dc:subject>phylogeny</dc:subject><dc:subject>reference genome</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Lizards (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Genetic Speciation (mesh)</dc:subject><dc:subject>Gene Flow (mesh)</dc:subject><dc:subject>CCGP</dc:subject><dc:subject>California Conservation Genomics Project</dc:subject><dc:subject>introgression</dc:subject><dc:subject>phylogeny</dc:subject><dc:subject>reference genome</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Lizards (mesh)</dc:subject><dc:subject>Genetic Speciation (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>Gene Flow (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>0601 Biochemistry and Cell Biology (for)</dc:subject><dc:subject>0603 Evolutionary Biology (for)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>Developmental Biology (science-metrix)</dc:subject><dc:subject>3101 Biochemistry and cell biology (for-2020)</dc:subject><dc:subject>3104 Evolutionary biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/53r2t6qh</dc:identifier><dc:identifier>https://escholarship.org/content/qt53r2t6qh/qt53r2t6qh.pdf</dc:identifier><dc:identifier>info:doi/10.1093/gbe/evaf218</dc:identifier><dc:type>article</dc:type><dc:source>Genome Biology and Evolution, vol 17, iss 12</dc:source><dc:coverage>evaf218</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1qs17737</identifier><datestamp>2026-09-16T03:37:33Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1qs17737</dc:identifier><dc:title>The future low-temperature geochemical data-scape as envisioned by the U.S. geochemical community</dc:title><dc:creator>Brantley, Susan L</dc:creator><dc:creator>Wen, Tao</dc:creator><dc:creator>Agarwal, Deborah A</dc:creator><dc:creator>Catalano, Jeffrey G</dc:creator><dc:creator>Schroeder, Paul A</dc:creator><dc:creator>Lehnert, Kerstin</dc:creator><dc:creator>Varadharajan, Charuleka</dc:creator><dc:creator>Pett-Ridge, Julie</dc:creator><dc:creator>Engle, Mark</dc:creator><dc:creator>Castronova, Anthony M</dc:creator><dc:creator>Hooper, Richard P</dc:creator><dc:creator>Ma, Xiaogang</dc:creator><dc:creator>Jin, Lixin</dc:creator><dc:creator>McHenry, Kenton</dc:creator><dc:creator>Aronson, Emma</dc:creator><dc:creator>Shaughnessy, Andrew R</dc:creator><dc:creator>Derry, Louis A</dc:creator><dc:creator>Richardson, Justin</dc:creator><dc:creator>Bales, Jerad</dc:creator><dc:creator>Pierce, Eric M</dc:creator><dc:date>2021-12-01</dc:date><dc:description>Data sharing benefits the researcher, the scientific community, and the public by allowing the impact of data to be generalized beyond one project and by making science more transparent. However, many scientific communities have not developed protocols or standards for publishing, citing, and versioning datasets. One community that lags in data management is that of low-temperature geochemistry (LTG). This paper resulted from an initiative from 2018 through 2020 to convene LTG and data scientists in the U.S. to strategize future management of LTG data. Through webinars, a workshop, a preprint, a townhall, and a community survey, the group of U.S. scientists discussed the landscape of data management for LTG – the data-scape. Currently this data-scape includes a “street bazaar” of data repositories. This was deemed appropriate in the same way that LTG scientists publish articles in many journals. The variety of data repositories and journals reflect that LTG scientists target many different scientific questions, produce data with extremely different structures and volumes, and utilize copious and complex metadata. Nonetheless, the group agreed that publication of LTG science must be accompanied by sharing of data in publicly accessible repositories, and, for sample-based data, registration of samples with globally unique persistent identifiers. LTG scientists should use certified data repositories that are either highly structured databases designed for specialized types of data, or unstructured generalized data systems. Recognizing the need for tools to enable search and cross-referencing across the proliferating data repositories, the group proposed that the overall data informatics paradigm in LTG should shift from “build data repository, data will come” to “publish data online, cybertools will find”. Funding agencies could also provide portals for LTG scientists to register funded projects and datasets, and forge approaches that cross national boundaries. The needed transformation of the LTG data culture requires emphasis in student education on science and management of data.</dc:description><dc:subject>46 Information and Computing Sciences (for-2020)</dc:subject><dc:subject>4610 Library and Information Studies (for-2020)</dc:subject><dc:subject>Data Science (rcdc)</dc:subject><dc:subject>Data management</dc:subject><dc:subject>Data repositories</dc:subject><dc:subject>Geochemistry</dc:subject><dc:subject>Metadata</dc:subject><dc:subject>Data sharing</dc:subject><dc:subject>Open science</dc:subject><dc:subject>04 Earth Sciences (for)</dc:subject><dc:subject>08 Information and Computing Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Geochemistry &amp; Geophysics (science-metrix)</dc:subject><dc:subject>37 Earth sciences (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>46 Information and computing sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1qs17737</dc:identifier><dc:identifier>https://escholarship.org/content/qt1qs17737/qt1qs17737.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.cageo.2021.104933</dc:identifier><dc:type>article</dc:type><dc:source>Computers &amp; Geosciences, vol 157</dc:source><dc:coverage>104933</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0w96p15x</identifier><datestamp>2026-09-16T03:37:28Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0w96p15x</dc:identifier><dc:title>Eco-Labeling Strategies and Price-Premium</dc:title><dc:creator>Delmas, Magali A</dc:creator><dc:creator>Grant, Laura E</dc:creator><dc:date>2014-01-01</dc:date><dc:description>Although there is increasing use of eco-labeling, conditions under which eco-labels can command price premiums are not fully understood. In this article, we demonstrate that the certification of environmental practices by a third party should be analyzed as a strategy distinct from—although related to—the disclosure of the eco-certification through a label posted on the product. By assessing eco-labeling and eco-certification strategies separately, researchers can identify benefits associated with the certification process, such as improved reputation in the industry or increased product quality, independently from those associated with the actual label. In the context of the wine industry, we show that eco-certification leads to a price premium while the use of the eco-label does not.</dc:description><dc:subject>35 Commerce</dc:subject><dc:subject>Management</dc:subject><dc:subject>Tourism and Services (for-2020)</dc:subject><dc:subject>3507 Strategy</dc:subject><dc:subject>Management and Organisational Behaviour (for-2020)</dc:subject><dc:subject>information disclosure policy</dc:subject><dc:subject>eco-label</dc:subject><dc:subject>certification</dc:subject><dc:subject>hedonic regression</dc:subject><dc:subject>information asymmetry</dc:subject><dc:subject>Information disclosure policy</dc:subject><dc:subject>eco-label</dc:subject><dc:subject>certification</dc:subject><dc:subject>hedonic regression</dc:subject><dc:subject>information asymmetry</dc:subject><dc:subject>1503 Business and Management (for)</dc:subject><dc:subject>Business &amp; Management (science-metrix)</dc:subject><dc:subject>3507 Strategy</dc:subject><dc:subject>management and organisational behaviour (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0w96p15x</dc:identifier><dc:identifier>https://escholarship.org/content/qt0w96p15x/qt0w96p15x.pdf</dc:identifier><dc:identifier>info:doi/10.1177/0007650310362254</dc:identifier><dc:type>article</dc:type><dc:source>Business &amp; Society, vol 53, iss 1</dc:source><dc:coverage>6 - 44</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt867528n7</identifier><datestamp>2026-09-16T03:33:25Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt867528n7</dc:identifier><dc:title>DESI 2024: reconstructing dark energy using crossing statistics with DESI DR1 BAO data</dc:title><dc:creator>Calderon, R</dc:creator><dc:creator>Lodha, K</dc:creator><dc:creator>Shafieloo, A</dc:creator><dc:creator>Linder, E</dc:creator><dc:creator>Sohn, W</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Cervantes-Cota, JL</dc:creator><dc:creator>Crittenden, R</dc:creator><dc:creator>Davis, TM</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Kim, AG</dc:creator><dc:creator>Matthewson, W</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Park, S</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Allen, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Ruhlmann-Kleider, V</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Taylor, P</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2024-10-01</dc:date><dc:description>We implement Crossing Statistics to reconstruct in a model-agnostic manner the expansion history of the universe and properties of dark energy, using DESI Data Release 1 (DR1) BAO data in combination with one of three different supernova compilations (PantheonPlus, Union3, and DES-SN5YR) and Planck CMB observations. Our results hint towards an evolving and emergent dark energy behaviour, with negligible presence of dark energy at z ≳ 1, at varying significance depending on data sets combined. In all these reconstructions, the cosmological constant lies outside the 95% confidence intervals for some redshift ranges. This dark energy behaviour, reconstructed using Crossing Statistics, is in agreement with results from the conventional w 0–w a dark energy equation of state parametrization reported in the DESI Key cosmology paper. Our results add an extensive class of model-agnostic reconstructions with acceptable fits to the data, including models where cosmic acceleration slows down at low redshifts. We also report constraints on H 0 r d from our model-agnostic analysis, independent of the pre-recombination physics.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>dark energy experiments</dc:subject><dc:subject>dark energy theory</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/867528n7</dc:identifier><dc:identifier>https://escholarship.org/content/qt867528n7/qt867528n7.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2024/10/048</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2024, iss 10</dc:source><dc:coverage>048</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt68g1b51r</identifier><datestamp>2026-09-16T03:32:56Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt68g1b51r</dc:identifier><dc:title>Measurement of transverse single-spin asymmetries of π0 and electromagnetic jets at forward rapidity in 200 and 500 GeV transversely polarized proton-proton collisions</dc:title><dc:creator>Adam, J</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, JR</dc:creator><dc:creator>Adkins, JK</dc:creator><dc:creator>Agakishiev, G</dc:creator><dc:creator>Aggarwal, MM</dc:creator><dc:creator>Ahammed, Z</dc:creator><dc:creator>Alekseev, I</dc:creator><dc:creator>Anderson, DM</dc:creator><dc:creator>Aparin, A</dc:creator><dc:creator>Aschenauer, EC</dc:creator><dc:creator>Ashraf, MU</dc:creator><dc:creator>Atetalla, FG</dc:creator><dc:creator>Attri, A</dc:creator><dc:creator>Averichev, GS</dc:creator><dc:creator>Bairathi, V</dc:creator><dc:creator>Barish, K</dc:creator><dc:creator>Behera, A</dc:creator><dc:creator>Bellwied, R</dc:creator><dc:creator>Bhasin, A</dc:creator><dc:creator>Bielcik, J</dc:creator><dc:creator>Bielcikova, J</dc:creator><dc:creator>Bland, LC</dc:creator><dc:creator>Bordyuzhin, IG</dc:creator><dc:creator>Brandenburg, JD</dc:creator><dc:creator>Brandin, AV</dc:creator><dc:creator>Butterworth, J</dc:creator><dc:creator>Caines, H</dc:creator><dc:creator>de la Barca Sánchez, M Calderón</dc:creator><dc:creator>Cebra, D</dc:creator><dc:creator>Chakaberia, I</dc:creator><dc:creator>Chaloupka, P</dc:creator><dc:creator>Chan, BK</dc:creator><dc:creator>Chang, F-H</dc:creator><dc:creator>Chang, Z</dc:creator><dc:creator>Chankova-Bunzarova, N</dc:creator><dc:creator>Chatterjee, A</dc:creator><dc:creator>Chen, D</dc:creator><dc:creator>Chen, J</dc:creator><dc:creator>Chen, JH</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Chen, Z</dc:creator><dc:creator>Cheng, J</dc:creator><dc:creator>Cherney, M</dc:creator><dc:creator>Chevalier, M</dc:creator><dc:creator>Choudhury, S</dc:creator><dc:creator>Christie, W</dc:creator><dc:creator>Chu, X</dc:creator><dc:creator>Crawford, HJ</dc:creator><dc:creator>Csanád, M</dc:creator><dc:creator>Daugherity, M</dc:creator><dc:creator>Dedovich, TG</dc:creator><dc:creator>Deppner, IM</dc:creator><dc:creator>Derevschikov, AA</dc:creator><dc:creator>Didenko, L</dc:creator><dc:creator>Dilks, C</dc:creator><dc:creator>Dong, X</dc:creator><dc:creator>Drachenberg, JL</dc:creator><dc:creator>Dunlop, JC</dc:creator><dc:creator>Edmonds, T</dc:creator><dc:creator>Elsey, N</dc:creator><dc:creator>Engelage, J</dc:creator><dc:creator>Eppley, G</dc:creator><dc:creator>Esumi, S</dc:creator><dc:creator>Evdokimov, O</dc:creator><dc:creator>Ewigleben, A</dc:creator><dc:creator>Eyser, O</dc:creator><dc:creator>Fatemi, R</dc:creator><dc:creator>Fazio, S</dc:creator><dc:creator>Federic, P</dc:creator><dc:creator>Fedorisin, J</dc:creator><dc:creator>Feng, CJ</dc:creator><dc:creator>Feng, Y</dc:creator><dc:creator>Filip, P</dc:creator><dc:creator>Finch, E</dc:creator><dc:creator>Fisyak, Y</dc:creator><dc:creator>Francisco, A</dc:creator><dc:creator>Fulek, L</dc:creator><dc:creator>Gagliardi, CA</dc:creator><dc:creator>Galatyuk, T</dc:creator><dc:creator>Geurts, F</dc:creator><dc:creator>Ghimire, N</dc:creator><dc:creator>Gibson, A</dc:creator><dc:creator>Gopal, K</dc:creator><dc:creator>Gou, X</dc:creator><dc:creator>Grosnick, D</dc:creator><dc:creator>Guryn, W</dc:creator><dc:creator>Hamad, AI</dc:creator><dc:creator>Hamed, A</dc:creator><dc:creator>Harabasz, S</dc:creator><dc:creator>Harris, JW</dc:creator><dc:creator>He, S</dc:creator><dc:creator>He, W</dc:creator><dc:creator>He, XH</dc:creator><dc:creator>He, Y</dc:creator><dc:creator>Heppelmann, S</dc:creator><dc:creator>Heppelmann, S</dc:creator><dc:creator>Herrmann, N</dc:creator><dc:creator>Hoffman, E</dc:creator><dc:creator>Holub, L</dc:creator><dc:date>2021-05-01</dc:date><dc:description>The STAR Collaboration reports measurements of the transverse single-spin asymmetry (TSSA) of inclusive π0 at center-of-mass energies (s) of 200 GeV and 500 GeV in transversely polarized proton-proton collisions in the pseudo-rapidity region 2.7 to 4.0. The results at the two different energies show a continuous increase of the TSSA with Feynman-x, and, when compared to previous measurements, no dependence on s from 19.4 GeV to 500 GeV is found. To investigate the underlying physics leading to this large TSSA, different topologies have been studied. π0 with no nearby particles tend to have a higher TSSA than inclusive π0. The TSSA for inclusive electromagnetic jets, sensitive to the Sivers effect in the initial state, is substantially smaller, but shows the same behavior as the inclusive π0 asymmetry as a function of Feynman-x. To investigate final-state effects, the Collins asymmetry of π0 inside electromagnetic jets has been measured. The Collins asymmetry is analyzed for its dependence on the π0 momentum transverse to the jet thrust axis and its dependence on the fraction of jet energy carried by the π0. The asymmetry was found to be small in each case for both center-of-mass energies. All the measurements are compared to QCD-based theoretical calculations for transverse-momentum-dependent parton distribution functions and fragmentation functions. Some discrepancies are found, which indicates new mechanisms might be involved.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>4902 Mathematical Physics (for-2020)</dc:subject><dc:subject>49 Mathematical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>NSD-Relativistic Nuclear Collisions (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/68g1b51r</dc:identifier><dc:identifier>https://escholarship.org/content/qt68g1b51r/qt68g1b51r.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevd.103.092009</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 103, iss 9</dc:source><dc:coverage>092009</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9zg247nt</identifier><datestamp>2026-09-16T03:32:35Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9zg247nt</dc:identifier><dc:title>Perspectives of lowering CUORE thresholds with Optimum Trigger</dc:title><dc:creator>Dompè, V</dc:creator><dc:creator>Adams, DQ</dc:creator><dc:creator>Alduino, C</dc:creator><dc:creator>Alfonso, K</dc:creator><dc:creator>Avignone, FT</dc:creator><dc:creator>Azzolini, O</dc:creator><dc:creator>Bari, G</dc:creator><dc:creator>Bellini, F</dc:creator><dc:creator>Benato, G</dc:creator><dc:creator>Bersani, A</dc:creator><dc:creator>Biassoni, M</dc:creator><dc:creator>Branca, A</dc:creator><dc:creator>Brofferio, C</dc:creator><dc:creator>Bucci, C</dc:creator><dc:creator>Caminata, A</dc:creator><dc:creator>Campani, A</dc:creator><dc:creator>Canonica, L</dc:creator><dc:creator>Cao, XG</dc:creator><dc:creator>Capelli, S</dc:creator><dc:creator>Cappelli, L</dc:creator><dc:creator>Cardani, L</dc:creator><dc:creator>Carniti, P</dc:creator><dc:creator>Casali, N</dc:creator><dc:creator>Chiesa, D</dc:creator><dc:creator>Chott, N</dc:creator><dc:creator>Clemenza, M</dc:creator><dc:creator>Copello, S</dc:creator><dc:creator>Cosmelli, C</dc:creator><dc:creator>Cremonesi, O</dc:creator><dc:creator>Creswick, RJ</dc:creator><dc:creator>Cushman, JS</dc:creator><dc:creator>D’Addabbo, A</dc:creator><dc:creator>D’Aguanno, D</dc:creator><dc:creator>Dafinei, I</dc:creator><dc:creator>Davis, CJ</dc:creator><dc:creator>Dell’Oro, S</dc:creator><dc:creator>Di Domizio, S</dc:creator><dc:creator>Drobizhev, A</dc:creator><dc:creator>Fang, DQ</dc:creator><dc:creator>Fantini, G</dc:creator><dc:creator>Faverzani, M</dc:creator><dc:creator>Ferri, E</dc:creator><dc:creator>Ferroni, F</dc:creator><dc:creator>Fiorini, E</dc:creator><dc:creator>Franceschi, MA</dc:creator><dc:creator>Freedman, SJ</dc:creator><dc:creator>Fujikawa, BK</dc:creator><dc:creator>Giachero, A</dc:creator><dc:creator>Gironi, L</dc:creator><dc:creator>Giuliani, A</dc:creator><dc:creator>Gorla, P</dc:creator><dc:creator>Gotti, C</dc:creator><dc:creator>Gutierrez, TD</dc:creator><dc:creator>Han, K</dc:creator><dc:creator>Heeger, KM</dc:creator><dc:creator>Huang, RG</dc:creator><dc:creator>Huang, HZ</dc:creator><dc:creator>Johnston, J</dc:creator><dc:creator>Keppel, G</dc:creator><dc:creator>Kolomensky, Yu G</dc:creator><dc:creator>Leder, A</dc:creator><dc:creator>Ligi, C</dc:creator><dc:creator>G, Y</dc:creator><dc:creator>Marini, L</dc:creator><dc:creator>Martinez, M</dc:creator><dc:creator>Maruyama, RH</dc:creator><dc:creator>Mei, Y</dc:creator><dc:creator>Moggi, N</dc:creator><dc:creator>Morganti, S</dc:creator><dc:creator>Napolitano, T</dc:creator><dc:creator>Nastasi, M</dc:creator><dc:creator>Nones, C</dc:creator><dc:creator>Norman, EB</dc:creator><dc:creator>Novati, V</dc:creator><dc:creator>Nucciotti, A</dc:creator><dc:creator>Nutini, I</dc:creator><dc:creator>O’Donnell, T</dc:creator><dc:creator>Ouellet, JL</dc:creator><dc:creator>Pagliarone, CE</dc:creator><dc:creator>Pallavicini, M</dc:creator><dc:creator>Pattavina, L</dc:creator><dc:creator>Pavan, M</dc:creator><dc:creator>Pessina, G</dc:creator><dc:creator>Pettinacci, V</dc:creator><dc:creator>Pira, C</dc:creator><dc:creator>Pirro, S</dc:creator><dc:creator>Pozzi, S</dc:creator><dc:creator>Previtali, E</dc:creator><dc:creator>Puiu, A</dc:creator><dc:creator>Rosenfeld, C</dc:creator><dc:creator>Rusconi, C</dc:creator><dc:creator>Sakai, M</dc:creator><dc:creator>Sangiorgio, S</dc:creator><dc:creator>Schmidt, B</dc:creator><dc:creator>Scielzo, ND</dc:creator><dc:creator>Singh, V</dc:creator><dc:creator>Sisti, M</dc:creator><dc:creator>Speller, D</dc:creator><dc:creator>Taffarello, L</dc:creator><dc:creator>Terranova, F</dc:creator><dc:date>2020-12-01</dc:date><dc:description>CUORE is a cryogenic experiment that focuses on the search of neutrinoless double beta decay in 130Te and it is located at the Gran Sasso National Laboratories. Its detector consists of 988 TeO2 crystals operating at a base temperature of ∼10 mK. It is the first ton-scale bolometric experiment ever realized for this purpose. Thanks to its large target mass and ultra-low background, the CUORE detector is also suitable for the search of other rare phenomena. In particular the low energy part of the spectra is interesting for the detection of WIMP-nuclei scattering reactions. One of the most important requirements to perform these studies is represented by the achievement of a stable energy threshold lower than 10 keV. Here, the CUORE capability to accomplish this purpose using a low energy software trigger will be presented and described.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>NSD-Neutrinos (c-lbnl-label)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0299 Other Physical Sciences (for)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9zg247nt</dc:identifier><dc:identifier>https://escholarship.org/content/qt9zg247nt/qt9zg247nt.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1742-6596/1643/1/012020</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Physics Conference Series, vol 1643, iss 1</dc:source><dc:coverage>012020</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3rs3q5cx</identifier><datestamp>2026-09-16T03:28:47Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3rs3q5cx</dc:identifier><dc:title>Impact of heteroresistance on treatment outcomes of people with drug-resistant TB</dc:title><dc:creator>Crowder, R</dc:creator><dc:creator>Kato-Maeda, M</dc:creator><dc:creator>Schwem, B</dc:creator><dc:creator>dela Tonga, A</dc:creator><dc:creator>Geocaniga-Gaviola, DM</dc:creator><dc:creator>Lopez, E</dc:creator><dc:creator>Valdez, CL</dc:creator><dc:creator>Lim, AR</dc:creator><dc:creator>Hunat, N</dc:creator><dc:creator>Sedusta, AG</dc:creator><dc:creator>Sacopon, CA</dc:creator><dc:creator>Atienza, GAM</dc:creator><dc:creator>Bulag, E</dc:creator><dc:creator>Lim, D</dc:creator><dc:creator>Bascuña, J</dc:creator><dc:creator>Shah, K</dc:creator><dc:creator>Basillio, RP</dc:creator><dc:creator>Berger, CA</dc:creator><dc:creator>Lopez, MCDP</dc:creator><dc:creator>Sen, S</dc:creator><dc:creator>Allender, C</dc:creator><dc:creator>Folkerts, M</dc:creator><dc:creator>Karaoz, U</dc:creator><dc:creator>Brodie, E</dc:creator><dc:creator>Mitarai, S</dc:creator><dc:creator>Garfin, AMC</dc:creator><dc:creator>Ama, MC</dc:creator><dc:creator>Engelthaler, DM</dc:creator><dc:creator>Cattamanchi, A</dc:creator><dc:creator>Destura, R</dc:creator><dc:date>2024-10-01</dc:date><dc:description>BACKGROUND: Poor treatment outcomes among people with drug-resistant TB (DR-TB) are a major concern. Heteroresistance (presence of susceptible and resistant Mycobacterium tuberculosis in the same sample) has been identified in some people with TB, but its impact on treatment outcomes is unknown.
METHODS: We used targeted deep sequencing to identify mutations associated with DR-TB and heteroresistance in culture samples of 624 people with DR-TB. We evaluated the association between heteroresistance and time to unfavorable treatment outcome using Cox proportional hazards regression.
RESULTS: The proportion of drug-resistant isolates with a known mutation conferring resistance was lower for streptomycin (45.2%) and second-line injectables (79.1%) than for fluoroquinolones (86.7%), isoniazid (93.2%) and rifampin (96.5%). Fifty-two (8.3%) had heteroresistance, and it was more common for fluoroquinolones (4.6%) than rifampin (2.2%), second-line injectables (1.4%), streptomycin (1.7%), or isoniazid (1.3%). There was no association between heteroresistance and time to unfavorable outcome among people with multidrug-resistant TB (adjusted hazard ratio [aHR] 1.74, 95% CI 0.39-7.72) or pre-extensively DR-TB (aHR 0.65, 95% CI 0.24-1.72).
CONCLUSIONS: Heteroresistance was relatively common (8.3%) among people with DR-TB in the Philippines. However, we found insufficient evidence to demonstrate an impact on unfavorable treatment outcomes.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>Antimicrobial Resistance (rcdc)</dc:subject><dc:subject>Orphan Drug (rcdc)</dc:subject><dc:subject>Infectious Diseases (rcdc)</dc:subject><dc:subject>Tuberculosis (rcdc)</dc:subject><dc:subject>Emerging Infectious Diseases (rcdc)</dc:subject><dc:subject>Rare Diseases (rcdc)</dc:subject><dc:subject>Biodefense (rcdc)</dc:subject><dc:subject>2.1 Biological and endogenous factors (hrcs-rac)</dc:subject><dc:subject>6.1 Pharmaceuticals (hrcs-rac)</dc:subject><dc:subject>Infection (hrcs-hc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>DR-TB</dc:subject><dc:subject>Drug resistance-associated mutations</dc:subject><dc:subject>tuberculosis</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3rs3q5cx</dc:identifier><dc:identifier>https://escholarship.org/content/qt3rs3q5cx/qt3rs3q5cx.pdf</dc:identifier><dc:identifier>info:doi/10.5588/ijtldopen.24.0343</dc:identifier><dc:type>article</dc:type><dc:source>IJTLD OPEN, vol 1, iss 10</dc:source><dc:coverage>466 - 472</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt08b4f1cg</identifier><datestamp>2026-09-16T03:28:11Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt08b4f1cg</dc:identifier><dc:title>Bioenergy Cropping Reduces the Spatiotemporal Scaling of Soil Bacterial Biodiversity</dc:title><dc:creator>Ye, Zhencheng</dc:creator><dc:creator>Kuang, Jialiang</dc:creator><dc:creator>Bates, Colin T</dc:creator><dc:creator>Escalas, Arthur</dc:creator><dc:creator>Ning, Daliang</dc:creator><dc:creator>Wu, Liyou</dc:creator><dc:creator>Liu, Suo</dc:creator><dc:creator>Deng, Sihang</dc:creator><dc:creator>Lei, Jiesi</dc:creator><dc:creator>Chen, Xiangwen</dc:creator><dc:creator>Pett‐Ridge, Jennifer</dc:creator><dc:creator>Saha, Malay</dc:creator><dc:creator>Hale, Lauren</dc:creator><dc:creator>Wang, Gangsheng</dc:creator><dc:creator>Tian, Renmao</dc:creator><dc:creator>Fu, Ying</dc:creator><dc:creator>Tang, Yu</dc:creator><dc:creator>Firestone, Mary</dc:creator><dc:creator>Zhou, Jizhong</dc:creator><dc:creator>Yang, Yunfeng</dc:creator><dc:date>2026-05-01</dc:date><dc:description>Widespread bioenergy cropping can transform landscapes, strongly affecting biodiversity. However, the impact of bioenergy cropping on the spatiotemporal scaling of soil biodiversity remains virtually unknown, despite its profound implications for the functioning of the ecological community. Here, we investigated how bioenergy cropping influenced the spatiotemporal scaling of soil bacterial biodiversity in marginal soils (sandy loam and clay loam soils) in Oklahoma, USA. We detected strong, significant species-time-area relationships (STARs) and phylogenetic-time-area relationships (PTARs) in bacterial communities and their lineages, suggesting that STARs and PTARs exist in microbial ecology within the studied system. Also, spatiotemporal scaling rates (the slopes of STAR and PTAR models) varied substantially among bacterial lineages and were positively correlated with their 16S rRNA gene copy numbers, a genomic trait indicative of microbial growth potentials. Strikingly, bioenergy cropping significantly reduced spatiotemporal scaling rates by 6.8%-14.1%, with a more pronounced reduction observed in sandy loam soils, where those rates were significantly lower than in clay loam soils. The heterogeneity of soil phosphorus and carbon resulted in variations in bacterial spatiotemporal scaling rates. Collectively, our findings suggest that bioenergy cropping may alleviate rapid shifts in soil biodiversity across space and time, thereby stabilizing soil biodiversity and supporting its role as part of sustainable land management and climate mitigation strategies.</dc:description><dc:subject>30 Agricultural</dc:subject><dc:subject>Veterinary and Food Sciences (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>3007 Forestry Sciences (for-2020)</dc:subject><dc:subject>15 Life on Land (sdg)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>RNA</dc:subject><dc:subject>Ribosomal</dc:subject><dc:subject>16S (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Agriculture (mesh)</dc:subject><dc:subject>Oklahoma (mesh)</dc:subject><dc:subject>Biofuels (mesh)</dc:subject><dc:subject>bacterial diversity</dc:subject><dc:subject>bioenergy cropping</dc:subject><dc:subject>spatial scaling</dc:subject><dc:subject>species-time-area relationship</dc:subject><dc:subject>temporal scaling</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>RNA</dc:subject><dc:subject>Ribosomal</dc:subject><dc:subject>16S (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Agriculture (mesh)</dc:subject><dc:subject>Oklahoma (mesh)</dc:subject><dc:subject>Biofuels (mesh)</dc:subject><dc:subject>bacterial diversity</dc:subject><dc:subject>bioenergy cropping</dc:subject><dc:subject>spatial scaling</dc:subject><dc:subject>species‐time‐area relationship</dc:subject><dc:subject>temporal scaling</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>RNA</dc:subject><dc:subject>Ribosomal</dc:subject><dc:subject>16S (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Agriculture (mesh)</dc:subject><dc:subject>Oklahoma (mesh)</dc:subject><dc:subject>Biofuels (mesh)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/08b4f1cg</dc:identifier><dc:identifier>https://escholarship.org/content/qt08b4f1cg/qt08b4f1cg.pdf</dc:identifier><dc:identifier>info:doi/10.1002/advs.202518964</dc:identifier><dc:type>article</dc:type><dc:source>Advanced Science, vol 13, iss 29</dc:source><dc:coverage>e18964</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1zf6h82v</identifier><datestamp>2026-09-16T03:16:00Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1zf6h82v</dc:identifier><dc:title>Just Write Fortran: Experiences with a Language-Based Alternative to MPI+X</dc:title><dc:creator>Rouson, Damian</dc:creator><dc:creator>Dibba, Baboucarr</dc:creator><dc:creator>Rasmussen, Katherine</dc:creator><dc:creator>Richardson, Brad</dc:creator><dc:creator>Torres, David</dc:creator><dc:creator>Zhang, Yunhao</dc:creator><dc:creator>Gutmann, Ethan</dc:creator><dc:creator>Ergawy, Kareem</dc:creator><dc:creator>Klemm, Michael</dc:creator><dc:creator>Shende, Sameer</dc:creator><dc:date>2024-11-17</dc:date><dc:description>Fortran 2023, with its "do concurrent" and coarray parallel programming features, displaces many uses of extra-language parallel programming models such as MPI, OpenMP, and OpenACC. The Cray, Intel, LFortran, LLVM, and NVIDIA compilers automatically parallelize do concurrent in shared memory. The Cray, Intel, and GNU compilers support coarrays in shared- and distributed-memory, while the NAG compiler supports coarrays in shared memory. Thus, language-based parallelism is emerging as a portable alternative to MPI+X.

This talk will present experiences with automatic "do concurrent" parallelization in the deep learning library Inference-Engine and coarray communication in the Intermediate Complexity Atmospheric Research (ICAR), respectively.</dc:description><dc:subject>climate modeling</dc:subject><dc:subject>Coarray Fortran</dc:subject><dc:subject>deep learning</dc:subject><dc:subject>high-performance computing</dc:subject><dc:subject>parallel programming</dc:subject><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1zf6h82v</dc:identifier><dc:identifier>https://escholarship.org/content/qt1zf6h82v/qt1zf6h82v.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S4H88D</dc:identifier><dc:type>non_textual</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4tw8j7f8</identifier><datestamp>2026-09-16T03:15:57Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4tw8j7f8</dc:identifier><dc:title>Do small effects matter more in vulnerable populations? an investigation using Environmental influences on Child Health Outcomes (ECHO) cohorts</dc:title><dc:creator>Peacock, Janet L</dc:creator><dc:creator>Coto, Susana Diaz</dc:creator><dc:creator>Rees, Judy R</dc:creator><dc:creator>Sauzet, Odile</dc:creator><dc:creator>Jensen, Elizabeth T</dc:creator><dc:creator>Fichorova, Raina</dc:creator><dc:creator>Dunlop, Anne L</dc:creator><dc:creator>Paneth, Nigel</dc:creator><dc:creator>Padula, Amy</dc:creator><dc:creator>Woodruff, Tracey</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Trowbridge, Jessica</dc:creator><dc:creator>Goin, Dana</dc:creator><dc:creator>Maldonado, Luis E</dc:creator><dc:creator>Niu, Zhongzheng</dc:creator><dc:creator>Ghassabian, Akhgar</dc:creator><dc:creator>Transande, Leonardo</dc:creator><dc:creator>Ferrara, Assiamira</dc:creator><dc:creator>Croen, Lisa A</dc:creator><dc:creator>Alexeeff, Stacey</dc:creator><dc:creator>Breton, Carrie</dc:creator><dc:creator>Litonjua, Augusto</dc:creator><dc:creator>O’Connor, Thomas G</dc:creator><dc:creator>Lyall, Kristen</dc:creator><dc:creator>Volk, Heather</dc:creator><dc:creator>Alshawabkeh, Akram</dc:creator><dc:creator>Manjourides, Justin</dc:creator><dc:creator>Camargo, Carlos A</dc:creator><dc:creator>Dabelea, Dana</dc:creator><dc:creator>Hockett, Christine W</dc:creator><dc:creator>Bendixsen, Casper G</dc:creator><dc:creator>Hertz-Picciotto, Irva</dc:creator><dc:creator>Schmidt, Rebecca J</dc:creator><dc:creator>Hipwell, Alison E</dc:creator><dc:creator>Keenan, Kate</dc:creator><dc:creator>Karr, Catherine</dc:creator><dc:creator>LeWinn, Kaja Z</dc:creator><dc:creator>Lester, Barry</dc:creator><dc:creator>Camerota, Marie</dc:creator><dc:creator>Ganiban, Jody</dc:creator><dc:creator>McEvoy, Cynthia</dc:creator><dc:creator>Elliott, Michael R</dc:creator><dc:creator>Sathyanarayana, Sheela</dc:creator><dc:creator>Ji, Nan</dc:creator><dc:creator>Braun, Joseph M</dc:creator><dc:creator>Karagas, Margaret R</dc:creator><dc:date>2024-09-28</dc:date><dc:description>BackgroundA major challenge in epidemiology is knowing when an exposure effect is large enough to be clinically important, in particular how to interpret a difference in mean outcome in unexposed/exposed groups. Where it can be calculated, the proportion/percentage beyond a suitable cut-point is useful in defining individuals at high risk to give a more meaningful outcome. In this simulation study we compute differences in outcome means and proportions that arise from hypothetical small effects in vulnerable sub-populations.MethodsData from over 28,000 mother/child pairs belonging to the Environmental influences on Child Health Outcomes Program were used to examine the impact of hypothetical environmental exposures on mean birthweight, and low birthweight (LBW) (birthweight &amp;lt; 2500g). We computed mean birthweight in unexposed/exposed groups by sociodemographic categories (maternal education, health insurance, race, ethnicity) using a range of hypothetical exposure effect sizes. We compared the difference in mean birthweight and the percentage LBW, calculated using a distributional approach.ResultsWhen the hypothetical mean exposure effect was fixed (at 50, 125, 167 or 250g), the absolute difference in % LBW (risk difference) was not constant but varied by socioeconomic categories. The risk differences were greater in sub-populations with the highest baseline percentages LBW: ranging from 3.1–5.3 percentage points for exposure effect of 125g. Similar patterns were seen for other mean exposure sizes simulated.ConclusionsVulnerable sub-populations with greater baseline percentages at high risk fare worse when exposed to a small insult compared to the general population. This illustrates another facet of health disparity in vulnerable individuals.</dc:description><dc:subject>4206 Public Health (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>Perinatal Period - Conditions Originating in Perinatal Period (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>2.2 Factors relating to the physical environment (hrcs-rac)</dc:subject><dc:subject>Generic health relevance (hrcs-hc)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Vulnerable Populations (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Low Birth Weight (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Child Health (mesh)</dc:subject><dc:subject>Birth Weight (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Socioeconomic Factors (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Pregnancy outcomes</dc:subject><dc:subject>Child health outcome</dc:subject><dc:subject>Health disparities</dc:subject><dc:subject>Environmental exposure</dc:subject><dc:subject>Social determinants of health</dc:subject><dc:subject>Program Collaborators for Environmental influences on Child Health Outcomes</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Birth Weight (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Socioeconomic Factors (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Low Birth Weight (mesh)</dc:subject><dc:subject>Vulnerable Populations (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Child Health (mesh)</dc:subject><dc:subject>Child health outcome</dc:subject><dc:subject>Environmental exposure</dc:subject><dc:subject>Health disparities</dc:subject><dc:subject>Pregnancy outcomes</dc:subject><dc:subject>Social determinants of health</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Vulnerable Populations (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Low Birth Weight (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Child Health (mesh)</dc:subject><dc:subject>Birth Weight (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Socioeconomic Factors (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>1117 Public Health and Health Services (for)</dc:subject><dc:subject>Public Health (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4tw8j7f8</dc:identifier><dc:identifier>https://escholarship.org/content/qt4tw8j7f8/qt4tw8j7f8.pdf</dc:identifier><dc:identifier>info:doi/10.1186/s12889-024-20075-x</dc:identifier><dc:type>article</dc:type><dc:source>BMC Public Health, vol 24, iss 1</dc:source><dc:coverage>2655</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt13124758</identifier><datestamp>2026-09-16T03:15:04Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt13124758</dc:identifier><dc:title>Probabilistic Invasion Underlies Natural Gut Microbiome Stability</dc:title><dc:creator>Obadia, Benjamin</dc:creator><dc:creator>Güvener, ZT</dc:creator><dc:creator>Zhang, Vivian</dc:creator><dc:creator>Ceja-Navarro, Javier A</dc:creator><dc:creator>Brodie, Eoin L</dc:creator><dc:creator>Ja, William W</dc:creator><dc:creator>Ludington, William B</dc:creator><dc:date>2017-07-01</dc:date><dc:description>Species compositions of gut microbiomes impact host health [1-3], but the processes determining these compositions are largely unknown. An unexplained observation is that gut species composition varies widely between individuals but is largely stable over time within individuals [4, 5]. Stochastic factors during establishment may drive these alternative stable states (colonized versus non-colonized) [6, 7], which can influence susceptibility to pathogens, such as Clostridium difficile. Here we sought to quantify and model the dose response, dynamics, and stability of bacterial colonization in the fruit fly (Drosophila melanogaster) gut. Our precise, high-throughput technique revealed stable between-host variation in colonization when individual germ-free flies were fed their own natural commensals (including the probiotic Lactobacillus plantarum). Some flies were colonized while others remained germ-free even at extremely high bacterial doses. Thus, alternative stable states of colonization exist even in this low-complexity model of host-microbe interactions. These alternative states are driven by a fundamental asymmetry between the inoculum population and the stably colonized population that is mediated by spatial localization and a population bottleneck, which makes stochastic effects important by lowering the effective population size. Prior colonization with other bacteria reduced the chances of subsequent colonization, thus increasing the stability of higher-diversity guts. Therefore, stable gut diversity may be driven by inherently stochastic processes, which has important implications for combatting infectious diseases and for stably establishing probiotics in the gut.</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>Infectious Diseases (rcdc)</dc:subject><dc:subject>Emerging Infectious Diseases (rcdc)</dc:subject><dc:subject>Digestive Diseases (rcdc)</dc:subject><dc:subject>Microbiome (rcdc)</dc:subject><dc:subject>Nutrition (rcdc)</dc:subject><dc:subject>Complementary and Integrative Health (rcdc)</dc:subject><dc:subject>1.1 Normal biological development and functioning (hrcs-rac)</dc:subject><dc:subject>2.1 Biological and endogenous factors (hrcs-rac)</dc:subject><dc:subject>Infection (hrcs-hc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Drosophila melanogaster (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Gastrointestinal Microbiome (mesh)</dc:subject><dc:subject>Gastrointestinal Tract (mesh)</dc:subject><dc:subject>Probability (mesh)</dc:subject><dc:subject>Symbiosis (mesh)</dc:subject><dc:subject>Gastrointestinal Tract (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Drosophila melanogaster (mesh)</dc:subject><dc:subject>Probability (mesh)</dc:subject><dc:subject>Symbiosis (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Gastrointestinal Microbiome (mesh)</dc:subject><dc:subject>Drosophila</dc:subject><dc:subject>Lactobacillus</dc:subject><dc:subject>bacterial community</dc:subject><dc:subject>colonization</dc:subject><dc:subject>gut bacteria</dc:subject><dc:subject>invasion</dc:subject><dc:subject>lottery model</dc:subject><dc:subject>microbiome</dc:subject><dc:subject>population bottleneck</dc:subject><dc:subject>stochastic assembly</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Drosophila melanogaster (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Gastrointestinal Microbiome (mesh)</dc:subject><dc:subject>Gastrointestinal Tract (mesh)</dc:subject><dc:subject>Probability (mesh)</dc:subject><dc:subject>Symbiosis (mesh)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>17 Psychology and Cognitive Sciences (for)</dc:subject><dc:subject>Developmental Biology (science-metrix)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:subject>52 Psychology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/13124758</dc:identifier><dc:identifier>https://escholarship.org/content/qt13124758/qt13124758.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.cub.2017.05.034</dc:identifier><dc:type>article</dc:type><dc:source>Current Biology, vol 27, iss 13</dc:source><dc:coverage>1999 - 2006.e8</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt71p278hr</identifier><datestamp>2026-09-16T03:11:09Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt71p278hr</dc:identifier><dc:title>Empowering former smokers to become agents of change through thirdhand smoke education</dc:title><dc:creator>Ma, Carmen</dc:creator><dc:creator>Vang, Weeko</dc:creator><dc:creator>Yu, Edgar</dc:creator><dc:creator>Chen, Julin</dc:creator><dc:creator>Wong, Ching</dc:creator><dc:creator>Cheng, Joyce</dc:creator><dc:creator>Jacob, Peyton</dc:creator><dc:creator>Tsoh, Janice Y</dc:creator><dc:date>2024-03-20</dc:date><dc:description>Significance: Thirdhand smoke (THS), which includes secondhand smoke contami- nants, can be re-emitted and re-suspended into the air and are embedded into carpets, floors, and clothing. The awareness of THS and the health impacts from exposure to its harmful residues is low in the general population of the United States, especially in immigrant communities where smoking remains prevalent. Our study implemented a THS family-based intervention to promote THS awareness among Chinese American immigrants. Methods: The THS intervention included an education and home cleaning component delivered by lay health workers to 30 Chinese American dyads (N=60). Dyads consisted of former smokers who quit within the last two years and their non-smoking family member living in the same household. Participants completed pre- and post-in- tervention survey interviews and a sub-sample (N=15; 8 former smokers and 7 family members) participated in a post-intervention focus group. Multivariable regression adjusted for dyadic data was conducted to compare pre- and post-intervention changes in the Beliefs About Thirdhand Smoke (BATHS) overall and subscale (Persistence and Health) scores. Transcriptions from focus group interviews, conducted in Cantonese, were transcribed and translated, coded by two independent researchers and themati- cally analyzed using Dedoose. Results: All participants were born outside the US and 59% immigrated at age 30 or older (range: 7 to 63 years old). A majority (82%) spoke English less than “well” and 87% were married. BATHS scores analyses suggested that former smokers increased their THS awareness from pre- to post-intervention: BATHS Overall (M=3.95 [SD=0.50], p=0.021); Persistence (M=3.95 [SD=0.48], p=0.031) and Health (M=3.94 [SD=0.58], p=0.038), and their post-intervention THS scores became similar to the BATH scores of non-smoking family members which did not change at post-intervention. Thematic analyses of focus group interviews revealed emerging themes highlighting impacts on former smokers in increasing THS knowledge and strengthening desires to create dialogue about tobacco use with friends; for example, a former smoker shared “I will share my [THS] knowledge with others. I think it will help [my friends] as well.” Conclusion: A family-based THS education intervention has promising impacts to advance tobacco control in Chinese American immigrant communities by providing new THS knowledge and encouraging former smokers to become agents of change. Future research on empowering former smokers to become effective agents of change to promote tobacco-free communities is warranted.</dc:description><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/71p278hr</dc:identifier><dc:identifier/><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5r82464k</identifier><datestamp>2026-09-16T03:10:45Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5r82464k</dc:identifier><dc:title>CMB lensing and Lyα forest cross bispectrum from DESI’s first-year quasar sample</dc:title><dc:creator>Karaçaylı, Naim Göksel</dc:creator><dc:creator>Martini, Paul</dc:creator><dc:creator>Weinberg, David H</dc:creator><dc:creator>Ferraro, Simone</dc:creator><dc:creator>de Belsunce, Roger</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gonzalez-Morales, AX</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlafly, EF</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tan, T</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2024-09-15</dc:date><dc:description>The squeezed cross-bispectrum Bκ,Lyα between the gravitational lensing in the cosmic microwave background and the 1D Lyα forest power spectrum can constrain bias parameters and break degeneracies between σ8 and other cosmological parameters. We detect Bκ,Lyα with 4.8σ significance at an effective redshift zeff=2.4 using Planck PR3 lensing map and over 280,000 quasar spectra from the Dark Energy Spectroscopic Instrument’s first-year data. We test our measurement against metal contamination and foregrounds such as Galactic extinction and clusters of galaxies by deprojecting the thermal Sunyaev-Zeldovich effect. We compare our results to a tree-level perturbation theory calculation and find reasonable agreement between the model and measurement.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5r82464k</dc:identifier><dc:identifier>https://escholarship.org/content/qt5r82464k/qt5r82464k.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevd.110.063505</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 110, iss 6</dc:source><dc:coverage>063505</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt20q8g3mt</identifier><datestamp>2026-09-16T03:07:45Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt20q8g3mt</dc:identifier><dc:title>Baryon acoustic oscillation theory and modelling systematics for the DESI 2024 results</dc:title><dc:creator>Chen, Shi-Fan</dc:creator><dc:creator>Howlett, Cullan</dc:creator><dc:creator>White, Martin</dc:creator><dc:creator>McDonald, Patrick</dc:creator><dc:creator>Ross, Ashley J</dc:creator><dc:creator>Seo, Hee-Jong</dc:creator><dc:creator>Padmanabhan, Nikhil</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alam, S</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>Blum, R</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Sánchez, D</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Hanif, MMS</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Mena-Fernández, J</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Munoz-Gutierrez, A</dc:creator><dc:creator>Paillas, E</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Pérez-Fernández, A</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Rashkovetskyi, M</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rosado-Marin, A</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Ruggeri, R</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yu, J</dc:creator><dc:creator>Yuan, S</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zhou, Z</dc:creator><dc:date>2024-09-20</dc:date><dc:description>Abstract This paper provides a comprehensive overview of how fitting of Baryon Acoustic Oscillations (BAO) is carried out within the upcoming Dark Energy Spectroscopic Instrument’s (DESI) 2024 results using its DR1 dataset, and the associated systematic error budget from theory and modelling of the BAO. We derive new results showing how non-linearities in the clustering of galaxies can cause potential biases in measurements of the isotropic (αiso) and anisotropic (αap) BAO distance scales, and how these can be effectively removed with an appropriate choice of reconstruction algorithm. We then demonstrate how theory leads to a clear choice for how to model the BAO and develop, implement and validate a new model for the remaining smooth-broadband (i.e., without BAO) component of the galaxy clustering. Finally, we explore the impact of all remaining modelling choices on the BAO constraints from DESI using a suite of high-precision simulations, arriving at a set of best-practices for DESI BAO fits, and an associated theory and modelling systematic error. Overall, our results demonstrate the remarkable robustness of the BAO to all our modelling choices and motivate a combined theory and modelling systematic error contribution to the post-reconstruction DESI BAO measurements of no more than 0.1% (0.2%) for its isotropic (anisotropic) distance measurements. We expect the theory and best-practices laid out to here to be applicable to other BAO experiments in the era of DESI and beyond.</dc:description><dc:subject>5109 Space Sciences (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>cosmological parameters</dc:subject><dc:subject>distance scale</dc:subject><dc:subject>large-scale structure of Universe</dc:subject><dc:subject>cosmology: theory</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/20q8g3mt</dc:identifier><dc:identifier>https://escholarship.org/content/qt20q8g3mt/qt20q8g3mt.pdf</dc:identifier><dc:identifier>info:doi/10.1093/mnras/stae2090</dc:identifier><dc:type>article</dc:type><dc:source>Monthly Notices of the Royal Astronomical Society, vol 534, iss 1</dc:source><dc:coverage>544 - 574</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2928g9bt</identifier><datestamp>2026-09-16T03:07:34Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2928g9bt</dc:identifier><dc:title>The 3D Lyman-α forest power spectrum from eBOSS DR16</dc:title><dc:creator>de Belsunce, Roger</dc:creator><dc:creator>Philcox, Oliver HE</dc:creator><dc:creator>Iršič, Vid</dc:creator><dc:creator>McDonald, Patrick</dc:creator><dc:creator>Guy, Julien</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:date>2024-08-29</dc:date><dc:description>ABSTRACT We measure the three-dimensional power spectrum (P3D) of the transmitted flux in the Lyman-$\alpha$ (Ly $\alpha$) forest using the complete extended Baryon Oscillation Spectroscopic Survey data release 16 (eBOSS DR16). This sample consists of $\sim$205 000 quasar spectra in the redshift range $2\le z \le 4$ at an effective redshift $z=2.334$. We propose a pair-count spectral estimator in configuration space, weighting each pair by $\exp (i\mathbf {k}\cdot \mathbf {r})$, for wave vector $\mathbf {k}$ and pixel pair separation $\mathbf {r}$, effectively measuring the anisotropic power spectrum without the need for fast Fourier transforms. This accounts for the window matrix in a tractable way, avoiding artefacts found in Fourier-transform based power spectrum estimators due to the sparse sampling transverse to the line of sight of Ly $\alpha$ skewers. We extensively test our pipeline on two sets of mocks: (i) idealized Gaussian random fields with a sparse sampling of Ly $\alpha$ skewers, and (ii) log-normal LyaCoLoRe mocks including realistic noise levels, the eBOSS survey geometry and contaminants. On eBOSS DR16 data, the Kaiser formula with a non-linear correction term obtained from hydrodynamic simulations yields a good fit to the power spectrum data in the range $(0.02 \le k \le 0.35)\, h\, {\rm Mpc}^{-1}\,$ at the 1–2σ level with a covariance matrix derived from LyaCoLoRe mocks. We demonstrate a promising new approach for full-shape cosmological analyses of Ly $\alpha$ forest data from cosmological surveys such as eBOSS, the currently observing Dark Energy Spectroscopic Instrument and future surveys such as the Prime Focus Spectrograph, WEAVE-QSO, and 4MOST.</dc:description><dc:subject>5109 Space Sciences (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>methods: statistical</dc:subject><dc:subject>galaxies: statistics</dc:subject><dc:subject>Cosmology: large-scale structure of Universe</dc:subject><dc:subject>Cosmology: theory</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2928g9bt</dc:identifier><dc:identifier>https://escholarship.org/content/qt2928g9bt/qt2928g9bt.pdf</dc:identifier><dc:identifier>info:doi/10.1093/mnras/stae2035</dc:identifier><dc:type>article</dc:type><dc:source>Monthly Notices of the Royal Astronomical Society, vol 533, iss 3</dc:source><dc:coverage>3756 - 3770</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt53z9v017</identifier><datestamp>2026-09-16T03:07:26Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt53z9v017</dc:identifier><dc:title>Environmental hazards, social inequality, and fetal loss: Implications of live-birth bias for estimation of disparities in birth outcomes</dc:title><dc:creator>Goin, Dana E</dc:creator><dc:creator>Casey, Joan A</dc:creator><dc:creator>Kioumourtzoglou, Marianthi-Anna</dc:creator><dc:creator>Cushing, Lara J</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:date>2021-04-01</dc:date><dc:description>Restricting to live births can induce bias in studies of pregnancy and developmental outcomes, but whether this live-birth bias results in underestimating disparities is unknown. Bias may arise from collider stratification due to an unmeasured common cause of fetal loss and the outcome of interest, or depletion of susceptibles, where exposure differentially causes fetal loss among those with underlying susceptibility.
METHODS: We conducted a simulation study to examine the magnitude of live-birth bias in a population parameterized to resemble one year of conceptions in California (N = 625,000). We simulated exposure to a non-time-varying environmental hazard, risk of spontaneous abortion, and time to live birth using 1000 Monte Carlo simulations. Our outcome of interest was preterm birth. We included a social vulnerability factor to represent social disadvantage, and estimated overall risk differences for exposure and preterm birth using linear probability models and stratified by the social vulnerability factor. We calculated how often confidence intervals included the true point estimate (CI coverage probabilities) to illustrate whether effect estimates differed qualitatively from the truth.
RESULTS: Depletion of susceptibles resulted in a larger magnitude of bias compared with collider stratification, with larger bias among the socially vulnerable group. Coverage probabilities were not adversely affected by bias due to collider stratification. Depletion of susceptibles reduced coverage, especially among the socially vulnerable (coverage among socially vulnerable = 46%, coverage among nonsocially vulnerable = 91% in the most extreme scenario).
CONCLUSIONS: In simulations, hazardous environmental exposures induced live-birth bias and the bias was larger for socially vulnerable women.</dc:description><dc:subject>4202 Epidemiology (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>Perinatal Period - Conditions Originating in Perinatal Period (rcdc)</dc:subject><dc:subject>Conditions Affecting the Embryonic and Fetal Periods (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Pregnancy (rcdc)</dc:subject><dc:subject>Infant Mortality (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Reproductive health and childbirth (hrcs-hc)</dc:subject><dc:subject>preterm birth</dc:subject><dc:subject>Environmental hazard</dc:subject><dc:subject>selection bias</dc:subject><dc:subject>fetal loss</dc:subject><dc:subject>miscarriage</dc:subject><dc:subject>spontaneous abortion</dc:subject><dc:subject>health disparities</dc:subject><dc:subject>perinatal health</dc:subject><dc:subject>live-birth bias</dc:subject><dc:subject>Environmental hazard</dc:subject><dc:subject>fetal loss</dc:subject><dc:subject>health disparities</dc:subject><dc:subject>live-birth bias</dc:subject><dc:subject>miscarriage</dc:subject><dc:subject>perinatal health</dc:subject><dc:subject>preterm birth</dc:subject><dc:subject>selection bias</dc:subject><dc:subject>spontaneous abortion</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/53z9v017</dc:identifier><dc:identifier>https://escholarship.org/content/qt53z9v017/qt53z9v017.pdf</dc:identifier><dc:identifier>info:doi/10.1097/ee9.0000000000000131</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Epidemiology, vol 5, iss 2</dc:source><dc:coverage>e131</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt33c2k5jx</identifier><datestamp>2026-09-16T03:07:22Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt33c2k5jx</dc:identifier><dc:title>Exometabolite niche partitioning among sympatric soil bacteria</dc:title><dc:creator>Baran, Richard</dc:creator><dc:creator>Brodie, Eoin L</dc:creator><dc:creator>Mayberry-Lewis, Jazmine</dc:creator><dc:creator>Hummel, Eric</dc:creator><dc:creator>Da Rocha, Ulisses Nunes</dc:creator><dc:creator>Chakraborty, Romy</dc:creator><dc:creator>Bowen, Benjamin P</dc:creator><dc:creator>Karaoz, Ulas</dc:creator><dc:creator>Cadillo-Quiroz, Hinsby</dc:creator><dc:creator>Garcia-Pichel, Ferran</dc:creator><dc:creator>Northen, Trent R</dc:creator><dc:date>2015-09-01</dc:date><dc:description>Soils are arguably the most microbially diverse ecosystems. Physicochemical properties have been associated with the maintenance of this diversity. Yet, the role of microbial substrate specialization is largely unexplored since substrate utilization studies have focused on simple substrates, not the complex mixtures representative of the soil environment. Here we examine the exometabolite composition of desert biological soil crusts (biocrusts) and the substrate preferences of seven biocrust isolates. The biocrust's main primary producer releases a diverse array of metabolites, and isolates of physically associated taxa use unique subsets of the complex metabolite pool. Individual isolates use only 13−26% of available metabolites, with only 2 out of 470 used by all and 40% not used by any. An extension of this approach to a mesophilic soil environment also reveals high levels of microbial substrate specialization. These results suggest that exometabolite niche partitioning may be an important factor in the maintenance of microbial diversity.</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Cyanobacteria (mesh)</dc:subject><dc:subject>Desert Climate (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Utah (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Cyanobacteria (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Desert Climate (mesh)</dc:subject><dc:subject>Utah (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Cyanobacteria (mesh)</dc:subject><dc:subject>Desert Climate (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Utah (mesh)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/33c2k5jx</dc:identifier><dc:identifier>https://escholarship.org/content/qt33c2k5jx/qt33c2k5jx.pdf</dc:identifier><dc:identifier>info:doi/10.1038/ncomms9289</dc:identifier><dc:type>article</dc:type><dc:source>Nature Communications, vol 6, iss 1</dc:source><dc:coverage>8289</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8c22s5vs</identifier><datestamp>2026-09-16T03:07:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8c22s5vs</dc:identifier><dc:title>Isolation of a significant fraction of non-phototroph diversity from a desert Biological Soil Crust</dc:title><dc:creator>da Rocha, Ulisses Nunes</dc:creator><dc:creator>Cadillo-Quiroz, Hinsby</dc:creator><dc:creator>Karaoz, Ulas</dc:creator><dc:creator>Rajeev, Lara</dc:creator><dc:creator>Klitgord, Niels</dc:creator><dc:creator>Dunn, Sean</dc:creator><dc:creator>Truong, Viet</dc:creator><dc:creator>Buenrostro, Mayra</dc:creator><dc:creator>Bowen, Benjamin P</dc:creator><dc:creator>Garcia-Pichel, Ferran</dc:creator><dc:creator>Mukhopadhyay, Aindrila</dc:creator><dc:creator>Northen, Trent R</dc:creator><dc:creator>Brodie, Eoin L</dc:creator><dc:date>2015-04-14</dc:date><dc:description>Biological Soil Crusts (BSCs) are organosedimentary assemblages comprised of microbes and minerals in topsoil of terrestrial environments. BSCs strongly impact soil quality in dryland ecosystems (e.g., soil structure and nutrient yields) due to pioneer species such as Microcoleus vaginatus; phototrophs that produce filaments that bind the soil together, and support an array of heterotrophic microorganisms. These microorganisms in turn contribute to soil stability and biogeochemistry of BSCs. Non-cyanobacterial populations of BSCs are less well known than cyanobacterial populations. Therefore, we attempted to isolate a broad range of numerically significant and phylogenetically representative BSC aerobic heterotrophs. Combining simple pre-treatments (hydration of BSCs under dark and light) and isolation strategies (media with varying nutrient availability and protection from oxidative stress) we recovered 402 bacterial and one fungal isolate in axenic culture, which comprised 116 phylotypes (at 97% 16S rRNA gene sequence homology), 115 bacterial and one fungal. Each medium enriched a mostly distinct subset of phylotypes, and cultivated phylotypes varied due to the BSC pre-treatment. The fraction of the total phylotype diversity isolated, weighted by relative abundance in the community, was determined by the overlap between isolate sequences and OTUs reconstructed from metagenome or metatranscriptome reads. Together, more than 8% of relative abundance of OTUs in the metagenome was represented by our isolates, a cultivation efficiency much larger than typically expected from most soils. We conclude that simple cultivation procedures combined with specific pre-treatment of samples afford a significant reduction in the culturability gap, enabling physiological and metabolic assays that rely on ecologically relevant axenic cultures.</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>biological soil crusts</dc:subject><dc:subject>culturability</dc:subject><dc:subject>isolation</dc:subject><dc:subject>dryland microbiology</dc:subject><dc:subject>microbial diversity</dc:subject><dc:subject>biological soil crusts</dc:subject><dc:subject>culturability</dc:subject><dc:subject>dryland microbiology</dc:subject><dc:subject>isolation</dc:subject><dc:subject>microbial diversity</dc:subject><dc:subject>0502 Environmental Science and Management (for)</dc:subject><dc:subject>0503 Soil Sciences (for)</dc:subject><dc:subject>0605 Microbiology (for)</dc:subject><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>3207 Medical microbiology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8c22s5vs</dc:identifier><dc:identifier>https://escholarship.org/content/qt8c22s5vs/qt8c22s5vs.pdf</dc:identifier><dc:identifier>info:doi/10.3389/fmicb.2015.00277</dc:identifier><dc:type>article</dc:type><dc:source>Frontiers in Microbiology, vol 6, iss MAR</dc:source><dc:coverage>277</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2228m7tq</identifier><datestamp>2026-09-16T03:06:44Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2228m7tq</dc:identifier><dc:title>Parallel Runtime Interface for Fortran (PRIF): A Multi-Image Solution for LLVM Flang</dc:title><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Rasmussen, Katherine</dc:creator><dc:creator>Richardson, Brad</dc:creator><dc:creator>Rouson, Damian</dc:creator><dc:date>2024-11-17</dc:date><dc:description>Fortran compilers that provide support for Fortran's native parallel features often do so with a runtime library that depends on details of both the compiler implementation and the communication library, while others provide limited or no support at all. This paper introduces a new generalized interface that is both compiler- and runtime-library-agnostic, providing flexibility while fully supporting all of Fortran's parallel features. The Parallel Runtime Interface for Fortran (PRIF) was developed to be portable across shared- and distributed-memory systems, with varying operating systems, toolchains and architectures. It achieves this by defining a set of Fortran procedures corresponding to each of the parallel features defined in the Fortran standard that may be invoked by a Fortran compiler and implemented by a runtime library. PRIF aims to be used as the solution for LLVM Flang to provide parallel Fortran support. This paper also briefly describes our PRIF prototype implementation: Caffeine.</dc:description><dc:subject>46 Information and Computing Sciences (for-2020)</dc:subject><dc:subject>4601 Applied Computing (for-2020)</dc:subject><dc:subject>Fortran</dc:subject><dc:subject>Parallel Fortran</dc:subject><dc:subject>HPC</dc:subject><dc:subject>PGAS</dc:subject><dc:subject>RMA</dc:subject><dc:subject>LLVM Flang</dc:subject><dc:subject>Runtime Libraries</dc:subject><dc:subject>Caffeine</dc:subject><dc:subject>GASNet-EX</dc:subject><dc:subject>Caffeine</dc:subject><dc:subject>Fortran</dc:subject><dc:subject>GASNet-EX</dc:subject><dc:subject>HPC</dc:subject><dc:subject>LLVM Flang</dc:subject><dc:subject>Parallel Fortran</dc:subject><dc:subject>PGAS</dc:subject><dc:subject>RMA</dc:subject><dc:subject>Runtime Libraries</dc:subject><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2228m7tq</dc:identifier><dc:identifier>https://escholarship.org/content/qt2228m7tq/qt2228m7tq.pdf</dc:identifier><dc:identifier>info:doi/10.1109/scw63240.2024.00134</dc:identifier><dc:type>article</dc:type><dc:source>PROCEEDINGS OF SC24-W: WORKSHOPS OF THE INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS</dc:source><dc:coverage>950 - 960</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt32q554jm</identifier><datestamp>2026-09-16T03:06:40Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt32q554jm</dc:identifier><dc:title>A Full-Stack Exploration of Language-Based Parallelism in Fortran 2023</dc:title><dc:creator>Rasmussen, Katherine</dc:creator><dc:creator>Rouson, Damian</dc:creator><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Richardson, Brad</dc:creator><dc:date>2024-09-30</dc:date><dc:description>This poster explores native parallel features in Fortran 2023 through the lens of supporting applications with libraries, compilers, and parallel runtimes. The language revision informally named Fortran 2008 introduced parallelism in the form of Single Program Multiple Data (SPMD) execution with two broad feature sets: (1) loop-level parallelism via do concurrent and (2) a Partitioned Global Address Space (PGAS) comprised of distributed “coarray” data structures. Fortran’s native parallelism has demonstrated high performance [1] and reduced the burden of inserting what sometimes amounts to more directives than code. Several compilers support both feature sets, typically by translating do concurrent into serial do loops annotated by parallel directives and by translating SPMD/PGAS features into direct calls to a communication library. Our research focuses primarily on two questions: (1) can the compiler’s parallel runtime library be developed in the language being compiled (Fortran) and (2) can we define an interface to the runtime that liberates compilers from being hardwired to one runtime and vice versa. We are answering these questions by developing the Parallel Runtime Interface for Fortran (PRIF) [2] and the Co-Array Fortran Framework of Efficient Interfaces to Network Environments (Caffeine) [3]. Caffeine is initially targeting adoption by LLVM Flang, a new open-source Fortran compiler developed by a broad community in industry, academia, and government labs. We are also exploring the use of these features in Inference-Engine, a deep learning library designed to facilitate neural network training and inference for high-performance computing applications written in modern Fortran.</dc:description><dc:subject>Caffeine</dc:subject><dc:subject>GASNet-EX</dc:subject><dc:subject>HPC</dc:subject><dc:subject>LLVM Flang</dc:subject><dc:subject>Parallel Fortran</dc:subject><dc:subject>PGAS</dc:subject><dc:subject>RMA</dc:subject><dc:subject>Runtime Libraries</dc:subject><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/32q554jm</dc:identifier><dc:identifier>https://escholarship.org/content/qt32q554jm/qt32q554jm.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S4RP5K</dc:identifier><dc:type>non_textual</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt53h4r3m0</identifier><datestamp>2026-09-16T03:06:37Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt53h4r3m0</dc:identifier><dc:title>Reference genome of the kidnapper ant, Polyergus mexicanus</dc:title><dc:creator>Cash, Elizabeth I</dc:creator><dc:creator>Escalona, Merly</dc:creator><dc:creator>Ward, Philip S</dc:creator><dc:creator>Sahasrabudhe, Ruta</dc:creator><dc:creator>Miller, Courtney</dc:creator><dc:creator>Toffelmier, Erin</dc:creator><dc:creator>Fairbairn, Colin</dc:creator><dc:creator>Seligmann, William</dc:creator><dc:creator>Shaffer, H Bradley</dc:creator><dc:creator>Tsutsui, Neil D</dc:creator><dc:contributor>Sethuraman, Arun</dc:contributor><dc:date>2025-06-02</dc:date><dc:description>Polyergus kidnapper ants are widely distributed, but relatively uncommon, throughout the Holarctic, spanning an elevational range from sea level to over 3,000 m. These species are well known for their obligate social parasitism with various Formica ant species, which they kidnap in dramatic, highly coordinated raids. Kidnapped Formica larvae and pupae become integrated into the Polyergus colony where they develop into adults and perform nearly all of the necessary colony tasks for the benefit of their captors. In California, Polyergus mexicanus is the most widely distributed Polyergus, but recent evidence has identified substantial genetic polymorphism within this species, including genetically divergent lineages associated with the use of different Formica host species. Given its unique behavior and genetic diversity, P. mexicanus plays a critical role in maintaining ecosystem balance by influencing the population dynamics and genetic diversity of its host ant species, Formica, highlighting its conservation value and importance in the context of biodiversity preservation. Here, we present a high-quality genome assembly of P. mexicanus from a sample collected in Plumas County, CA, United States, in the foothills of the central Sierra Nevada. This genome assembly consists of 364 scaffolds spanning 252.31 Mb, with contig N50 of 481,250 kb, scaffold N50 of 10.36 Mb, and Benchmarking Universal Single-Copy Orthologs (BUSCO) completeness of 95.4%. We also assembled the genome of the Wolbachia endosymbiont of P. mexicanus-a single, circular contig spanning 1.23 Mb. These genome sequences provide essential resources for future studies of conservation genetics, population genetics, speciation, and behavioral ecology in this charismatic social insect.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Ants (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Genome</dc:subject><dc:subject>Insect (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Genetic Variation (mesh)</dc:subject><dc:subject>California Conservation Genomics Project</dc:subject><dc:subject>dulosis</dc:subject><dc:subject>Formicidae</dc:subject><dc:subject>Formica</dc:subject><dc:subject>host race</dc:subject><dc:subject>social parasite</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Ants (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Genome</dc:subject><dc:subject>Insect (mesh)</dc:subject><dc:subject>Genetic Variation (mesh)</dc:subject><dc:subject>Formica</dc:subject><dc:subject>California Conservation Genomics Project</dc:subject><dc:subject>Formicidae</dc:subject><dc:subject>dulosis</dc:subject><dc:subject>host race</dc:subject><dc:subject>social parasite</dc:subject><dc:subject>Ants (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Genome</dc:subject><dc:subject>Insect (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Genetic Variation (mesh)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>Evolutionary Biology (science-metrix)</dc:subject><dc:subject>3104 Evolutionary biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/53h4r3m0</dc:identifier><dc:identifier>https://escholarship.org/content/qt53h4r3m0/qt53h4r3m0.pdf</dc:identifier><dc:identifier>info:doi/10.1093/jhered/esae047</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Heredity, vol 116, iss 3</dc:source><dc:coverage>293 - 302</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2259n8zn</identifier><datestamp>2026-09-16T03:03:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2259n8zn</dc:identifier><dc:title>Advanced Monitoring Technology Report For an Integrated Risk Management and Decision-Support System (IRMDSS) for Assuring the Integrity of Underground Natural Gas Storage Infrastructure in California</dc:title><dc:creator>Zhang, Yingqi</dc:creator><dc:creator>Rodriguez Tribaldos, Veronica</dc:creator><dc:creator>Vasco, Donald</dc:creator><dc:creator>Freifeld, Barry</dc:creator><dc:creator>Foxall, William</dc:creator><dc:creator>Wang, Kang</dc:creator><dc:creator>Burgmann, Roland</dc:creator><dc:creator>Leen, Brian</dc:creator><dc:creator>Baer, Doug</dc:creator><dc:creator>Oldenburg, Curt</dc:creator><dc:date>2024-09-09</dc:date><dc:description>Previous studies have shown that underground natural gas storage (UGS) in California has served a critical role in meeting energy demands in California, and there is no immediate alternative. Therefore, it is important to ensure the safety of UGS infrastructure, especially considering that many of the UGS sites are using a combination of new and old wells, some of which were installed decades ago and re-purposed for UGS. The purpose of this project is to develop an integrated risk management and decision support system (IRMDSS) to manage risks associated with this heterogeneous subsurface infrastructure. 
The approach of the IRMDSS is to take advantage of the predictive capability of mechanistic models, with support from data acquired from advanced monitoring technologies, for evaluation and analysis of various incident scenarios or potential threats. In this project, we have demonstrated data collection by four advanced monitoring technologies. These include two downhole monitoring technologies, distributed temperature sensing (DTS), distributed acoustic sensing (DAS), and two surface monitoring technologies, Interferometric Synthetic Aperture Radar (InSAR), and unmanned aerial vehicle (UAV). DTS and DAS data are collected continuously, providing information related to individual wells. InSAR data are collected frequently (~every 24 days), and UAV data can be collected as frequently as is practical depending on need. Together, these subsurface and surface monitoring technologies provide near real-time information useful for risk management of UGS facilities.</dc:description><dc:subject>UGS</dc:subject><dc:subject>risk management</dc:subject><dc:subject>advanced monitoring technologies</dc:subject><dc:subject>DTS</dc:subject><dc:subject>DAS</dc:subject><dc:subject>InSAR</dc:subject><dc:subject>UAV</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2259n8zn</dc:identifier><dc:identifier>https://escholarship.org/content/qt2259n8zn/qt2259n8zn.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8gg3z5b3</identifier><datestamp>2026-09-16T03:02:39Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8gg3z5b3</dc:identifier><dc:title>DESI 2024 V: Full-Shape galaxy clustering from galaxies and quasars</dc:title><dc:creator>Adame, AG</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alam, S</dc:creator><dc:creator>Alexander, DM</dc:creator><dc:creator>Alvarez, M</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Anand, A</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Avila, S</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Awan, H</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Baltay, C</dc:creator><dc:creator>Bault, A</dc:creator><dc:creator>Behera, J</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Beutler, F</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Blake, C</dc:creator><dc:creator>Blum, R</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Buckley-Geer, E</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Calderon, R</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Cereskaite, R</dc:creator><dc:creator>Cervantes-Cota, JL</dc:creator><dc:creator>Chabanier, S</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Davis, TM</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Deiosso, N</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Edelstein, J</dc:creator><dc:creator>Eftekharzadeh, S</dc:creator><dc:creator>Eisenstein, DJ</dc:creator><dc:creator>Elliott, A</dc:creator><dc:creator>Fagrelius, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Ereza, J</dc:creator><dc:creator>Findlay, N</dc:creator><dc:creator>Flaugher, B</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Sánchez, D</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Garrison, LH</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gonzalez-Morales, AX</dc:creator><dc:creator>Gonzalez-Perez, V</dc:creator><dc:creator>Gordon, C</dc:creator><dc:creator>Green, D</dc:creator><dc:creator>Gruen, D</dc:creator><dc:creator>Gsponer, R</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hadzhiyska, B</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Hanif, MMS</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Iršič, V</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Karaçaylı, NG</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kent, S</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kong, H</dc:creator><dc:creator>Koposov, SE</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Krolewski, A</dc:creator><dc:creator>Lai, Y</dc:creator><dc:creator>Lan, T-W</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Lang, D</dc:creator><dc:creator>Lasker, J</dc:creator><dc:creator>Le Goff, JM</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:date>2025-09-01</dc:date><dc:description>We present the measurements and cosmological implications of the galaxy two-point clustering using over 4.7 million unique galaxy and quasar redshifts in the range 0.1 &amp;lt; z &amp;lt; 2.1 divided into six redshift bins over a ∼ 7,500 square degree footprint, from the first year of observations with the Dark Energy Spectroscopic Instrument (DESI Data Release 1). By fitting the full power spectrum, we extend previous DESI DR1 baryon acoustic oscillation (BAO) measurements to include redshift-space distortions and signals from the matter-radiation equality scale. For the first time, this Full-Shape analysis is blinded at the catalogue-level to avoid confirmation bias and the systematic errors are accounted for at the two-point clustering level, which automatically propagates them into any cosmological parameter. When analysing the data in terms of compressed model-agnostic variables, we obtain a combined precision of 4.7% on the amplitude of the redshift space distortion (RSD) signal reaching a similar precision with just one year of DESI data than with twenty years of observation from the previous generation survey. We also analyse the data to directly constrain the cosmological parameters within the ΛCDM model using perturbation theory and combine this information with the reconstructed DESI DR1 galaxy BAO. Using a Big Bang Nucleosynthesis Gaussian prior on the baryon density parameter, ωb , and a weak Gaussian prior on the spectral index, ns , we constrain the matter density is Ω m = 0.296±0.010 and the Hubble constant H 0 = (68.63 ± 0.79)[km s-1Mpc-1]. Additionally, we measure the amplitude of clustering σ 8 = 0.841±0.034. The DESI DR1 galaxy clustering results are in agreement with the ΛCDM model based on general relativity with parameters consistent with those from Planck. The cosmological interpretation of these results in combination with DESI DR1 Ly-α forest data and external datasets are presented in the companion paper [1].</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8gg3z5b3</dc:identifier><dc:identifier>https://escholarship.org/content/qt8gg3z5b3/qt8gg3z5b3.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/09/008</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 09</dc:source><dc:coverage>008</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1gx6f0c3</identifier><datestamp>2026-09-16T03:02:31Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1gx6f0c3</dc:identifier><dc:title>Routes and rates of bacterial dispersal impact surface soil microbiome composition and functioning</dc:title><dc:creator>Walters, Kendra E</dc:creator><dc:creator>Capocchi, Joia K</dc:creator><dc:creator>Albright, Michaeline BN</dc:creator><dc:creator>Hao, Zhao</dc:creator><dc:creator>Brodie, Eoin L</dc:creator><dc:creator>Martiny, Jennifer BH</dc:creator><dc:date>2022-10-01</dc:date><dc:description>Recent evidence suggests that, similar to larger organisms, dispersal is a key driver of microbiome assembly; however, our understanding of the rates and taxonomic composition of microbial dispersal in natural environments is limited. Here, we characterized the rate and composition of bacteria dispersing into surface soil via three dispersal routes (from the air above the vegetation, from nearby vegetation and leaf litter near the soil surface, and from the bulk soil and litter below the top layer). We then quantified the impact of those routes on microbial community composition and functioning in the topmost litter layer. The bacterial dispersal rate onto the surface layer was low (7900 cells/cm2/day) relative to the abundance of the resident community. While bacteria dispersed through all three routes at the same rate, only dispersal from above and near the soil surface impacted microbiome composition, suggesting that the composition, not rate, of dispersal influenced community assembly. Dispersal also impacted microbiome functioning. When exposed to dispersal, leaf litter decomposed faster than when dispersal was excluded, although neither decomposition rate nor litter chemistry differed by route. Overall, we conclude that the dispersal routes transport distinct bacterial communities that differentially influence the composition of the surface soil microbiome.</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>Microbiome (rcdc)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>05 Environmental Sciences (for)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>10 Technology (for)</dc:subject><dc:subject>Microbiology (science-metrix)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>41 Environmental sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1gx6f0c3</dc:identifier><dc:identifier>https://escholarship.org/content/qt1gx6f0c3/qt1gx6f0c3.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41396-022-01269-w</dc:identifier><dc:type>article</dc:type><dc:source>The ISME Journal: Multidisciplinary Journal of Microbial Ecology, vol 16, iss 10</dc:source><dc:coverage>2295 - 2304</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7x35r02g</identifier><datestamp>2026-09-16T03:02:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7x35r02g</dc:identifier><dc:title>Warming and snow loss increase reliance on old groundwater in a Colorado River headwater</dc:title><dc:creator>Siirila-Woodburn, Erica R</dc:creator><dc:creator>Thiros, Nicholas</dc:creator><dc:creator>Newcomer, Michelle</dc:creator><dc:creator>Rudisill, William</dc:creator><dc:creator>Dennedy-Frank, P James</dc:creator><dc:creator>Feldman, Daniel</dc:creator><dc:creator>Sprenger, Matthias</dc:creator><dc:creator>Carroll, Rosemary WH</dc:creator><dc:creator>Williams, Kenneth H</dc:creator><dc:creator>Brodie, Eoin</dc:creator><dc:date>2026-05-01</dc:date><dc:description>Atmospheric warming is reducing snowpack, with uncertain effects on mountainous streamflow, a crucial water resource. Despite limited historical observations of groundwater–streamflow interactions above 2,500 m, new measurements in the Upper Colorado River headwaters indicate declining groundwater storage that is dated decades to millennia old. Here we use integrated hydrologic modelling spanning water years 2015–2021 to determine whether the loss of old-age groundwater buffers streamflow during low-snow years and whether that loss is exacerbated with warming. Results show that old-groundwater contributions to streams remain relatively steady through time, unlike the more variable contributions from young groundwater. Numerical experiments of increased surface air temperatures (+2.5 °C and +4 °C) increase rain–snow fractions and evapotranspiration and decrease runoff ratio by 2–3% per degree Celsius increase. As streamflow declines with warming, the age of groundwater supporting it gets older, in part owing to intermediate-aged (1–3 year) groundwater declining twice as fast. Simulations show that water table depths at higher elevations (&amp;gt;3,700 m) decline disproportionately and fail to recover even during wet years. These findings suggest altered groundwater–streamflow interactions with warming and snow loss, with implications for water resources.</dc:description><dc:subject>3707 Hydrology (for-2020)</dc:subject><dc:subject>3701 Atmospheric Sciences (for-2020)</dc:subject><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>Meteorology &amp; Atmospheric Sciences (science-metrix)</dc:subject><dc:subject>3709 Physical geography and environmental geoscience (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7x35r02g</dc:identifier><dc:identifier>https://escholarship.org/content/qt7x35r02g/qt7x35r02g.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41561-026-01945-y</dc:identifier><dc:type>article</dc:type><dc:source>Nature Geoscience, vol 19, iss 5</dc:source><dc:coverage>549 - 555</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6nk3r61c</identifier><datestamp>2026-09-16T02:58:41Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6nk3r61c</dc:identifier><dc:title>Simultaneous Heat and Electricity Storage in a Flow Battery System</dc:title><dc:creator>Song, Youngsup</dc:creator><dc:creator>Lilley, Drew</dc:creator><dc:creator>Kaur, Sumanjeet</dc:creator><dc:creator>Prasher, Ravi S</dc:creator><dc:date>2025-12-02</dc:date><dc:description>This study investigates the dual-storage capability of a redox flow battery (RFB) system, enabling simultaneous storage of heat and electricity within a single platform. Through electrochemical and thermal experiments, we evaluated how heat storage affects battery performance and vice versa using a counterflow heat exchanger integrated in a conventional RFB configuration. The results show that incorporating heat storage had a minimal impact on the electrochemical charging and discharging processes. Further, the heat discharge operated independently of electrochemical storage, confirming that both functions can coexist without interference. The combined system also enhanced overall energy conversion efficiency, demonstrating its potential as an efficient solution for supplying both thermal and electrical energythe two most widely used energy forms.</dc:description><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>34 Chemical Sciences (for-2020)</dc:subject><dc:subject>3406 Physical Chemistry (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>0904 Chemical Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>3403 Macromolecular and materials chemistry (for-2020)</dc:subject><dc:subject>3406 Physical chemistry (for-2020)</dc:subject><dc:subject>4004 Chemical engineering (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6nk3r61c</dc:identifier><dc:identifier>https://escholarship.org/content/qt6nk3r61c/qt6nk3r61c.pdf</dc:identifier><dc:identifier>info:doi/10.1021/acsomega.5c04280</dc:identifier><dc:type>article</dc:type><dc:source>ACS Omega, vol 10, iss 47</dc:source><dc:coverage>57348 - 57353</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9jd644qn</identifier><datestamp>2026-09-16T02:58:07Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9jd644qn</dc:identifier><dc:title>High redshift LBGs from deep broadband imaging for future spectroscopic surveys</dc:title><dc:creator>Ruhlmann-Kleider, Vanina</dc:creator><dc:creator>Yèche, Christophe</dc:creator><dc:creator>Magneville, Christophe</dc:creator><dc:creator>Coquinot, Henri</dc:creator><dc:creator>Armengaud, Eric</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Raichoor, Anand</dc:creator><dc:creator>Aguilar, Jessica Nicole</dc:creator><dc:creator>Ahlen, Steven</dc:creator><dc:creator>Arnouts, Stéphane</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>Chaussidon, Edmond</dc:creator><dc:creator>Claybaugh, Todd</dc:creator><dc:creator>Dawson, Kyle</dc:creator><dc:creator>de la Macorra, Axel</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Doel, Peter</dc:creator><dc:creator>Fanning, Kevin</dc:creator><dc:creator>Ferraro, Simone</dc:creator><dc:creator>Forero-Romero, Jaime E</dc:creator><dc:creator>Gontcho, Satya Gontcho A</dc:creator><dc:creator>Gutierrez, Gaston</dc:creator><dc:creator>Gwyn, Stephen</dc:creator><dc:creator>Honscheid, Klaus</dc:creator><dc:creator>Juneau, Stephanie</dc:creator><dc:creator>Kehoe, Robert</dc:creator><dc:creator>Kisner, Theodore</dc:creator><dc:creator>Kremin, Anthony</dc:creator><dc:creator>Lambert, Andrew</dc:creator><dc:creator>Landriau, Martin</dc:creator><dc:creator>Le Guillou, Laurent</dc:creator><dc:creator>Levi, Michael E</dc:creator><dc:creator>Manera, Marc</dc:creator><dc:creator>Martini, Paul</dc:creator><dc:creator>Meisner, Aaron</dc:creator><dc:creator>Miquel, Ramon</dc:creator><dc:creator>Moustakas, John</dc:creator><dc:creator>Mueller, Eva-Maria</dc:creator><dc:creator>Muñoz-Gutiérrez, Andrea</dc:creator><dc:creator>Newman, Jeffrey A</dc:creator><dc:creator>Nie, Jundan</dc:creator><dc:creator>Niz, Gustavo</dc:creator><dc:creator>Payerne, Constantin</dc:creator><dc:creator>Picouet, Vincent</dc:creator><dc:creator>Ravoux, Corentin</dc:creator><dc:creator>Rezaie, Mehdi</dc:creator><dc:creator>Rossi, Graziano</dc:creator><dc:creator>Sanchez, Eusebio</dc:creator><dc:creator>Sawicki, Marcin</dc:creator><dc:creator>Schlafly, Edward F</dc:creator><dc:creator>Schlegel, David</dc:creator><dc:creator>Schubnell, Michael</dc:creator><dc:creator>Seo, Hee-Jong</dc:creator><dc:creator>Silber, Joseph</dc:creator><dc:creator>Sprayberry, David</dc:creator><dc:creator>Taran, Julien</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Weaver, Benjamin A</dc:creator><dc:creator>White, Martin</dc:creator><dc:creator>Wilson, Michael J</dc:creator><dc:creator>Zhou, Zhimin</dc:creator><dc:creator>Zou, Hu</dc:creator><dc:date>2024-08-01</dc:date><dc:description>Lyman break galaxies (LBGs) are promising probes for clustering measurements at high redshift, z &amp;gt; 2, a region only covered so far by Lyman-α forest measurements. In this paper, we investigate the feasibility of selecting LBGs by exploiting the existence of a strong deficit of flux shortward of the Lyman limit, due to various absorption processes along the line of sight. The target selection relies on deep imaging data from the HSC and CLAUDS surveys in the g, r, z and u bands, respectively, with median depths reaching 27 AB in all bands. The selections were validated by several dedicated spectroscopic observation campaigns with DESI. Visual inspection of spectra has enabled us to develop an automated spectroscopic typing and redshift estimation algorithm specific to LBGs. Based on these data and tools, we assess the efficiency and purity of target selections optimised for different purposes. Selections providing a wide redshift coverage retain 57% of the observed targets after spectroscopic confirmation with DESI, and provide an efficiency for LBGs of 83±3%, for a purity of the selected LBG sample of 90±2%. This would deliver a confirmed LBG density of ~ 620 deg-2 in the range 2.3 &amp;lt; z &amp;lt; 3.5 for a r-band limiting magnitude r &amp;lt; 24.2. Selections optimised for high redshift efficiency retain 73% of the observed targets after spectroscopic confirmation, with 89±4% efficiency for 97±2% purity. This would provide a confirmed LBG density of ~ 470 deg-2 in the range 2.8 &amp;lt; z &amp;lt; 3.5 for a r-band limiting magnitude r &amp;lt; 24.5. A preliminary study of the LBG sample 3d-clustering properties is also presented and used to estimate the LBG linear bias. A value of b LBG = 3.3 ± 0.2 (stat.) is obtained for a mean redshift of 2.9 and a limiting magnitude in r of 24.2, in agreement with results reported in the literature.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>galaxy clustering</dc:subject><dc:subject>high redshift galaxies</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>galaxy surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9jd644qn</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1088/1475-7516/2024/08/059</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2024, iss 08</dc:source><dc:coverage>059</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5bh0d8zz</identifier><datestamp>2026-09-16T02:49:25Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5bh0d8zz</dc:identifier><dc:title>Laser-plasma ion beam booster based on hollow-channel magnetic vortex acceleration</dc:title><dc:creator>Garten, Marco</dc:creator><dc:creator>Bulanov, Stepan S</dc:creator><dc:creator>Hakimi, Sahel</dc:creator><dc:creator>Obst-Huebl, Lieselotte</dc:creator><dc:creator>Mitchell, Chad E</dc:creator><dc:creator>Schroeder, Carl B</dc:creator><dc:creator>Esarey, Eric</dc:creator><dc:creator>Geddes, Cameron GR</dc:creator><dc:creator>Vay, Jean-Luc</dc:creator><dc:creator>Huebl, Axel</dc:creator><dc:date>2024-08-01</dc:date><dc:description>Laser-driven ion acceleration provides ultrashort, high-charge, low-emittance beams, which are desirable for a wide range of high-impact applications. Yet after decades of research, a significant increase in maximum ion energy is still needed. This paper introduces a quality-preserving staging concept for ultraintense ion bunches that is seamlessly applicable from the nonrelativistic plasma source to the relativistic regime. Full three-dimensional particle-in-cell simulations prove robustness and capture of a high-charge proton bunch, suitable for readily available and near-term laser facilities.     Published by the American Physical Society 2024</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>ATAP-2024 (c-lbnl-label)</dc:subject><dc:subject>ATAP-AMP (c-lbnl-label)</dc:subject><dc:subject>ATAP-BELLA Center (c-lbnl-label)</dc:subject><dc:subject>ATAP-GENERAL (c-lbnl-label)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5bh0d8zz</dc:identifier><dc:identifier>https://escholarship.org/content/qt5bh0d8zz/qt5bh0d8zz.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevresearch.6.033148</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review Research, vol 6, iss 3</dc:source><dc:coverage>033148</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt41j6v1xm</identifier><datestamp>2026-09-16T02:45:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt41j6v1xm</dc:identifier><dc:title>Memory Performance and Hippocampal Volumes in Healthy Weight Children at High‐ and Low‐Familial Risk for Obesity</dc:title><dc:creator>Dratva, Melanie A</dc:creator><dc:creator>Lanman, Zoe L</dc:creator><dc:creator>Bischoff‐Grethe, Amanda</dc:creator><dc:creator>Eichen, Dawn M</dc:creator><dc:creator>Strong, David R</dc:creator><dc:creator>Wierenga, Christina E</dc:creator><dc:creator>Boutelle, Kerri N</dc:creator><dc:date>2026-01-01</dc:date><dc:description>BACKGROUND: Children with overweight or obesity (OW/OB), relative to healthy weight (HW), have lower cognitive performance and hippocampal volumes. Whether this extends to children with HW at familial risk for future OW/OB is unknown.
OBJECTIVES: To compare memory performance and hippocampal subfield volumes between HW children at high risk (HR) and low risk (LR) for OW/OB.
METHODS: HW children (n = 95, aged 8-11), classified as HR (n = 43, both parents with OW/OB) or LR (n = 52, both parents with HW), underwent structural magnetic resonance imaging and memory testing (Verbal List Learning Test-Food-Child Version (VLLT-Food-C) and Child Memory Scale subtests: word pairs, dot locations). Linear models tested group differences in memory scores, hippocampal and subfield (CA1, CA3, dentate gyrus (DG), subiculum) volumes.
RESULTS: Groups did not differ on demographics except body mass index (HR &amp;gt; LR, p = 0.003), despite all children being HW. LR children performed better on VLLT-Food-C short- (   = 0.34, p &amp;lt; 0.01) and long-delay cued recall (   = 0.21, p = 0.04) and word pairs delayed recall (   = 0.21, p = 0.04). Children with HR had smaller bilateral whole hippocampus, CA1, DG and right CA3 volumes (ps &amp;lt; 0.05); only the right DG remained significant (   = 0.15, p = 0.04) after intracranial volume adjustment.
CONCLUSIONS: Memory and hippocampal volume differences may reflect underlying familial risk of OW/OB in HW children.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3210 Nutrition and Dietetics (for-2020)</dc:subject><dc:subject>Basic Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Nutrition (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Mental Health (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Obesity (rcdc)</dc:subject><dc:subject>Childhood Obesity (rcdc)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Hippocampus (mesh)</dc:subject><dc:subject>Pediatric Obesity (mesh)</dc:subject><dc:subject>Magnetic Resonance Imaging (mesh)</dc:subject><dc:subject>Memory (mesh)</dc:subject><dc:subject>Organ Size (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>Body Mass Index (mesh)</dc:subject><dc:subject>hippocampal subfields</dc:subject><dc:subject>hippocampus</dc:subject><dc:subject>memory</dc:subject><dc:subject>obesity risk</dc:subject><dc:subject>preclinical changes</dc:subject><dc:subject>Hippocampus (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Magnetic Resonance Imaging (mesh)</dc:subject><dc:subject>Body Mass Index (mesh)</dc:subject><dc:subject>Organ Size (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>Memory (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Pediatric Obesity (mesh)</dc:subject><dc:subject>hippocampal subfields</dc:subject><dc:subject>hippocampus</dc:subject><dc:subject>memory</dc:subject><dc:subject>obesity risk</dc:subject><dc:subject>preclinical changes</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Hippocampus (mesh)</dc:subject><dc:subject>Pediatric Obesity (mesh)</dc:subject><dc:subject>Magnetic Resonance Imaging (mesh)</dc:subject><dc:subject>Memory (mesh)</dc:subject><dc:subject>Organ Size (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>Body Mass Index (mesh)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:subject>42 Health sciences (for-2020)</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/41j6v1xm</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1111/ijpo.70061</dc:identifier><dc:type>multimedia</dc:type><dc:source>Pediatric Obesity, vol 21, iss 1</dc:source><dc:coverage>e70061</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5h9732wt</identifier><datestamp>2026-09-16T02:40:50Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5h9732wt</dc:identifier><dc:title>2024 SBM Annual Meeting Abstracts Supplement</dc:title><dc:creator>Ma, Carmen</dc:creator><dc:creator>Vang, Weeko</dc:creator><dc:creator>Yu, Edgar</dc:creator><dc:creator>Chen, Julin</dc:creator><dc:creator>Wong, Ching</dc:creator><dc:creator>Cheng, Joyce</dc:creator><dc:creator>Jacob, Peyton</dc:creator><dc:creator>Tsoh, Janice Y</dc:creator><dc:date>2024-04-01</dc:date><dc:description>Background: Thirdhand smoke (THS) contains toxic residues, including carcinogens, which persist on surfaces and clothes even after cigarette smoke dissipates. The public awareness of THS and its health effects remain low. Objective: This study examined beliefs about THS among Chinese-speaking former smokers and their non-smoking family members, before and after participating in a family-based THS education program. Methods: We implemented a 2-week THS education intervention delivered by lay health workers with 30 Chinese American dyads (N=60) residing in Northern California, consisting of former smokers who quit within the past 2 years and their family members. THS beliefs were assessed using the Beliefs About Thirdhand Smoke (BATHS) questionnaire administered at pre- and postintervention. Focus groups with 8 former smokers and 7 family participants were conducted. We used multivariable regression with Generalized Estimating Equations to account for time points and household correlations to assess changes in BATHS scores (Overall, Persistence and Health subscales). Focus group transcripts underwent independent coding by two researchers and thematic analysis. Results: The study sample included 30 male former smokers (37% with slight to mild craving for smoking), and 30 family members (97% female) who never smoked. A majority (82%) spoke English less than well, 83% were married, 58% lived with children and 27% with current smokers. All multivariable models showed a significant time x role (former smokers vs family) interaction (p &amp;lt; 0.05). Former smokers had lower BATHS scores than their family at preintervention (p &amp;lt; 0.01), but their scores became similar at post-intervention. Former smokers’ BATHS scores increased from pre- to post-intervention (Overall: p=0.02; Persistence: p=0.03; Health: p=0.04) while family had no significant change. Prominent themes from focus groups supported gaining new knowledge for both persistence and health effects of THS. Both former smokers and family members appreciated learning about cleaning methods and both shared increased family discussions and collaboration in household cleaning post intervention. Conclusion: THS education impacts former smokers and their non-smoking family members differently. Family-based interventions are promising to align beliefs and promote collaboration within households in addressing THS. Future randomized controlled trials should investigate broader impacts of the program on enhancing support for motivating quitting for current smokers, maintaining smoking abstinence, and in reducing THS exposure.</dc:description><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>52 Psychology (for-2020)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>13 Education (for)</dc:subject><dc:subject>17 Psychology and Cognitive Sciences (for)</dc:subject><dc:subject>Public Health (science-metrix)</dc:subject><dc:subject>42 Health sciences (for-2020)</dc:subject><dc:subject>52 Psychology (for-2020)</dc:subject><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5h9732wt</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1093/abm/kaae014</dc:identifier><dc:type>article</dc:type><dc:source>Annals of Behavioral Medicine, vol 58, iss Supplement_1</dc:source><dc:coverage>s1 - s705</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5rq8d2fq</identifier><datestamp>2026-09-16T02:37:24Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5rq8d2fq</dc:identifier><dc:title>Data-driven emulation of modal aerosol microphysics via neural operator-based modeling</dc:title><dc:creator>Bai, Zhe</dc:creator><dc:creator>Rouson, Damian</dc:creator><dc:date>2025-12-01</dc:date><dc:description>The complexity and the small characteristic scales of aerosol microphysical processes pose a big challenge for accurate and efficient Earth system simulations at regional and global scales. In this work, we construct and evaluate a surrogate model: the aerosol deep operator network (ADON), a physics-inspired dual-net architecture for emulating the aerosol microphysics parameterization suite in the version 2 of the Energy Earth System Model (E3SMv2). The current version of the surrogate model is trained on a dataset comprising 9.8 million samples obtained from a global E3SMv2 simulation with the horizontal resolution of about one degree under cloud-free conditions. Incorporating domain spatial and temporal coordinates, as well as principle components extracted from training data, the dual-net surrogate model effectively captures the intricate representations of aerosol and the relationship with atmospheric state variables, achieving an R-squared score over $$95.7\%$$ for all the lognormal aerosol modes in the extrapolated regime. The validated model provides feature importance of input variables and their impact on the predictive capacity of the surrogate model in relation to the E3SM. The computational cost of online inference time deployed on CPUs and GPUs with lower precisions highlights ADON’s efficiency and potential in robust predictive modeling for large-scale Earth system computations.</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>3701 Atmospheric Sciences (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>Networking and Information Technology R&amp;D (NITRD) (rcdc)</dc:subject><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5rq8d2fq</dc:identifier><dc:identifier>https://escholarship.org/content/qt5rq8d2fq/qt5rq8d2fq.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41598-025-33209-x</dc:identifier><dc:type>article</dc:type><dc:source>Scientific Reports, vol 16, iss 1</dc:source><dc:coverage>3211</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9dc9017g</identifier><datestamp>2026-09-16T02:36:21Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9dc9017g</dc:identifier><dc:title>Parallel Runtime Interface for Fortran (PRIF) Specification, Revision 0.4</dc:title><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Rasmussen, Katherine</dc:creator><dc:creator>Richardson, Brad</dc:creator><dc:creator>Rouson, Damian</dc:creator><dc:date>2024-07-12</dc:date><dc:description>This document specifies an interface to support the parallel features of Fortran, named the Parallel Runtime Interface for Fortran (PRIF). PRIF is a proposed solution in which the runtime library is responsible for coarray allocation, deallocation and accesses, image synchronization, atomic operations, events, and teams. In this interface, the compiler is responsible for transforming the invocation of Fortran-level parallel features into procedure calls to the necessary PRIF procedures. The interface is designed for portability across shared- and distributed-memory machines, different operating systems, and multiple architectures. Implementations of this interface are intended as an augmentation for the compiler's own runtime library. With an implementation-agnostic interface, alternative parallel runtime libraries may be developed that support the same interface. One benefit of this approach is the ability to vary the communication substrate. A central aim of this document is to define a parallel runtime interface in standard Fortran syntax, which enables us to leverage Fortran to succinctly express various properties of the procedure interfaces, including argument attributes.</dc:description><dc:subject>Caffeine</dc:subject><dc:subject>Coarray</dc:subject><dc:subject>Compilers</dc:subject><dc:subject>Fortran</dc:subject><dc:subject>Library specification</dc:subject><dc:subject>Parallel programming</dc:subject><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9dc9017g</dc:identifier><dc:identifier>https://escholarship.org/content/qt9dc9017g/qt9dc9017g.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S4WG64</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9hv8k11n</identifier><datestamp>2026-09-16T02:36:15Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9hv8k11n</dc:identifier><dc:title>The Early Data Release of the Dark Energy Spectroscopic Instrument</dc:title><dc:creator>Collaboration, DESI</dc:creator><dc:creator>Adame, AG</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alam, S</dc:creator><dc:creator>Aldering, G</dc:creator><dc:creator>Alexander, DM</dc:creator><dc:creator>Alfarsy, R</dc:creator><dc:creator>Prieto, C Allende</dc:creator><dc:creator>Alvarez, M</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Anand, A</dc:creator><dc:creator>Andrade-Oliveira, F</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Asorey, J</dc:creator><dc:creator>Avila, S</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Balaguera-Antolínez, A</dc:creator><dc:creator>Ballester, O</dc:creator><dc:creator>Baltay, C</dc:creator><dc:creator>Bault, A</dc:creator><dc:creator>Bautista, J</dc:creator><dc:creator>Behera, J</dc:creator><dc:creator>Beltran, SF</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Silva, L Beraldo E</dc:creator><dc:creator>Bermejo-Climent, JR</dc:creator><dc:creator>Berti, A</dc:creator><dc:creator>Besuner, R</dc:creator><dc:creator>Beutler, F</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Blake, C</dc:creator><dc:creator>Blum, R</dc:creator><dc:creator>Bolton, AS</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Brown, Z</dc:creator><dc:creator>Buckley-Geer, E</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Cabayol-Garcia, L</dc:creator><dc:creator>Cai, Z</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Cardiel-Sas, L</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Castander, FJ</dc:creator><dc:creator>Cervantes-Cota, JL</dc:creator><dc:creator>Chabanier, S</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Chuang, C</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Cooper, AP</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Davis, TM</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de Belsunce, R</dc:creator><dc:creator>de la Cruz, R</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Della Costa, J</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Demina, R</dc:creator><dc:creator>Demirbozan, U</dc:creator><dc:creator>DeRose, J</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Dhungana, G</dc:creator><dc:creator>Ding, J</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Doshi, R</dc:creator><dc:creator>Douglass, K</dc:creator><dc:creator>Edge, A</dc:creator><dc:creator>Eftekharzadeh, S</dc:creator><dc:creator>Eisenstein, DJ</dc:creator><dc:creator>Elliott, A</dc:creator><dc:creator>Ereza, J</dc:creator><dc:creator>Escoffier, S</dc:creator><dc:creator>Fagrelius, P</dc:creator><dc:creator>Fan, X</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Fawcett, VA</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Flaugher, B</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Forero-Sánchez, D</dc:creator><dc:creator>Frenk, CS</dc:creator><dc:creator>Gänsicke, BT</dc:creator><dc:creator>García, LÁ</dc:creator><dc:creator>García-Bellido, J</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Garrison, LH</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Golden-Marx, J</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:date>2024-08-01</dc:date><dc:description>The Dark Energy Spectroscopic Instrument (DESI) completed its 5 month Survey Validation in 2021 May. Spectra of stellar and extragalactic targets from Survey Validation constitute the first major data sample from the DESI survey. This paper describes the public release of those spectra, the catalogs of derived properties, and the intermediate data products. In total, the public release includes good-quality spectral information from 466,447 objects targeted as part of the Milky Way Survey, 428,758 as part of the Bright Galaxy Survey, 227,318 as part of the Luminous Red Galaxy sample, 437,664 as part of the Emission Line Galaxy sample, and 76,079 as part of the Quasar sample. In addition, the release includes spectral information from 137,148 objects that expand the scope beyond the primary samples as part of a series of secondary programs. Here, we describe the spectral data, data quality, data products, Large-Scale Structure science catalogs, access to the data, and references that provide relevant background to using these spectra.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9hv8k11n</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.3847/1538-3881/ad3217</dc:identifier><dc:type>article</dc:type><dc:source>The Astronomical Journal, vol 168, iss 2</dc:source><dc:coverage>58</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt62t3f61h</identifier><datestamp>2026-09-16T02:28:17Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt62t3f61h</dc:identifier><dc:title>Climate forcing controls on carbon terrestrial fluxes during shale weathering</dc:title><dc:creator>Stolze, Lucien</dc:creator><dc:creator>Arora, Bhavna</dc:creator><dc:creator>Dwivedi, Dipankar</dc:creator><dc:creator>Steefel, Carl I</dc:creator><dc:creator>Bandai, Toshiyuki</dc:creator><dc:creator>Wu, Yuxin</dc:creator><dc:creator>Nico, Peter</dc:creator><dc:date>2024-07-02</dc:date><dc:description>Climate influences near-surface biogeochemical processes and thereby determines the partitioning of carbon dioxide (CO2) in shale, and yet the controls on carbon (C) weathering fluxes remain poorly constrained. Using a dataset that characterizes biogeochemical responses to climate forcing in shale regolith, we implement a numerical model that describes the effects of water infiltration events, gas exchange, and temperature fluctuations on soil respiration and mineral weathering at a seasonal timescale. Our modeling approach allows us to quantitatively disentangle the controls of transient climate forcing and biogeochemical mechanisms on C partitioning. We find that ~3% of soil CO2 (1.02 mol C/m2/y) is exported to the subsurface during large infiltration events. Here, net atmospheric CO2 drawdown primarily occurs during spring snowmelt, governs the aqueous C exports (61%), and exceeds the CO2 flux generated by pyrite and petrogenic organic matter oxidation (~0.2 mol C/m2/y). We show that shale CO2 consumption results from the temporal coupling between soil microbial respiration and carbonate weathering. This coupling is driven by the impacts of hydrologic fluctuations on fresh organic matter availability and CO2 transport to the weathering front. Diffusion-limited transport of gases under transient hydrological conditions exerts an important control on CO2(g) egress patterns and thus must be considered when inferring soil CO2 drawdown from the gas phase composition. Our findings emphasize the importance of seasonal climate forcing in shaping the net contribution of shale weathering to terrestrial C fluxes and suggest that warmer conditions could reduce the potential for shale weathering to act as a CO2 sink.</dc:description><dc:subject>3707 Hydrology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>14 Life Below Water (sdg)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>carbon cycling</dc:subject><dc:subject>soil respiration</dc:subject><dc:subject>shale weathering</dc:subject><dc:subject>climate forcing</dc:subject><dc:subject>multiphase transport</dc:subject><dc:subject>carbon cycling</dc:subject><dc:subject>climate forcing</dc:subject><dc:subject>multiphase transport</dc:subject><dc:subject>shale weathering</dc:subject><dc:subject>soil respiration</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/62t3f61h</dc:identifier><dc:identifier>https://escholarship.org/content/qt62t3f61h/qt62t3f61h.pdf</dc:identifier><dc:identifier>info:doi/10.1073/pnas.2400230121</dc:identifier><dc:type>article</dc:type><dc:source>Proceedings of the National Academy of Sciences of the United States of America, vol 121, iss 27</dc:source><dc:coverage>e2400230121</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5b1797n9</identifier><datestamp>2026-09-16T02:27:49Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5b1797n9</dc:identifier><dc:title>Perspectives of peripartum people on opportunities for personal and collective action to reduce exposure to everyday chemicals: Focus groups to inform exposure report-back</dc:title><dc:creator>Oksas, Catherine</dc:creator><dc:creator>Brody, Julia Green</dc:creator><dc:creator>Brown, Phil</dc:creator><dc:creator>Boronow, Katherine E</dc:creator><dc:creator>DeMicco, Erin</dc:creator><dc:creator>Charlesworth, Annemarie</dc:creator><dc:creator>Juarez, Maribel</dc:creator><dc:creator>Geiger, Sarah</dc:creator><dc:creator>Schantz, Susan L</dc:creator><dc:creator>Woodruff, Tracey J</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Padula, Amy M</dc:creator><dc:creator>Outcomes, program collaborators for Environmental influences on Child Health</dc:creator><dc:date>2022-09-01</dc:date><dc:description>Participants in biomonitoring studies who receive personal exposure reports seek information to reduce exposures. Many chemical exposures are driven by systems-level policies rather than individual actions; therefore, change requires engagement in collective action. Participants' perceptions of collective action and use of report-back to support engagement remain unclear. We conducted virtual focus groups during summer 2020 in a diverse group of peripartum people from cohorts in the Environmental influences on Child Health Outcomes (ECHO) Program (N&amp;nbsp;=&amp;nbsp;18). We assessed baseline exposure and collective action experience, and report-back preferences. Participants were motivated to protect the health of their families and communities despite significant time and cognitive burdens. They requested time-conscious tactics and accessible information to enable action to reduce individual and collective exposures. Participant input informed the design of digital report-back in the cohorts. This study highlights opportunities to shift responsibility from individuals to policymakers to reduce chemical exposures at the systems level.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>34 Chemical Sciences (for-2020)</dc:subject><dc:subject>Minority Health (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>2.2 Factors relating to the physical environment (hrcs-rac)</dc:subject><dc:subject>Mental health (hrcs-hc)</dc:subject><dc:subject>Generic health relevance (hrcs-hc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Environmental Monitoring (mesh)</dc:subject><dc:subject>Focus Groups (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Peripartum Period (mesh)</dc:subject><dc:subject>Biomonitoring</dc:subject><dc:subject>Return of results</dc:subject><dc:subject>Environmental chemicals</dc:subject><dc:subject>Exposure reduction</dc:subject><dc:subject>Environmental health literacy</dc:subject><dc:subject>Collective action</dc:subject><dc:subject>Environmental health</dc:subject><dc:subject>Health literacy</dc:subject><dc:subject>Digital health communications</dc:subject><dc:subject>per</dc:subject><dc:subject>and polyfluoroalkyl substances</dc:subject><dc:subject>Phenolic compounds</dc:subject><dc:subject>Polybrominated diphenyl ethers</dc:subject><dc:subject>program collaborators for Environmental influences on Child Health Outcomes</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Focus Groups (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Environmental Monitoring (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Peripartum Period (mesh)</dc:subject><dc:subject>Biomonitoring</dc:subject><dc:subject>Collective action</dc:subject><dc:subject>Digital health communications</dc:subject><dc:subject>Environmental chemicals</dc:subject><dc:subject>Environmental health</dc:subject><dc:subject>Environmental health literacy</dc:subject><dc:subject>Exposure reduction</dc:subject><dc:subject>Health literacy</dc:subject><dc:subject>Phenolic compounds</dc:subject><dc:subject>Polybrominated diphenyl ethers</dc:subject><dc:subject>Return of results</dc:subject><dc:subject>per- and polyfluoroalkyl substances</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Environmental Monitoring (mesh)</dc:subject><dc:subject>Focus Groups (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Peripartum Period (mesh)</dc:subject><dc:subject>03 Chemical Sciences (for)</dc:subject><dc:subject>05 Environmental Sciences (for)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>Toxicology (science-metrix)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>34 Chemical sciences (for-2020)</dc:subject><dc:subject>41 Environmental sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5b1797n9</dc:identifier><dc:identifier>https://escholarship.org/content/qt5b1797n9/qt5b1797n9.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.envres.2022.113173</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Research, vol 212, iss Pt A</dc:source><dc:coverage>113173</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1fc587c6</identifier><datestamp>2026-09-16T02:23:48Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1fc587c6</dc:identifier><dc:title>Historical redlining is associated with disparities in wildlife biodiversity in four California cities</dc:title><dc:creator>Estien, Cesar O</dc:creator><dc:creator>Fidino, Mason</dc:creator><dc:creator>Wilkinson, Christine E</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Schell, Christopher J</dc:creator><dc:date>2024-06-18</dc:date><dc:description>Legacy effects describe the persistent, long-term impacts on an ecosystem following the removal of an abiotic or biotic feature. Redlining, a policy that codified racial segregation and disinvestment in minoritized neighborhoods, has produced legacy effects with profound impacts on urban ecosystem structure and health. These legacies have detrimentally impacted public health outcomes, socioeconomic stability, and environmental health. However, the collateral impacts of redlining on wildlife communities are uncertain. Here, we investigated whether faunal biodiversity was associated with redlining. We used home-owner loan corporation (HOLC) maps [grades A (i.e., "best" and "greenlined"), B, C, and D (i.e., "hazardous" and "redlined")] across four cities in California and contributory science data (iNaturalist) to estimate alpha and beta diversity across six clades (mammals, birds, insects, arachnids, reptiles, and amphibians) as a function of HOLC grade. We found that in greenlined neighborhoods, unique species were detected with less sampling effort, with redlined neighborhoods needing over 8,000 observations to detect the same number of unique species. Historically redlined neighborhoods had lower native and nonnative species richness compared to greenlined neighborhoods across each city, with disparities remaining at the clade level. Further, community composition (i.e., beta diversity) consistently differed among HOLC grades for all cities, including large differences in species assemblage observed between green and redlined neighborhoods. Our work spotlights the lasting effects of social injustices on the community ecology of cities, emphasizing that urban conservation and management efforts must incorporate an antiracist, justice-informed lens to improve biodiversity in urban environments.</dc:description><dc:subject>4102 Ecological Applications (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>4206 Public Health (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>44 Human Society (for-2020)</dc:subject><dc:subject>4406 Human Geography (for-2020)</dc:subject><dc:subject>Basic Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>15 Life on Land (sdg)</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Cities (mesh)</dc:subject><dc:subject>Animals</dc:subject><dc:subject>Wild (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Conservation of Natural Resources (mesh)</dc:subject><dc:subject>redlining</dc:subject><dc:subject>iNaturalist</dc:subject><dc:subject>environmental</dc:subject><dc:subject>justice</dc:subject><dc:subject>legacy effects</dc:subject><dc:subject>species richness</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Animals</dc:subject><dc:subject>Wild (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Cities (mesh)</dc:subject><dc:subject>Conservation of Natural Resources (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>environmental justice</dc:subject><dc:subject>iNaturalist</dc:subject><dc:subject>legacy effects</dc:subject><dc:subject>redlining</dc:subject><dc:subject>species richness</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Cities (mesh)</dc:subject><dc:subject>Animals</dc:subject><dc:subject>Wild (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Conservation of Natural Resources (mesh)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1fc587c6</dc:identifier><dc:identifier>https://escholarship.org/content/qt1fc587c6/qt1fc587c6.pdf</dc:identifier><dc:identifier>info:doi/10.1073/pnas.2321441121</dc:identifier><dc:type>article</dc:type><dc:source>Proceedings of the National Academy of Sciences of the United States of America, vol 121, iss 25</dc:source><dc:coverage>e2321441121</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt756344xm</identifier><datestamp>2026-09-16T02:20:12Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt756344xm</dc:identifier><dc:title>Evaluation of SARS-CoV-2 serology assays reveals a range of test performance</dc:title><dc:creator>Whitman, Jeffrey D</dc:creator><dc:creator>Hiatt, Joseph</dc:creator><dc:creator>Mowery, Cody T</dc:creator><dc:creator>Shy, Brian R</dc:creator><dc:creator>Yu, Ruby</dc:creator><dc:creator>Yamamoto, Tori N</dc:creator><dc:creator>Rathore, Ujjwal</dc:creator><dc:creator>Goldgof, Gregory M</dc:creator><dc:creator>Whitty, Caroline</dc:creator><dc:creator>Woo, Jonathan M</dc:creator><dc:creator>Gallman, Antonia E</dc:creator><dc:creator>Miller, Tyler E</dc:creator><dc:creator>Levine, Andrew G</dc:creator><dc:creator>Nguyen, David N</dc:creator><dc:creator>Bapat, Sagar P</dc:creator><dc:creator>Balcerek, Joanna</dc:creator><dc:creator>Bylsma, Sophia A</dc:creator><dc:creator>Lyons, Ana M</dc:creator><dc:creator>Li, Stacy</dc:creator><dc:creator>Wong, Allison Wai-yi</dc:creator><dc:creator>Gillis-Buck, Eva Mae</dc:creator><dc:creator>Steinhart, Zachary B</dc:creator><dc:creator>Lee, Youjin</dc:creator><dc:creator>Apathy, Ryan</dc:creator><dc:creator>Lipke, Mitchell J</dc:creator><dc:creator>Smith, Jennifer Anne</dc:creator><dc:creator>Zheng, Tina</dc:creator><dc:creator>Boothby, Ian C</dc:creator><dc:creator>Isaza, Erin</dc:creator><dc:creator>Chan, Jackie</dc:creator><dc:creator>Acenas, Dante D</dc:creator><dc:creator>Lee, Jinwoo</dc:creator><dc:creator>Macrae, Trisha A</dc:creator><dc:creator>Kyaw, Than S</dc:creator><dc:creator>Wu, David</dc:creator><dc:creator>Ng, Dianna L</dc:creator><dc:creator>Gu, Wei</dc:creator><dc:creator>York, Vanessa A</dc:creator><dc:creator>Eskandarian, Haig Alexander</dc:creator><dc:creator>Callaway, Perri C</dc:creator><dc:creator>Warrier, Lakshmi</dc:creator><dc:creator>Moreno, Mary E</dc:creator><dc:creator>Levan, Justine</dc:creator><dc:creator>Torres, Leonel</dc:creator><dc:creator>Farrington, Lila A</dc:creator><dc:creator>Loudermilk, Rita P</dc:creator><dc:creator>Koshal, Kanishka</dc:creator><dc:creator>Zorn, Kelsey C</dc:creator><dc:creator>Garcia-Beltran, Wilfredo F</dc:creator><dc:creator>Yang, Diane</dc:creator><dc:creator>Astudillo, Michael G</dc:creator><dc:creator>Bernstein, Bradley E</dc:creator><dc:creator>Gelfand, Jeffrey A</dc:creator><dc:creator>Ryan, Edward T</dc:creator><dc:creator>Charles, Richelle C</dc:creator><dc:creator>Iafrate, A John</dc:creator><dc:creator>Lennerz, Jochen K</dc:creator><dc:creator>Miller, Steve</dc:creator><dc:creator>Chiu, Charles Y</dc:creator><dc:creator>Stramer, Susan L</dc:creator><dc:creator>Wilson, Michael R</dc:creator><dc:creator>Manglik, Aashish</dc:creator><dc:creator>Ye, Chun Jimmie</dc:creator><dc:creator>Krogan, Nevan J</dc:creator><dc:creator>Anderson, Mark S</dc:creator><dc:creator>Cyster, Jason G</dc:creator><dc:creator>Ernst, Joel D</dc:creator><dc:creator>Wu, Alan HB</dc:creator><dc:creator>Lynch, Kara L</dc:creator><dc:creator>Bern, Caryn</dc:creator><dc:creator>Hsu, Patrick D</dc:creator><dc:creator>Marson, Alexander</dc:creator><dc:date>2020-10-01</dc:date><dc:description>Appropriate use and interpretation of serological tests for assessments of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure, infection and potential immunity require accurate data on assay performance. We conducted a head-to-head evaluation of ten point-of-care-style lateral flow assays (LFAs) and two laboratory-based enzyme-linked immunosorbent assays to detect anti-SARS-CoV-2 IgM and IgG antibodies in 5-d time intervals from symptom onset and studied the specificity of each assay in pre-coronavirus disease 2019 specimens. The percent of seropositive individuals increased with time, peaking in the latest time interval tested (&amp;gt;20 d after symptom onset). Test specificity ranged from 84.3% to 100.0% and was predominantly affected by variability in IgM results. LFA specificity could be increased by considering weak bands as negative, but this decreased detection of antibodies (sensitivity) in a subset of SARS-CoV-2 real-time PCR-positive cases. Our results underline the importance of seropositivity threshold determination and reader training for reliable LFA deployment. Although there was no standout serological assay, four tests achieved more than 80% positivity at later time points tested and more than 95% specificity.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>Emerging Infectious Diseases (rcdc)</dc:subject><dc:subject>Infectious Diseases (rcdc)</dc:subject><dc:subject>Coronaviruses (rcdc)</dc:subject><dc:subject>4.2 Evaluation of markers and technologies (hrcs-rac)</dc:subject><dc:subject>Infection (hrcs-hc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Aged</dc:subject><dc:subject>80 and over (mesh)</dc:subject><dc:subject>Antibodies</dc:subject><dc:subject>Viral (mesh)</dc:subject><dc:subject>Betacoronavirus (mesh)</dc:subject><dc:subject>Biotechnology (mesh)</dc:subject><dc:subject>COVID-19 (mesh)</dc:subject><dc:subject>COVID-19 Testing (mesh)</dc:subject><dc:subject>Chromatography</dc:subject><dc:subject>Affinity (mesh)</dc:subject><dc:subject>Clinical Laboratory Techniques (mesh)</dc:subject><dc:subject>Coronavirus Infections (mesh)</dc:subject><dc:subject>Enzyme-Linked Immunosorbent Assay (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Immunoglobulin G (mesh)</dc:subject><dc:subject>Immunoglobulin M (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Pandemics (mesh)</dc:subject><dc:subject>Pneumonia</dc:subject><dc:subject>Viral (mesh)</dc:subject><dc:subject>Point-of-Care Testing (mesh)</dc:subject><dc:subject>Reverse Transcriptase Polymerase Chain Reaction (mesh)</dc:subject><dc:subject>SARS-CoV-2 (mesh)</dc:subject><dc:subject>Sensitivity and Specificity (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Pneumonia</dc:subject><dc:subject>Viral (mesh)</dc:subject><dc:subject>Coronavirus Infections (mesh)</dc:subject><dc:subject>Immunoglobulin G (mesh)</dc:subject><dc:subject>Immunoglobulin M (mesh)</dc:subject><dc:subject>Antibodies</dc:subject><dc:subject>Viral (mesh)</dc:subject><dc:subject>Enzyme-Linked Immunosorbent Assay (mesh)</dc:subject><dc:subject>Chromatography</dc:subject><dc:subject>Affinity (mesh)</dc:subject><dc:subject>Clinical Laboratory Techniques (mesh)</dc:subject><dc:subject>Sensitivity and Specificity (mesh)</dc:subject><dc:subject>Reverse Transcriptase Polymerase Chain Reaction (mesh)</dc:subject><dc:subject>Biotechnology (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Aged</dc:subject><dc:subject>80 and over (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:subject>Pandemics (mesh)</dc:subject><dc:subject>Point-of-Care Testing (mesh)</dc:subject><dc:subject>Betacoronavirus (mesh)</dc:subject><dc:subject>COVID-19 (mesh)</dc:subject><dc:subject>SARS-CoV-2 (mesh)</dc:subject><dc:subject>COVID-19 Testing (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Aged</dc:subject><dc:subject>80 and over (mesh)</dc:subject><dc:subject>Antibodies</dc:subject><dc:subject>Viral (mesh)</dc:subject><dc:subject>Betacoronavirus (mesh)</dc:subject><dc:subject>Biotechnology (mesh)</dc:subject><dc:subject>COVID-19 (mesh)</dc:subject><dc:subject>COVID-19 Testing (mesh)</dc:subject><dc:subject>Chromatography</dc:subject><dc:subject>Affinity (mesh)</dc:subject><dc:subject>Clinical Laboratory Techniques (mesh)</dc:subject><dc:subject>Coronavirus Infections (mesh)</dc:subject><dc:subject>Enzyme-Linked Immunosorbent Assay (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Immunoglobulin G (mesh)</dc:subject><dc:subject>Immunoglobulin M (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Pandemics (mesh)</dc:subject><dc:subject>Pneumonia</dc:subject><dc:subject>Viral (mesh)</dc:subject><dc:subject>Point-of-Care Testing (mesh)</dc:subject><dc:subject>Reverse Transcriptase Polymerase Chain Reaction (mesh)</dc:subject><dc:subject>SARS-CoV-2 (mesh)</dc:subject><dc:subject>Sensitivity and Specificity (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/756344xm</dc:identifier><dc:identifier>https://escholarship.org/content/qt756344xm/qt756344xm.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41587-020-0659-0</dc:identifier><dc:type>article</dc:type><dc:source>Nature Biotechnology, vol 38, iss 10</dc:source><dc:coverage>1174 - 1183</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt90q5432z</identifier><datestamp>2026-09-16T02:11:27Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt90q5432z</dc:identifier><dc:title>Comparison of Experimental vs Theoretical Abundances of 13CH3D and 12CH2D2 for Isotopically Equilibrated Systems from 1 to 500 °C</dc:title><dc:creator>Eldridge, Daniel L</dc:creator><dc:creator>Korol, Roman</dc:creator><dc:creator>Lloyd, Max K</dc:creator><dc:creator>Turner, Andrew C</dc:creator><dc:creator>Webb, Michael A</dc:creator><dc:creator>Miller, Thomas F</dc:creator><dc:creator>Stolper, Daniel A</dc:creator><dc:date>2019-12-19</dc:date><dc:description>Abstract Methane is produced and consumed via numerous microbial and chemical reactions in atmospheric, hydrothermal, and magmatic reactions. The stable isotopic composition of methane has been used extensively for decades to constrain the source of methane in the environment. A recently introduced isotopic parameter used to study the formation temperature and formational conditions of methane is the measurement of molecules of methane with multiple rare, heavy isotopes (“clumped”) such as 13CH3D and 12CH2D2. In order to place methane-clumped isotope measurements into a thermodynamic reference frame that allows calculations of clumped isotope-based temperatures (geothermometry) and comparison between laboratories, all past studies have calibrated their measurements using a combination of experiment and theory based on the temperature dependence of clumped isotopologue distributions for isotopically equilibrated systems. These have previously been performed at relatively high temperatures (&amp;gt;150 °C). Given that many natural occurrences of methane form below these temperatures, previous calibrations require extrapolation when calculating clumped isotope-based temperatures outside of this calibration range. We provide a new experimental calibration of the relative equilibrium abundances of 13CH3D and 12CH2D2 from 1 to 500 °C using a combination of γ-Al2O3- and Ni-based catalysts and compare them to new theoretical computations using Path Integral Monte Carlo (PIMC) methods and find 1:1 agreement (within ±1 standard error) for the observed temperature dependence of clumping between experiment and theory over this range. This demonstrates that measurements, experiments, and theory agree from 1 to 500 °C, providing confidence in the overall approaches. Polynomial fits to PIMC computations, which are considered the most rigorous theoretical approach available, are given as follows (valid T ≥ 270 K): Δ13CH3D ≅ 1000 × ln(K13CH3D) = (1.47348 × 1019)/T7 – (2.08648 × 1017)/T6 + (1.19810 × 1015)/T5 – (3.54757 × 1012)/T4 + (5.54476 × 109)/T3 – (3.49294 × 106)/T2 + (8.89370 × 102)/T and Δ12CH2D2 ≅ 1000 × ln(8/3K12CH2D2) = −(9.67634 × 1015)/T6 + (1.71917 × 1014)/T5 – (1.24819 × 1012)/T4 + (4.30283 × 109)/T3 – (4.48660 × 106)/T2 + (1.86258 × 103)/T. We additionally compare PIMC computations to those performed utilizing traditional approaches that are the basis of most previous calibrations (Bigeleisen, Mayer, and Urey model, BMU) and discuss the potential sources of error in the BMU model relative to PIMC computations.</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>3703 Geochemistry (for-2020)</dc:subject><dc:subject>3705 Geology (for-2020)</dc:subject><dc:subject>Methane Clumped Isotopes</dc:subject><dc:subject>Methane Isotope Equilibration</dc:subject><dc:subject>Methane Geochemistry</dc:subject><dc:subject>Path Integral Monte Carlo Calculations</dc:subject><dc:subject>253 Ultra</dc:subject><dc:subject>34 Chemical sciences (for-2020)</dc:subject><dc:subject>37 Earth sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/90q5432z</dc:identifier><dc:identifier>https://escholarship.org/content/qt90q5432z/qt90q5432z.pdf</dc:identifier><dc:identifier>info:doi/10.1021/acsearthspacechem.9b00244</dc:identifier><dc:type>article</dc:type><dc:source>ACS Earth and Space Chemistry, vol 3, iss 12</dc:source><dc:coverage>2747 - 2764</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt50v0z603</identifier><datestamp>2026-09-16T02:07:02Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt50v0z603</dc:identifier><dc:title>Machine-learning-assisted long-term G functions for bidirectional aquifer thermal energy storage system operation</dc:title><dc:creator>Chen, Kecheng</dc:creator><dc:creator>Sun, Xiang</dc:creator><dc:creator>Soga, Kenichi</dc:creator><dc:creator>Nico, Peter S</dc:creator><dc:creator>Dobson, Patrick F</dc:creator><dc:date>2024-08-01</dc:date><dc:description>Optimization of aquifer thermal energy storage (ATES) performance in a building system is an important topic for maximizing the seasonal offset between energy demand and supply and minimizing the building's primary energy consumption. To evaluate ATES performance with bidirectional operation, this study develops an analytical solution-based model to simulate the spatiotemporal thermal response in an aquifer. The model consists of three temperature response functions, similar to the G functions in borehole thermal energy storage (BTES), to estimate the transient temperature profile in the aquifer during seasonally varying injection and extraction of hot/cold water. Applying machine learning (ML) based data classification and regression techniques to the results of a series of finite element (FE) benchmark simulations of typical ATES configurations, model input parameters are linked to the subsurface thermal, hydrogeological, and ATES operational properties. Compared to the benchmark simulation results, the errors of the proposed model in estimating the annual energy storage and locating the thermally affected area are about 3&amp;nbsp;% and 1&amp;nbsp;%, respectively. The model was applied to a previous short-term case study, and the error in the transient production temperature estimation is about 1&amp;nbsp;%. The long-term heat recovery ratio estimated from the model also compares well to those calculated from the previous study and the validated numerical model. Because of its fast computation, the proposed model can be coupled with the individual building system simulation and used for preliminary ATES design, and this will allow for greater exploration of ATES operational space and, therefore, better choices of ATES operating conditions. The proposed model can also be coupled with the district heating and cooling network simulation for computationally efficient city-scale long-term ATES potential assessment.</dc:description><dc:subject>4012 Fluid Mechanics and Thermal Engineering (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>4008 Electrical Engineering (for-2020)</dc:subject><dc:subject>4017 Mechanical Engineering (for-2020)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>0913 Mechanical Engineering (for)</dc:subject><dc:subject>0914 Resources Engineering and Extractive Metallurgy (for)</dc:subject><dc:subject>0915 Interdisciplinary Engineering (for)</dc:subject><dc:subject>Energy (science-metrix)</dc:subject><dc:subject>4008 Electrical engineering (for-2020)</dc:subject><dc:subject>4012 Fluid mechanics and thermal engineering (for-2020)</dc:subject><dc:subject>4017 Mechanical engineering (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/50v0z603</dc:identifier><dc:identifier>https://escholarship.org/content/qt50v0z603/qt50v0z603.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.energy.2024.131638</dc:identifier><dc:type>article</dc:type><dc:source>Energy, vol 301</dc:source><dc:coverage>131638</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6p44s2tv</identifier><datestamp>2026-09-16T02:06:32Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6p44s2tv</dc:identifier><dc:title>Adiabatic matching of particle bunches in a plasma-based accelerator in the presence of ion motion</dc:title><dc:creator>Benedetti, C</dc:creator><dc:creator>Mehrling, TJ</dc:creator><dc:creator>Schroeder, CB</dc:creator><dc:creator>Geddes, CGR</dc:creator><dc:creator>Esarey, E</dc:creator><dc:date>2021-05-01</dc:date><dc:description>Witness beam stability and preservation of its ultra-low emittance have been identified as critical challenges toward realizing a TeV-class, plasma-based linear collider. In fact, the witness bunch parameters required by a future TeV-class collider have been expected to trigger hosing instability and background ion motion, leading to emittance degradation and, potentially, to bunch loss. Recently, it has been shown that ion motion suppresses the hosing instability, and proper longitudinal bunch shaping can eliminate the ion-motion-induced emittance growth. In this paper, we propose and analyze a plasma-based method to generate the shaped bunches that enable emittance preservation in the presence of ion motion. The method is based on an adiabatic matching procedure, where a bunch with an initially untapered profile is injected in the plasma accelerator stage with an energy low enough that ion motion effects are initially small. As the bunch accelerates, it is adiabatically compressed, ion motion is gradually triggered, and the bunch slowly but continuously readjusts itself in the ion motion-perturbed wakefield acquiring the desired taper. The production of tapered witness bunch profiles that minimize energy spread and preserve emittance for collider-relevant parameters could enable the use of plasma-based accelerators for high-energy physics applications.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0203 Classical Physics (for)</dc:subject><dc:subject>Fluids &amp; Plasmas (science-metrix)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6p44s2tv</dc:identifier><dc:identifier>https://escholarship.org/content/qt6p44s2tv/qt6p44s2tv.pdf</dc:identifier><dc:identifier>info:doi/10.1063/5.0043847</dc:identifier><dc:type>article</dc:type><dc:source>Physics of Plasmas, vol 28, iss 5</dc:source><dc:coverage>053102</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6p04b9c0</identifier><datestamp>2026-09-16T02:05:56Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6p04b9c0</dc:identifier><dc:title>Soil management practices can contribute to net carbon neutrality in California</dc:title><dc:creator>Di Vittorio, Alan V</dc:creator><dc:creator>Simmonds, Maegen B</dc:creator><dc:creator>Jones, Andrew</dc:creator><dc:creator>Silver, Whendee L</dc:creator><dc:creator>Houlton, Benjamin</dc:creator><dc:creator>Torn, Margaret</dc:creator><dc:creator>Almaraz, Maya</dc:creator><dc:creator>Nico, Peter</dc:creator><dc:date>2024-06-01</dc:date><dc:description>Stabilizing climate requires reducing greenhouse gas (GHG) emissions and storing atmospheric carbon dioxide (CO2) in land or ocean systems. Soil management practices can reduce GHG emissions or sequester atmospheric CO2 into inorganic and organic forms. However, whether soil carbon strategies represent a viable and impactful climate mitigation pathway is uncertain. A specific question concerns the role that land-management practices and soil amendments can play in realizing California’s ambition for carbon neutrality by 2045. Here we examine the carbon flux impacts of soil conservation (i.e., compost, reduced tillage, cover crop) and enhanced silicate rock weathering (EW) practices at different areal extents of implementation in cropland, grassland, and savanna in California under two climate change cases. We show that with implementation areas of 15% or 50% of private cultivated land, grassland, and savanna in California, soil conservation practices alone can contribute 1.40.72.1 % ( −1.8−0.9−2.7 Mt CO2eq y−1) and 4.62.36.9 % ( −6.0−3.0−8.9 Mt CO2eq y−1) of the additional emissions reduction needed (beyond previous targets) to meet the 2045 net neutrality goal (−129.3 Mt CO2eq y−1), respectively, on an average annual basis, including climate uncertainty. Including EW in these scenarios increases the total contributions of management practices to 4.12.55.6 % ( −5.2−3.2−7.3 Mt CO2eq y−1) and 13.58.218.6 % ( −17.5−10.7−24.2 Mt CO2eq y−1), respectively, of this reduction. This highlights that the extent of implementation area is a major factor in determining benefits and that EW has the potential to make a real contribution to net reduction targets. Results are similar across climate cases, indicating that contemporary field data can be used to make future projections. With EW there remains mechanistic uncertainties, however, such as rock dissolution rate and environmental controls on weathering products, which require additional field research to improve understanding of the technological efficacy of this approach for California’s 2045 carbon neutrality goal.</dc:description><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>4104 Environmental Management (for-2020)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>15 Life on Land (sdg)</dc:subject><dc:subject>emissions reduction</dc:subject><dc:subject>land use</dc:subject><dc:subject>soil carbon</dc:subject><dc:subject>inorganic carbon</dc:subject><dc:subject>enhanced weathering</dc:subject><dc:subject>CALAND</dc:subject><dc:subject>climate change mitigation</dc:subject><dc:subject>Meteorology &amp; Atmospheric Sciences (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6p04b9c0</dc:identifier><dc:identifier>https://escholarship.org/content/qt6p04b9c0/qt6p04b9c0.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1748-9326/ad4b41</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Research Letters, vol 19, iss 6</dc:source><dc:coverage>064034</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6vm8g67s</identifier><datestamp>2026-09-16T02:02:51Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6vm8g67s</dc:identifier><dc:title>Representation and inclusion among members and affiliates of the Society for Epidemiologic Research: findings from the 2021 diversity and inclusion survey</dc:title><dc:creator>González, David JX</dc:creator><dc:creator>Staley, Brooke S</dc:creator><dc:creator>Andrea, Sarah B</dc:creator><dc:creator>DeVilbiss, Elizabeth A</dc:creator><dc:creator>Fink, David S</dc:creator><dc:creator>Peña, Courtney</dc:creator><dc:creator>Reed, Domonique M</dc:creator><dc:creator>Santana, Mary V Díaz</dc:creator><dc:creator>Fasehun, Luther-King O</dc:creator><dc:creator>Alvero, AJ</dc:creator><dc:creator>Babalola, Obafemi</dc:creator><dc:creator>Puac-Polanco, Victor</dc:creator><dc:creator>Thompson, Caroline A</dc:creator><dc:creator>Frankenfeld, Cara L</dc:creator><dc:creator>Fernández-Rhodes, Lindsay</dc:creator><dc:creator>Lopez, David S</dc:creator><dc:creator>Magid, Hoda S Abdel</dc:creator><dc:creator>Committee, on behalf of the Society for Epidemiologic Research Diversity and Inclusion</dc:creator><dc:date>2025-06-03</dc:date><dc:description>Diverse representation and inclusion are stated priorities for scientific institutions and professional
societies, including the Society for Epidemiologic Research (SER). Prior studies have reported
persistent underrepresentation and exclusion of marginalized groups across the sciences. We
conducted a representation and inclusion survey among SER affiliates in 2021, following up on a
similar 2018 survey. In 2021, we observed broad representation from diverse groups across multiple
dimensions. However, across both surveys we found persistent underrepresentation of several
marginalized groups, including Black or African American and Hispanic/Latinx people. Some
groups reported feeling excluded in both the 2018 and 2021 surveys, and there was
disproportionately high representation from a subset of higher-ranked US academic institutions. For
several indicators of inclusion, perceptions of inclusion were more positive among White
respondents compared to other respondents. Opportunities to work towards achieving SER’s
diversity and inclusion aims include increasing outreach to epidemiology trainees and Minority
Serving Institutions, addressing cultural and financial barriers to participation, and improving access
for epidemiologists with disabilities. Iterative follow-up work with diversity and inclusion scholars
could improve our understanding of barriers to diversity and inclusion within SER and, more
broadly, the field of epidemiology.</dc:description><dc:subject>4202 Epidemiology (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>representation</dc:subject><dc:subject>diversity</dc:subject><dc:subject>inclusion</dc:subject><dc:subject>Society for Epidemiologic Research Diversity and Inclusion Committee</dc:subject><dc:subject>diversity</dc:subject><dc:subject>inclusion</dc:subject><dc:subject>representation</dc:subject><dc:subject>diversity</dc:subject><dc:subject>inclusion</dc:subject><dc:subject>representation</dc:subject><dc:subject>01 Mathematical Sciences (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>Epidemiology (science-metrix)</dc:subject><dc:subject>4202 Epidemiology (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6vm8g67s</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1093/aje/kwae104</dc:identifier><dc:type>multimedia</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8fd3468t</identifier><datestamp>2026-09-16T02:01:51Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8fd3468t</dc:identifier><dc:title>Creation of an axially uniform plasma channel in a laser-assisted capillary discharge</dc:title><dc:creator>Bagdasarov, GA</dc:creator><dc:creator>Bobrova, NA</dc:creator><dc:creator>Olkhovskaya, OG</dc:creator><dc:creator>Gasilov, VA</dc:creator><dc:creator>Benedetti, C</dc:creator><dc:creator>Bulanov, SS</dc:creator><dc:creator>Gonsalves, AJ</dc:creator><dc:creator>Pieronek, CV</dc:creator><dc:creator>van Tilborg, J</dc:creator><dc:creator>Geddes, CGR</dc:creator><dc:creator>Schroeder, CB</dc:creator><dc:creator>Sasorov, PV</dc:creator><dc:creator>Bulanov, SV</dc:creator><dc:creator>Korn, G</dc:creator><dc:creator>Esarey, E</dc:creator><dc:date>2021-05-01</dc:date><dc:description>Dissipative capillary discharges form plasma channels which allow for high power laser guiding, enabling efficient electron acceleration in a laser wakefield accelerator. However, at the low plasma densities required to produce high-energy electrons, in order to avoid capillary wall damage, high power lasers need a tighter transverse confinement that cannot be achieved by the capillary discharge powered by Ohmic heating alone. The introduction of an additional laser for heating of the plasma leads to deeper and narrower plasma channels. Here we investigate the formation of laser-heated axially uniform plasma channels. We show that a high degree of longitudinal uniformity can be achieved despite significant evolution of the heater laser during its propagation through the channel.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0203 Classical Physics (for)</dc:subject><dc:subject>Fluids &amp; Plasmas (science-metrix)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8fd3468t</dc:identifier><dc:identifier>https://escholarship.org/content/qt8fd3468t/qt8fd3468t.pdf</dc:identifier><dc:identifier>info:doi/10.1063/5.0046428</dc:identifier><dc:type>article</dc:type><dc:source>Physics of Plasmas, vol 28, iss 5</dc:source><dc:coverage>053104</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8vv9390p</identifier><datestamp>2026-09-16T01:58:06Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8vv9390p</dc:identifier><dc:title>Predicting Resource Utilization Trends with Southern California Petabyte Scale Cache</dc:title><dc:creator>Sim, Caitlin</dc:creator><dc:creator>Wu, Kesheng</dc:creator><dc:creator>Sim, Alex</dc:creator><dc:creator>Monga, Inder</dc:creator><dc:creator>Guok, Chin</dc:creator><dc:creator>Hazen, Damian</dc:creator><dc:creator>Würthwein, Frank</dc:creator><dc:creator>Davila, Diego</dc:creator><dc:creator>Newman, Harvey</dc:creator><dc:creator>Balcas, Justas</dc:creator><dc:contributor>De Vita, R</dc:contributor><dc:contributor>Espinal, X</dc:contributor><dc:contributor>Laycock, P</dc:contributor><dc:contributor>Shadura, O</dc:contributor><dc:date>2024-01-01</dc:date><dc:description>Large community of high-energy physicists share their data all around world making it necessary to ship a large number of files over wide- area networks. Regional disk caches such as the Southern California Petabyte Scale Cache have been deployed to reduce the data access latency. We observe that about 94% of the requested data volume were served from this cache, without remote transfers, between Sep. 2022 and July 2023. In this paper, we show the predictability of the resource utilization by exploring the trends of recent cache usage. The time series based prediction is made with a machine learning approach and the prediction errors are small relative to the variation in the input data. This work would help understanding the characteristics of the resource utilization and plan for additional deployments of caches in the future.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and accelerators (for-2020)</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8vv9390p</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1051/epjconf/202429501044</dc:identifier><dc:type>article</dc:type><dc:source>EPJ Web of Conferences, vol 295</dc:source><dc:coverage>01044</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt53x3s0hd</identifier><datestamp>2026-09-16T01:57:55Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt53x3s0hd</dc:identifier><dc:title>Researching COVID to enhance recovery (RECOVER) pediatric study protocol: Rationale, objectives and design</dc:title><dc:creator>Gross, Rachel S</dc:creator><dc:creator>Thaweethai, Tanayott</dc:creator><dc:creator>Rosenzweig, Erika B</dc:creator><dc:creator>Chan, James</dc:creator><dc:creator>Chibnik, Lori B</dc:creator><dc:creator>Cicek, Mine S</dc:creator><dc:creator>Elliott, Amy J</dc:creator><dc:creator>Flaherman, Valerie J</dc:creator><dc:creator>Foulkes, Andrea S</dc:creator><dc:creator>Witvliet, Margot Gage</dc:creator><dc:creator>Gallagher, Richard</dc:creator><dc:creator>Gennaro, Maria Laura</dc:creator><dc:creator>Jernigan, Terry L</dc:creator><dc:creator>Karlson, Elizabeth W</dc:creator><dc:creator>Katz, Stuart D</dc:creator><dc:creator>Kinser, Patricia A</dc:creator><dc:creator>Kleinman, Lawrence C</dc:creator><dc:creator>Lamendola-Essel, Michelle F</dc:creator><dc:creator>Milner, Joshua D</dc:creator><dc:creator>Mohandas, Sindhu</dc:creator><dc:creator>Mudumbi, Praveen C</dc:creator><dc:creator>Newburger, Jane W</dc:creator><dc:creator>Rhee, Kyung E</dc:creator><dc:creator>Salisbury, Amy L</dc:creator><dc:creator>Snowden, Jessica N</dc:creator><dc:creator>Stein, Cheryl R</dc:creator><dc:creator>Stockwell, Melissa S</dc:creator><dc:creator>Tantisira, Kelan G</dc:creator><dc:creator>Thomason, Moriah E</dc:creator><dc:creator>Truong, Dongngan T</dc:creator><dc:creator>Warburton, David</dc:creator><dc:creator>Wood, John C</dc:creator><dc:creator>Ahmed, Shifa</dc:creator><dc:creator>Akerlundh, Almary</dc:creator><dc:creator>Alshawabkeh, Akram N</dc:creator><dc:creator>Anderson, Brett R</dc:creator><dc:creator>Aschner, Judy L</dc:creator><dc:creator>Atz, Andrew M</dc:creator><dc:creator>Aupperle, Robin L</dc:creator><dc:creator>Baker, Fiona C</dc:creator><dc:creator>Balaraman, Venkataraman</dc:creator><dc:creator>Banerjee, Dithi</dc:creator><dc:creator>Barch, Deanna M</dc:creator><dc:creator>Baskin-Sommers, Arielle</dc:creator><dc:creator>Bhuiyan</dc:creator><dc:creator>Bind, Marie-Abele C</dc:creator><dc:creator>Bogie, Amanda L</dc:creator><dc:creator>Bradford, Tamara</dc:creator><dc:creator>Buchbinder, Natalie C</dc:creator><dc:creator>Bueler, Elliott</dc:creator><dc:creator>Bükülmez, Hülya</dc:creator><dc:creator>Casey, BJ</dc:creator><dc:creator>Chang, Linda</dc:creator><dc:creator>Chrisant, Maryanne</dc:creator><dc:creator>Clark, Duncan B</dc:creator><dc:creator>Clifton, Rebecca G</dc:creator><dc:creator>Clouser, Katharine N</dc:creator><dc:creator>Cottrell, Lesley</dc:creator><dc:creator>Cowan, Kelly</dc:creator><dc:creator>D’Sa, Viren</dc:creator><dc:creator>Dapretto, Mirella</dc:creator><dc:creator>Dasgupta, Soham</dc:creator><dc:creator>Dehority, Walter</dc:creator><dc:creator>Dionne, Audrey</dc:creator><dc:creator>Dummer, Kirsten B</dc:creator><dc:creator>Elias, Matthew D</dc:creator><dc:creator>Esquenazi-Karonika, Shari</dc:creator><dc:creator>Evans, Danielle N</dc:creator><dc:creator>Faustino, E Vincent S</dc:creator><dc:creator>Fiks, Alexander G</dc:creator><dc:creator>Forsha, Daniel</dc:creator><dc:creator>Foxe, John J</dc:creator><dc:creator>Friedman, Naomi P</dc:creator><dc:creator>Fry, Greta</dc:creator><dc:creator>Gaur, Sunanda</dc:creator><dc:creator>Gee, Dylan G</dc:creator><dc:creator>Gray, Kevin M</dc:creator><dc:creator>Handler, Stephanie</dc:creator><dc:creator>Harahsheh, Ashraf S</dc:creator><dc:creator>Hasbani, Keren</dc:creator><dc:creator>Heath, Andrew C</dc:creator><dc:creator>Hebson, Camden</dc:creator><dc:creator>Heitzeg, Mary M</dc:creator><dc:creator>Hester, Christina M</dc:creator><dc:creator>Hill, Sophia</dc:creator><dc:creator>Hobart-Porter, Laura</dc:creator><dc:creator>Hong, Travis KF</dc:creator><dc:creator>Horowitz, Carol R</dc:creator><dc:creator>Hsia, Daniel S</dc:creator><dc:creator>Huentelman, Matthew</dc:creator><dc:creator>Hummel, Kathy D</dc:creator><dc:creator>Irby, Katherine</dc:creator><dc:creator>Jacobus, Joanna</dc:creator><dc:creator>Jacoby, Vanessa L</dc:creator><dc:creator>Jone, Pei-Ni</dc:creator><dc:creator>Kaelber, David C</dc:creator><dc:creator>Kasmarcak, Tyler J</dc:creator><dc:creator>Kluko, Matthew J</dc:creator><dc:creator>Kosut, Jessica S</dc:creator><dc:creator>Laird, Angela R</dc:creator><dc:contributor>Nejadghaderi, Seyed Aria</dc:contributor><dc:date>2024-05-07</dc:date><dc:description>IMPORTANCE: The prevalence, pathophysiology, and long-term outcomes of COVID-19 (post-acute sequelae of SARS-CoV-2 [PASC] or "Long COVID") in children and young adults remain unknown. Studies must address the urgent need to define PASC, its mechanisms, and potential treatment targets in children and young adults.
OBSERVATIONS: We describe the protocol for the Pediatric Observational Cohort Study of the NIH's REsearching COVID to Enhance Recovery (RECOVER) Initiative. RECOVER-Pediatrics is an observational meta-cohort study of caregiver-child pairs (birth through 17 years) and young adults (18 through 25 years), recruited from more than 100 sites across the US. This report focuses on two of four cohorts that comprise RECOVER-Pediatrics: 1) a de novo RECOVER prospective cohort of children and young adults with and without previous or current infection; and 2) an extant cohort derived from the Adolescent Brain Cognitive Development (ABCD) study (n = 10,000). The de novo cohort incorporates three tiers of data collection: 1) remote baseline assessments (Tier 1, n = 6000); 2) longitudinal follow-up for up to 4 years (Tier 2, n = 6000); and 3) a subset of participants, primarily the most severely affected by PASC, who will undergo deep phenotyping to explore PASC pathophysiology (Tier 3, n = 600). Youth enrolled in the ABCD study participate in Tier 1. The pediatric protocol was developed as a collaborative partnership of investigators, patients, researchers, clinicians, community partners, and federal partners, intentionally promoting inclusivity and diversity. The protocol is adaptive to facilitate responses to emerging science.
CONCLUSIONS AND RELEVANCE: RECOVER-Pediatrics seeks to characterize the clinical course, underlying mechanisms, and long-term effects of PASC from birth through 25 years old. RECOVER-Pediatrics is designed to elucidate the epidemiology, four-year clinical course, and sociodemographic correlates of pediatric PASC. The data and biosamples will allow examination of mechanistic hypotheses and biomarkers, thus providing insights into potential therapeutic interventions.
CLINICAL TRIALS.GOV IDENTIFIER: Clinical Trial Registration: http://www.clinicaltrials.gov. Unique identifier: NCT05172011.</dc:description><dc:subject>4203 Health Services and Systems (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>Biodefense (rcdc)</dc:subject><dc:subject>Infectious Diseases (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Cancer (rcdc)</dc:subject><dc:subject>Pediatric Cancer (rcdc)</dc:subject><dc:subject>Emerging Infectious Diseases (rcdc)</dc:subject><dc:subject>Coronaviruses Disparities and At-Risk Populations (rcdc)</dc:subject><dc:subject>Rare Diseases (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Clinical Trials and Supportive Activities (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Coronaviruses (rcdc)</dc:subject><dc:subject>Post-Acute Sequelae of SARS-CoV-2 infection (PASC) including Long COVID (rcdc)</dc:subject><dc:subject>2.4 Surveillance and distribution (hrcs-rac)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>COVID-19 (mesh)</dc:subject><dc:subject>Adolescent (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Child</dc:subject><dc:subject>Preschool (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Infant (mesh)</dc:subject><dc:subject>SARS-CoV-2 (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>Research Design (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Post-Acute COVID-19 Syndrome (mesh)</dc:subject><dc:subject>RECOVER-Pediatric Consortium</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>Research Design (mesh)</dc:subject><dc:subject>Adolescent (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Child</dc:subject><dc:subject>Preschool (mesh)</dc:subject><dc:subject>Infant (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:subject>COVID-19 (mesh)</dc:subject><dc:subject>SARS-CoV-2 (mesh)</dc:subject><dc:subject>Post-Acute COVID-19 Syndrome (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>COVID-19 (mesh)</dc:subject><dc:subject>Adolescent (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Child</dc:subject><dc:subject>Preschool (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Infant (mesh)</dc:subject><dc:subject>SARS-CoV-2 (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>Research Design (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Post-Acute COVID-19 Syndrome (mesh)</dc:subject><dc:subject>General Science &amp; Technology (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/53x3s0hd</dc:identifier><dc:identifier>https://escholarship.org/content/qt53x3s0hd/qt53x3s0hd.pdf</dc:identifier><dc:identifier>info:doi/10.1371/journal.pone.0285635</dc:identifier><dc:type>article</dc:type><dc:source>PLOS ONE, vol 19, iss 5</dc:source><dc:coverage>e0285635</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2dw6j7s1</identifier><datestamp>2026-09-16T01:54:33Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2dw6j7s1</dc:identifier><dc:title>Parallel Runtime Interface for Fortran (PRIF) Specification, Revision 0.3</dc:title><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Rasmussen, Katherine</dc:creator><dc:creator>Richardson, Bradley</dc:creator><dc:creator>Rouson, Damian</dc:creator><dc:date>2024-05-03</dc:date><dc:description>This document specifies an interface to support the parallel features of Fortran, named the Parallel Runtime Interface for Fortran (PRIF). PRIF is a proposed solution in which the runtime library is responsible for coarray allocation, deallocation and accesses, image synchronization, atomic operations, events, and teams. In this interface, the compiler is responsible for transforming the invocation of Fortran-level parallel features into procedure calls to the necessary PRIF procedures. The interface is designed for portability across shared- and distributed-memory machines, different operating systems, and multiple architectures. Implementations of this interface are intended as an augmentation for the compiler's own runtime library. With an implementation-agnostic interface, alternative parallel runtime libraries may be developed that support the same interface. One benefit of this approach is the ability to vary the communication substrate. A central aim of this document is to define a parallel runtime interface in standard Fortran syntax, which enables us to leverage Fortran to succinctly express various properties of the procedure interfaces, including argument attributes.</dc:description><dc:subject>Caffeine</dc:subject><dc:subject>Coarray</dc:subject><dc:subject>Compilers</dc:subject><dc:subject>Fortran</dc:subject><dc:subject>Library specification</dc:subject><dc:subject>Parallel programming</dc:subject><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2dw6j7s1</dc:identifier><dc:identifier>https://escholarship.org/content/qt2dw6j7s1/qt2dw6j7s1.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S4501W</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2wx7k6xf</identifier><datestamp>2026-09-16T01:53:59Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2wx7k6xf</dc:identifier><dc:title>Electrical and seismic response of saline permafrost soil during freeze - Thaw transition</dc:title><dc:creator>Wu, Yuxin</dc:creator><dc:creator>Nakagawa, Seiji</dc:creator><dc:creator>Kneafsey, Timothy J</dc:creator><dc:creator>Dafflon, Baptiste</dc:creator><dc:creator>Hubbard, Susan</dc:creator><dc:date>2017-01-01</dc:date><dc:description>We conducted laboratory studies on the geophysical signals from Arctic saline permafrost soils to help understand the physical and mechanical processes during freeze-thaw cycles. Our results revealed low electrical resistivity (&amp;lt;20Ωm) and elastic moduli (7.7GPa for Young’s modulus and 2.9GPa for shear modulus) at temperatures down to  −10°C, indicating the presence of a significant amount of unfrozen saline water under the current field conditions. The spectral induced polarization signal showed a systematic shift during the freezing process, affected by concurrent changes of temperature, salinity, and ice formation. An anomalous induced polarization response was first observed during the transient period of supercooling and the onset of ice nucleation. Seismic measurements showed a characteristic maximal attenuation at the temperatures immediately below the freezing point, followed by a decrease with decreasing temperature. The calculated elastic moduli showed a non-hysteric response during the freeze – thaw cycle, which was different from the concurrently measured electrical resistivity response where a differential resistivity signal is observed depending on whether the soil is experiencing freezing or thawing. The differential electrical resistivity signal presents challenges for unfrozen water content estimation based on Archie’s law. Using an improved formulation of Archie’s law with a variable cementation exponent, the unfrozen water content estimation showed a large variation depending on the choice of the resistivity data during either a freezing or thawing cycle. Combining the electrical and seismic results, we suggest that, rather than a large hysteresis in the actual unfrozen water content, the shift of the resistivity response may reflect the changes of the distribution pattern of the unfrozen water (or ice) in the soil matrix during repeated freeze and thaw processes. Collectively, our results provide an improved petrophysical understanding of the physical and mechanical properties of saline permafrost during freeze – thaw transitions, and suggest that large uncertainty may exist when estimating the unfrozen water content using electrical resistivity data.</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>3706 Geophysics (for-2020)</dc:subject><dc:subject>Saline permafrost</dc:subject><dc:subject>Electrical resistivity</dc:subject><dc:subject>Induced polarization</dc:subject><dc:subject>Seismic property</dc:subject><dc:subject>Freeze - thaw</dc:subject><dc:subject>Unfrozen water content</dc:subject><dc:subject>0404 Geophysics (for)</dc:subject><dc:subject>0909 Geomatic Engineering (for)</dc:subject><dc:subject>Geochemistry &amp; Geophysics (science-metrix)</dc:subject><dc:subject>3704 Geoinformatics (for-2020)</dc:subject><dc:subject>3706 Geophysics (for-2020)</dc:subject><dc:subject>4104 Environmental management (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2wx7k6xf</dc:identifier><dc:identifier>https://escholarship.org/content/qt2wx7k6xf/qt2wx7k6xf.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.jappgeo.2017.08.008</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Applied Geophysics, vol 146</dc:source><dc:coverage>16 - 26</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5nr3s7jj</identifier><datestamp>2026-09-16T01:53:46Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5nr3s7jj</dc:identifier><dc:title>The Type Ia Supernova Rate at z ≈ 0.5 from the Supernova Legacy Survey**Based on observations obtained with MegaPrime/MegaCam, a joint project of the Canada-France-Hawaii Telescope (CFHT) and CEA/DAPNIA, at CFHT, which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l’Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is based in part on data products produced at the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS. This work is also based on observations obtained at the European Southern Observatory using the Very Large Telescope on the Cerro Paranal (ESO Large Program 171.A-0486), and on observations (programs GN-2004A-Q-19, GS-2004A-Q-11, GN-2003B-Q-9, and GS-2003B-Q-8) obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperati</dc:title><dc:creator>Neill, JD</dc:creator><dc:creator>Sullivan, M</dc:creator><dc:creator>Balam, D</dc:creator><dc:creator>Pritchet, CJ</dc:creator><dc:creator>Howell, DA</dc:creator><dc:creator>Perrett, K</dc:creator><dc:creator>Astier, P</dc:creator><dc:creator>Aubourg, E</dc:creator><dc:creator>Basa, S</dc:creator><dc:creator>Carlberg, RG</dc:creator><dc:creator>Conley, A</dc:creator><dc:creator>Fabbro, S</dc:creator><dc:creator>Fouchez, D</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hook, I</dc:creator><dc:creator>Pain, R</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Regnault, N</dc:creator><dc:creator>Rich, J</dc:creator><dc:creator>Taillet, R</dc:creator><dc:creator>Aldering, G</dc:creator><dc:creator>Antilogus, P</dc:creator><dc:creator>Arsenijevic, V</dc:creator><dc:creator>Balland, C</dc:creator><dc:creator>Baumont, S</dc:creator><dc:creator>Bronder, J</dc:creator><dc:creator>Ellis, RS</dc:creator><dc:creator>Filiol, M</dc:creator><dc:creator>Gonçalves, AC</dc:creator><dc:creator>Hardin, D</dc:creator><dc:creator>Kowalski, M</dc:creator><dc:creator>Lidman, C</dc:creator><dc:creator>Lusset, V</dc:creator><dc:creator>Mouchet, M</dc:creator><dc:creator>Mourao, A</dc:creator><dc:creator>Perlmutter, S</dc:creator><dc:creator>Ripoche, P</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Tao, C</dc:creator><dc:date>2006-09-01</dc:date><dc:description>We present a measurement of the distant Type Ia supernova (SN Ia) rate derived from the first 2 yr of the Canada-France-Hawaii Telescope Supernova Legacy Survey. We observed four 1° × 1° fields with a typical temporal frequency of ⟨Δt⟩ ∼ 4 observer-frame days over time spans of 158-211 days per season for each field, with breaks during the full Moon. We used 8-10 m class telescopes for spectroscopic follow-up to confirm our candidates and determine their redshifts. Our starting sample consists of 73 spectroscopically verified SNe Ia in the redshift range 0.2 &amp;lt; z &amp;lt; 0.6. We derive a volumetric SN Ia rate of rV(⟨z⟩ = 0.47) = × 10-4 yr-1 Mpc3, assuming h = 0.7, Ωm = 0.3, and a flat cosmology. Using recently published galaxy luminosity functions derived in our redshift range, we derive a SN Ia rate per unit luminosity of rL(⟨z⟩ = 0.47) = 0.154(syst.)(stat.) SN units. Using our rate alone, we place an upper limit on the component of SN Ia production that tracks the cosmic star formation history of 1 SN Ia per 103 M⊙ of stars formed. Our rate and other rates from surveys using spectroscopic sample confirmation display only a modest evolution out to z = 0.55.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>galaxies : evolution</dc:subject><dc:subject>galaxies : high redshift</dc:subject><dc:subject>supernovae : general</dc:subject><dc:subject>astro-ph</dc:subject><dc:subject>astro-ph</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5nr3s7jj</dc:identifier><dc:identifier>https://escholarship.org/content/qt5nr3s7jj/qt5nr3s7jj.pdf</dc:identifier><dc:identifier>info:doi/10.1086/505532</dc:identifier><dc:type>article</dc:type><dc:source>The Astronomical Journal, vol 132, iss 3</dc:source><dc:coverage>1126 - 1145</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt35m4g718</identifier><datestamp>2026-09-16T01:49:58Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt35m4g718</dc:identifier><dc:title>Search for supersymmetry in final states with disappearing tracks in proton-proton collisions at s=13 TeV</dc:title><dc:creator>Hayrapetyan, A</dc:creator><dc:creator>Tumasyan, A</dc:creator><dc:creator>Adam, W</dc:creator><dc:creator>Andrejkovic, JW</dc:creator><dc:creator>Bergauer, T</dc:creator><dc:creator>Chatterjee, S</dc:creator><dc:creator>Damanakis, K</dc:creator><dc:creator>Dragicevic, M</dc:creator><dc:creator>Del Valle, A Escalante</dc:creator><dc:creator>Hussain, PS</dc:creator><dc:creator>Jeitler, M</dc:creator><dc:creator>Krammer, N</dc:creator><dc:creator>Liko, D</dc:creator><dc:creator>Mikulec, I</dc:creator><dc:creator>Schieck, J</dc:creator><dc:creator>Schöfbeck, R</dc:creator><dc:creator>Schwarz, D</dc:creator><dc:creator>Sonawane, M</dc:creator><dc:creator>Templ, S</dc:creator><dc:creator>Waltenberger, W</dc:creator><dc:creator>Wulz, C-E</dc:creator><dc:creator>Darwish, MR</dc:creator><dc:creator>Janssen, T</dc:creator><dc:creator>Van Mechelen, P</dc:creator><dc:creator>Bols, ES</dc:creator><dc:creator>D’Hondt, J</dc:creator><dc:creator>Dansana, S</dc:creator><dc:creator>De Moor, A</dc:creator><dc:creator>Delcourt, M</dc:creator><dc:creator>Faham, H El</dc:creator><dc:creator>Lowette, S</dc:creator><dc:creator>Makarenko, I</dc:creator><dc:creator>Müller, D</dc:creator><dc:creator>Sahasransu, AR</dc:creator><dc:creator>Tavernier, S</dc:creator><dc:creator>Tytgat, M</dc:creator><dc:creator>Van Putte, S</dc:creator><dc:creator>Vannerom, D</dc:creator><dc:creator>Clerbaux, B</dc:creator><dc:creator>De Lentdecker, G</dc:creator><dc:creator>Favart, L</dc:creator><dc:creator>Hohov, D</dc:creator><dc:creator>Jaramillo, J</dc:creator><dc:creator>Khalilzadeh, A</dc:creator><dc:creator>Lee, K</dc:creator><dc:creator>Mahdavikhorrami, M</dc:creator><dc:creator>Malara, A</dc:creator><dc:creator>Paredes, S</dc:creator><dc:creator>Pétré, L</dc:creator><dc:creator>Postiau, N</dc:creator><dc:creator>Thomas, L</dc:creator><dc:creator>Bemden, M Vanden</dc:creator><dc:creator>Vander Velde, C</dc:creator><dc:creator>Vanlaer, P</dc:creator><dc:creator>De Coen, M</dc:creator><dc:creator>Dobur, D</dc:creator><dc:creator>Hong, Y</dc:creator><dc:creator>Knolle, J</dc:creator><dc:creator>Lambrecht, L</dc:creator><dc:creator>Mestdach, G</dc:creator><dc:creator>Rendón, C</dc:creator><dc:creator>Samalan, A</dc:creator><dc:creator>Skovpen, K</dc:creator><dc:creator>Van Den Bossche, N</dc:creator><dc:creator>Wezenbeek, L</dc:creator><dc:creator>Benecke, A</dc:creator><dc:creator>Bruno, G</dc:creator><dc:creator>Caputo, C</dc:creator><dc:creator>Delaere, C</dc:creator><dc:creator>Donertas, IS</dc:creator><dc:creator>Giammanco, A</dc:creator><dc:creator>Jaffel, K</dc:creator><dc:creator>Jain</dc:creator><dc:creator>Lemaitre, V</dc:creator><dc:creator>Lidrych, J</dc:creator><dc:creator>Mastrapasqua, P</dc:creator><dc:creator>Mondal, K</dc:creator><dc:creator>Tran, TT</dc:creator><dc:creator>Wertz, S</dc:creator><dc:creator>Alves, GA</dc:creator><dc:creator>Coelho, E</dc:creator><dc:creator>Hensel, C</dc:creator><dc:creator>De Oliveira, T Menezes</dc:creator><dc:creator>Moraes, A</dc:creator><dc:creator>Teles, P Rebello</dc:creator><dc:creator>Soeiro, M</dc:creator><dc:creator>Júnior, WL Aldá</dc:creator><dc:creator>Pereira, M Alves Gallo</dc:creator><dc:creator>Filho, M Barroso Ferreira</dc:creator><dc:creator>Malbouisson, H Brandao</dc:creator><dc:creator>Carvalho, W</dc:creator><dc:creator>Chinellato, J</dc:creator><dc:creator>Da Costa, EM</dc:creator><dc:creator>Da Silveira, GG</dc:creator><dc:creator>De Jesus Damiao, D</dc:creator><dc:creator>De Souza, S Fonseca</dc:creator><dc:creator>Martins, J</dc:creator><dc:creator>Herrera, C Mora</dc:creator><dc:creator>Amarilo, K Mota</dc:creator><dc:creator>Mundim, L</dc:creator><dc:date>2024-04-01</dc:date><dc:description>A search is presented for charged, long-lived supersymmetric particles in final states with one or more disappearing tracks. The search is based on data from proton-proton collisions at a center-of-mass energy of 13&amp;nbsp;TeV collected with the CMS detector at the CERN LHC between 2016 and 2018, corresponding to an integrated luminosity of  . The search is performed over final states characterized by varying numbers of jets,  -tagged jets, electrons, and muons. The length of signal-candidate tracks in the plane perpendicular to the beam axis is used to characterize the lifetimes of wino- and Higgsino-like charginos produced in the context of the minimal supersymmetric standard model. The  energy loss of signal-candidate tracks is used to increase the sensitivity to charginos with a large mass and thus a small Lorentz boost. The observed results are found to be statistically consistent with the background-only hypothesis. Limits on the pair-production cross section of gluinos and squarks are presented in the framework of simplified models of supersymmetric particle production and decay, and for electroweakino production based on models of wino and Higgsino dark matter. The limits presented are the most stringent to date for scenarios with light third-generation squarks and a wino- or Higgsino-like dark matter candidate capable of explaining the observed dark matter relic density.      © 2024 CERN, for the CMS Collaboration 2024 CERN</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/35m4g718</dc:identifier><dc:identifier>https://escholarship.org/content/qt35m4g718/qt35m4g718.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevd.109.072007</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 109, iss 7</dc:source><dc:coverage>072007</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7wt9x8n3</identifier><datestamp>2026-09-16T01:46:15Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7wt9x8n3</dc:identifier><dc:title>A deep population reference panel of tandem repeat variation</dc:title><dc:creator>Ziaei Jam, Helyaneh</dc:creator><dc:creator>Li, Yang</dc:creator><dc:creator>DeVito, Ross</dc:creator><dc:creator>Mousavi, Nima</dc:creator><dc:creator>Ma, Nichole</dc:creator><dc:creator>Lujumba, Ibra</dc:creator><dc:creator>Adam, Yagoub</dc:creator><dc:creator>Maksimov, Mikhail</dc:creator><dc:creator>Huang, Bonnie</dc:creator><dc:creator>Dolzhenko, Egor</dc:creator><dc:creator>Qiu, Yunjiang</dc:creator><dc:creator>Kakembo, Fredrick Elishama</dc:creator><dc:creator>Joseph, Habi</dc:creator><dc:creator>Onyido, Blessing</dc:creator><dc:creator>Adeyemi, Jumoke</dc:creator><dc:creator>Bakhtiari, Mehrdad</dc:creator><dc:creator>Park, Jonghun</dc:creator><dc:creator>Javadzadeh, Sara</dc:creator><dc:creator>Jjingo, Daudi</dc:creator><dc:creator>Adebiyi, Ezekiel</dc:creator><dc:creator>Bafna, Vineet</dc:creator><dc:creator>Gymrek, Melissa</dc:creator><dc:date>2023-10-23</dc:date><dc:description>Tandem repeats (TRs) represent one of the largest sources of genetic variation in humans and are implicated in a range of phenotypes. Here we present a deep characterization of TR variation based on high coverage whole genome sequencing from 3550 diverse individuals from the 1000 Genomes Project and H3Africa cohorts. We develop a method, EnsembleTR, to integrate genotypes from four separate methods resulting in high-quality genotypes at more than 1.7 million TR loci. Our catalog reveals novel sequence features influencing TR heterozygosity, identifies population-specific trinucleotide expansions, and finds hundreds of novel eQTL signals. Finally, we generate a phased haplotype panel which can be used to impute most TRs from nearby single nucleotide polymorphisms (SNPs) with high accuracy. Overall, the TR genotypes and reference haplotype panel generated here will serve as valuable resources for future genome-wide and population-wide studies of TRs and their role in human phenotypes.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Biotechnology (rcdc)</dc:subject><dc:subject>Generic health relevance (hrcs-hc)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Tandem Repeat Sequences (mesh)</dc:subject><dc:subject>Polymorphism</dc:subject><dc:subject>Single Nucleotide (mesh)</dc:subject><dc:subject>Genotype (mesh)</dc:subject><dc:subject>Whole Genome Sequencing (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Tandem Repeat Sequences (mesh)</dc:subject><dc:subject>Genotype (mesh)</dc:subject><dc:subject>Polymorphism</dc:subject><dc:subject>Single Nucleotide (mesh)</dc:subject><dc:subject>Whole Genome Sequencing (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Tandem Repeat Sequences (mesh)</dc:subject><dc:subject>Polymorphism</dc:subject><dc:subject>Single Nucleotide (mesh)</dc:subject><dc:subject>Genotype (mesh)</dc:subject><dc:subject>Whole Genome Sequencing (mesh)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7wt9x8n3</dc:identifier><dc:identifier>https://escholarship.org/content/qt7wt9x8n3/qt7wt9x8n3.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41467-023-42278-3</dc:identifier><dc:type>article</dc:type><dc:source>Nature Communications, vol 14, iss 1</dc:source><dc:coverage>6711</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt969749jn</identifier><datestamp>2026-09-16T01:45:43Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt969749jn</dc:identifier><dc:title>3,3'-Dichlorobiphenyl (PCB 11) alters the hepatic expression of cytochrome P450 enzymes in the liver of mouse dams exposed orally during pregnancy and lactation</dc:title><dc:creator>Roach, Crystal M</dc:creator><dc:creator>Koester, Nate R</dc:creator><dc:creator>Li, Xueshu</dc:creator><dc:creator>Ahn, Jeonghyeon</dc:creator><dc:creator>Pope, R Marshall</dc:creator><dc:creator>Wilson, Rebecca J</dc:creator><dc:creator>Mendieta, Rosalia</dc:creator><dc:creator>Valenzuela, Anthony</dc:creator><dc:creator>Han, Weiguo</dc:creator><dc:creator>Ding, Xinxin</dc:creator><dc:creator>Lein, Pamela J</dc:creator><dc:creator>Lehmler, Hans-Joachim</dc:creator><dc:date>2026-03-01</dc:date><dc:description>Healthy maternal metabolism is critical during pregnancy and lactation to support fetal development and protect against environmental toxins. Polychlorinated biphenyl 11 (PCB 11), a lower-chlorinated, non-legacy congener, is detected in human serum, including pregnant women and children; however, its impact during these sensitive life stages remains poorly understood. This study presents the first comprehensive hepatic proteome analysis of mouse dams exposed to PCB 11 during pregnancy and lactation. Female C57BL/6&amp;nbsp;J mice received daily oral doses of PCB 11 (0, 1.0 or 6.0&amp;nbsp;mg/kg) prior to conception through lactation. At postpartum day 21, brain, liver, and serum samples were analyzed for PCB 11 and its metabolites, and hepatic proteomic changes were assessed. Low detection of PCB 11 and its metabolites was observed in tissues, suggesting rapid clearance. Metabolite screening revealed OH-PCB 11, PCB 11 sulfate, and OH-PCB 11 sulfate metabolites in serum. Global proteomics identified significant alterations in hepatic protein expression, including downregulation of cytochrome P450 enzymes, solute carriers, and enzymes involved in fatty acid and steroid metabolism. Pathway enrichment analyses indicated disruptions in xenobiotic metabolism and endocrine pathways. These findings suggest that PCB 11 exposure during pregnancy and lactation impairs hepatic detoxification and metabolic capacity, potentially compromising maternal and offspring health. This work highlights the need for further investigation into the long-term consequences of PCB 11 exposure during pregnancy and lactation.</dc:description><dc:subject>3215 Reproductive Medicine (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Nutrition (rcdc)</dc:subject><dc:subject>Breastfeeding</dc:subject><dc:subject>Lactation and Breast Milk (rcdc)</dc:subject><dc:subject>Maternal Health (rcdc)</dc:subject><dc:subject>Endocrine Disruptors (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Perinatal Period - Conditions Originating in Perinatal Period (rcdc)</dc:subject><dc:subject>Digestive Diseases (rcdc)</dc:subject><dc:subject>Liver Disease (rcdc)</dc:subject><dc:subject>Pregnancy (rcdc)</dc:subject><dc:subject>Reproductive health and childbirth (hrcs-hc)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Polychlorinated Biphenyls (mesh)</dc:subject><dc:subject>Lactation (mesh)</dc:subject><dc:subject>Liver (mesh)</dc:subject><dc:subject>Mice</dc:subject><dc:subject>Inbred C57BL (mesh)</dc:subject><dc:subject>Cytochrome P-450 Enzyme System (mesh)</dc:subject><dc:subject>Maternal Exposure (mesh)</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Proteomics (mesh)</dc:subject><dc:subject>Administration</dc:subject><dc:subject>Oral (mesh)</dc:subject><dc:subject>Proteome (mesh)</dc:subject><dc:subject>PCB 11</dc:subject><dc:subject>Cytochrome P450 enzymes</dc:subject><dc:subject>Hepatic proteomics</dc:subject><dc:subject>Xenobiotic metabolism</dc:subject><dc:subject>Dietary exposure</dc:subject><dc:subject>Pregnancy</dc:subject><dc:subject>Liver (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Mice</dc:subject><dc:subject>Inbred C57BL (mesh)</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>Polychlorinated Biphenyls (mesh)</dc:subject><dc:subject>Cytochrome P-450 Enzyme System (mesh)</dc:subject><dc:subject>Proteome (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Administration</dc:subject><dc:subject>Oral (mesh)</dc:subject><dc:subject>Proteomics (mesh)</dc:subject><dc:subject>Maternal Exposure (mesh)</dc:subject><dc:subject>Lactation (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Cytochrome P450 enzymes</dc:subject><dc:subject>Dietary exposure</dc:subject><dc:subject>Hepatic proteomics</dc:subject><dc:subject>PCB 11</dc:subject><dc:subject>Pregnancy</dc:subject><dc:subject>Xenobiotic metabolism</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Polychlorinated Biphenyls (mesh)</dc:subject><dc:subject>Lactation (mesh)</dc:subject><dc:subject>Liver (mesh)</dc:subject><dc:subject>Mice</dc:subject><dc:subject>Inbred C57BL (mesh)</dc:subject><dc:subject>Cytochrome P-450 Enzyme System (mesh)</dc:subject><dc:subject>Maternal Exposure (mesh)</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Proteomics (mesh)</dc:subject><dc:subject>Administration</dc:subject><dc:subject>Oral (mesh)</dc:subject><dc:subject>Proteome (mesh)</dc:subject><dc:subject>1115 Pharmacology and Pharmaceutical Sciences (for)</dc:subject><dc:subject>Toxicology (science-metrix)</dc:subject><dc:subject>3101 Biochemistry and cell biology (for-2020)</dc:subject><dc:subject>3214 Pharmacology and pharmaceutical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/969749jn</dc:identifier><dc:identifier>https://escholarship.org/content/qt969749jn/qt969749jn.pdf</dc:identifier><dc:identifier>info:doi/10.1007/s00204-025-04241-7</dc:identifier><dc:type>article</dc:type><dc:source>Archives of Toxicology, vol 100, iss 3</dc:source><dc:coverage>943 - 957</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt75b8x71r</identifier><datestamp>2026-09-16T01:45:11Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt75b8x71r</dc:identifier><dc:title>Search for flavor changing neutral current interactions of the top quark in final states with a photon and additional jets in proton-proton collisions at s=13 TeV</dc:title><dc:creator>Hayrapetyan, A</dc:creator><dc:creator>Tumasyan, A</dc:creator><dc:creator>Adam, W</dc:creator><dc:creator>Andrejkovic, JW</dc:creator><dc:creator>Bergauer, T</dc:creator><dc:creator>Chatterjee, S</dc:creator><dc:creator>Damanakis, K</dc:creator><dc:creator>Dragicevic, M</dc:creator><dc:creator>Del Valle, A Escalante</dc:creator><dc:creator>Hussain, PS</dc:creator><dc:creator>Jeitler, M</dc:creator><dc:creator>Krammer, N</dc:creator><dc:creator>Liko, D</dc:creator><dc:creator>Mikulec, I</dc:creator><dc:creator>Schieck, J</dc:creator><dc:creator>Schöfbeck, R</dc:creator><dc:creator>Schwarz, D</dc:creator><dc:creator>Sonawane, M</dc:creator><dc:creator>Templ, S</dc:creator><dc:creator>Waltenberger, W</dc:creator><dc:creator>Wulz, C-E</dc:creator><dc:creator>Darwish, MR</dc:creator><dc:creator>Janssen, T</dc:creator><dc:creator>Van Mechelen, P</dc:creator><dc:creator>Bols, ES</dc:creator><dc:creator>D’Hondt, J</dc:creator><dc:creator>Dansana, S</dc:creator><dc:creator>De Moor, A</dc:creator><dc:creator>Delcourt, M</dc:creator><dc:creator>Faham, H El</dc:creator><dc:creator>Lowette, S</dc:creator><dc:creator>Makarenko, I</dc:creator><dc:creator>Müller, D</dc:creator><dc:creator>Sahasransu, AR</dc:creator><dc:creator>Tavernier, S</dc:creator><dc:creator>Tytgat, M</dc:creator><dc:creator>Van Putte, S</dc:creator><dc:creator>Vannerom, D</dc:creator><dc:creator>Clerbaux, B</dc:creator><dc:creator>De Lentdecker, G</dc:creator><dc:creator>Favart, L</dc:creator><dc:creator>Hohov, D</dc:creator><dc:creator>Jaramillo, J</dc:creator><dc:creator>Khalilzadeh, A</dc:creator><dc:creator>Lee, K</dc:creator><dc:creator>Mahdavikhorrami, M</dc:creator><dc:creator>Malara, A</dc:creator><dc:creator>Paredes, S</dc:creator><dc:creator>Pétré, L</dc:creator><dc:creator>Postiau, N</dc:creator><dc:creator>Thomas, L</dc:creator><dc:creator>Bemden, M Vanden</dc:creator><dc:creator>Vander Velde, C</dc:creator><dc:creator>Vanlaer, P</dc:creator><dc:creator>De Coen, M</dc:creator><dc:creator>Dobur, D</dc:creator><dc:creator>Hong, Y</dc:creator><dc:creator>Knolle, J</dc:creator><dc:creator>Lambrecht, L</dc:creator><dc:creator>Mestdach, G</dc:creator><dc:creator>Rendón, C</dc:creator><dc:creator>Samalan, A</dc:creator><dc:creator>Skovpen, K</dc:creator><dc:creator>Van Den Bossche, N</dc:creator><dc:creator>Wezenbeek, L</dc:creator><dc:creator>Benecke, A</dc:creator><dc:creator>Bruno, G</dc:creator><dc:creator>Caputo, C</dc:creator><dc:creator>Delaere, C</dc:creator><dc:creator>Donertas, IS</dc:creator><dc:creator>Giammanco, A</dc:creator><dc:creator>Jaffel, K</dc:creator><dc:creator>Jain</dc:creator><dc:creator>Lemaitre, V</dc:creator><dc:creator>Lidrych, J</dc:creator><dc:creator>Mastrapasqua, P</dc:creator><dc:creator>Mondal, K</dc:creator><dc:creator>Tran, TT</dc:creator><dc:creator>Wertz, S</dc:creator><dc:creator>Alves, GA</dc:creator><dc:creator>Coelho, E</dc:creator><dc:creator>Hensel, C</dc:creator><dc:creator>De Oliveira, T Menezes</dc:creator><dc:creator>Moraes, A</dc:creator><dc:creator>Teles, P Rebello</dc:creator><dc:creator>Soeiro, M</dc:creator><dc:creator>Júnior, WL Aldá</dc:creator><dc:creator>Pereira, M Alves Gallo</dc:creator><dc:creator>Filho, M Barroso Ferreira</dc:creator><dc:creator>Malbouisson, H Brandao</dc:creator><dc:creator>Carvalho, W</dc:creator><dc:creator>Chinellato, J</dc:creator><dc:creator>Da Costa, EM</dc:creator><dc:creator>Da Silveira, GG</dc:creator><dc:creator>De Jesus Damiao, D</dc:creator><dc:creator>De Souza, S Fonseca</dc:creator><dc:creator>Martins, J</dc:creator><dc:creator>Herrera, C Mora</dc:creator><dc:creator>Amarilo, K Mota</dc:creator><dc:creator>Mundim, L</dc:creator><dc:date>2024-04-01</dc:date><dc:description>A search for the production of a top quark in association with a photon and additional jets via flavor changing neutral current interactions is presented. The analysis uses proton-proton collision data recorded by the CMS detector at a center-of-mass energy of 13&amp;nbsp;TeV, corresponding to an integrated luminosity of  . The search is performed by looking for processes where a single top quark is produced in association with a photon, or a pair of top quarks where one of the top quarks decays into a photon and an up or charm quark. Events with an electron or a muon, a photon, one or more jets, and missing transverse momentum are selected. Multivariate analysis techniques are used to discriminate signal and standard model background processes. No significant deviation is observed over the predicted background. Observed (expected) upper limits are set on the branching fractions of top quark decays:  (  ) and  (  ) at 95%&amp;nbsp;confidence level, assuming a single nonzero coupling at a time. The obtained limit for  is similar to the current best limit, while the limit for  is significantly tighter than previous results.      © 2024 CERN, for the CMS Collaboration 2024 CERN</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>4902 Mathematical Physics (for-2020)</dc:subject><dc:subject>49 Mathematical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/75b8x71r</dc:identifier><dc:identifier>https://escholarship.org/content/qt75b8x71r/qt75b8x71r.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevd.109.072004</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 109, iss 7</dc:source><dc:coverage>072004</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4v4096gw</identifier><datestamp>2026-09-16T01:36:59Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4v4096gw</dc:identifier><dc:title>High-quality draft genome sequence of Gracilimonas tropica CL-CB462T (DSM 19535T), isolated from a Synechococcus culture</dc:title><dc:creator>Choi, Dong Han</dc:creator><dc:creator>Ahn, Chisang</dc:creator><dc:creator>Jang, Gwang Il</dc:creator><dc:creator>Lapidus, Alla</dc:creator><dc:creator>Han, James</dc:creator><dc:creator>Reddy, TBK</dc:creator><dc:creator>Huntemann, Marcel</dc:creator><dc:creator>Pati, Amrita</dc:creator><dc:creator>Ivanova, Natalia</dc:creator><dc:creator>Markowitz, Victor</dc:creator><dc:creator>Rohde, Manfred</dc:creator><dc:creator>Tindall, Brian</dc:creator><dc:creator>Göker, Markus</dc:creator><dc:creator>Woyke, Tanja</dc:creator><dc:creator>Klenk, Hans-Peter</dc:creator><dc:creator>Kyrpides, Nikos C</dc:creator><dc:creator>Cho, Byung Cheol</dc:creator><dc:date>2015-11-11</dc:date><dc:description>Gracilimonas tropica Choi et al. 2009 is a member of order Sphingobacteriales, class Sphingobacteriia. Three species of the genus Gracilimonas have been isolated from marine seawater or a salt mine and showed extremely halotolerant and mesophilic features, although close relatives are extremely halophilic or thermophilic. The type strain of the type species of Gracilimonas, G. tropica DSM19535T, was isolated from a Synechococcus culture which was established from the tropical sea-surface water of the Pacific Ocean. The genome of the strain DSM19535T was sequenced through the Genomic Encyclopedia of Type Strains, Phase I: the one thousand microbial genomes project. Here, we describe the genomic features of the strain. The 3,831,242&amp;nbsp;bp long draft genome consists of 48 contigs with 3373 protein-coding and 53 RNA genes. The strain seems to adapt to phosphate limitation and requires amino acids from external environment. In addition, genomic analyses and pasteurization experiment suggested that G. tropica DSM19535T did not form spore.</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Biotechnology (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>14 Life Below Water (sdg)</dc:subject><dc:subject>Genome</dc:subject><dc:subject>Gracilimonas tropica</dc:subject><dc:subject>Marine</dc:subject><dc:subject>Sphingobacteriia</dc:subject><dc:subject>GEBA</dc:subject><dc:subject>GEBA</dc:subject><dc:subject>Genome</dc:subject><dc:subject>Gracilimonas tropica</dc:subject><dc:subject>Marine</dc:subject><dc:subject>Sphingobacteriia</dc:subject><dc:subject>0601 Biochemistry and Cell Biology (for)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4v4096gw</dc:identifier><dc:identifier>https://escholarship.org/content/qt4v4096gw/qt4v4096gw.pdf</dc:identifier><dc:identifier>info:doi/10.1186/s40793-015-0088-8</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Microbiome, vol 10, iss 1</dc:source><dc:coverage>98</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7986g7rp</identifier><datestamp>2026-09-16T01:33:39Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7986g7rp</dc:identifier><dc:title>High-quality draft genome sequence of Flavobacterium suncheonense GH29-5T (DSM 17707T) isolated from greenhouse soil in South Korea, and emended description of Flavobacterium suncheonense GH29-5T</dc:title><dc:creator>Tashkandy, Nisreen</dc:creator><dc:creator>Sabban, Sari</dc:creator><dc:creator>Fakieh, Mohammad</dc:creator><dc:creator>Meier-Kolthoff, Jan P</dc:creator><dc:creator>Huang, Sixing</dc:creator><dc:creator>Tindall, Brian J</dc:creator><dc:creator>Rohde, Manfred</dc:creator><dc:creator>Baeshen, Mohammed N</dc:creator><dc:creator>Baeshen, Nabih A</dc:creator><dc:creator>Lapidus, Alla</dc:creator><dc:creator>Copeland, Alex</dc:creator><dc:creator>Pillay, Manoj</dc:creator><dc:creator>Reddy, TBK</dc:creator><dc:creator>Huntemann, Marcel</dc:creator><dc:creator>Pati, Amrita</dc:creator><dc:creator>Ivanova, Natalia</dc:creator><dc:creator>Markowitz, Victor</dc:creator><dc:creator>Woyke, Tanja</dc:creator><dc:creator>Göker, Markus</dc:creator><dc:creator>Klenk, Hans-Peter</dc:creator><dc:creator>Kyrpides, Nikos C</dc:creator><dc:creator>Hahnke, Richard L</dc:creator><dc:date>2016-06-16</dc:date><dc:description>Flavobacterium suncheonense is a member of the family Flavobacteriaceae in the phylum Bacteroidetes. Strain GH29-5T (DSM 17707T) was isolated from greenhouse soil in Suncheon, South Korea. F. suncheonense GH29-5T is part of the GenomicEncyclopedia ofBacteria andArchaea project. The 2,880,663&amp;nbsp;bp long draft genome consists of 54 scaffolds with 2739 protein-coding genes and 82 RNA genes. The genome of strain GH29-5T has 117 genes encoding peptidases but a small number of genes encoding carbohydrate active enzymes (51 CAZymes). Metallo and serine peptidases were found most frequently. Among CAZymes, eight glycoside hydrolase families, nine glycosyl transferase families, two carbohydrate binding module families and four carbohydrate esterase families were identified. Suprisingly, polysaccharides utilization loci (PULs) were not found in strain GH29-5T. Based on the coherent physiological and genomic characteristics we suggest that F. suncheonense GH29-5T feeds rather on proteins than saccharides and lipids.</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Aerobic</dc:subject><dc:subject>Gliding motility</dc:subject><dc:subject>Greenhouse soil</dc:subject><dc:subject>Flavobacteriaceae</dc:subject><dc:subject>Bacteroidetes</dc:subject><dc:subject>GEBA</dc:subject><dc:subject>KMG-1</dc:subject><dc:subject>Tree of Life</dc:subject><dc:subject>GGDC</dc:subject><dc:subject>Carbohydrate active enzyme</dc:subject><dc:subject>Polysaccharide utilization loci</dc:subject><dc:subject>Aerobic</dc:subject><dc:subject>Bacteroidetes</dc:subject><dc:subject>Carbohydrate active enzyme</dc:subject><dc:subject>Flavobacteriaceae</dc:subject><dc:subject>GEBA</dc:subject><dc:subject>GGDC</dc:subject><dc:subject>Gliding motility</dc:subject><dc:subject>Greenhouse soil</dc:subject><dc:subject>KMG-1</dc:subject><dc:subject>Polysaccharide utilization loci</dc:subject><dc:subject>Tree of Life</dc:subject><dc:subject>0601 Biochemistry and Cell Biology (for)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7986g7rp</dc:identifier><dc:identifier>https://escholarship.org/content/qt7986g7rp/qt7986g7rp.pdf</dc:identifier><dc:identifier>info:doi/10.1186/s40793-016-0159-5</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Microbiome, vol 11, iss 1</dc:source><dc:coverage>42</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1b90s5nr</identifier><datestamp>2026-09-16T01:29:08Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1b90s5nr</dc:identifier><dc:title>A Tale of Two Catchments: Causality Analysis and Isotope Systematics Reveal Mountainous Watershed Traits That Regulate the Retention and Release of Nitrogen</dc:title><dc:creator>Bouskill, NJ</dc:creator><dc:creator>Newcomer, M</dc:creator><dc:creator>Carroll, RWH</dc:creator><dc:creator>Beutler, C</dc:creator><dc:creator>Bill, M</dc:creator><dc:creator>Brown, WS</dc:creator><dc:creator>Conrad, M</dc:creator><dc:creator>Dong, WS</dc:creator><dc:creator>Falco, N</dc:creator><dc:creator>Maavara, T</dc:creator><dc:creator>Newman, A</dc:creator><dc:creator>Sorensen, PO</dc:creator><dc:creator>Tokunaga, TK</dc:creator><dc:creator>Wan, J</dc:creator><dc:creator>Wainwright, H</dc:creator><dc:creator>Zhu, Q</dc:creator><dc:creator>Brodie, EL</dc:creator><dc:creator>Williams, KH</dc:creator><dc:date>2024-03-01</dc:date><dc:description>Abstract  Mountainous watersheds are characterized by variability in functional traits, including vegetation, topography, geology, and geomorphology, which determine nitrogen (N) retention, and release. Coal Creek and East River are two contrasting catchments within the Upper Colorado River Basin that differ markedly in total nitrate (NO 3 − ) export. The East River has a diverse vegetation cover, and sinuous floodplains, and is underlain by N‐rich marine shale. At 0.21&amp;nbsp;±&amp;nbsp;0.14&amp;nbsp;kg&amp;nbsp;ha −1 &amp;nbsp;yr −1 , the East River exports ∼3.5 times more NO 3 − relative to the conifer‐dominated Coal Creek (0.06&amp;nbsp;±&amp;nbsp;0.02&amp;nbsp;kg&amp;nbsp;ha −1 &amp;nbsp;yr −1 ). While this can partly be explained by the larger size of the East River, the distinct watershed traits of these two catchments imply different mechanisms controlling the aggregate N‐export signal. A causality analysis shows physical and biogenic processes were critical in determining NO 3 − export from the East River catchment. Stable isotope ratios of NO 3 − (δ 15 N NO3 and δ 18 O NO3 ) show the East River catchment is a strong hotspot for biogeochemical processing of NO 3 − at the hillslope soil‐saprolite. By contrast, the conifer‐dominated Coal Creek retained nearly all atmospherically deposited NO 3 − , and its export was controlled by catchment hydrological traits (i.e., snowmelt periods and water table depth). The conservative N‐cycle within Coal Creek is likely due to the abundance of conifer trees, and smaller riparian regions, retaining more NO 3 − overall and reduced processing prior to export. This study highlights the value of integrating isotope systematics to link watershed functional traits to mechanisms of watershed element retention and release. 
Plain Language Summary  The role different functional traits play in the retention and release of nitrogen remains uncertain. Here we describe how two neighboring catchments in the Upper Colorado River Basin, characterized by contrasting vegetation, geology, and geomorphology, cycle and export nitrogen. The East River catchment, which is underlain by nitrogen‐rich shale, and has a diverse vegetation cover, releases over three times as much nitrate (NO 3 − ) than the conifer‐dominated Coal Creek, which is underlain by granitic rock. However, a suite of analyses show that the distinct watershed traits of these two catchments lead to diverse pathways of nitrogen cycling. Biogenic processes, critical to determining NO 3 − export in East River, impart strong biogeochemical processing prior to export. By contrast, Coal Creek retains almost all of the atmospherically deposited NO 3 − , likely due to uptake by conifers, and a small riparian region. This study highlights the use of nitrate isotope systematics to parse different mechanisms leading to NO 3 − export. 
Key Points    Comparing and contrasting neighboring catchments identifies watershed traits regulating the cycling, retention and release of nitrogen   Conifer forest‐dominated catchments show a conservative nitrogen cycling, retaining ∼97% of atmospherically dominated nitrate   By contrast, meadow‐dominated catchments underlain Mancos shale are biogeochemical hotspots for N‐cycling, and export higher nitrate loads</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>3706 Geophysics (for-2020)</dc:subject><dc:subject>catchment science</dc:subject><dc:subject>nitrogen cycling</dc:subject><dc:subject>causality analysis</dc:subject><dc:subject>nitrate isotopes</dc:subject><dc:subject>cQ analysis</dc:subject><dc:subject>mountainous ecosystem</dc:subject><dc:subject>0404 Geophysics (for)</dc:subject><dc:subject>3706 Geophysics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1b90s5nr</dc:identifier><dc:identifier>https://escholarship.org/content/qt1b90s5nr/qt1b90s5nr.pdf</dc:identifier><dc:identifier>info:doi/10.1029/2023jg007532</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Geophysical Research Biogeosciences, vol 129, iss 3</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3wt134z7</identifier><datestamp>2026-09-16T01:24:44Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3wt134z7</dc:identifier><dc:title>Hot, cold, or just right? An infrared biometric sensor to improve occupant comfort and reduce overcooling in buildings via closed-loop control</dc:title><dc:creator>Levinson, Ronnen</dc:creator><dc:creator>Kim, Donghun</dc:creator><dc:creator>Goudey, Howdy</dc:creator><dc:creator>Chen, Sharon</dc:creator><dc:creator>Zhang, Hui</dc:creator><dc:creator>Ghahramani, Ali</dc:creator><dc:creator>Huizenga, Charlie</dc:creator><dc:creator>He, Yingdong</dc:creator><dc:creator>Nomoto, Akihisa</dc:creator><dc:creator>Arens, Edward</dc:creator><dc:creator>Suárez, Ana Álvarez</dc:creator><dc:creator>Ritter, David</dc:creator><dc:creator>Tarin, Markus</dc:creator><dc:creator>Prickett, Robert</dc:creator><dc:date>2024-06-01</dc:date><dc:description>To improve occupant comfort and save energy in buildings, we have developed a closed-loop air conditioning (AC) sensor-controller that predicts occupant thermal sensation from the thermographic measurement of skin temperature distribution, then uses this information to reduce overcooling (cooling-energy overuse that discomforts occupants) by regulating AC output. Taking measures to protect privacy, it combines thermal-infrared (TIR) and color (visible spectrum) cameras with machine vision to measure the skin-surface temperature profile. Since the human thermoregulation system uses skin blood flow to maintain thermoneutrality, the distribution of skin temperature can be used to predict warm, neutral, and cool thermal states. We conducted a series of human-subject thermal-sensation trials in cold-to-hot environments, measuring skin temperatures and recording thermal sensation votes. We then trained random-forest classification machine-learning models (classifiers) to estimate thermal sensation from skin temperatures or skin-temperature differences. The estimated thermal sensation was input to a proportional integral (PI) control algorithm for the AC, targeting a sensation level between neutral and warm. Our sensor-controller includes a sensor assembly, server software, and client software. The server software orients the cameras and transmits images to the client software, which in turn assesses occupant skin temperature distribution, estimates occupant thermal sensation, and controls AC operation. A demonstration conducted in a conference room in an office building near Houston, TX showed that our system reduced overcooling, decreasing AC load by 42% when the room was occupied while improving occupant comfort (fraction of “comfortable” votes) by 15 percentage points.</dc:description><dc:subject>33 Built Environment and Design (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>3301 Architecture (for-2020)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>Networking and Information Technology R&amp;D (NITRD) (rcdc)</dc:subject><dc:subject>Air conditioning</dc:subject><dc:subject>Overcooling</dc:subject><dc:subject>Thermal comfort</dc:subject><dc:subject>Skin temperature</dc:subject><dc:subject>Infrared thermography</dc:subject><dc:subject>Machine vision</dc:subject><dc:subject>Closed-loop control</dc:subject><dc:subject>Energy savings</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>12 Built Environment and Design (for)</dc:subject><dc:subject>Building &amp; Construction (science-metrix)</dc:subject><dc:subject>33 Built environment and design (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3wt134z7</dc:identifier><dc:identifier>https://escholarship.org/content/qt3wt134z7/qt3wt134z7.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.enbuild.2024.114063</dc:identifier><dc:type>article</dc:type><dc:source>Energy and Buildings, vol 312</dc:source><dc:coverage>114063</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt168747wv</identifier><datestamp>2026-09-16T01:21:22Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt168747wv</dc:identifier><dc:title>Advanced denoising for X-ray ptychography.</dc:title><dc:creator>Chang, Huibin</dc:creator><dc:creator>Enfedaque, Pablo</dc:creator><dc:creator>Zhang, Jie</dc:creator><dc:creator>Reinhardt, Juliane</dc:creator><dc:creator>Enders, Bjoern</dc:creator><dc:creator>Yu, Young-Sang</dc:creator><dc:creator>Shapiro, David</dc:creator><dc:creator>Schroer, Christian G</dc:creator><dc:creator>Zeng, Tieyong</dc:creator><dc:creator>Marchesini, Stefano</dc:creator><dc:date>2019-04-15</dc:date><dc:description>The success of ptychographic imaging experiments strongly depends on achieving high signal-to-noise ratio. This is particularly important in nanoscale imaging experiments when diffraction signals are very weak and the experiments are accompanied by significant parasitic scattering (background), outliers or correlated noise sources. It is also critical when rare events, such as cosmic rays, or bad frames caused by electronic glitches or shutter timing malfunction take place. In this paper, we propose a novel iterative algorithm with rigorous analysis that exploits the direct forward model for parasitic noise and sample smoothness to achieve a thorough characterization and removal of structured and random noise. We present a formal description of the proposed algorithm and prove its convergence under mild conditions. Numerical experiments from simulations and real data (both soft and hard X-ray beamlines) demonstrate that the proposed algorithms produce better results when compared to state-of-the-art methods.</dc:description><dc:subject>4006 Communications Engineering (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>Biomedical Imaging (rcdc)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>eess.IV</dc:subject><dc:subject>eess.IV</dc:subject><dc:subject>math.OC</dc:subject><dc:subject>physics.optics</dc:subject><dc:subject>ALS-Beamline 10.3.2 (c-lbnl-label)</dc:subject><dc:subject>0205 Optical Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>1005 Communications Technologies (for)</dc:subject><dc:subject>Optics (science-metrix)</dc:subject><dc:subject>4006 Communications engineering (for-2020)</dc:subject><dc:subject>4009 Electronics</dc:subject><dc:subject>sensors and digital hardware (for-2020)</dc:subject><dc:subject>5102 Atomic</dc:subject><dc:subject>molecular and optical physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/168747wv</dc:identifier><dc:identifier>https://escholarship.org/content/qt168747wv/qt168747wv.pdf</dc:identifier><dc:identifier>info:doi/10.1364/oe.27.010395</dc:identifier><dc:type>article</dc:type><dc:source>Optics Express, vol 27, iss 8</dc:source><dc:coverage>10395 - 10418</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt36q3d77h</identifier><datestamp>2026-09-16T01:02:32Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt36q3d77h</dc:identifier><dc:title>The path from root input to mineral-associated soil carbon is dictated by habitat-specific microbial traits and soil moisture</dc:title><dc:creator>Sokol, Noah W</dc:creator><dc:creator>Foley, Megan M</dc:creator><dc:creator>Blazewicz, Steven J</dc:creator><dc:creator>Bhattacharyya, Amrita</dc:creator><dc:creator>DiDonato, Nicole</dc:creator><dc:creator>Estera-Molina, Katerina</dc:creator><dc:creator>Firestone, Mary</dc:creator><dc:creator>Greenlon, Alex</dc:creator><dc:creator>Hungate, Bruce A</dc:creator><dc:creator>Kimbrel, Jeffrey</dc:creator><dc:creator>Liquet, Jose</dc:creator><dc:creator>Lafler, Marissa</dc:creator><dc:creator>Marple, Maxwell</dc:creator><dc:creator>Nico, Peter S</dc:creator><dc:creator>Paša-Tolić, Ljiljana</dc:creator><dc:creator>Slessarev, Eric</dc:creator><dc:creator>Pett-Ridge, Jennifer</dc:creator><dc:date>2024-06-01</dc:date><dc:description>Soil microorganisms help transform plant inputs into mineral-associated soil organic carbon (SOC) – the largest and slowest-cycling pool of organic carbon on land. However, the microbial traits that influence this process are widely debated. While current theory and biogeochemical models have settled on carbon-use efficiency (CUE) and growth rate as positive predictors of mineral-associated SOC, empirical tests are sparse, with contradictory observations. Using 13C-labeling of an annual grass (Avena barbata) under two moisture regimes, we found that microbial traits associated with formation of 13C-mineral-associated SOC varied by soil habitat, as did active microbial taxa and SOC chemical composition. In the rhizosphere, bacterial-dominated communities with fast growth, high biomass, and high extracellular polymeric substance (EPS) production were positively associated with 13C-mineral-associated SOC. In contrast, the detritusphere held communities dominated by fungi and more filamentous bacteria, and with greater exoenzyme activity; there, 13C-mineral-associated SOC was associated with slower microbial growth and lower microbial biomass. CUE was a negative predictor of 13C-mineral-associated SOC in both habitats. Using 13C-quantitative stable isotope probing, we found that the majority of 13C assimilation in the rhizosphere and detritusphere at week 12 of the experiment was performed by very few bacterial and fungal taxa (3–5% of the total taxa that assimilated 13C). Several complementary chemical analyses (13C-NMR, FTICR-MS, and STXM-NEXAFS) suggested that SOC in the rhizosphere had a more oxidized chemical signature, while SOC in the detritusphere had a less oxidized, more lignin-like chemical signature. Our findings challenge current theory by demonstrating that microbial traits linked with mineral-associated SOC are not universal, but vary with soil habitat and moisture conditions, and are shaped by a small number of active taxa. Emerging SOC models that explicitly reflect these interactions may better predict SOC storage, since climate change causes shifts in soil moisture regimes and the ratio of living versus decaying roots.</dc:description><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>4106 Soil Sciences (for-2020)</dc:subject><dc:subject>Soil carbon</dc:subject><dc:subject>Microbial traits</dc:subject><dc:subject>Mineral -associated organic carbon</dc:subject><dc:subject>Drought</dc:subject><dc:subject>Carbon cycle</dc:subject><dc:subject>Global change</dc:subject><dc:subject>Stable isotope probing</dc:subject><dc:subject>05 Environmental Sciences (for)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>07 Agricultural and Veterinary Sciences (for)</dc:subject><dc:subject>Agronomy &amp; Agriculture (science-metrix)</dc:subject><dc:subject>4106 Soil sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/36q3d77h</dc:identifier><dc:identifier>https://escholarship.org/content/qt36q3d77h/qt36q3d77h.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.soilbio.2024.109367</dc:identifier><dc:type>article</dc:type><dc:source>Soil Biology and Biochemistry, vol 193</dc:source><dc:coverage>109367</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8j65c1qs</identifier><datestamp>2026-09-16T01:02:05Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8j65c1qs</dc:identifier><dc:title>Shell-Based Support Structure for the 45 GHz ECR Ion Source MARS-D</dc:title><dc:creator>Juchno, M</dc:creator><dc:creator>Benitez, JY</dc:creator><dc:creator>Doyle, J</dc:creator><dc:creator>Hodgkinson, A</dc:creator><dc:creator>Leow, T</dc:creator><dc:creator>Phair, LW</dc:creator><dc:creator>Todd, DS</dc:creator><dc:creator>Wang, L</dc:creator><dc:creator>Xie, D vv Z</dc:creator><dc:date>2022-09-01</dc:date><dc:description>Superconducting electron cyclotron resonance ion sources (ECRISs) using NbTi coils and optimized for 28 GHz resonant heating have been successfully operated for almost two decades. Moving to higher heating frequencies requires increased magnetic fields, but traditional racetrack-and-solenoid ECRIS structures are at their limit using NbTi. Rather than moving to a superconductor untested in this field, the Mixed Axial and Radial field System (MARS) being developed at Lawrence Berkeley National Laboratory employs a novel closed-loop-coil design that more efficiently utilizes conductor fields and will allow the use of NbTi in a next-generation, 45 GHz ECRIS. This article presents the design of the shell-based support structure central to the MARS-D magnet design, as well as structural analysis of its components and optimization of pre-load parameters that will guarantee its successful operation.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Coils</dc:subject><dc:subject>Superconducting magnets</dc:subject><dc:subject>Solenoids</dc:subject><dc:subject>Stress</dc:subject><dc:subject>Aluminum</dc:subject><dc:subject>Magnetomechanical effects</dc:subject><dc:subject>Magnetic resonance</dc:subject><dc:subject>ECR ion source</dc:subject><dc:subject>magnet structure</dc:subject><dc:subject>minimum-B fields</dc:subject><dc:subject>special coils</dc:subject><dc:subject>superconducting magnets</dc:subject><dc:subject>NSD-88-Inch Cyclotron (c-lbnl-label)</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>4008 Electrical engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8j65c1qs</dc:identifier><dc:identifier>https://escholarship.org/content/qt8j65c1qs/qt8j65c1qs.pdf</dc:identifier><dc:identifier>info:doi/10.1109/tasc.2022.3158375</dc:identifier><dc:type>article</dc:type><dc:source>IEEE Transactions on Applied Superconductivity, vol 32, iss 6</dc:source><dc:coverage>1 - 5</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7w04z1kv</identifier><datestamp>2026-09-16T00:58:32Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7w04z1kv</dc:identifier><dc:title>Muon identification using multivariate techniques in the CMS experiment in proton-proton collisions at sqrt(s) = 13 TeV</dc:title><dc:creator>Hayrapetyan, A</dc:creator><dc:creator>Tumasyan, A</dc:creator><dc:creator>Adam, W</dc:creator><dc:creator>Andrejkovic, JW</dc:creator><dc:creator>Bergauer, T</dc:creator><dc:creator>Chatterjee, S</dc:creator><dc:creator>Damanakis, K</dc:creator><dc:creator>Dragicevic, M</dc:creator><dc:creator>Del Valle, A Escalante</dc:creator><dc:creator>Hussain, PS</dc:creator><dc:creator>Jeitler, M</dc:creator><dc:creator>Krammer, N</dc:creator><dc:creator>Liko, D</dc:creator><dc:creator>Mikulec, I</dc:creator><dc:creator>Schieck, J</dc:creator><dc:creator>Schöfbeck, R</dc:creator><dc:creator>Schwarz, D</dc:creator><dc:creator>Sonawane, M</dc:creator><dc:creator>Templ, S</dc:creator><dc:creator>Waltenberger, W</dc:creator><dc:creator>Wulz, C-E</dc:creator><dc:creator>Darwish, MR</dc:creator><dc:creator>Janssen, T</dc:creator><dc:creator>Van Mechelen, P</dc:creator><dc:creator>Bols, ES</dc:creator><dc:creator>D'Hondt, J</dc:creator><dc:creator>Dansana, S</dc:creator><dc:creator>De Moor, A</dc:creator><dc:creator>Delcourt, M</dc:creator><dc:creator>Faham, H El</dc:creator><dc:creator>Lowette, S</dc:creator><dc:creator>Makarenko, I</dc:creator><dc:creator>Müller, D</dc:creator><dc:creator>Sahasransu, AR</dc:creator><dc:creator>Tavernier, S</dc:creator><dc:creator>Tytgat, M</dc:creator><dc:creator>Van Putte, S</dc:creator><dc:creator>Vannerom, D</dc:creator><dc:creator>Clerbaux, B</dc:creator><dc:creator>De Lentdecker, G</dc:creator><dc:creator>Favart, L</dc:creator><dc:creator>Hohov, D</dc:creator><dc:creator>Jaramillo, J</dc:creator><dc:creator>Khalilzadeh, A</dc:creator><dc:creator>Lee, K</dc:creator><dc:creator>Mahdavikhorrami, M</dc:creator><dc:creator>Malara, A</dc:creator><dc:creator>Paredes, S</dc:creator><dc:creator>Pétré, L</dc:creator><dc:creator>Postiau, N</dc:creator><dc:creator>Thomas, L</dc:creator><dc:creator>Bemden, M Vanden</dc:creator><dc:creator>Vander Velde, C</dc:creator><dc:creator>Vanlaer, P</dc:creator><dc:creator>De Coen, M</dc:creator><dc:creator>Dobur, D</dc:creator><dc:creator>Hong, Y</dc:creator><dc:creator>Knolle, J</dc:creator><dc:creator>Lambrecht, L</dc:creator><dc:creator>Mestdach, G</dc:creator><dc:creator>Rendón, C</dc:creator><dc:creator>Samalan, A</dc:creator><dc:creator>Skovpen, K</dc:creator><dc:creator>Van Den Bossche, N</dc:creator><dc:creator>Wezenbeek, L</dc:creator><dc:creator>Benecke, A</dc:creator><dc:creator>Bruno, G</dc:creator><dc:creator>Caputo, C</dc:creator><dc:creator>Delaere, C</dc:creator><dc:creator>Donertas, IS</dc:creator><dc:creator>Giammanco, A</dc:creator><dc:creator>Jaffel, K</dc:creator><dc:creator>Jain</dc:creator><dc:creator>Lemaitre, V</dc:creator><dc:creator>Lidrych, J</dc:creator><dc:creator>Mastrapasqua, P</dc:creator><dc:creator>Mondal, K</dc:creator><dc:creator>Tran, TT</dc:creator><dc:creator>Wertz, S</dc:creator><dc:creator>Alves, GA</dc:creator><dc:creator>Coelho, E</dc:creator><dc:creator>Hensel, C</dc:creator><dc:creator>De Oliveira, T Menezes</dc:creator><dc:creator>Moraes, A</dc:creator><dc:creator>Teles, P Rebello</dc:creator><dc:creator>Soeiro, M</dc:creator><dc:creator>Júnior, WL Aldá</dc:creator><dc:creator>Pereira, M Alves Gallo</dc:creator><dc:creator>Filho, M Barroso Ferreira</dc:creator><dc:creator>Malbouisson, H Brandao</dc:creator><dc:creator>Carvalho, W</dc:creator><dc:creator>Chinellato, J</dc:creator><dc:creator>Da Costa, EM</dc:creator><dc:creator>Da Silveira, GG</dc:creator><dc:creator>De Jesus Damiao, D</dc:creator><dc:creator>De Souza, S Fonseca</dc:creator><dc:creator>Martins, J</dc:creator><dc:creator>Herrera, C Mora</dc:creator><dc:creator>Amarilo, K Mota</dc:creator><dc:creator>Mundim, L</dc:creator><dc:date>2024-02-01</dc:date><dc:description>The identification of prompt and isolated muons, as well as muons from heavy-flavour hadron decays, is an important task. We developed two multivariate techniques to provide highly efficient identification for muons with transverse momentum greater than 10 GeV. One provides a continuous variable as an alternative to a cut-based identification selection and offers a better discrimination power against misidentified muons. The other one selects prompt and isolated muons by using isolation requirements to reduce the contamination from nonprompt muons arising in heavy-flavour hadron decays. Both algorithms are developed using 59.7 fb-1 of proton-proton collisions data at a centre-of-mass energy of √(s)=13 TeV collected in 2018 with the CMS experiment at the CERN LHC.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Muon spectrometers</dc:subject><dc:subject>Particle identification methods</dc:subject><dc:subject>Particle tracking detectors</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7w04z1kv</dc:identifier><dc:identifier>https://escholarship.org/content/qt7w04z1kv/qt7w04z1kv.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1748-0221/19/02/p02031</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Instrumentation, vol 19, iss 02</dc:source><dc:coverage>p02031</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9vc0m8rh</identifier><datestamp>2026-09-16T00:54:12Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9vc0m8rh</dc:identifier><dc:title>Fabrication of First 4-m Coils for the LARP MQXFA Quadrupole and Assembly in Mirror Structure</dc:title><dc:creator>Holik, Eddie Frank</dc:creator><dc:creator>Ambrosio, Giorgio</dc:creator><dc:creator>Anerella, Michael</dc:creator><dc:creator>Bossert, Rodger</dc:creator><dc:creator>Cavanna, Eugenio</dc:creator><dc:creator>Cheng, Daniel</dc:creator><dc:creator>Dietderich, Daniel R</dc:creator><dc:creator>Ferracin, Paolo</dc:creator><dc:creator>Ghosh, Arup K</dc:creator><dc:creator>Bermudez, Susana Izquierdo</dc:creator><dc:creator>Krave, Steven</dc:creator><dc:creator>Nobrega, Alfred</dc:creator><dc:creator>Perez, Juan Carlos</dc:creator><dc:creator>Pong, Ian</dc:creator><dc:creator>Sabbi, GianLuca</dc:creator><dc:creator>Santini, Carlo</dc:creator><dc:creator>Schmalzle, Jesse</dc:creator><dc:creator>Wanderer, Peter</dc:creator><dc:creator>Wang, Xiaorong</dc:creator><dc:creator>Yu, Miao</dc:creator><dc:date>2017-06-01</dc:date><dc:description>The US LHC Accelerator Research Program is constructing prototype interaction region quadrupoles as part of the US in-kind contribution to the Hi-Lumi LHC project. The low-beta MQXFA Q1/Q3 coils have a 4-m length and a 150 mm bore. The design was previously validated on short, one meter models (MQXFS) developed as part of the longstanding Nb3Sn quadrupole R&amp;amp;D by LARP in collaboration with CERN. In parallel, facilities and tooling are being developed and refined at BNL, LBNL, and FNAL to enable long coil production, assembly, and cold testing. Long length scale-up is based on the experience from the LARP 90-mm aperture (TQ-LQ) and 120-mm aperture (HQ and Long HQ) programs. A 4-m long MQXF practice coil was fabricated to verify procedures, parts, and tooling. In parallel, the first complete prototype coil (QXFP01a) was fabricated and assembled in a long magnetic mirror, MQXFPM1, to provide early feedback on coil design and fabrication following the successful experience of previous LARP mirror tests.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>High luminosity LHC</dc:subject><dc:subject>Long Nb3Sn coil</dc:subject><dc:subject>mirror magnet</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>4008 Electrical engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9vc0m8rh</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1109/tasc.2017.2656155</dc:identifier><dc:type>article</dc:type><dc:source>IEEE Transactions on Applied Superconductivity, vol 27, iss 4</dc:source><dc:coverage>1 - 5</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5qc2v372</identifier><datestamp>2026-09-16T00:54:08Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5qc2v372</dc:identifier><dc:title>Fabrication and Analysis of 150-mm-Aperture Nb3Sn MQXF Coils</dc:title><dc:creator>Holik, EF</dc:creator><dc:creator>Ambrosio, G</dc:creator><dc:creator>Anerella, M</dc:creator><dc:creator>Bossert, R</dc:creator><dc:creator>Cavanna, E</dc:creator><dc:creator>Cheng, D</dc:creator><dc:creator>Dietderich, DR</dc:creator><dc:creator>Ferracin, P</dc:creator><dc:creator>Ghosh, AK</dc:creator><dc:creator>Bermudez, S Izquierdo</dc:creator><dc:creator>Krave, S</dc:creator><dc:creator>Nobrega, A</dc:creator><dc:creator>Perez, JC</dc:creator><dc:creator>Pong, I</dc:creator><dc:creator>Rochepault, E</dc:creator><dc:creator>Sabbi, GL</dc:creator><dc:creator>Schmalzle, J</dc:creator><dc:creator>Yu, M</dc:creator><dc:date>2016-06-01</dc:date><dc:description>The U.S. LHC Accelerator Research Program (LARP) and CERN are combining efforts for the HiLumi-LHC upgrade to design and fabricate 150-mm-aperture interaction region quadrupoles with a nominal gradient of 130 T/m using Nb3Sn. To successfully produce the necessary long MQXF triplets, the HiLumi-LHC collaboration is systematically reducing risk and design modification by heavily relying upon the experience gained from the successful 120-mm-aperture LARP HQ program. First-generation MQXF short (MQXFS) coils were predominately a scaling up of the HQ quadrupole design, allowing comparable cable expansion during Nb3Sn formation heat treatment and increased insulation fraction for electrical robustness. A total of 13 first-generation MQXFS coils were fabricated between LARP and CERN. Systematic differences in coil size, coil alignment symmetry, and coil length contraction during heat treatment are observed and likely due to slight variances in tooling and insulation/cable systems. Analysis of coil cross sections indicate that field-shaping wedges and adjacent coil turns are systematically displaced from the nominal location and the cable is expanding less than nominally designed. A second-generation MQXF coil design seeks to correct the expansion and displacement discrepancies by increasing insulation and adding adjustable shims at the coil pole and midplanes to correct allowed magnetic field harmonics.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>High-luminosity LHC</dc:subject><dc:subject>low-beta quadrupole</dc:subject><dc:subject>Nb3Sn magnet</dc:subject><dc:subject>superconducting accelerator magnets</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>4008 Electrical engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5qc2v372</dc:identifier><dc:identifier>https://escholarship.org/content/qt5qc2v372/qt5qc2v372.pdf</dc:identifier><dc:identifier>info:doi/10.1109/tasc.2015.2514193</dc:identifier><dc:type>article</dc:type><dc:source>IEEE Transactions on Applied Superconductivity, vol 26, iss 4</dc:source><dc:coverage>1 - 7</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7f9599h9</identifier><datestamp>2026-09-16T00:53:51Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7f9599h9</dc:identifier><dc:title>Communication: Hydrogen bonding interactions in water-alcohol mixtures from X-ray absorption spectroscopy</dc:title><dc:creator>Lam, Royce K</dc:creator><dc:creator>Smith, Jacob W</dc:creator><dc:creator>Saykally, Richard J</dc:creator><dc:date>2016-05-21</dc:date><dc:description>While methanol and ethanol are macroscopically miscible with water, their mixtures exhibit negative excess entropies of mixing. Despite considerable effort in both experiment and theory, there remains significant disagreement regarding the origin of this effect. Different models for the liquid mixture structure have been proposed to address this behavior, including the enhancement of the water hydrogen bonding network around the alcohol hydrophobic groups and microscopic immiscibility or clustering. We have investigated mixtures of methanol, ethanol, and isopropanol with water by liquid microjet X-ray absorption spectroscopy on the oxygen K-edge, an atom-specific probe providing details of both inter- and intra-molecular structure. The measured spectra evidence a significant enhancement of hydrogen bonding originating from the methanol and ethanol hydroxyl groups upon the addition of water. These additional hydrogen bonding interactions would strengthen the liquid-liquid interactions, resulting in additional ordering in the liquid structures and leading to a reduction in entropy and a negative enthalpy of mixing, consistent with existing thermodynamic data. In contrast, the spectra of the isopropanol-water mixtures exhibit an increase in the number of broken alcohol hydrogen bonds for mixtures containing up to 0.5 water mole fraction, an observation consistent with existing enthalpy of mixing data, suggesting that the measured negative excess entropy is a result of clustering or micro-immiscibility.</dc:description><dc:subject>34 Chemical Sciences (for-2020)</dc:subject><dc:subject>3406 Physical Chemistry (for-2020)</dc:subject><dc:subject>Substance Misuse (rcdc)</dc:subject><dc:subject>Alcoholism</dc:subject><dc:subject>Alcohol Use and Health (rcdc)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>03 Chemical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Chemical Physics (science-metrix)</dc:subject><dc:subject>34 Chemical sciences (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7f9599h9</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1063/1.4951010</dc:identifier><dc:type>multimedia</dc:type><dc:source>The Journal of Chemical Physics, vol 144, iss 19</dc:source><dc:coverage>191103</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt38h6q1jg</identifier><datestamp>2026-09-16T00:53:45Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt38h6q1jg</dc:identifier><dc:title>Repeated Evolution of Power-Amplified Predatory Strikes in Trap-Jaw Spiders</dc:title><dc:creator>Wood, Hannah M</dc:creator><dc:creator>Parkinson, Dilworth Y</dc:creator><dc:creator>Griswold, Charles E</dc:creator><dc:creator>Gillespie, Rosemary G</dc:creator><dc:creator>Elias, Damian O</dc:creator><dc:date>2016-04-01</dc:date><dc:description>Small animals possess intriguing morphological and behavioral traits that allow them to capture prey, including innovative structural mechanisms that produce ballistic movements by amplifying power [1-6]. Power amplification occurs when an organism produces a relatively high power output by releasing slowly stored energy almost instantaneously, resulting in movements that surpass the maximal power output of muscles [7]. For example, trap-jaw, power-amplified mechanisms have been described for several ant genera [5, 8], which have evolved some of the fastest known movements in the animal kingdom [6]. However, power-amplified predatory strikes were not previously known in one of the largest animal classes, the arachnids. Mecysmaucheniidae spiders, which occur only in New Zealand and southern South America, are tiny, cryptic, ground-dwelling spiders that rely on hunting rather than web-building to capture prey [9]. Analysis of high-speed video revealed that power-amplified mechanisms occur in some mecysmaucheniid species, with the fastest species being two orders of magnitude faster than the slowest species. Molecular phylogenetic analysis revealed that power-amplified cheliceral strikes have evolved four times independently within the family. Furthermore, we identified morphological innovations that directly relate to cheliceral function: a highly modified carapace in which the cheliceral muscles are oriented horizontally; modification of a cheliceral sclerite to have muscle attachments; and, in the power-amplified species, a thicker clypeus and clypeal apodemes. These structural innovations may have set the stage for the parallel evolution of ballistic predatory strikes.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>3104 Evolutionary Biology (for-2020)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Biomechanical Phenomena (mesh)</dc:subject><dc:subject>Evolution</dc:subject><dc:subject>Molecular (mesh)</dc:subject><dc:subject>Movement (mesh)</dc:subject><dc:subject>Muscle</dc:subject><dc:subject>Skeletal (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Predatory Behavior (mesh)</dc:subject><dc:subject>Spiders (mesh)</dc:subject><dc:subject>Muscle</dc:subject><dc:subject>Skeletal (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Spiders (mesh)</dc:subject><dc:subject>Predatory Behavior (mesh)</dc:subject><dc:subject>Evolution</dc:subject><dc:subject>Molecular (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Movement (mesh)</dc:subject><dc:subject>Biomechanical Phenomena (mesh)</dc:subject><dc:subject>arachnid</dc:subject><dc:subject>ballistic movement</dc:subject><dc:subject>morphology</dc:subject><dc:subject>parallel evolution</dc:subject><dc:subject>phylogenetics</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Biomechanical Phenomena (mesh)</dc:subject><dc:subject>Evolution</dc:subject><dc:subject>Molecular (mesh)</dc:subject><dc:subject>Movement (mesh)</dc:subject><dc:subject>Muscle</dc:subject><dc:subject>Skeletal (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Predatory Behavior (mesh)</dc:subject><dc:subject>Spiders (mesh)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>17 Psychology and Cognitive Sciences (for)</dc:subject><dc:subject>Developmental Biology (science-metrix)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:subject>52 Psychology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/38h6q1jg</dc:identifier><dc:identifier>https://escholarship.org/content/qt38h6q1jg/qt38h6q1jg.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.cub.2016.02.029</dc:identifier><dc:type>article</dc:type><dc:source>Current Biology, vol 26, iss 8</dc:source><dc:coverage>1057 - 1061</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4tw2d1nt</identifier><datestamp>2026-09-16T00:53:35Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4tw2d1nt</dc:identifier><dc:title>Apolipoprotein E ε4 genotype status is not associated with neuroimaging outcomes in a large cohort of HIV+ individuals</dc:title><dc:creator>Cooley, Sarah A</dc:creator><dc:creator>Paul, Robert H</dc:creator><dc:creator>Fennema-Notestine, Christine</dc:creator><dc:creator>Morgan, Erin E</dc:creator><dc:creator>Vaida, Florin</dc:creator><dc:creator>Deng, Qianqian</dc:creator><dc:creator>Chen, Jie Ashley</dc:creator><dc:creator>Letendre, Scott</dc:creator><dc:creator>Ellis, Ronald</dc:creator><dc:creator>Clifford, David B</dc:creator><dc:creator>Marra, Christina M</dc:creator><dc:creator>Collier, Ann C</dc:creator><dc:creator>Gelman, Benjamin B</dc:creator><dc:creator>McArthur, Justin C</dc:creator><dc:creator>McCutchan, J Allen</dc:creator><dc:creator>Simpson, David M</dc:creator><dc:creator>Morgello, Susan</dc:creator><dc:creator>Grant, Igor</dc:creator><dc:creator>Ances, Beau M</dc:creator><dc:creator>for the CNS HIV Anti-Retroviral Therapy Effects Research (CHARTER) Group</dc:creator><dc:date>2016-10-01</dc:date><dc:description>Previous neuroimaging studies suggest a negative relationship between the apolipoprotein (ApoE) ε4 allele and brain integrity in human immunodeficiency virus (HIV)-infected (HIV+) individuals, although the presence of this relationship across adulthood remains unclear. The purpose of this study is to clarify the discrepancies using a large, diverse group of HIV+ individuals and multiple imaging modalities sensitive to HIV. The association of ApoE ε4 with structural neuroimaging and magnetic resonance spectroscopy (MRS) was examined in 237 HIV+ individuals in the CNS HIV Anti-Retroviral Therapy Effects Research (CHARTER) study. Cortical and subcortical gray matter, abnormal and total white matter, ventricles, sulcal cerebrospinal fluid (CSF), and cerebellar gray matter, white matter, and CSF volumes, and MRS concentrations of myo-inositol, creatine, N-acetyl-aspartate, and choline in the frontal white matter (FWM), frontal gray matter (FGM), and basal ganglia were examined. Secondary analyses explored this relationship separately in individuals ≥50&amp;nbsp;years old (n = 173) and &amp;lt;50&amp;nbsp;years old (n = 63). No significant differences were observed between ApoE ε4+ (ApoE ε3/ε4 and ApoE ε4/ε4) individuals (n = 69) and ApoE ε4− (ApoE ε2/ε3 and ApoE ε3/ε3) individuals (n = 167). When individuals were further divided by age, no significant genotype group differences were identified in individuals &amp;lt;50 or ≥50&amp;nbsp;years of age on any neuroimaging outcome. The ApoE ε4 allele did not affect brain integrity in this large, diverse sample of HIV+ individuals. The effects of ApoE ε4 may not be apparent until more advanced ages and may be more prominent when present along with other risk factors for neuronal damage.</dc:description><dc:subject>3207 Medical Microbiology (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>HIV/AIDS (rcdc)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>Aging (rcdc)</dc:subject><dc:subject>Brain Disorders (rcdc)</dc:subject><dc:subject>Infectious Diseases (rcdc)</dc:subject><dc:subject>Biomedical Imaging (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Neurological (hrcs-hc)</dc:subject><dc:subject>Infection (hrcs-hc)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Alleles (mesh)</dc:subject><dc:subject>Antineoplastic Agents (mesh)</dc:subject><dc:subject>Apolipoprotein E4 (mesh)</dc:subject><dc:subject>Basal Ganglia (mesh)</dc:subject><dc:subject>Cerebellum (mesh)</dc:subject><dc:subject>Cerebral Cortex (mesh)</dc:subject><dc:subject>Cerebral Ventricles (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Gene Expression (mesh)</dc:subject><dc:subject>Genotype (mesh)</dc:subject><dc:subject>Gray Matter (mesh)</dc:subject><dc:subject>HIV Infections (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Magnetic Resonance Imaging (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Neuroimaging (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>White Matter (mesh)</dc:subject><dc:subject>HIV/AIDS</dc:subject><dc:subject>Genetics</dc:subject><dc:subject>Magnetic resonance spectroscopy</dc:subject><dc:subject>Brain volumetrics</dc:subject><dc:subject>CNS HIV Anti-Retroviral Therapy Effects Research (CHARTER) Group</dc:subject><dc:subject>Cerebellum (mesh)</dc:subject><dc:subject>Cerebral Ventricles (mesh)</dc:subject><dc:subject>Basal Ganglia (mesh)</dc:subject><dc:subject>Cerebral Cortex (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>HIV Infections (mesh)</dc:subject><dc:subject>Antineoplastic Agents (mesh)</dc:subject><dc:subject>Magnetic Resonance Imaging (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Gene Expression (mesh)</dc:subject><dc:subject>Genotype (mesh)</dc:subject><dc:subject>Alleles (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Apolipoprotein E4 (mesh)</dc:subject><dc:subject>Neuroimaging (mesh)</dc:subject><dc:subject>White Matter (mesh)</dc:subject><dc:subject>Gray Matter (mesh)</dc:subject><dc:subject>Brain volumetrics</dc:subject><dc:subject>Genetics</dc:subject><dc:subject>HIV/AIDS</dc:subject><dc:subject>Magnetic resonance spectroscopy</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Alleles (mesh)</dc:subject><dc:subject>Antineoplastic Agents (mesh)</dc:subject><dc:subject>Apolipoprotein E4 (mesh)</dc:subject><dc:subject>Basal Ganglia (mesh)</dc:subject><dc:subject>Cerebellum (mesh)</dc:subject><dc:subject>Cerebral Cortex (mesh)</dc:subject><dc:subject>Cerebral Ventricles (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Gene Expression (mesh)</dc:subject><dc:subject>Genotype (mesh)</dc:subject><dc:subject>Gray Matter (mesh)</dc:subject><dc:subject>HIV Infections (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Magnetic Resonance Imaging (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Neuroimaging (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>White Matter (mesh)</dc:subject><dc:subject>1103 Clinical Sciences (for)</dc:subject><dc:subject>1108 Medical Microbiology (for)</dc:subject><dc:subject>1109 Neurosciences (for)</dc:subject><dc:subject>Virology (science-metrix)</dc:subject><dc:subject>3202 Clinical sciences (for-2020)</dc:subject><dc:subject>3207 Medical microbiology (for-2020)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4tw2d1nt</dc:identifier><dc:identifier>https://escholarship.org/content/qt4tw2d1nt/qt4tw2d1nt.pdf</dc:identifier><dc:identifier>info:doi/10.1007/s13365-016-0434-7</dc:identifier><dc:type>article</dc:type><dc:source>Journal of NeuroVirology, vol 22, iss 5</dc:source><dc:coverage>607 - 614</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9g15583q</identifier><datestamp>2026-09-16T00:49:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9g15583q</dc:identifier><dc:title>Study of azimuthal anisotropy of ϒ(1S) mesons in pPb collisions at s NN = 8.16 TeV</dc:title><dc:creator>Tumasyan, A</dc:creator><dc:creator>Adam, W</dc:creator><dc:creator>Andrejkovic, JW</dc:creator><dc:creator>Bergauer, T</dc:creator><dc:creator>Chatterjee, S</dc:creator><dc:creator>Damanakis, K</dc:creator><dc:creator>Dragicevic, M</dc:creator><dc:creator>Del Valle, A Escalante</dc:creator><dc:creator>Hussain, PS</dc:creator><dc:creator>Jeitler, M</dc:creator><dc:creator>Krammer, N</dc:creator><dc:creator>Lechner, L</dc:creator><dc:creator>Liko, D</dc:creator><dc:creator>Mikulec, I</dc:creator><dc:creator>Paulitsch, P</dc:creator><dc:creator>Pitters, FM</dc:creator><dc:creator>Schieck, J</dc:creator><dc:creator>Schöfbeck, R</dc:creator><dc:creator>Schwarz, D</dc:creator><dc:creator>Sonawane, M</dc:creator><dc:creator>Templ, S</dc:creator><dc:creator>Waltenberger, W</dc:creator><dc:creator>Wulz, C-E</dc:creator><dc:creator>Darwish, MR</dc:creator><dc:creator>Janssen, T</dc:creator><dc:creator>Kello, T</dc:creator><dc:creator>Sfar, H Rejeb</dc:creator><dc:creator>Van Mechelen, P</dc:creator><dc:creator>Bols, ES</dc:creator><dc:creator>D'Hondt, J</dc:creator><dc:creator>De Moor, A</dc:creator><dc:creator>Delcourt, M</dc:creator><dc:creator>Faham, H El</dc:creator><dc:creator>Lowette, S</dc:creator><dc:creator>Moortgat, S</dc:creator><dc:creator>Morton, A</dc:creator><dc:creator>Müller, D</dc:creator><dc:creator>Sahasransu, AR</dc:creator><dc:creator>Tavernier, S</dc:creator><dc:creator>Van Doninck, W</dc:creator><dc:creator>Vannerom, D</dc:creator><dc:creator>Clerbaux, B</dc:creator><dc:creator>De Lentdecker, G</dc:creator><dc:creator>Favart, L</dc:creator><dc:creator>Hohov, D</dc:creator><dc:creator>Jaramillo, J</dc:creator><dc:creator>Lee, K</dc:creator><dc:creator>Mahdavikhorrami, M</dc:creator><dc:creator>Makarenko, I</dc:creator><dc:creator>Malara, A</dc:creator><dc:creator>Paredes, S</dc:creator><dc:creator>Pétré, L</dc:creator><dc:creator>Postiau, N</dc:creator><dc:creator>Thomas, L</dc:creator><dc:creator>Bemden, M Vanden</dc:creator><dc:creator>Vander Velde, C</dc:creator><dc:creator>Vanlaer, P</dc:creator><dc:creator>Dobur, D</dc:creator><dc:creator>Knolle, J</dc:creator><dc:creator>Lambrecht, L</dc:creator><dc:creator>Mestdach, G</dc:creator><dc:creator>Niedziela, M</dc:creator><dc:creator>Rendón, C</dc:creator><dc:creator>Roskas, C</dc:creator><dc:creator>Samalan, A</dc:creator><dc:creator>Skovpen, K</dc:creator><dc:creator>Tytgat, M</dc:creator><dc:creator>Van Den Bossche, N</dc:creator><dc:creator>Vermassen, B</dc:creator><dc:creator>Wezenbeek, L</dc:creator><dc:creator>Benecke, A</dc:creator><dc:creator>Bruno, G</dc:creator><dc:creator>Bury, F</dc:creator><dc:creator>Caputo, C</dc:creator><dc:creator>David, P</dc:creator><dc:creator>Delaere, C</dc:creator><dc:creator>Donertas, IS</dc:creator><dc:creator>Giammanco, A</dc:creator><dc:creator>Jaffel, K</dc:creator><dc:creator>Jain</dc:creator><dc:creator>Lemaitre, V</dc:creator><dc:creator>Mondal, K</dc:creator><dc:creator>Taliercio, A</dc:creator><dc:creator>Tran, TT</dc:creator><dc:creator>Vischia, P</dc:creator><dc:creator>Wertz, S</dc:creator><dc:creator>Alves, GA</dc:creator><dc:creator>Coelho, E</dc:creator><dc:creator>Hensel, C</dc:creator><dc:creator>Moraes, A</dc:creator><dc:creator>Teles, P Rebello</dc:creator><dc:creator>Júnior, WL Aldá</dc:creator><dc:creator>Pereira, M Alves Gallo</dc:creator><dc:creator>Filho, M Barroso Ferreira</dc:creator><dc:creator>Malbouisson, H Brandao</dc:creator><dc:creator>Carvalho, W</dc:creator><dc:creator>Chinellato, J</dc:creator><dc:creator>Da Costa, EM</dc:creator><dc:creator>Da Silveira, GG</dc:creator><dc:creator>De Jesus Damiao, D</dc:creator><dc:date>2024-03-01</dc:date><dc:description>The azimuthal anisotropy of Image 1 mesons in high-multiplicity proton-lead collisions is studied using data collected by the CMS experiment at a nucleon-nucleon center-of-mass energy of 8.16 TeV . The Image 1 mesons are reconstructed using their dimuon decay channel. The anisotropy is characterized by the second Fourier harmonic coefficients, found using a two-particle correlation technique, in which the Image 1 mesons are correlated with charged hadrons. A large pseudorapidity gap is used to suppress short-range correlations. Nonflow contamination from the dijet background is removed using a low-multiplicity subtraction method, and the results are presented as a function of Image 1 transverse momentum. The azimuthal anisotropies are smaller than those found for charmonia in proton-lead collisions at the same collision energy, but are consistent with values found for Image 1 mesons in lead-lead interactions at a nucleon-nucleon center-of-mass energy of 5.02 TeV.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>CMS</dc:subject><dc:subject>pPb</dc:subject><dc:subject>Heavy ion</dc:subject><dc:subject>v2</dc:subject><dc:subject>Upsilon</dc:subject><dc:subject>Flow</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9g15583q</dc:identifier><dc:identifier>https://escholarship.org/content/qt9g15583q/qt9g15583q.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.physletb.2024.138518</dc:identifier><dc:type>article</dc:type><dc:source>Physics Letters B, vol 850</dc:source><dc:coverage>138518</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7kw0g7vh</identifier><datestamp>2026-09-16T00:49:06Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7kw0g7vh</dc:identifier><dc:title>Measurements of azimuthal anisotropy of nonprompt D0 mesons in PbPb collisions at s NN = 5.02 TeV</dc:title><dc:creator>Tumasyan, A</dc:creator><dc:creator>Adam, W</dc:creator><dc:creator>Andrejkovic, JW</dc:creator><dc:creator>Bergauer, T</dc:creator><dc:creator>Chatterjee, S</dc:creator><dc:creator>Damanakis, K</dc:creator><dc:creator>Dragicevic, M</dc:creator><dc:creator>Del Valle, A Escalante</dc:creator><dc:creator>Hussain, PS</dc:creator><dc:creator>Jeitler, M</dc:creator><dc:creator>Krammer, N</dc:creator><dc:creator>Lechner, L</dc:creator><dc:creator>Liko, D</dc:creator><dc:creator>Mikulec, I</dc:creator><dc:creator>Paulitsch, P</dc:creator><dc:creator>Pitters, FM</dc:creator><dc:creator>Schieck, J</dc:creator><dc:creator>Schöfbeck, R</dc:creator><dc:creator>Schwarz, D</dc:creator><dc:creator>Sonawane, M</dc:creator><dc:creator>Templ, S</dc:creator><dc:creator>Waltenberger, W</dc:creator><dc:creator>Wulz, C-E</dc:creator><dc:creator>Darwish, MR</dc:creator><dc:creator>Janssen, T</dc:creator><dc:creator>Kello, T</dc:creator><dc:creator>Sfar, H Rejeb</dc:creator><dc:creator>Van Mechelen, P</dc:creator><dc:creator>Bols, ES</dc:creator><dc:creator>D'Hondt, J</dc:creator><dc:creator>De Moor, A</dc:creator><dc:creator>Delcourt, M</dc:creator><dc:creator>Faham, H El</dc:creator><dc:creator>Lowette, S</dc:creator><dc:creator>Moortgat, S</dc:creator><dc:creator>Morton, A</dc:creator><dc:creator>Müller, D</dc:creator><dc:creator>Sahasransu, AR</dc:creator><dc:creator>Tavernier, S</dc:creator><dc:creator>Van Doninck, W</dc:creator><dc:creator>Vannerom, D</dc:creator><dc:creator>Clerbaux, B</dc:creator><dc:creator>De Lentdecker, G</dc:creator><dc:creator>Favart, L</dc:creator><dc:creator>Hohov, D</dc:creator><dc:creator>Jaramillo, J</dc:creator><dc:creator>Lee, K</dc:creator><dc:creator>Mahdavikhorrami, M</dc:creator><dc:creator>Makarenko, I</dc:creator><dc:creator>Malara, A</dc:creator><dc:creator>Paredes, S</dc:creator><dc:creator>Pétré, L</dc:creator><dc:creator>Postiau, N</dc:creator><dc:creator>Thomas, L</dc:creator><dc:creator>Bemden, M Vanden</dc:creator><dc:creator>Vander Velde, C</dc:creator><dc:creator>Vanlaer, P</dc:creator><dc:creator>Dobur, D</dc:creator><dc:creator>Knolle, J</dc:creator><dc:creator>Lambrecht, L</dc:creator><dc:creator>Mestdach, G</dc:creator><dc:creator>Rendón, C</dc:creator><dc:creator>Samalan, A</dc:creator><dc:creator>Skovpen, K</dc:creator><dc:creator>Tytgat, M</dc:creator><dc:creator>Van Den Bossche, N</dc:creator><dc:creator>Vermassen, B</dc:creator><dc:creator>Wezenbeek, L</dc:creator><dc:creator>Benecke, A</dc:creator><dc:creator>Bruno, G</dc:creator><dc:creator>Bury, F</dc:creator><dc:creator>Caputo, C</dc:creator><dc:creator>David, P</dc:creator><dc:creator>Delaere, C</dc:creator><dc:creator>Donertas, IS</dc:creator><dc:creator>Giammanco, A</dc:creator><dc:creator>Jaffel, K</dc:creator><dc:creator>Jain</dc:creator><dc:creator>Lemaitre, V</dc:creator><dc:creator>Mondal, K</dc:creator><dc:creator>Taliercio, A</dc:creator><dc:creator>Tran, TT</dc:creator><dc:creator>Vischia, P</dc:creator><dc:creator>Wertz, S</dc:creator><dc:creator>Alves, GA</dc:creator><dc:creator>Coelho, E</dc:creator><dc:creator>Hensel, C</dc:creator><dc:creator>Moraes, A</dc:creator><dc:creator>Teles, P Rebello</dc:creator><dc:creator>Júnior, WL Aldá</dc:creator><dc:creator>Pereira, M Alves Gallo</dc:creator><dc:creator>Filho, M Barroso Ferreira</dc:creator><dc:creator>Malbouisson, H Brandao</dc:creator><dc:creator>Carvalho, W</dc:creator><dc:creator>Chinellato, J</dc:creator><dc:creator>Da Costa, EM</dc:creator><dc:creator>Da Silveira, GG</dc:creator><dc:creator>De Jesus Damiao, D</dc:creator><dc:creator>Dos Santos Sousa, V</dc:creator><dc:creator>De Souza, S Fonseca</dc:creator><dc:date>2024-03-01</dc:date><dc:description>Measurements of the elliptic ( v 2 ) and triangular ( v 3 ) azimuthal anisotropy coefficients are presented for Image 1 mesons produced in Image 2 hadron decays (nonprompt Image 1 mesons) in lead-lead collisions at s NN = 5.02 TeV . The results are compared with previously published charm meson anisotropies measured using prompt Image 1 mesons. The data were collected with the CMS detector in 2018 with an integrated luminosity of 0.58 nb − 1 . Azimuthal anisotropy is sensitive to the interactions of quarks with the hot and dense medium created in heavy ion collisions. Comparing results for prompt and nonprompt Image 1 mesons can assist in understanding the mass dependence of these interactions. The nonprompt results show lower magnitudes of v 2 and v 3 and weaker dependences on the meson transverse momentum and collision centrality than those found for prompt Image 1 mesons. The results are in agreement with theoretical predictions that include a mass dependence in the interactions of quarks with the medium.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>CMS</dc:subject><dc:subject>Heavy ions</dc:subject><dc:subject>QPG</dc:subject><dc:subject>Flow</dc:subject><dc:subject>Heavy flavor</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7kw0g7vh</dc:identifier><dc:identifier>https://escholarship.org/content/qt7kw0g7vh/qt7kw0g7vh.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.physletb.2023.138389</dc:identifier><dc:type>article</dc:type><dc:source>Physics Letters B, vol 850</dc:source><dc:coverage>138389</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9hw4w5rg</identifier><datestamp>2026-09-16T00:48:56Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9hw4w5rg</dc:identifier><dc:title>Optimal 1D Ly α forest power spectrum estimation – III. DESI early data</dc:title><dc:creator>Karaçaylı, Naim Göksel</dc:creator><dc:creator>Martini, Paul</dc:creator><dc:creator>Guy, Julien</dc:creator><dc:creator>Ravoux, Corentin</dc:creator><dc:creator>Karim, Marie Lynn Abdul</dc:creator><dc:creator>Armengaud, Eric</dc:creator><dc:creator>Walther, Michael</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Bautista, J</dc:creator><dc:creator>Beltran, SF</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Cabayol-Garcia, L</dc:creator><dc:creator>Chabanier, S</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Cruz, R</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gonzalez-Morales, AX</dc:creator><dc:creator>Gordon, C</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Iršič, V</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Lukić, Z</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Napolitano, L</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Pieri, M</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Ramírez-Pérez, C</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sinigaglia, F</dc:creator><dc:creator>Tan, T</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Wang, B</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yéche, C</dc:creator><dc:creator>Zhou, Z</dc:creator><dc:date>2024-02-07</dc:date><dc:description>ABSTRACT The 1D power spectrum P1D of the Ly α forest provides important information about cosmological and astrophysical parameters, including constraints on warm dark matter models, the sum of the masses of the three neutrino species, and the thermal state of the intergalactic medium. We present the first measurement of P1D with the quadratic maximum likelihood estimator (QMLE) from the Dark Energy Spectroscopic Instrument (DESI) survey early data sample. This early sample of 54&amp;nbsp;600 quasars is already comparable in size to the largest previous studies, and we conduct a thorough investigation of numerous instrumental and analysis systematic errors to evaluate their impact on DESI data with QMLE. We demonstrate the excellent performance of the spectroscopic pipeline noise estimation and the impressive accuracy of the spectrograph resolution matrix with 2D image simulations of raw DESI images that we processed with the DESI spectroscopic pipeline. We also study metal line contamination and noise calibration systematics with quasar spectra on the red side of the Ly α emission line. In a companion paper, we present a similar analysis based on the Fast Fourier Transform estimate of the power spectrum. We conclude with a comparison of these two approaches and discuss the key sources of systematic error that we need to address with the upcoming DESI Year 1 analysis.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>methods: data analysis</dc:subject><dc:subject>intergalactic medium</dc:subject><dc:subject>quasars: absorption lines</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9hw4w5rg</dc:identifier><dc:identifier>https://escholarship.org/content/qt9hw4w5rg/qt9hw4w5rg.pdf</dc:identifier><dc:identifier>info:doi/10.1093/mnras/stae171</dc:identifier><dc:type>article</dc:type><dc:source>Monthly Notices of the Royal Astronomical Society, vol 528, iss 3</dc:source><dc:coverage>3941 - 3963</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt47p3g092</identifier><datestamp>2026-09-16T00:44:30Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt47p3g092</dc:identifier><dc:title>Bacterial population-level trade-offs between drought tolerance and resource acquisition traits impact decomposition</dc:title><dc:creator>Malik, Ashish A</dc:creator><dc:creator>Martiny, Jennifer BH</dc:creator><dc:creator>Ribeiro, Antonio</dc:creator><dc:creator>Sheridan, Paul O</dc:creator><dc:creator>Weihe, Claudia</dc:creator><dc:creator>Brodie, Eoin L</dc:creator><dc:creator>Allison, Steven D</dc:creator><dc:date>2024-01-08</dc:date><dc:description>Microbes drive fundamental ecosystem processes, such as decomposition. Environmental stressors are known to affect microbes, their fitness, and the ecosystem functions that they perform; yet, understanding the causal mechanisms behind this influence has been difficult. We used leaf litter on soil surface as a model in situ system to assess changes in bacterial genomic traits and decomposition rates for 18&amp;nbsp;months with drought as a stressor. We hypothesized that genome-scale trade-offs due to investment in stress tolerance traits under drought reduce the capacity for bacterial populations to carry out decomposition, and that these population-level trade-offs scale up to impact emergent community traits, thereby reducing decomposition rates. We observed drought tolerance mechanisms that were heightened in bacterial populations under drought, identified as higher gene copy numbers in metagenome-assembled genomes. A subset of populations under drought had reduced carbohydrate-active enzyme genes that suggested-as a trade-off-a decline in decomposition capabilities. These trade-offs were driven by community succession and taxonomic shifts as distinct patterns appeared in populations. We show that trait-trade-offs in bacterial populations under drought could scale up to reduce overall decomposition capabilities and litter decay rates. Using a trait-based approach to assess the population ecology of soil bacteria, we demonstrate genome-level trade-offs in response to drought with consequences for decomposition rates.</dc:description><dc:subject>4101 Climate Change Impacts and Adaptation (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Droughts (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Metagenome (mesh)</dc:subject><dc:subject>Stress</dc:subject><dc:subject>Physiological (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Drought Resistance (mesh)</dc:subject><dc:subject>bacteria</dc:subject><dc:subject>drought</dc:subject><dc:subject>genomics</dc:subject><dc:subject>litter decomposition</dc:subject><dc:subject>microbial traits</dc:subject><dc:subject>population ecology</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Stress</dc:subject><dc:subject>Physiological (mesh)</dc:subject><dc:subject>Droughts (mesh)</dc:subject><dc:subject>Metagenome (mesh)</dc:subject><dc:subject>Drought Resistance (mesh)</dc:subject><dc:subject>bacteria</dc:subject><dc:subject>drought</dc:subject><dc:subject>genomics</dc:subject><dc:subject>litter decomposition</dc:subject><dc:subject>microbial traits</dc:subject><dc:subject>population ecology</dc:subject><dc:subject>Droughts (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Metagenome (mesh)</dc:subject><dc:subject>Stress</dc:subject><dc:subject>Physiological (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Drought Resistance (mesh)</dc:subject><dc:subject>05 Environmental Sciences (for)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>10 Technology (for)</dc:subject><dc:subject>Microbiology (science-metrix)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>41 Environmental sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/47p3g092</dc:identifier><dc:identifier>https://escholarship.org/content/qt47p3g092/qt47p3g092.pdf</dc:identifier><dc:identifier>info:doi/10.1093/ismejo/wrae224</dc:identifier><dc:type>article</dc:type><dc:source>The ISME Journal: Multidisciplinary Journal of Microbial Ecology, vol 18, iss 1</dc:source><dc:coverage>wrae224</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8x36h534</identifier><datestamp>2026-09-16T00:44:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8x36h534</dc:identifier><dc:title>A computational model predicts sex-specific responses to calcium channel blockers in mammalian mesenteric vascular smooth muscle</dc:title><dc:creator>Hernandez-Hernandez, Gonzalo</dc:creator><dc:creator>O'Dwyer, Samantha C</dc:creator><dc:creator>Yang, Pei-Chi</dc:creator><dc:creator>Matsumoto, Collin</dc:creator><dc:creator>Tieu, Mindy</dc:creator><dc:creator>Fong, Zhihui</dc:creator><dc:creator>Lewis, Timothy J</dc:creator><dc:creator>Santana, L Fernando</dc:creator><dc:creator>Clancy, Colleen E</dc:creator><dc:date>2024-02-09</dc:date><dc:description>The function of the smooth muscle cells lining the walls of mammalian systemic arteries and arterioles is to regulate the diameter of the vessels to control blood flow and blood pressure. Here, we describe an in silico model, which we call the 'Hernandez-Hernandez model', of electrical and Ca2+ signaling in arterial myocytes based on new experimental data indicating sex-specific differences in male and female arterial myocytes from murine resistance arteries. The model suggests the fundamental ionic mechanisms underlying membrane potential and intracellular Ca2+ signaling during the development of myogenic tone in arterial blood vessels. Although experimental data suggest that KV1.5 channel currents have similar amplitudes, kinetics, and voltage dependencies in male and female myocytes, simulations suggest that the KV1.5 current is the dominant current regulating membrane potential in male myocytes. In female cells, which have larger KV2.1 channel expression and longer time constants for activation than male myocytes, predictions from simulated female myocytes suggest that KV2.1 plays a primary role in the control of membrane potential. Over the physiological range of membrane potentials, the gating of a small number of voltage-gated K+ channels and L-type Ca2+ channels are predicted to drive sex-specific differences in intracellular Ca2+ and excitability. We also show that in an idealized computational model of a vessel, female arterial smooth muscle exhibits heightened sensitivity to commonly used Ca2+ channel blockers compared to male. In summary, we present a new model framework to investigate the potential sex-specific impact of antihypertensive drugs.</dc:description><dc:subject>3208 Medical Physiology (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>Cardiovascular (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Hypertension (rcdc)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>1.1 Normal biological development and functioning (hrcs-rac)</dc:subject><dc:subject>Cardiovascular (hrcs-hc)</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Calcium Channel Blockers (mesh)</dc:subject><dc:subject>Muscle</dc:subject><dc:subject>Smooth</dc:subject><dc:subject>Vascular (mesh)</dc:subject><dc:subject>Arteries (mesh)</dc:subject><dc:subject>Blood Pressure (mesh)</dc:subject><dc:subject>Potassium Channels</dc:subject><dc:subject>Voltage-Gated (mesh)</dc:subject><dc:subject>Calcium (mesh)</dc:subject><dc:subject>Mammals (mesh)</dc:subject><dc:subject>computer model</dc:subject><dc:subject>digital twin</dc:subject><dc:subject>simulation</dc:subject><dc:subject>hypertension</dc:subject><dc:subject>sex differences</dc:subject><dc:subject>Mouse</dc:subject><dc:subject>Muscle</dc:subject><dc:subject>Smooth</dc:subject><dc:subject>Vascular (mesh)</dc:subject><dc:subject>Arteries (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Mammals (mesh)</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>Calcium (mesh)</dc:subject><dc:subject>Potassium Channels</dc:subject><dc:subject>Voltage-Gated (mesh)</dc:subject><dc:subject>Calcium Channel Blockers (mesh)</dc:subject><dc:subject>Blood Pressure (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>computational biology</dc:subject><dc:subject>computer model</dc:subject><dc:subject>digital twin</dc:subject><dc:subject>hypertension</dc:subject><dc:subject>medicine</dc:subject><dc:subject>mouse</dc:subject><dc:subject>sex differences</dc:subject><dc:subject>simulation</dc:subject><dc:subject>systems biology</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Calcium Channel Blockers (mesh)</dc:subject><dc:subject>Muscle</dc:subject><dc:subject>Smooth</dc:subject><dc:subject>Vascular (mesh)</dc:subject><dc:subject>Arteries (mesh)</dc:subject><dc:subject>Blood Pressure (mesh)</dc:subject><dc:subject>Potassium Channels</dc:subject><dc:subject>Voltage-Gated (mesh)</dc:subject><dc:subject>Calcium (mesh)</dc:subject><dc:subject>Mammals (mesh)</dc:subject><dc:subject>0601 Biochemistry and Cell Biology (for)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:subject>42 Health sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8x36h534</dc:identifier><dc:identifier>https://escholarship.org/content/qt8x36h534/qt8x36h534.pdf</dc:identifier><dc:identifier>info:doi/10.7554/elife.90604</dc:identifier><dc:type>article</dc:type><dc:source>ELIFE, vol 12</dc:source><dc:coverage>rp90604</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8sq3n3c6</identifier><datestamp>2026-09-16T00:44:05Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8sq3n3c6</dc:identifier><dc:title>Search for new Higgs bosons via same-sign top quark pair production in association with a jet in proton-proton collisions at s = 13 TeV</dc:title><dc:creator>Hayrapetyan, A</dc:creator><dc:creator>Tumasyan, A</dc:creator><dc:creator>Adam, W</dc:creator><dc:creator>Andrejkovic, JW</dc:creator><dc:creator>Bergauer, T</dc:creator><dc:creator>Chatterjee, S</dc:creator><dc:creator>Damanakis, K</dc:creator><dc:creator>Dragicevic, M</dc:creator><dc:creator>Hussain, PS</dc:creator><dc:creator>Jeitler, M</dc:creator><dc:creator>Krammer, N</dc:creator><dc:creator>Li, A</dc:creator><dc:creator>Liko, D</dc:creator><dc:creator>Mikulec, I</dc:creator><dc:creator>Schieck, J</dc:creator><dc:creator>Schöfbeck, R</dc:creator><dc:creator>Schwarz, D</dc:creator><dc:creator>Sonawane, M</dc:creator><dc:creator>Templ, S</dc:creator><dc:creator>Waltenberger, W</dc:creator><dc:creator>Wulz, C-E</dc:creator><dc:creator>Darwish, MR</dc:creator><dc:creator>Janssen, T</dc:creator><dc:creator>Van Mechelen, P</dc:creator><dc:creator>Bols, ES</dc:creator><dc:creator>D'Hondt, J</dc:creator><dc:creator>Dansana, S</dc:creator><dc:creator>De Moor, A</dc:creator><dc:creator>Delcourt, M</dc:creator><dc:creator>Faham, H El</dc:creator><dc:creator>Lowette, S</dc:creator><dc:creator>Makarenko, I</dc:creator><dc:creator>Müller, D</dc:creator><dc:creator>Sahasransu, AR</dc:creator><dc:creator>Tavernier, S</dc:creator><dc:creator>Tytgat, M</dc:creator><dc:creator>Van Putte, S</dc:creator><dc:creator>Vannerom, D</dc:creator><dc:creator>Clerbaux, B</dc:creator><dc:creator>De Lentdecker, G</dc:creator><dc:creator>Favart, L</dc:creator><dc:creator>Hohov, D</dc:creator><dc:creator>Jaramillo, J</dc:creator><dc:creator>Khalilzadeh, A</dc:creator><dc:creator>Lee, K</dc:creator><dc:creator>Mahdavikhorrami, M</dc:creator><dc:creator>Malara, A</dc:creator><dc:creator>Paredes, S</dc:creator><dc:creator>Pétré, L</dc:creator><dc:creator>Postiau, N</dc:creator><dc:creator>Thomas, L</dc:creator><dc:creator>Bemden, M Vanden</dc:creator><dc:creator>Vander Velde, C</dc:creator><dc:creator>Vanlaer, P</dc:creator><dc:creator>De Coen, M</dc:creator><dc:creator>Dobur, D</dc:creator><dc:creator>Hong, Y</dc:creator><dc:creator>Knolle, J</dc:creator><dc:creator>Lambrecht, L</dc:creator><dc:creator>Mestdach, G</dc:creator><dc:creator>Rendón, C</dc:creator><dc:creator>Samalan, A</dc:creator><dc:creator>Skovpen, K</dc:creator><dc:creator>Van Den Bossche, N</dc:creator><dc:creator>van der Linden, J</dc:creator><dc:creator>Wezenbeek, L</dc:creator><dc:creator>Benecke, A</dc:creator><dc:creator>Bruno, G</dc:creator><dc:creator>Caputo, C</dc:creator><dc:creator>Delaere, C</dc:creator><dc:creator>Donertas, IS</dc:creator><dc:creator>Giammanco, A</dc:creator><dc:creator>Jaffel, K</dc:creator><dc:creator>Jain</dc:creator><dc:creator>Lemaitre, V</dc:creator><dc:creator>Lidrych, J</dc:creator><dc:creator>Mastrapasqua, P</dc:creator><dc:creator>Mondal, K</dc:creator><dc:creator>Tran, TT</dc:creator><dc:creator>Wertz, S</dc:creator><dc:creator>Alves, GA</dc:creator><dc:creator>Coelho, E</dc:creator><dc:creator>Hensel, C</dc:creator><dc:creator>De Oliveira, T Menezes</dc:creator><dc:creator>Moraes, A</dc:creator><dc:creator>Teles, P Rebello</dc:creator><dc:creator>Soeiro, M</dc:creator><dc:creator>Júnior, WL Aldá</dc:creator><dc:creator>Pereira, M Alves Gallo</dc:creator><dc:creator>Filho, M Barroso Ferreira</dc:creator><dc:creator>Malbouisson, H Brandao</dc:creator><dc:creator>Carvalho, W</dc:creator><dc:creator>Chinellato, J</dc:creator><dc:creator>Da Costa, EM</dc:creator><dc:creator>Da Silveira, GG</dc:creator><dc:creator>De Jesus Damiao, D</dc:creator><dc:creator>De Souza, S Fonseca</dc:creator><dc:creator>Martins, J</dc:creator><dc:creator>Herrera, C Mora</dc:creator><dc:creator>Amarilo, K Mota</dc:creator><dc:date>2024-03-01</dc:date><dc:description>A search is presented for new Higgs bosons in proton-proton (pp) collision events in which a same-sign top quark pair is produced in association with a jet, via the p p → t H / A → t t c ‾ and p p → t H / A → t t u ‾ processes. Here, H and A represent the extra scalar and pseudoscalar boson, respectively, of the second Higgs doublet in the generalized two-Higgs-doublet model (g2HDM). The search is based on pp collision data collected at a center-of-mass energy of 13 TeV with the CMS detector at the LHC, corresponding to an integrated luminosity of 138fb−1. Final states with a same-sign lepton pair in association with jets and missing transverse momentum are considered. New Higgs bosons in the 200–1000 GeV mass range and new Yukawa couplings between 0.1 and 1.0 are targeted in the search, for scenarios in which either H or A appear alone, or in which they coexist and interfere. No significant excess above the standard model prediction is observed. Exclusion limits are derived in the context of the g2HDM.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>CMS</dc:subject><dc:subject>Top quarks</dc:subject><dc:subject>Extra Higgs boson</dc:subject><dc:subject>Yukawa couplings</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8sq3n3c6</dc:identifier><dc:identifier>https://escholarship.org/content/qt8sq3n3c6/qt8sq3n3c6.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.physletb.2024.138478</dc:identifier><dc:type>article</dc:type><dc:source>Physics Letters B, vol 850</dc:source><dc:coverage>138478</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt06q3q7sx</identifier><datestamp>2026-09-16T00:43:55Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt06q3q7sx</dc:identifier><dc:title>Predictions of rhizosphere microbiome dynamics with a genome-informed and trait-based energy budget model</dc:title><dc:creator>Marschmann, Gianna L</dc:creator><dc:creator>Tang, Jinyun</dc:creator><dc:creator>Zhalnina, Kateryna</dc:creator><dc:creator>Karaoz, Ulas</dc:creator><dc:creator>Cho, Heejung</dc:creator><dc:creator>Le, Beatrice</dc:creator><dc:creator>Pett-Ridge, Jennifer</dc:creator><dc:creator>Brodie, Eoin L</dc:creator><dc:date>2024-02-01</dc:date><dc:description>Soil microbiomes are highly diverse, and to improve their representation in biogeochemical models, microbial genome data can be leveraged to infer key functional traits. By integrating genome-inferred traits into a theory-based hierarchical framework, emergent behaviour arising from interactions of individual traits can be predicted. Here we combine theory-driven predictions of substrate uptake kinetics with a genome-informed trait-based dynamic energy budget model to predict emergent life-history traits and trade-offs in soil bacteria. When applied to a plant microbiome system, the model accurately predicted distinct substrate-acquisition strategies that aligned with observations, uncovering resource-dependent trade-offs between microbial growth rate and efficiency. For instance, inherently slower-growing microorganisms, favoured by organic acid exudation at later plant growth stages, exhibited enhanced carbon use efficiency (yield) without sacrificing growth rate (power). This insight has implications for retaining plant root-derived carbon in soils and highlights the power of data-driven, trait-based approaches for improving microbial representation in biogeochemical models.</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>Microbiome (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>14 Life Below Water (sdg)</dc:subject><dc:subject>Rhizosphere (mesh)</dc:subject><dc:subject>Plant Roots (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Plants (mesh)</dc:subject><dc:subject>Carbon (mesh)</dc:subject><dc:subject>Plants (mesh)</dc:subject><dc:subject>Plant Roots (mesh)</dc:subject><dc:subject>Carbon (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Rhizosphere (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Rhizosphere (mesh)</dc:subject><dc:subject>Plant Roots (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Plants (mesh)</dc:subject><dc:subject>Carbon (mesh)</dc:subject><dc:subject>0605 Microbiology (for)</dc:subject><dc:subject>1108 Medical Microbiology (for)</dc:subject><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/06q3q7sx</dc:identifier><dc:identifier>https://escholarship.org/content/qt06q3q7sx/qt06q3q7sx.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41564-023-01582-w</dc:identifier><dc:type>article</dc:type><dc:source>Nature Microbiology, vol 9, iss 2</dc:source><dc:coverage>421 - 433</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4278p9c3</identifier><datestamp>2026-09-16T00:40:52Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4278p9c3</dc:identifier><dc:title>Historical Redlining Is Associated with Disparities in Environmental Quality across California</dc:title><dc:creator>Estien, Cesar O</dc:creator><dc:creator>Wilkinson, Christine E</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Schell, Christopher J</dc:creator><dc:date>2024-02-13</dc:date><dc:description>Historical policies have been shown to underpin environmental quality. In the 1930s, the federal Home Owners' Loan Corporation (HOLC) developed the most comprehensive archive of neighborhoods that would have been redlined by local lenders and the Federal Housing Administration, often applying racist criteria. Our study explored how redlining is associated with environmental quality across eight California cities. We integrated HOLC's graded maps [grades A (i.e., "best" and "greenlined"), B, C, and D (i.e., "hazardous" and "redlined")] with 10 environmental hazards using data from 2018 to 2021 to quantify the spatial overlap among redlined neighborhoods and environmental hazards. We found that formerly redlined neighborhoods have poorer environmental quality relative to those of other HOLC grades via higher pollution, more noise, less vegetation, and elevated temperatures. Additionally, we found that intraurban disparities were consistently worse for formerly redlined neighborhoods across environmental hazards, with redlined neighborhoods having higher pollution burdens (77% of redlined neighborhoods vs 18% of greenlined neighborhoods), more noise (72% vs 18%), less vegetation (86% vs 12%), and elevated temperature (72% vs 20%), than their respective city's average. Our findings highlight that redlining, a policy abolished in 1968, remains an environmental justice concern by shaping the environmental quality of Californian urban neighborhoods.</dc:description><dc:subject>4004 Chemical Engineering (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>4105 Pollution and Contamination (for-2020)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>environmental justice</dc:subject><dc:subject>pollution</dc:subject><dc:subject>noise</dc:subject><dc:subject>inequity</dc:subject><dc:subject>redlining</dc:subject><dc:subject>CalEnviroScreen</dc:subject><dc:subject>0502 Environmental Science and Management (for)</dc:subject><dc:subject>0907 Environmental Engineering (for)</dc:subject><dc:subject>1002 Environmental Biotechnology (for)</dc:subject><dc:subject>4004 Chemical engineering (for-2020)</dc:subject><dc:subject>4105 Pollution and contamination (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4278p9c3</dc:identifier><dc:identifier>https://escholarship.org/content/qt4278p9c3/qt4278p9c3.pdf</dc:identifier><dc:identifier>info:doi/10.1021/acs.estlett.3c00870</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Science &amp; Technology Letters, vol 11, iss 2</dc:source><dc:coverage>54 - 59</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3cq0b6g2</identifier><datestamp>2026-09-16T00:36:38Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3cq0b6g2</dc:identifier><dc:title>Associations of Organophosphate Ester Flame Retardant Exposures during Pregnancy with Gestational Duration and Fetal Growth: The Environmental influences on Child Health Outcomes (ECHO) Program</dc:title><dc:creator>Oh, Jiwon</dc:creator><dc:creator>Buckley, Jessie P</dc:creator><dc:creator>Li, Xuan</dc:creator><dc:creator>Gachigi, Kennedy K</dc:creator><dc:creator>Kannan, Kurunthachalam</dc:creator><dc:creator>Lyu, Wenjie</dc:creator><dc:creator>Ames, Jennifer L</dc:creator><dc:creator>Barrett, Emily S</dc:creator><dc:creator>Bastain, Theresa M</dc:creator><dc:creator>Breton, Carrie V</dc:creator><dc:creator>Buss, Claudia</dc:creator><dc:creator>Croen, Lisa A</dc:creator><dc:creator>Dunlop, Anne L</dc:creator><dc:creator>Ferrara, Assiamira</dc:creator><dc:creator>Ghassabian, Akhgar</dc:creator><dc:creator>Herbstman, Julie B</dc:creator><dc:creator>Hernandez-Castro, Ixel</dc:creator><dc:creator>Hertz-Picciotto, Irva</dc:creator><dc:creator>Kahn, Linda G</dc:creator><dc:creator>Karagas, Margaret R</dc:creator><dc:creator>Kuiper, Jordan R</dc:creator><dc:creator>McEvoy, Cindy T</dc:creator><dc:creator>Meeker, John D</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Padula, Amy M</dc:creator><dc:creator>Romano, Megan E</dc:creator><dc:creator>Sathyanarayana, Sheela</dc:creator><dc:creator>Schantz, Susan</dc:creator><dc:creator>Schmidt, Rebecca J</dc:creator><dc:creator>Simhan, Hyagriv</dc:creator><dc:creator>Starling, Anne P</dc:creator><dc:creator>Tylavsky, Frances A</dc:creator><dc:creator>Volk, Heather E</dc:creator><dc:creator>Woodruff, Tracey J</dc:creator><dc:creator>Zhu, Yeyi</dc:creator><dc:creator>Bennett, Deborah H</dc:creator><dc:creator>Outcomes, program collaborators for Environmental influences on Child Health</dc:creator><dc:date>2024-01-01</dc:date><dc:description>BACKGROUND: Widespread exposure to organophosphate ester (OPE) flame retardants with potential reproductive toxicity raises concern regarding the impacts of gestational exposure on birth outcomes. Previous studies of prenatal OPE exposure and birth outcomes had limited sample sizes, with inconclusive results.
OBJECTIVES: We conducted a collaborative analysis of associations between gestational OPE exposures and adverse birth outcomes and tested whether associations were modified by sex.
METHODS: We included 6,646 pregnant participants from 16 cohorts in the Environmental influences on Child Health Outcomes (ECHO) Program. Nine OPE biomarkers were quantified in maternal urine samples collected primarily during the second and third trimester and modeled as -transformed continuous, categorized (high/low/nondetect), or dichotomous (detect/nondetect) variables depending on detection frequency. We used covariate-adjusted linear, logistic, and multinomial regression with generalized estimating equations, accounting for cohort-level clustering, to estimate associations of OPE biomarkers with gestational length and birth weight outcomes. Secondarily, we assessed effect modification by sex.
RESULTS: Three OPE biomarkers [diphenyl phosphate (DPHP), a composite of dibutyl phosphate and di-isobutyl phosphate (DBUP/DIBP), and bis(1,3-dichloro-2-propyl) phosphate] were detected in  of participants. In adjusted models, DBUP/DIBP [odds ratio (OR) per ; 95% confidence interval (CI): 1.02, 1.12] and bis(butoxyethyl) phosphate (OR for high vs. ; 95% CI: 1.06, 1.46), but not other OPE biomarkers, were associated with higher odds of preterm birth. We observed effect modification by sex for associations of DPHP and high bis(2-chloroethyl) phosphate with completed gestational weeks and odds of preterm birth, with adverse associations among females. In addition, newborns of mothers with detectable bis(1-chloro-2-propyl) phosphate, bis(2-methylphenyl) phosphate, and dipropyl phosphate had higher birth weight-for-gestational-age -scores ( for detect vs. ); other chemicals showed null associations.
DISCUSSION: In the largest study to date, we find gestational exposures to several OPEs are associated with earlier timing of birth, especially among female neonates, or with greater fetal growth. https://doi.org/10.1289/EHP13182.</dc:description><dc:subject>3215 Reproductive Medicine (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Pregnancy (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Perinatal Period - Conditions Originating in Perinatal Period (rcdc)</dc:subject><dc:subject>Contraception/Reproduction (rcdc)</dc:subject><dc:subject>Maternal Health (rcdc)</dc:subject><dc:subject>Infant Mortality (rcdc)</dc:subject><dc:subject>Conditions Affecting the Embryonic and Fetal Periods (rcdc)</dc:subject><dc:subject>Endocrine Disruptors (rcdc)</dc:subject><dc:subject>Reproductive health and childbirth (hrcs-hc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Flame Retardants (mesh)</dc:subject><dc:subject>Birth Weight (mesh)</dc:subject><dc:subject>Premature Birth (mesh)</dc:subject><dc:subject>Phosphates (mesh)</dc:subject><dc:subject>Fetal Development (mesh)</dc:subject><dc:subject>Organophosphates (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:subject>Outcome Assessment</dc:subject><dc:subject>Health Care (mesh)</dc:subject><dc:subject>Esters (mesh)</dc:subject><dc:subject>Biphenyl Compounds (mesh)</dc:subject><dc:subject>program collaborators for Environmental influences on Child Health Outcomes</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Premature Birth (mesh)</dc:subject><dc:subject>Birth Weight (mesh)</dc:subject><dc:subject>Phosphates (mesh)</dc:subject><dc:subject>Esters (mesh)</dc:subject><dc:subject>Biphenyl Compounds (mesh)</dc:subject><dc:subject>Flame Retardants (mesh)</dc:subject><dc:subject>Fetal Development (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Organophosphates (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:subject>Outcome Assessment</dc:subject><dc:subject>Health Care (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Flame Retardants (mesh)</dc:subject><dc:subject>Birth Weight (mesh)</dc:subject><dc:subject>Premature Birth (mesh)</dc:subject><dc:subject>Phosphates (mesh)</dc:subject><dc:subject>Fetal Development (mesh)</dc:subject><dc:subject>Organophosphates (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:subject>Outcome Assessment</dc:subject><dc:subject>Health Care (mesh)</dc:subject><dc:subject>Esters (mesh)</dc:subject><dc:subject>Biphenyl Compounds (mesh)</dc:subject><dc:subject>05 Environmental Sciences (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>Toxicology (science-metrix)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:subject>41 Environmental sciences (for-2020)</dc:subject><dc:subject>42 Health sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>https://creativecommons.org/publicdomain/zero/1.0/</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3cq0b6g2</dc:identifier><dc:identifier>https://escholarship.org/content/qt3cq0b6g2/qt3cq0b6g2.pdf</dc:identifier><dc:identifier>info:doi/10.1289/ehp13182</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Health Perspectives, vol 132, iss 1</dc:source><dc:coverage>017004</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3q517872</identifier><datestamp>2026-09-16T00:35:59Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3q517872</dc:identifier><dc:title>Demonstration of cooling by the Muon Ionization Cooling Experiment</dc:title><dc:creator>Bogomilov, M</dc:creator><dc:creator>Tsenov, R</dc:creator><dc:creator>Vankova-Kirilova, G</dc:creator><dc:creator>Song, YP</dc:creator><dc:creator>Tang, JY</dc:creator><dc:creator>Li, ZH</dc:creator><dc:creator>Bertoni, R</dc:creator><dc:creator>Bonesini, M</dc:creator><dc:creator>Chignoli, F</dc:creator><dc:creator>Mazza, R</dc:creator><dc:creator>Palladino, V</dc:creator><dc:creator>de Bari, A</dc:creator><dc:creator>Orestano, D</dc:creator><dc:creator>Tortora, L</dc:creator><dc:creator>Kuno, Y</dc:creator><dc:creator>Sakamoto, H</dc:creator><dc:creator>Sato, A</dc:creator><dc:creator>Ishimoto, S</dc:creator><dc:creator>Chung, M</dc:creator><dc:creator>Sung, CK</dc:creator><dc:creator>Filthaut, F</dc:creator><dc:creator>Jokovic, D</dc:creator><dc:creator>Maletic, D</dc:creator><dc:creator>Savic, M</dc:creator><dc:creator>Jovancevic, N</dc:creator><dc:creator>Nikolov, J</dc:creator><dc:creator>Vretenar, M</dc:creator><dc:creator>Ramberger, S</dc:creator><dc:creator>Asfandiyarov, R</dc:creator><dc:creator>Blondel, A</dc:creator><dc:creator>Drielsma, F</dc:creator><dc:creator>Karadzhov, Y</dc:creator><dc:creator>Boyd, S</dc:creator><dc:creator>Greis, JR</dc:creator><dc:creator>Lord, T</dc:creator><dc:creator>Pidcott, C</dc:creator><dc:creator>Taylor, I</dc:creator><dc:creator>Charnley, G</dc:creator><dc:creator>Collomb, N</dc:creator><dc:creator>Dumbell, K</dc:creator><dc:creator>Gallagher, A</dc:creator><dc:creator>Grant, A</dc:creator><dc:creator>Griffiths, S</dc:creator><dc:creator>Hartnett, T</dc:creator><dc:creator>Martlew, B</dc:creator><dc:creator>Moss, A</dc:creator><dc:creator>Muir, A</dc:creator><dc:creator>Mullacrane, I</dc:creator><dc:creator>Oates, A</dc:creator><dc:creator>Owens, P</dc:creator><dc:creator>Stokes, G</dc:creator><dc:creator>Warburton, P</dc:creator><dc:creator>White, C</dc:creator><dc:creator>Adams, D</dc:creator><dc:creator>Bayliss, V</dc:creator><dc:creator>Boehm, J</dc:creator><dc:creator>Bradshaw, TW</dc:creator><dc:creator>Brown, C</dc:creator><dc:creator>Courthold, M</dc:creator><dc:creator>Govans, J</dc:creator><dc:creator>Hills, M</dc:creator><dc:creator>Lagrange, J-B</dc:creator><dc:creator>Macwaters, C</dc:creator><dc:creator>Nichols, A</dc:creator><dc:creator>Preece, R</dc:creator><dc:creator>Ricciardi, S</dc:creator><dc:creator>Rogers, C</dc:creator><dc:creator>Stanley, T</dc:creator><dc:creator>Tarrant, J</dc:creator><dc:creator>Tucker, M</dc:creator><dc:creator>Watson, S</dc:creator><dc:creator>Wilson, A</dc:creator><dc:creator>Bayes, R</dc:creator><dc:creator>Nugent, JC</dc:creator><dc:creator>Soler, FJP</dc:creator><dc:creator>Chatzitheodoridis, GT</dc:creator><dc:creator>Dick, AJ</dc:creator><dc:creator>Ronald, K</dc:creator><dc:creator>Whyte, CG</dc:creator><dc:creator>Young, AR</dc:creator><dc:creator>Gamet, R</dc:creator><dc:creator>Cooke, P</dc:creator><dc:creator>Blackmore, VJ</dc:creator><dc:creator>Colling, D</dc:creator><dc:creator>Dobbs, A</dc:creator><dc:creator>Dornan, P</dc:creator><dc:creator>Franchini, P</dc:creator><dc:creator>Hunt, C</dc:creator><dc:creator>Jurj, PB</dc:creator><dc:creator>Kurup, A</dc:creator><dc:creator>Long, K</dc:creator><dc:creator>Martyniak, J</dc:creator><dc:creator>Middleton, S</dc:creator><dc:creator>Pasternak, J</dc:creator><dc:creator>Uchida, MA</dc:creator><dc:creator>Cobb, JH</dc:creator><dc:creator>Booth, CN</dc:creator><dc:creator>Hodgson, P</dc:creator><dc:creator>Langlands, J</dc:creator><dc:creator>Overton, E</dc:creator><dc:date>2020-02-06</dc:date><dc:description>The use of accelerated beams of electrons, protons or ions has furthered the development of nearly every scientific discipline. However, high-energy muon beams of equivalent quality have not yet been delivered. Muon beams can be created through the decay of pions produced by the interaction of a proton beam with a target. Such ‘tertiary’ beams have much lower brightness than those created by accelerating electrons, protons or ions. High-brightness muon beams comparable to those produced by state-of-the-art electron, proton and ion accelerators could facilitate the study of lepton–antilepton collisions at extremely high energies and provide well characterized neutrino beams1–6. Such muon beams could be realized using ionization cooling, which has been proposed to increase muon-beam brightness7,8. Here we report the realization of ionization cooling, which was confirmed by the observation of an increased number of low-amplitude muons after passage of the muon beam through an absorber, as well as an increase in the corresponding phase-space density. The simulated performance of the ionization cooling system is consistent with the measured data, validating designs of the ionization cooling channel in which the cooling process is repeated to produce a substantial cooling effect9–11. The results presented here are an important step towards achieving the muon-beam quality required to search for phenomena at energy scales beyond the reach of the Large Hadron Collider at a facility of equivalent or reduced footprint6.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>MICE collaboration</dc:subject><dc:subject>ATAP-2020 (c-lbnl-label)</dc:subject><dc:subject>ATAP-GENERAL (c-lbnl-label)</dc:subject><dc:subject>ATAP-BACI (c-lbnl-label)</dc:subject><dc:subject>General Science &amp; Technology (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3q517872</dc:identifier><dc:identifier>https://escholarship.org/content/qt3q517872/qt3q517872.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41586-020-1958-9</dc:identifier><dc:type>article</dc:type><dc:source>Nature, vol 578, iss 7793</dc:source><dc:coverage>53 - 59</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0164f9r6</identifier><datestamp>2026-09-16T00:32:29Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0164f9r6</dc:identifier><dc:title>Foreword</dc:title><dc:creator>Cooper, Cary</dc:creator><dc:creator>Pearce, Jone L</dc:creator><dc:contributor>Brief, Arthur P</dc:contributor><dc:date>2008-04-24</dc:date><dc:description>We are pleased to introduce Art Brief's Diversity at Work, as part of the Cambridge Companions to Management series. The series is intended to advance knowledge in the fields of management by presenting the latest scholarship and research on topics of growing importance. Bridging the gap between journal articles and student textbooks, the volumes offer in-depth treatment of selected management topics, exploring the current knowledge base and identifying future opportunities for research. Each topic covered in the series is one with great future promise, and one that also has developed a sufficient body of research to allow informed reviews and debate. Management scholarship is increasingly international in scope. No longer can scholars read only the work conducted in their own countries, or talk only to their near neighbors. Creative and innovative work in management is now being conducted throughout the world. Each volume is organized by one of our most prominent scholars who brings researchers from several countries together to provide cross-national perspectives and debate. Through this series we hope to introduce readers to scholarship in their field they may not yet know, and open scholarship debate to a wider set of perspectives. We feel fortunate to be working with Cambridge University Press. Their rigorous independent scholarly reviews and board approval process helps ensure that only the highest-quality scholarship is published. We feel confident that scholars will find these books useful to their own research programs, as well as in their doctoral courses.</dc:description><dc:subject>46 Information and Computing Sciences (for-2020)</dc:subject><dc:subject>3602 Creative and Professional Writing (for-2020)</dc:subject><dc:subject>36 Creative Arts and Writing (for-2020)</dc:subject><dc:subject>Diversity in the workplace</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0164f9r6</dc:identifier><dc:identifier>https://escholarship.org/content/qt0164f9r6/qt0164f9r6.pdf</dc:identifier><dc:identifier>info:doi/10.1017/cbo9780511753725.001</dc:identifier><dc:type>monograph</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3jj568gj</identifier><datestamp>2026-09-16T00:32:04Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3jj568gj</dc:identifier><dc:title>Feeding-Related Gut Microbial Composition Associates With Peripheral T-Cell Activation and Mucosal Gene Expression in African Infants</dc:title><dc:creator>Wood, Lianna F</dc:creator><dc:creator>Brown, Bryan P</dc:creator><dc:creator>Lennard, Katie</dc:creator><dc:creator>Karaoz, Ulas</dc:creator><dc:creator>Havyarimana, Enock</dc:creator><dc:creator>Passmore, Jo-Ann S</dc:creator><dc:creator>Hesseling, Anneke C</dc:creator><dc:creator>Edlefsen, Paul T</dc:creator><dc:creator>Kuhn, Louise</dc:creator><dc:creator>Mulder, Nicola</dc:creator><dc:creator>Brodie, Eoin L</dc:creator><dc:creator>Sodora, Donald L</dc:creator><dc:creator>Jaspan, Heather B</dc:creator><dc:date>2018-09-28</dc:date><dc:description>Background: Exclusive breastfeeding reduces the rate of postnatal human immunodeficiency virus (HIV) transmission compared to nonexclusive breastfeeding; however, the mechanisms of this protection are unknown. Our study aimed to interrogate the mechanisms underlying the protective effect of exclusive breastfeeding.
Methods: We performed a prospective, longitudinal study of infants from a high-HIV-prevalence, low-income setting in South Africa. We evaluated the role of any non-breast milk feeds, excluding prescribed medicines on stool microbial communities via 16S rRNA gene sequencing, peripheral T-cell activation via flow cytometry, and buccal mucosal gene expression via quantitative polymerase chain reaction assay.
Results: A total of 155 infants were recruited at birth with mean gestational age of 38.9 weeks and mean birth weight of 3.2 kg. All infants were exclusively breastfed (EBF) at birth, but only 43.5% and 20% remained EBF at 6 or 14 weeks of age, respectively. We observed lower stool microbial diversity and distinct microbial composition in exclusively breastfed infants. These microbial communities, and the relative abundance of key taxa, were correlated with peripheral CD4+ T-cell activation, which was lower in EBF infants. In the oral mucosa, gene expression of chemokine and chemokine receptors involved in recruitment of HIV target cells to tissues, as well as epithelial cytoskeletal proteins, was lower in EBF infants.
Conclusions: These data suggest that nonexclusive breastfeeding alters the gut microbiota, increasing T-cell activation and, potentially, mucosal recruitment of HIV target cells. Study findings highlight a biologically plausible mechanistic explanation for the reduced postnatal HIV transmission observed in EBF infants.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>Minority Health (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Microbiome (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>HIV/AIDS (rcdc)</dc:subject><dc:subject>Infant Mortality (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Perinatal Period - Conditions Originating in Perinatal Period (rcdc)</dc:subject><dc:subject>Nutrition (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Infectious Diseases (rcdc)</dc:subject><dc:subject>Breastfeeding</dc:subject><dc:subject>Lactation and Breast Milk (rcdc)</dc:subject><dc:subject>Pediatric AIDS (rcdc)</dc:subject><dc:subject>Reproductive health and childbirth (hrcs-hc)</dc:subject><dc:subject>Infection (hrcs-hc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Breast Feeding (mesh)</dc:subject><dc:subject>CD4-Positive T-Lymphocytes (mesh)</dc:subject><dc:subject>Chemokines (mesh)</dc:subject><dc:subject>Feces (mesh)</dc:subject><dc:subject>Gastrointestinal Microbiome (mesh)</dc:subject><dc:subject>Gene Expression (mesh)</dc:subject><dc:subject>HIV Infections (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Infant (mesh)</dc:subject><dc:subject>Infectious Disease Transmission</dc:subject><dc:subject>Vertical (mesh)</dc:subject><dc:subject>Longitudinal Studies (mesh)</dc:subject><dc:subject>Lymphocyte Activation (mesh)</dc:subject><dc:subject>Mouth Mucosa (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>RNA</dc:subject><dc:subject>Ribosomal</dc:subject><dc:subject>16S (mesh)</dc:subject><dc:subject>Receptors</dc:subject><dc:subject>Chemokine (mesh)</dc:subject><dc:subject>South Africa (mesh)</dc:subject><dc:subject>exclusive breastfeeding</dc:subject><dc:subject>gut microbiota</dc:subject><dc:subject>immune activation</dc:subject><dc:subject>HIV susceptibility</dc:subject><dc:subject>Mouth Mucosa (mesh)</dc:subject><dc:subject>CD4-Positive T-Lymphocytes (mesh)</dc:subject><dc:subject>Feces (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>HIV Infections (mesh)</dc:subject><dc:subject>Receptors</dc:subject><dc:subject>Chemokine (mesh)</dc:subject><dc:subject>RNA</dc:subject><dc:subject>Ribosomal</dc:subject><dc:subject>16S (mesh)</dc:subject><dc:subject>Chemokines (mesh)</dc:subject><dc:subject>Longitudinal Studies (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>Lymphocyte Activation (mesh)</dc:subject><dc:subject>Gene Expression (mesh)</dc:subject><dc:subject>Breast Feeding (mesh)</dc:subject><dc:subject>Infant (mesh)</dc:subject><dc:subject>South Africa (mesh)</dc:subject><dc:subject>Infectious Disease Transmission</dc:subject><dc:subject>Vertical (mesh)</dc:subject><dc:subject>Gastrointestinal Microbiome (mesh)</dc:subject><dc:subject>Breast Feeding (mesh)</dc:subject><dc:subject>CD4-Positive T-Lymphocytes (mesh)</dc:subject><dc:subject>Chemokines (mesh)</dc:subject><dc:subject>Feces (mesh)</dc:subject><dc:subject>Gastrointestinal Microbiome (mesh)</dc:subject><dc:subject>Gene Expression (mesh)</dc:subject><dc:subject>HIV Infections (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Infant (mesh)</dc:subject><dc:subject>Infectious Disease Transmission</dc:subject><dc:subject>Vertical (mesh)</dc:subject><dc:subject>Longitudinal Studies (mesh)</dc:subject><dc:subject>Lymphocyte Activation (mesh)</dc:subject><dc:subject>Mouth Mucosa (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>RNA</dc:subject><dc:subject>Ribosomal</dc:subject><dc:subject>16S (mesh)</dc:subject><dc:subject>Receptors</dc:subject><dc:subject>Chemokine (mesh)</dc:subject><dc:subject>South Africa (mesh)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>Microbiology (science-metrix)</dc:subject><dc:subject>3202 Clinical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3jj568gj</dc:identifier><dc:identifier>https://escholarship.org/content/qt3jj568gj/qt3jj568gj.pdf</dc:identifier><dc:identifier>info:doi/10.1093/cid/ciy265</dc:identifier><dc:type>article</dc:type><dc:source>Clinical Infectious Diseases, vol 67, iss 8</dc:source><dc:coverage>1237 - 1246</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2hd688mw</identifier><datestamp>2026-09-16T00:28:17Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2hd688mw</dc:identifier><dc:title>Discovery and verification of extracellular microRNA biomarkers for diagnostic and prognostic assessment of preeclampsia at triage</dc:title><dc:creator>Morey, Robert</dc:creator><dc:creator>Poling, Lara</dc:creator><dc:creator>Srinivasan, Srimeenakshi</dc:creator><dc:creator>Martinez-King, Carolina</dc:creator><dc:creator>Anyikam, Adanna</dc:creator><dc:creator>Zhang-Rutledge, Kathy</dc:creator><dc:creator>To, Cuong</dc:creator><dc:creator>Hakim, Abbas</dc:creator><dc:creator>Mochizuki, Marina</dc:creator><dc:creator>Verma, Kajal</dc:creator><dc:creator>Mason, Antoinette</dc:creator><dc:creator>Tran, Vy</dc:creator><dc:creator>Meads, Morgan</dc:creator><dc:creator>Lamale-Smith, Leah</dc:creator><dc:creator>Roeder, Hilary</dc:creator><dc:creator>Horii, Mariko</dc:creator><dc:creator>Ramos, Gladys A</dc:creator><dc:creator>DeHoff, Peter</dc:creator><dc:creator>Parast, Mana M</dc:creator><dc:creator>Pantham, Priyadarshini</dc:creator><dc:creator>Laurent, Louise C</dc:creator><dc:date>2023-12-22</dc:date><dc:description>We report on the identification of extracellular miRNA (ex-miRNA) biomarkers for early diagnosis and prognosis of preeclampsia (PE). Small RNA sequencing of maternal serum prospectively collected from participants undergoing evaluation for suspected PE revealed distinct patterns of ex-miRNA expression among different categories of hypertensive disorders in pregnancy. Applying an iterative machine learning method identified three bivariate miRNA biomarkers (miR-522-3p/miR-4732-5p, miR-516a-5p/miR-144-3p, and miR-27b-3p/let-7b-5p) that, when applied serially, distinguished between PE cases of different severity and differentiated cases from controls with a sensitivity of 93%, specificity of 79%, positive predictive value (PPV) of 55%, and negative predictive value (NPV) of 89%. In a small independent validation cohort, these ex-miRNA biomarkers had a sensitivity of 91% and specificity of 57%. Combining these ex-miRNA biomarkers with the established sFlt1:PlGF protein biomarker ratio performed better than either set of biomarkers alone (sensitivity of 89.4%, specificity of 91.3%, PPV of 95.5%, and NPV of 80.8%).</dc:description><dc:subject>3404 Medicinal and Biomolecular Chemistry (for-2020)</dc:subject><dc:subject>34 Chemical Sciences (for-2020)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Maternal Morbidity and Mortality (rcdc)</dc:subject><dc:subject>Hypertension (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>Contraception/Reproduction (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Pregnancy (rcdc)</dc:subject><dc:subject>Maternal Health (rcdc)</dc:subject><dc:subject>Precision Medicine (rcdc)</dc:subject><dc:subject>Biotechnology (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Cardiovascular (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>4.1 Discovery and preclinical testing of markers and technologies (hrcs-rac)</dc:subject><dc:subject>4.2 Evaluation of markers and technologies (hrcs-rac)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>MicroRNAs (mesh)</dc:subject><dc:subject>Vascular Endothelial Growth Factor Receptor-1 (mesh)</dc:subject><dc:subject>Prognosis (mesh)</dc:subject><dc:subject>Pre-Eclampsia (mesh)</dc:subject><dc:subject>Triage (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Pre-Eclampsia (mesh)</dc:subject><dc:subject>Vascular Endothelial Growth Factor Receptor-1 (mesh)</dc:subject><dc:subject>MicroRNAs (mesh)</dc:subject><dc:subject>Prognosis (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Triage (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>MicroRNAs (mesh)</dc:subject><dc:subject>Vascular Endothelial Growth Factor Receptor-1 (mesh)</dc:subject><dc:subject>Prognosis (mesh)</dc:subject><dc:subject>Pre-Eclampsia (mesh)</dc:subject><dc:subject>Triage (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2hd688mw</dc:identifier><dc:identifier>https://escholarship.org/content/qt2hd688mw/qt2hd688mw.pdf</dc:identifier><dc:identifier>info:doi/10.1126/sciadv.adg7545</dc:identifier><dc:type>article</dc:type><dc:source>Science Advances, vol 9, iss 51</dc:source><dc:coverage>eadg7545</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt39n696ct</identifier><datestamp>2026-09-16T00:27:34Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt39n696ct</dc:identifier><dc:title>EGS Collab SIGMA-V Project: Stimulation Investigations for Geothermal Modeling Analysis and Validation Phase 1 Report. For the period February 2017 – March 2019</dc:title><dc:creator>Kneafsey, Timothy</dc:creator><dc:creator>Blankenship, Doug</dc:creator><dc:creator>Dobson, Patrick</dc:creator><dc:creator>EGS Collab Team</dc:creator><dc:date>2019-05-31</dc:date><dc:description>The EGS Collab project was initiated in March 2017 to enable the subsurface modelling and research
community to establish validations against controlled, small-scale, in-situ experiments focused on rock
fracture behavior and permeability enhancement. The EGS Collab project is to provide the opportunity
for reservoir model prediction and validation, in coordination with in depth analysis of geophysical and
other fracture characterization data with an ultimate goal of further elucidating the basic relationship
between stress, seismicity and permeability enhancement. In addition, the project is to identify and
quantify other key governing parameters that impact permeability as well as understanding how these
parameters change throughout the three EGS development phases (identify/characterize site, create
reservoir, operate power plant). The project is to use comprehensive instrumentation and data
collection effort to inform baseline, predictive, and post stimulation reservoir modeling is essential.
This report describes the activities performed in Phase 1 of the project. The work done to date is
extensive, and a large number of participants have contributed significant effort to enable project
success. From planning to execution, we have stayed on track to address the objectives established by
the Department of Energy in the paragraph above.</dc:description><dc:subject>coupled process modeling</dc:subject><dc:subject>crystalline rock</dc:subject><dc:subject>EGS Collab</dc:subject><dc:subject>enhanced geothermal systesm</dc:subject><dc:subject>experimental</dc:subject><dc:subject>field test</dc:subject><dc:subject>flow test</dc:subject><dc:subject>Sanford Underground Research Facility</dc:subject><dc:subject>stimulation</dc:subject><dc:subject>enhanced geothermal systems</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-SA</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/39n696ct</dc:identifier><dc:identifier>https://escholarship.org/content/qt39n696ct/qt39n696ct.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5t88h0fg</identifier><datestamp>2026-09-16T00:23:44Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5t88h0fg</dc:identifier><dc:title>Regionalization of pancreatic surgery in California: Benefits for preventing postoperative deaths and reducing healthcare costs</dc:title><dc:creator>Perry, Lauren M</dc:creator><dc:creator>Canter, Robert J</dc:creator><dc:creator>Gaskill, Cameron E</dc:creator><dc:creator>Bold, Richard J</dc:creator><dc:date>2023-12-01</dc:date><dc:description>Introduction: Pancreatic cancer (PC) surgery has been associated with improved outcomes and value when performed at high-volume centers (HVC; ≥20 surgeries annually) compared to low-volume centers (LVC). Some have used these differences to suggest that regionalization of PC surgery would optimize patient outcomes and expenditures.
Methods: A Markov model was created to evaluate 30-day mortality, 30-day complications, and 30-day costs. The differences in these outcome measures between the current and future states were measured to assess the population-level benefits of regionalization. A sensitivity analysis was performed to evaluate the impact of variations of input variables in the model.
Results: Among 5958 new cases of pancreatic cancer in California in 2021, a total of 2443 cases (41&amp;nbsp;%) would be resectable; among patients with resectable PC, a total of 977 (40&amp;nbsp;%) patients would undergo surgery. In aggregate, HVC and LVC 30-day postoperative complications occurred in 364 patients, 30-day mortality in 35 patients, and healthcare costs expended managing complications were $6,120,660. In the predictive model of complete regionalization to only HVC in California, an estimated 29 fewer complications, 17 fewer deaths, and a cost savings of $487,635 per year would occur.
Conclusions and relevance: Pancreatic cancer (PC) surgery has been associated with improved outcomes and value when performed at high-volume centers (HVC; ≥20 surgeries annually) compared to low-volume centers (LVC). Complete regionalization of pancreatic cancer surgery predicted benefits in mortality, complications and cost, though implementing this strategy at a population-level may require investment of resources and redesigning care delivery models.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>3211 Oncology and Carcinogenesis (for-2020)</dc:subject><dc:subject>Pancreatic Cancer (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Cancer (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Rare Diseases (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Health Services (rcdc)</dc:subject><dc:subject>Patient Safety (rcdc)</dc:subject><dc:subject>Digestive Diseases (rcdc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Pancreatic surgery</dc:subject><dc:subject>Volume:outcome relationship</dc:subject><dc:subject>Regionalization</dc:subject><dc:subject>Pancreatic surgery</dc:subject><dc:subject>Regionalization</dc:subject><dc:subject>Volume:outcome relationship</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5t88h0fg</dc:identifier><dc:identifier>https://escholarship.org/content/qt5t88h0fg/qt5t88h0fg.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.sopen.2023.11.004</dc:identifier><dc:type>article</dc:type><dc:source>Surgery Open Science, vol 16</dc:source><dc:coverage>198 - 204</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7kk8b3zd</identifier><datestamp>2026-09-16T00:23:27Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7kk8b3zd</dc:identifier><dc:title>Watershed zonation through hillslope clustering for tractably quantifying above- and below-ground watershed heterogeneity and functions</dc:title><dc:creator>Wainwright, Haruko M</dc:creator><dc:creator>Uhlemann, Sebastian</dc:creator><dc:creator>Franklin, Maya</dc:creator><dc:creator>Falco, Nicola</dc:creator><dc:creator>Bouskill, Nicholas J</dc:creator><dc:creator>Newcomer, Michelle E</dc:creator><dc:creator>Dafflon, Baptiste</dc:creator><dc:creator>Siirila-Woodburn, Erica R</dc:creator><dc:creator>Minsley, Burke J</dc:creator><dc:creator>Williams, Kenneth H</dc:creator><dc:creator>Hubbard, Susan S</dc:creator><dc:date>2022-01-31</dc:date><dc:description>Abstract. In this study, we develop a watershed zonation approach for characterizing watershed organization and functions in a tractable manner by integrating multiple spatial data layers. We hypothesize that (1)&amp;nbsp;a hillslope is an appropriate unit for capturing the watershed-scale heterogeneity of key bedrock-through-canopy properties and for quantifying the co-variability of these properties representing coupled ecohydrological and biogeochemical interactions, (2)&amp;nbsp;remote sensing data layers and clustering methods can be used to identify watershed hillslope zones having the unique distributions of these properties relative to neighboring parcels, and (3)&amp;nbsp;property suites associated with the identified zones can be used to understand zone-based functions, such as response to early snowmelt or drought and solute exports to the river. We demonstrate this concept using unsupervised clustering methods that synthesize airborne remote sensing data (lidar, hyperspectral, and electromagnetic surveys) along with satellite and streamflow data collected in the East River Watershed, Crested Butte, Colorado, USA. Results show that (1)&amp;nbsp;we can define the scale of hillslopes at which the hillslope-averaged metrics can capture the majority of the overall variability in key properties (such as elevation, net potential annual radiation, and peak snow-water equivalent – SWE), (2)&amp;nbsp;elevation and aspect are independent controls on plant and snow signatures, (3)&amp;nbsp;near-surface bedrock electrical resistivity (top 20 m) and geological structures are significantly correlated with surface topography and plan species distribution, and (4)&amp;nbsp;K-means, hierarchical clustering, and Gaussian mixture clustering methods generate similar zonation patterns across the watershed. Using independently collected data, we show that the identified zones provide information about zone-based watershed functions, including foresummer drought sensitivity and river nitrogen exports. The approach is expected to be applicable to other sites and generally useful for guiding the selection of hillslope-experiment locations and informing model parameterization.</dc:description><dc:subject>3707 Hydrology (for-2020)</dc:subject><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>0406 Physical Geography and Environmental Geoscience (for)</dc:subject><dc:subject>0905 Civil Engineering (for)</dc:subject><dc:subject>0907 Environmental Engineering (for)</dc:subject><dc:subject>Environmental Engineering (science-metrix)</dc:subject><dc:subject>3707 Hydrology (for-2020)</dc:subject><dc:subject>3709 Physical geography and environmental geoscience (for-2020)</dc:subject><dc:subject>4013 Geomatic engineering (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7kk8b3zd</dc:identifier><dc:identifier>https://escholarship.org/content/qt7kk8b3zd/qt7kk8b3zd.pdf</dc:identifier><dc:identifier>info:doi/10.5194/hess-26-429-2022</dc:identifier><dc:type>article</dc:type><dc:source>Hydrology and Earth System Sciences, vol 26, iss 2</dc:source><dc:coverage>429 - 444</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt79c81353</identifier><datestamp>2026-09-16T00:23:23Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt79c81353</dc:identifier><dc:title>Phylogenomic Analysis Reveals Dispersal-Driven Speciation and Divergence with Gene Flow in Lesser Sunda Flying Lizards (Genus Draco)</dc:title><dc:creator>Reilly, Sean B</dc:creator><dc:creator>Stubbs, Alexander L</dc:creator><dc:creator>Arida, Evy</dc:creator><dc:creator>Karin, Benjamin R</dc:creator><dc:creator>Arifin, Umilaela</dc:creator><dc:creator>Kaiser, Hinrich</dc:creator><dc:creator>Bi, Ke</dc:creator><dc:creator>Iskandar, Djoko T</dc:creator><dc:creator>McGuire, Jimmy A</dc:creator><dc:contributor>Barrow, Lisa</dc:contributor><dc:date>2021-12-16</dc:date><dc:description>The Lesser Sunda Archipelago offers exceptional potential as a model system for studying the dynamics of dispersal-driven diversification. The geographic proximity of the islands suggests the possibility for successful dispersal, but this is countered by the permanence of the marine barriers and extreme intervening currents that are expected to hinder gene flow. Phylogenetic and species delimitation analyses of flying lizards (genus Draco) using single mitochondrial genes, complete mitochondrial genomes, and exome-capture data sets identified 9-11 deeply divergent lineages including single-island endemics, lineages that span multiple islands, and parapatrically distributed nonsister lineages on the larger islands. Population clustering and PCA confirmed these genetic boundaries with isolation-by-distance playing a role in some islands or island sets. While gdi estimates place most candidate species comparisons in the ambiguous zone, migration estimates suggest 9 or 10 species exist with nuclear introgression detected across some intra-island contact zones. Initial entry of Draco into the archipelago occurred at 5.5-7.5 Ma, with most inter-island colonization events having occurred between 1-3 Ma. Biogeographical model testing favors scenarios integrating geographic distance and historical island connectivity, including an initial stepping-stone dispersal process from the Greater Sunda Shelf through the Sunda Arc as far eastward as Lembata Island. However, rather than reaching the adjacent island of Pantar by dispersing over the 15-km wide Alor Strait, Draco ultimately reached Pantar (and much of the rest of the archipelago) by way of a circuitous route involving at least five overwater dispersal events. These findings suggest that historical geological and oceanographic conditions heavily influenced dispersal pathways and gene flow, which in turn drove species formation and shaped species boundaries. [Biogeography; genomics, Indonesia; lizards; phylogeography; reptiles].</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>3104 Evolutionary Biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>14 Life Below Water (sdg)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Gene Flow (mesh)</dc:subject><dc:subject>Indonesia (mesh)</dc:subject><dc:subject>Lizards (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Phylogeography (mesh)</dc:subject><dc:subject>Biogeography</dc:subject><dc:subject>genomics</dc:subject><dc:subject>Indonesia</dc:subject><dc:subject>lizards</dc:subject><dc:subject>phylogeography</dc:subject><dc:subject>reptiles</dc:subject><dc:subject>Biogeography</dc:subject><dc:subject>genomics</dc:subject><dc:subject>Indonesia</dc:subject><dc:subject>lizards</dc:subject><dc:subject>phylogeography</dc:subject><dc:subject>reptiles</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Lizards (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Indonesia (mesh)</dc:subject><dc:subject>Gene Flow (mesh)</dc:subject><dc:subject>Phylogeography (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Gene Flow (mesh)</dc:subject><dc:subject>Indonesia (mesh)</dc:subject><dc:subject>Lizards (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Phylogeography (mesh)</dc:subject><dc:subject>0603 Evolutionary Biology (for)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>Evolutionary Biology (science-metrix)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>3104 Evolutionary biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/79c81353</dc:identifier><dc:identifier>https://escholarship.org/content/qt79c81353/qt79c81353.pdf</dc:identifier><dc:identifier>info:doi/10.1093/sysbio/syab043</dc:identifier><dc:type>article</dc:type><dc:source>Systematic Biology, vol 71, iss 1</dc:source><dc:coverage>221 - 241</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt73h7m9nk</identifier><datestamp>2026-09-16T00:19:31Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt73h7m9nk</dc:identifier><dc:title>Exploring applications of non-targeted analysis in the characterization of the prenatal exposome</dc:title><dc:creator>Bland, Garret D</dc:creator><dc:creator>Abrahamsson, Dimitri</dc:creator><dc:creator>Wang, Miaomiao</dc:creator><dc:creator>Zlatnik, Marya</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Park, June-Soo</dc:creator><dc:creator>Sirota, Marina</dc:creator><dc:creator>Woodruff, Tracey J</dc:creator><dc:date>2024-02-01</dc:date><dc:description>Capturing the breadth of chemical exposures in utero is critical in understanding their long-term health effects for mother and child. We explored methodological adaptations in a Non-Targeted Analysis (NTA) pipeline and evaluated the effects on chemical annotation and discovery for maternal and infant exposure. We focus on lesser-known/underreported chemicals in maternal and umbilical cord serum analyzed with liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF/MS). The samples were collected from a demographically diverse cohort of 296 maternal-cord pairs (n&amp;nbsp;=&amp;nbsp;592) recruited in San Francisco Bay area. We developed and evaluated two data processing pipelines, primarily differing by detection frequency cut-off, to extract chemical features from non-targeted analysis (NTA). We annotated the detected chemical features by matching with EPA CompTox Chemicals Dashboard (n&amp;nbsp;=&amp;nbsp;860,000 chemicals) and Human Metabolome Database (n&amp;nbsp;=&amp;nbsp;3140 chemicals) and applied a Kendrick Mass Defect filter to detect homologous series. We collected fragmentation spectra (MS/MS) on a subset of serum samples and matched to an experimental MS/MS database within the MS-Dial website and other experimental MS/MS spectra collected from standards in our lab. We annotated ~72&amp;nbsp;% of the features (total features&amp;nbsp;=&amp;nbsp;32,197, levels 1-4). We confirmed 22 compounds with analytical standards, tentatively identified 88 compounds with MS/MS spectra, and annotated 4862 exogenous chemicals with an in-house developed annotation algorithm. We detected 36 chemicals that appear to not have been previously reported in human blood and 9 chemicals that were reported in less than five studies. Our findings underline the importance of NTA in the discovery of lesser-known/unreported chemicals important to characterize human exposures.</dc:description><dc:subject>3205 Medical Biochemistry and Metabolomics (for-2020)</dc:subject><dc:subject>3401 Analytical Chemistry (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>34 Chemical Sciences (for-2020)</dc:subject><dc:subject>Perinatal Period - Conditions Originating in Perinatal Period (rcdc)</dc:subject><dc:subject>Endocrine Disruptors (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>2.2 Factors relating to the physical environment (hrcs-rac)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Tandem Mass Spectrometry (mesh)</dc:subject><dc:subject>Chromatography</dc:subject><dc:subject>Liquid (mesh)</dc:subject><dc:subject>Exposome (mesh)</dc:subject><dc:subject>Liquid Chromatography-Mass Spectrometry (mesh)</dc:subject><dc:subject>San Francisco (mesh)</dc:subject><dc:subject>Non-targeted analysis</dc:subject><dc:subject>Exposome</dc:subject><dc:subject>Prenatal exposure</dc:subject><dc:subject>High resolution mass spectrometry</dc:subject><dc:subject>Data pipeline</dc:subject><dc:subject>Kendrick mass defect</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Chromatography</dc:subject><dc:subject>Liquid (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>San Francisco (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Tandem Mass Spectrometry (mesh)</dc:subject><dc:subject>Exposome (mesh)</dc:subject><dc:subject>Liquid Chromatography-Mass Spectrometry (mesh)</dc:subject><dc:subject>Data pipeline</dc:subject><dc:subject>Exposome</dc:subject><dc:subject>High resolution mass spectrometry</dc:subject><dc:subject>Kendrick mass defect</dc:subject><dc:subject>Non-targeted analysis</dc:subject><dc:subject>Prenatal exposure</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Tandem Mass Spectrometry (mesh)</dc:subject><dc:subject>Chromatography</dc:subject><dc:subject>Liquid (mesh)</dc:subject><dc:subject>Exposome (mesh)</dc:subject><dc:subject>Liquid Chromatography-Mass Spectrometry (mesh)</dc:subject><dc:subject>San Francisco (mesh)</dc:subject><dc:subject>Environmental Sciences (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/73h7m9nk</dc:identifier><dc:identifier>https://escholarship.org/content/qt73h7m9nk/qt73h7m9nk.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.scitotenv.2023.169458</dc:identifier><dc:type>article</dc:type><dc:source>The Science of The Total Environment, vol 912</dc:source><dc:coverage>169458</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt75f580zv</identifier><datestamp>2026-09-16T00:18:50Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt75f580zv</dc:identifier><dc:title>Selecting SNPs informative for African, American Indian and European Ancestry: application to the Family Investigation of Nephropathy and Diabetes (FIND)</dc:title><dc:creator>Williams, Robert C</dc:creator><dc:creator>Elston, Robert C</dc:creator><dc:creator>Kumar, Pankaj</dc:creator><dc:creator>Knowler, William C</dc:creator><dc:creator>Abboud, Hanna E</dc:creator><dc:creator>Adler, Sharon</dc:creator><dc:creator>Bowden, Donald W</dc:creator><dc:creator>Divers, Jasmin</dc:creator><dc:creator>Freedman, Barry I</dc:creator><dc:creator>Igo, Robert P</dc:creator><dc:creator>Ipp, Eli</dc:creator><dc:creator>Iyengar, Sudha K</dc:creator><dc:creator>Kimmel, Paul L</dc:creator><dc:creator>Klag, Michael J</dc:creator><dc:creator>Kohn, Orly</dc:creator><dc:creator>Langefeld, Carl D</dc:creator><dc:creator>Leehey, David J</dc:creator><dc:creator>Nelson, Robert G</dc:creator><dc:creator>Nicholas, Susanne B</dc:creator><dc:creator>Pahl, Madeleine V</dc:creator><dc:creator>Parekh, Rulan S</dc:creator><dc:creator>Rotter, Jerome I</dc:creator><dc:creator>Schelling, Jeffrey R</dc:creator><dc:creator>Sedor, John R</dc:creator><dc:creator>Shah, Vallabh O</dc:creator><dc:creator>Smith, Michael W</dc:creator><dc:creator>Taylor, Kent D</dc:creator><dc:creator>Thameem, Farook</dc:creator><dc:creator>Thornley-Brown, Denyse</dc:creator><dc:creator>Winkler, Cheryl A</dc:creator><dc:creator>Guo, Xiuqing</dc:creator><dc:creator>Zager, Phillip</dc:creator><dc:creator>Hanson, Robert L</dc:creator><dc:creator>the FIND Research Group</dc:creator><dc:date>2016-12-01</dc:date><dc:description>BackgroundThe presence of population structure in a sample may confound the search for important genetic loci associated with disease. Our four samples in the Family Investigation of Nephropathy and Diabetes (FIND), European Americans, Mexican Americans, African Americans, and American Indians are part of a genome- wide association study in which population structure might be particularly important. We therefore decided to study in detail one component of this, individual genetic ancestry (IGA). From SNPs present on the Affymetrix 6.0 Human SNP array, we identified 3 sets of ancestry informative markers (AIMs), each maximized for the information in one the three contrasts among ancestral populations: Europeans (HAPMAP, CEU), Africans (HAPMAP, YRI and LWK), and Native Americans (full heritage Pima Indians). We estimate IGA and present an algorithm for their standard errors, compare IGA to principal components, emphasize the importance of balancing information in the ancestry informative markers (AIMs), and test the association of IGA with diabetic nephropathy in the combined sample.ResultsA fixed parental allele maximum likelihood algorithm was applied to the FIND to estimate IGA in four samples: 869 American Indians; 1385 African Americans; 1451 Mexican Americans; and 826 European Americans. When the information in the AIMs is unbalanced, the estimates are incorrect with large error. Individual genetic admixture is highly correlated with principle components for capturing population structure. It takes ~700 SNPs to reduce the average standard error of individual admixture below 0.01. When the samples are combined, the resulting population structure creates associations between IGA and diabetic nephropathy.ConclusionsThe identified set of AIMs, which include American Indian parental allele frequencies, may be particularly useful for estimating genetic admixture in populations from the Americas. Failure to balance information in maximum likelihood, poly-ancestry models creates biased estimates of individual admixture with large error. This also occurs when estimating IGA using the Bayesian clustering method as implemented in the program STRUCTURE. Odds ratios for the associations of IGA with disease are consistent with what is known about the incidence and prevalence of diabetic nephropathy in these populations.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>American Indian or Alaska Native (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Minority Health (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Diabetes (rcdc)</dc:subject><dc:subject>Metabolic and endocrine (hrcs-hc)</dc:subject><dc:subject>Black or African American (mesh)</dc:subject><dc:subject>Algorithms (mesh)</dc:subject><dc:subject>Chromosome Mapping (mesh)</dc:subject><dc:subject>Diabetic Nephropathies (mesh)</dc:subject><dc:subject>Genetic Markers (mesh)</dc:subject><dc:subject>Genetic Predisposition to Disease (mesh)</dc:subject><dc:subject>Genome-Wide Association Study (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Indians</dc:subject><dc:subject>North American (mesh)</dc:subject><dc:subject>Likelihood Functions (mesh)</dc:subject><dc:subject>Mexican Americans (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Genetic (mesh)</dc:subject><dc:subject>Oligonucleotide Array Sequence Analysis (mesh)</dc:subject><dc:subject>Polymorphism</dc:subject><dc:subject>Single Nucleotide (mesh)</dc:subject><dc:subject>Principal Component Analysis (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>White People (mesh)</dc:subject><dc:subject>Individual genetic ancestry</dc:subject><dc:subject>Population structure</dc:subject><dc:subject>SNP</dc:subject><dc:subject>Diabetic nephropathy</dc:subject><dc:subject>FIND Research Group</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Diabetic Nephropathies (mesh)</dc:subject><dc:subject>Genetic Predisposition to Disease (mesh)</dc:subject><dc:subject>Genetic Markers (mesh)</dc:subject><dc:subject>Oligonucleotide Array Sequence Analysis (mesh)</dc:subject><dc:subject>Likelihood Functions (mesh)</dc:subject><dc:subject>Chromosome Mapping (mesh)</dc:subject><dc:subject>Polymorphism</dc:subject><dc:subject>Single Nucleotide (mesh)</dc:subject><dc:subject>Algorithms (mesh)</dc:subject><dc:subject>Principal Component Analysis (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Genetic (mesh)</dc:subject><dc:subject>Indians</dc:subject><dc:subject>North American (mesh)</dc:subject><dc:subject>Mexican Americans (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Genome-Wide Association Study (mesh)</dc:subject><dc:subject>White People (mesh)</dc:subject><dc:subject>Black or African American (mesh)</dc:subject><dc:subject>Diabetic nephropathy</dc:subject><dc:subject>Individual genetic ancestry</dc:subject><dc:subject>Population structure</dc:subject><dc:subject>SNP</dc:subject><dc:subject>Black or African American (mesh)</dc:subject><dc:subject>Algorithms (mesh)</dc:subject><dc:subject>Chromosome Mapping (mesh)</dc:subject><dc:subject>Diabetic Nephropathies (mesh)</dc:subject><dc:subject>Genetic Markers (mesh)</dc:subject><dc:subject>Genetic Predisposition to Disease (mesh)</dc:subject><dc:subject>Genome-Wide Association Study (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Indians</dc:subject><dc:subject>North American (mesh)</dc:subject><dc:subject>Likelihood Functions (mesh)</dc:subject><dc:subject>Mexican Americans (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Genetic (mesh)</dc:subject><dc:subject>Oligonucleotide Array Sequence Analysis (mesh)</dc:subject><dc:subject>Polymorphism</dc:subject><dc:subject>Single Nucleotide (mesh)</dc:subject><dc:subject>Principal Component Analysis (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>White People (mesh)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>08 Information and Computing Sciences (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>Bioinformatics (science-metrix)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/75f580zv</dc:identifier><dc:identifier>https://escholarship.org/content/qt75f580zv/qt75f580zv.pdf</dc:identifier><dc:identifier>info:doi/10.1186/s12864-016-2654-x</dc:identifier><dc:type>article</dc:type><dc:source>BMC Genomics, vol 17, iss 1</dc:source><dc:coverage>325</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5rq3t32d</identifier><datestamp>2026-09-16T00:09:55Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5rq3t32d</dc:identifier><dc:title>Rapidly changing high-latitude seasonality: implications for the 21st century carbon cycle in Alaska</dc:title><dc:creator>Shirley, Ian A</dc:creator><dc:creator>Mekonnen, Zelalem A</dc:creator><dc:creator>Grant, Robert F</dc:creator><dc:creator>Dafflon, Baptiste</dc:creator><dc:creator>Hubbard, Susan S</dc:creator><dc:creator>Riley, William J</dc:creator><dc:date>2022-01-01</dc:date><dc:description>Seasonal variations in high-latitude terrestrial carbon (C) fluxes are predominantly driven by air temperature and radiation. At present, high-latitude net C uptake is largest during the summer. Recent observations and modeling studies have demonstrated that ongoing and projected climate change will increase plant productivity, microbial respiration, and growing season lengths at high-latitudes, but impacts on high-latitude C cycle seasonality (and potential feedbacks to the climate system) remain uncertain. Here we use ecosys, a well-tested and process-rich mechanistic ecosystem model that we evaluate further in this study, to explore how climate warming under an RCP8.5 scenario will shift C cycle seasonality in Alaska throughout the 21st century. The model successfully reproduced recently reported large high-latitude C losses during the fall and winter and yet still predicts a high-latitude C sink, pointing to a resolution of the current conflict between process-model and observation-based estimates of high-latitude C balance. We find that warming will result in surprisingly large changes in net ecosystem exchange (NEE; defined as negative for uptake) seasonality, with spring net C uptake overtaking summer net C uptake by year 2100. This shift is driven by a factor of 3 relaxation of spring temperature limitation to plant productivity that results in earlier C uptake and a corresponding increase in magnitude of spring NEE from −19 to −144 gC m−2 season−1 by the end of the century. Although a similar relaxation of temperature limitation will occur in the fall, radiation limitation during those months will limit increases in C fixation. Additionally, warmer soil temperatures and increased carbon inputs from plants lead to combined fall and winter C losses (163 gC m−2) that are larger than summer net uptake (123 gC m−2 season−1) by year 2100. However, this increase in microbial activity leads to more rapid N cycling and increased plant N uptake during the fall and winter months that supports large increases in spring NPP. Due to the large increases in spring net C uptake, the high-latitude atmospheric C sink is projected to sustain throughout this century. Our analysis disentangles the effects of key environmental drivers of high-latitude seasonal C balances as climate changes over the 21st century.</dc:description><dc:subject>30 Agricultural</dc:subject><dc:subject>Veterinary and Food Sciences (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3007 Forestry Sciences (for-2020)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>seasonality</dc:subject><dc:subject>high-latitudes</dc:subject><dc:subject>carbon cycle</dc:subject><dc:subject>climate change</dc:subject><dc:subject>Meteorology &amp; Atmospheric Sciences (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5rq3t32d</dc:identifier><dc:identifier>https://escholarship.org/content/qt5rq3t32d/qt5rq3t32d.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1748-9326/ac4362</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Research Letters, vol 17, iss 1</dc:source><dc:coverage>014032</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5f7747b1</identifier><datestamp>2026-09-16T00:05:56Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5f7747b1</dc:identifier><dc:title>Parallel Runtime Interface for Fortran (PRIF) Design Document, Revision 0.2</dc:title><dc:creator>Rouson, Damian</dc:creator><dc:creator>Richardson, Brad</dc:creator><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Rasmussen, Katherine</dc:creator><dc:date>2023-12-20</dc:date><dc:description>This design document proposes an interface to support the parallel features of Fortran, named the Parallel Runtime Interface for Fortran (PRIF). PRIF is a proposed solution in which the runtime library is responsible for coarray allocation, deallocation and accesses, image synchronization, atomic operations, events, and teams. In this interface, the compiler is responsible for transforming the invocation of Fortran-level parallel features into procedure calls to the necessary PRIF procedures. The interface is designed for portability across shared- and distributed-memory machines, different operating systems, and multiple architectures. Implementations of this interface are intended as an augmentation for the compiler's own runtime library. With an implementation-agnostic interface, alternative parallel runtime libraries may be developed that support the same interface. One benefit of this approach is the ability to vary the communication substrate. A central aim of this document is to define a parallel runtime interface in standard Fortran syntax, which enables us to leverage Fortran to succinctly express various properties of the procedure interfaces, including argument attributes.</dc:description><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5f7747b1</dc:identifier><dc:identifier>https://escholarship.org/content/qt5f7747b1/qt5f7747b1.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S4DG6S</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5gm5k142</identifier><datestamp>2026-09-16T00:05:19Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5gm5k142</dc:identifier><dc:title>Microbial legacies alter decomposition in response to simulated global change</dc:title><dc:creator>Martiny, Jennifer BH</dc:creator><dc:creator>Martiny, Adam C</dc:creator><dc:creator>Weihe, Claudia</dc:creator><dc:creator>Lu, Ying</dc:creator><dc:creator>Berlemont, Renaud</dc:creator><dc:creator>Brodie, Eoin L</dc:creator><dc:creator>Goulden, Michael L</dc:creator><dc:creator>Treseder, Kathleen K</dc:creator><dc:creator>Allison, Steven D</dc:creator><dc:date>2017-02-01</dc:date><dc:description>Terrestrial ecosystem models assume that microbial communities respond instantaneously, or are immediately resilient, to environmental change. Here we tested this assumption by quantifying the resilience of a leaf litter community to changes in precipitation or nitrogen availability. By manipulating composition within a global change experiment, we decoupled the legacies of abiotic parameters versus that of the microbial community itself. After one rainy season, more variation in fungal composition could be explained by the original microbial inoculum than the litterbag environment (18% versus 5.5% of total variation). This compositional legacy persisted for 3 years, when 6% of the variability in fungal composition was still explained by the microbial origin. In contrast, bacterial composition was generally more resilient than fungal composition. Microbial functioning (measured as decomposition rate) was not immediately resilient to the global change manipulations; decomposition depended on both the contemporary environment and rainfall the year prior. Finally, using metagenomic sequencing, we showed that changes in precipitation, but not nitrogen availability, altered the potential for bacterial carbohydrate degradation, suggesting why the functional consequences of the two experiments may have differed. Predictions of how terrestrial ecosystem processes respond to environmental change may thus be improved by considering the legacies of microbial communities.</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Carbohydrate Metabolism (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Fungi (mesh)</dc:subject><dc:subject>Metagenomics (mesh)</dc:subject><dc:subject>Microbial Consortia (mesh)</dc:subject><dc:subject>Nitrogen (mesh)</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Rain (mesh)</dc:subject><dc:subject>Seasons (mesh)</dc:subject><dc:subject>Sequence Analysis</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>Time Factors (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Fungi (mesh)</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Nitrogen (mesh)</dc:subject><dc:subject>Sequence Analysis</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Rain (mesh)</dc:subject><dc:subject>Seasons (mesh)</dc:subject><dc:subject>Time Factors (mesh)</dc:subject><dc:subject>Carbohydrate Metabolism (mesh)</dc:subject><dc:subject>Metagenomics (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>Microbial Consortia (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Carbohydrate Metabolism (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Fungi (mesh)</dc:subject><dc:subject>Metagenomics (mesh)</dc:subject><dc:subject>Microbial Consortia (mesh)</dc:subject><dc:subject>Nitrogen (mesh)</dc:subject><dc:subject>Plant Leaves (mesh)</dc:subject><dc:subject>Rain (mesh)</dc:subject><dc:subject>Seasons (mesh)</dc:subject><dc:subject>Sequence Analysis</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>Time Factors (mesh)</dc:subject><dc:subject>05 Environmental Sciences (for)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>10 Technology (for)</dc:subject><dc:subject>Microbiology (science-metrix)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>41 Environmental sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5gm5k142</dc:identifier><dc:identifier>https://escholarship.org/content/qt5gm5k142/qt5gm5k142.pdf</dc:identifier><dc:identifier>info:doi/10.1038/ismej.2016.122</dc:identifier><dc:type>article</dc:type><dc:source>The ISME Journal: Multidisciplinary Journal of Microbial Ecology, vol 11, iss 2</dc:source><dc:coverage>490 - 499</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4d9982jd</identifier><datestamp>2026-09-16T00:01:50Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4d9982jd</dc:identifier><dc:title>UPC++ v1.0 Specification, Revision 2023.9.0</dc:title><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Kamil, Amir</dc:creator><dc:date>2023-12-15</dc:date><dc:description>UPC++ is a C++ library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). All communication operations are syntactically explicit and default to non-blocking; asynchrony is managed through the use of futures, promises and continuation callbacks, enabling the programmer to construct a graph of operations to execute asynchronously as high-latency dependencies are satisfied. A global pointer abstraction provides system-wide addressability of shared memory, including host and accelerator memories. The parallelism model is primarily process-based, but the interface is thread-safe and designed to allow efficient and expressive use in multi-threaded applications. The interface is designed for extreme scalability throughout, and deliberately avoids design features that could inhibit scalability.</dc:description><dc:subject>Exascale Computing</dc:subject><dc:subject>Library specification</dc:subject><dc:subject>parallel distributed programming</dc:subject><dc:subject>PGAS</dc:subject><dc:subject>scientific computing</dc:subject><dc:subject>UPC++</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4d9982jd</dc:identifier><dc:identifier>https://escholarship.org/content/qt4d9982jd/qt4d9982jd.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S4J592</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt269767k3</identifier><datestamp>2026-09-16T00:00:49Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt269767k3</dc:identifier><dc:title>Microbial Metagenomics Reveals Climate-Relevant Subsurface Biogeochemical Processes</dc:title><dc:creator>Long, Philip E</dc:creator><dc:creator>Williams, Kenneth H</dc:creator><dc:creator>Hubbard, Susan S</dc:creator><dc:creator>Banfield, Jillian F</dc:creator><dc:date>2016-08-01</dc:date><dc:description>Microorganisms play key roles in terrestrial system processes, including the turnover of natural organic carbon, such as leaf litter and woody debris that accumulate in soils and subsurface sediments. What has emerged from a series of recent DNA sequencing-based studies is recognition of the enormous variety of little known and previously unknown microorganisms that mediate recycling of these vast stores of buried carbon in subsoil compartments of the terrestrial system. More importantly, the genome resolution achieved in these studies has enabled association of specific members of these microbial communities with carbon compound transformations and other linked biogeochemical processes-such as the nitrogen cycle-that can impact the quality of groundwater, surface water, and atmospheric trace gas concentrations. The emerging view also emphasizes the importance of organism interactions through exchange of metabolic byproducts (e.g., within the carbon, nitrogen, and sulfur cycles) and via symbioses since many novel organisms exhibit restricted metabolic capabilities and an associated extremely small cell size. New, genome-resolved information reshapes our view of subsurface microbial communities and provides critical new inputs for advanced reactive transport models. These inputs are needed for accurate prediction of feedbacks in watershed biogeochemical functioning and their influence on the climate via the fluxes of greenhouse gases, CO2, CH4, and N2O.</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>14 Life Below Water (sdg)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>Atmosphere (mesh)</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:subject>Carbon (mesh)</dc:subject><dc:subject>Climate (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Gases (mesh)</dc:subject><dc:subject>Genome</dc:subject><dc:subject>Microbial (mesh)</dc:subject><dc:subject>Geologic Sediments (mesh)</dc:subject><dc:subject>Greenhouse Effect (mesh)</dc:subject><dc:subject>Groundwater (mesh)</dc:subject><dc:subject>Metabolic Networks and Pathways (mesh)</dc:subject><dc:subject>Metagenomics (mesh)</dc:subject><dc:subject>Microbial Consortia (mesh)</dc:subject><dc:subject>Microbial Interactions (mesh)</dc:subject><dc:subject>Nitrogen (mesh)</dc:subject><dc:subject>Nitrogen Cycle (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Sulfur (mesh)</dc:subject><dc:subject>Symbiosis (mesh)</dc:subject><dc:subject>Carbon (mesh)</dc:subject><dc:subject>Sulfur (mesh)</dc:subject><dc:subject>Nitrogen (mesh)</dc:subject><dc:subject>Gases (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:subject>Greenhouse Effect (mesh)</dc:subject><dc:subject>Atmosphere (mesh)</dc:subject><dc:subject>Climate (mesh)</dc:subject><dc:subject>Symbiosis (mesh)</dc:subject><dc:subject>Geologic Sediments (mesh)</dc:subject><dc:subject>Metabolic Networks and Pathways (mesh)</dc:subject><dc:subject>Metagenomics (mesh)</dc:subject><dc:subject>Microbial Interactions (mesh)</dc:subject><dc:subject>Nitrogen Cycle (mesh)</dc:subject><dc:subject>Microbial Consortia (mesh)</dc:subject><dc:subject>Groundwater (mesh)</dc:subject><dc:subject>Genome</dc:subject><dc:subject>Microbial (mesh)</dc:subject><dc:subject>greenhouse gases</dc:subject><dc:subject>metagenome</dc:subject><dc:subject>reaction pathway</dc:subject><dc:subject>subsurface biogeochemistry</dc:subject><dc:subject>Atmosphere (mesh)</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:subject>Carbon (mesh)</dc:subject><dc:subject>Climate (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Gases (mesh)</dc:subject><dc:subject>Genome</dc:subject><dc:subject>Microbial (mesh)</dc:subject><dc:subject>Geologic Sediments (mesh)</dc:subject><dc:subject>Greenhouse Effect (mesh)</dc:subject><dc:subject>Groundwater (mesh)</dc:subject><dc:subject>Metabolic Networks and Pathways (mesh)</dc:subject><dc:subject>Metagenomics (mesh)</dc:subject><dc:subject>Microbial Consortia (mesh)</dc:subject><dc:subject>Microbial Interactions (mesh)</dc:subject><dc:subject>Nitrogen (mesh)</dc:subject><dc:subject>Nitrogen Cycle (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Sulfur (mesh)</dc:subject><dc:subject>Symbiosis (mesh)</dc:subject><dc:subject>0605 Microbiology (for)</dc:subject><dc:subject>1108 Medical Microbiology (for)</dc:subject><dc:subject>Microbiology (science-metrix)</dc:subject><dc:subject>3101 Biochemistry and cell biology (for-2020)</dc:subject><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/269767k3</dc:identifier><dc:identifier>https://escholarship.org/content/qt269767k3/qt269767k3.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.tim.2016.04.006</dc:identifier><dc:type>article</dc:type><dc:source>Trends in Microbiology, vol 24, iss 8</dc:source><dc:coverage>600 - 610</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7gd937jf</identifier><datestamp>2026-09-15T23:57:08Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7gd937jf</dc:identifier><dc:title>The genome assemblies of the Tui chub, Siphateles bicolor, and Arroyo chub, Gila orcuttii</dc:title><dc:creator>Baker, Henry K</dc:creator><dc:creator>Payne, Cheyenne Y</dc:creator><dc:creator>Escalona, Merly</dc:creator><dc:creator>Rodzen, Jeff</dc:creator><dc:creator>Parmenter, Steve</dc:creator><dc:creator>Barabe, Russell M</dc:creator><dc:creator>Ingel, Claire</dc:creator><dc:creator>Marimuthu, Mohan PA</dc:creator><dc:creator>Nguyen, Oanh</dc:creator><dc:creator>Chumchim, Noravit</dc:creator><dc:creator>Beraut, Eric</dc:creator><dc:creator>Sacco, Samuel</dc:creator><dc:creator>Seligmann, William</dc:creator><dc:creator>Fairbairn, Colin W</dc:creator><dc:creator>Cooper, Robert D</dc:creator><dc:creator>Miller, Courtney</dc:creator><dc:creator>Toffelmier, Erin</dc:creator><dc:creator>Garza, J Carlos</dc:creator><dc:creator>Shaffer, H Bradley</dc:creator><dc:creator>Rennison, Diana J</dc:creator><dc:creator>Shurin, Jonathan B</dc:creator><dc:date>2026-07-02</dc:date><dc:description>We present genome assemblies for two cyprinoid fishes, the tui chub (Siphateles bicolor) and the arroyo chub (Gila orcuttii). These fishes are ecologically important representatives of native fish assemblages in the western United States and are both species of conservation concern. The two species hybridize where introductions bring them into contact, with potentially important ecological and evolutionary implications that have not yet been thoroughly examined from a genomic perspective. We present de novo assemblies for both species, representing the first scaffold-level genomes within their respective genera, which were developed as part of the California Conservation Genomics Project using Pacific Biosciences HiFi and Omni-C data. Our tui chub assembly consists of 258 scaffolds spanning 1,148,084,093 base pairs, has a scaffold N50 of 45.9&amp;nbsp;mb, a contig N50 of 23.7&amp;nbsp;mb, and a BUSCO completeness score of 98.1%. Our arroyo chub assembly consists of 179 scaffolds spanning 1,263,410,250 base pairs, has a scaffold N50 of 50.5&amp;nbsp;mb, a contig N50 of 13.1&amp;nbsp;mb, and a BUSCO completeness score of 97.8%. A comparative analysis of the two species revealed relatively conserved genomes, with the exception of two inversions at chromosome 20. We annotated a total of 34,090 genes with a BUSCO completeness score of 98.1% for the tui chub, and 28,193 genes with a score of 97.4% for the arroyo chub. These assemblies will be valuable resources for characterizing the species' phylogeographic histories and delineating the role of hybridization in their evolution.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3102 Bioinformatics and Computational Biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>Cypriniformes (mesh)</dc:subject><dc:subject>Sequence Analysis</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>California conservation genomics project</dc:subject><dc:subject>CCGP</dc:subject><dc:subject>conservation genetics</dc:subject><dc:subject>Cypriniformes</dc:subject><dc:subject>Leuciscidae</dc:subject><dc:subject>freshwater fish</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Cypriniformes (mesh)</dc:subject><dc:subject>Sequence Analysis</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>Cypriniformes</dc:subject><dc:subject>Leuciscidae</dc:subject><dc:subject>CCGP</dc:subject><dc:subject>California conservation genomics project</dc:subject><dc:subject>conservation genetics</dc:subject><dc:subject>freshwater fish</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>Cypriniformes (mesh)</dc:subject><dc:subject>Sequence Analysis</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>Evolutionary Biology (science-metrix)</dc:subject><dc:subject>3104 Evolutionary biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7gd937jf</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1093/jhered/esag002</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Heredity, vol 117, iss 4</dc:source><dc:coverage>843 - 855</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt70h2j51x</identifier><datestamp>2026-09-15T23:53:10Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt70h2j51x</dc:identifier><dc:title>A Pilot Biomonitoring Study of Cumulative Phthalates Exposure among Vietnamese American Nail Salon Workers</dc:title><dc:creator>Varshavsky, Julia R</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Harwani, Suhash</dc:creator><dc:creator>Snider, Martin</dc:creator><dc:creator>Petropoulou, Syrago-Styliani E</dc:creator><dc:creator>Park, June-Soo</dc:creator><dc:creator>Petreas, Myrto</dc:creator><dc:creator>Reynolds, Peggy</dc:creator><dc:creator>Nguyen, Tuan</dc:creator><dc:creator>Quach, Thu</dc:creator><dc:date>2020-01-01</dc:date><dc:description>Many California nail salon workers are low-income Vietnamese women of reproductive age who use nail products daily that contain androgen-disrupting phthalates, which may increase risk of male reproductive tract abnormalities during pregnancy. Yet, few studies have characterized phthalate exposures among this workforce. To characterize individual metabolites and cumulative phthalates exposure among a potentially vulnerable occupational group of nail salon workers, we collected 17 post-shift urine samples from Vietnamese workers at six San Francisco Bay Area nail salons in 2011, which were analyzed for four primary phthalate metabolites: mono-n-butyl-, mono-isobutyl-, mono(2-Ethylhexyl)-, and monoethyl phthalates (MnBP, MiBP, MEHP, and MEP, respectively; μg/L). Phthalate metabolite concentrations and a potency-weighted sum of parent compound daily intake (Σandrogen-disruptor, μg/kg/day) were compared to 203 Asian Americans from the 2011-2012 National Health and Nutritional Examination Survey (NHANES) using Student's t-test and Wilcoxin signed rank test. Creatinine-corrected MnBP, MiBP, MEHP (μg/g), and cumulative phthalates exposure (Σandrogen-disruptor, μg/kg/day) levels were 2.9 (p &amp;lt; 0.0001), 1.6 (p = 0.015), 2.6 (p &amp;lt; 0.0001), and 2.0 (p &amp;lt; 0.0001) times higher, respectively, in our nail salon worker population compared to NHANES Asian Americans. Levels exceeded the NHANES 95th or 75th percentiles among some workers. This pilot study suggests that nail salon workers are disproportionately exposed to multiple phthalates, a finding that warrants further investigation to assess their potential health significance.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>4105 Pollution and Contamination (for-2020)</dc:subject><dc:subject>Endocrine Disruptors (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Asian (mesh)</dc:subject><dc:subject>Beauty Culture (mesh)</dc:subject><dc:subject>Biological Monitoring (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Occupational Exposure (mesh)</dc:subject><dc:subject>Phthalic Acids (mesh)</dc:subject><dc:subject>Pilot Projects (mesh)</dc:subject><dc:subject>San Francisco (mesh)</dc:subject><dc:subject>Vietnam (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:subject>endocrine disrupting chemicals</dc:subject><dc:subject>exposure disparities</dc:subject><dc:subject>nail polish</dc:subject><dc:subject>occupational health</dc:subject><dc:subject>reproductive health</dc:subject><dc:subject>personal care products</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Phthalic Acids (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Pilot Projects (mesh)</dc:subject><dc:subject>Occupational Exposure (mesh)</dc:subject><dc:subject>Beauty Culture (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>San Francisco (mesh)</dc:subject><dc:subject>Vietnam (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:subject>Biological Monitoring (mesh)</dc:subject><dc:subject>Asian (mesh)</dc:subject><dc:subject>endocrine disrupting chemicals</dc:subject><dc:subject>exposure disparities</dc:subject><dc:subject>nail polish</dc:subject><dc:subject>occupational health</dc:subject><dc:subject>personal care products</dc:subject><dc:subject>reproductive health</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Asian (mesh)</dc:subject><dc:subject>Beauty Culture (mesh)</dc:subject><dc:subject>Biological Monitoring (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Occupational Exposure (mesh)</dc:subject><dc:subject>Phthalic Acids (mesh)</dc:subject><dc:subject>Pilot Projects (mesh)</dc:subject><dc:subject>San Francisco (mesh)</dc:subject><dc:subject>Vietnam (mesh)</dc:subject><dc:subject>Young Adult (mesh)</dc:subject><dc:subject>Toxicology (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/70h2j51x</dc:identifier><dc:identifier>https://escholarship.org/content/qt70h2j51x/qt70h2j51x.pdf</dc:identifier><dc:identifier>info:doi/10.3390/ijerph17010325</dc:identifier><dc:type>article</dc:type><dc:source>International Journal of Environmental Research and Public Health, vol 17, iss 1</dc:source><dc:coverage>325</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7v61p1g5</identifier><datestamp>2026-09-15T23:48:28Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7v61p1g5</dc:identifier><dc:title>Measuring long-term exposure to wildfire PM2.5 in California: Time-varying inequities in environmental burden</dc:title><dc:creator>Casey, Joan A</dc:creator><dc:creator>Kioumourtzoglou, Marianthi-Anna</dc:creator><dc:creator>Padula, Amy</dc:creator><dc:creator>González, David JX</dc:creator><dc:creator>Elser, Holly</dc:creator><dc:creator>Aguilera, Rosana</dc:creator><dc:creator>Northrop, Alexander J</dc:creator><dc:creator>Tartof, Sara Y</dc:creator><dc:creator>Mayeda, Elizabeth Rose</dc:creator><dc:creator>Braun, Danielle</dc:creator><dc:creator>Dominici, Francesca</dc:creator><dc:creator>Eisen, Ellen A</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Benmarhnia, Tarik</dc:creator><dc:date>2024-02-20</dc:date><dc:description>Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM2.5) concentrations differ from relatively smoothly varying total PM2.5. Thus, we introduced a conceptual model for computing long-term wildfire PM2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM2.5 exposure based on intermittent and extreme daily wildfire PM2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM2.5 &amp;lt; 5 μg/m3; 2) days with non-zero wildfire PM2.5; 3) mean wildfire PM2.5 during peak exposure week; 4) smoke waves (≥2 consecutive days with &amp;lt;15 μg/m3 wildfire PM2.5); and 5) mean annual wildfire PM2.5 concentration. We classified tracts by their racial/ethnic composition and CalEnviroScreen (CES) score, an environmental and social vulnerability composite measure. We examined associations of CES and racial/ethnic composition with the wildfire PM2.5 metrics using mixed-effects models. Averaged 2006 to 2020, we detected little difference in exposure by CES score or racial/ethnic composition, except for non-Hispanic American Indian and Alaska Native populations, where a 1-SD increase was associated with higher exposure for 4/5 metrics. CES or racial/ethnic × year interaction term models revealed exposure disparities in some years. Compared to their California-wide representation, the exposed populations of non-Hispanic American Indian and Alaska Native (1.68×, 95% CI: 1.01 to 2.81), white (1.13×, 95% CI: 0.99 to 1.32), and multiracial (1.06×, 95% CI: 0.97 to 1.23) people were over-represented from 2006 to 2020. In conclusion, during our study period in California, we detected disproportionate long-term wildfire PM2.5 exposure for several racial/ethnic groups.</dc:description><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>4105 Pollution and Contamination (for-2020)</dc:subject><dc:subject>American Indian or Alaska Native (rcdc)</dc:subject><dc:subject>Minority Health (rcdc)</dc:subject><dc:subject>Arctic (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Climate-Related Exposures and Conditions (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Health Effects of Indoor Air Pollution (rcdc)</dc:subject><dc:subject>Rural Health (rcdc)</dc:subject><dc:subject>2.2 Factors relating to the physical environment (hrcs-rac)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Wildfires (mesh)</dc:subject><dc:subject>Particulate Matter (mesh)</dc:subject><dc:subject>Smoke (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Racial Groups (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Air Pollutants (mesh)</dc:subject><dc:subject>wildfires</dc:subject><dc:subject>particulate matter</dc:subject><dc:subject>environmental justice</dc:subject><dc:subject>American Indian or Alaska Native</dc:subject><dc:subject>California</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Air Pollutants (mesh)</dc:subject><dc:subject>Smoke (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Particulate Matter (mesh)</dc:subject><dc:subject>Wildfires (mesh)</dc:subject><dc:subject>Racial Groups (mesh)</dc:subject><dc:subject>American Indian or Alaska Native</dc:subject><dc:subject>California</dc:subject><dc:subject>environmental justice</dc:subject><dc:subject>particulate matter</dc:subject><dc:subject>wildfires</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Wildfires (mesh)</dc:subject><dc:subject>Particulate Matter (mesh)</dc:subject><dc:subject>Smoke (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Racial Groups (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Air Pollutants (mesh)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7v61p1g5</dc:identifier><dc:identifier>https://escholarship.org/content/qt7v61p1g5/qt7v61p1g5.pdf</dc:identifier><dc:identifier>info:doi/10.1073/pnas.2306729121</dc:identifier><dc:type>article</dc:type><dc:source>Proceedings of the National Academy of Sciences of the United States of America, vol 121, iss 8</dc:source><dc:coverage>e2306729121</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8c65439n</identifier><datestamp>2026-09-15T23:47:22Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8c65439n</dc:identifier><dc:title>3D correlations in the Lyman-α forest from early DESI data</dc:title><dc:creator>Gordon, C</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>González-Morales, AX</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Bault, A</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>de la Cruz, R</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Iršič, V</dc:creator><dc:creator>Karaçaylı, NG</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Montero-Camacho, P</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Napolitano, L</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Pieri, M</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Ramírez-Pérez, C</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sinigaglia, F</dc:creator><dc:creator>Tan, T</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Walther, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yèche, C</dc:creator><dc:creator>Zhou, Z</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2023-11-01</dc:date><dc:description>We present the first measurements of Lyman-α (Lyα) forest correlations using early data from the Dark Energy Spectroscopic Instrument (DESI). We measure the auto-correlation of Lyα absorption using 88 509 quasars at z &amp;gt; 2, and its cross-correlation with quasars using a further 147 899 tracer quasars at z ≳ 1.77. Then, we fit these correlations using a 13-parameter model based on linear perturbation theory and find that it provides a good description of the data across a broad range of scales. We detect the BAO peak with a signal-to-noise ratio of 3.8σ, and show that our measurements of the auto- and cross-correlations are fully-consistent with previous measurements by the Extended Baryon Oscillation Spectroscopic Survey (eBOSS). Even though we only use here a small fraction of the final DESI dataset, our uncertainties are only a factor of 1.7 larger than those from the final eBOSS measurement. We validate the existing analysis methods of Lyα correlations in preparation for making a robust measurement of the BAO scale with the first year of DESI data.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>dark energy experiments</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>dark energy experiments</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8c65439n</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1088/1475-7516/2023/11/045</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2023, iss 11</dc:source><dc:coverage>045</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4x8868mf</identifier><datestamp>2026-09-15T23:44:20Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4x8868mf</dc:identifier><dc:title>Characterizing the Geothermal Lithium Resource at the Salton Sea</dc:title><dc:creator>Dobson, Patrick</dc:creator><dc:creator>Araya, Naod</dc:creator><dc:creator>Brounce, Maryjo</dc:creator><dc:creator>Busse, Margaret</dc:creator><dc:creator>Camarillo, Mary Kay</dc:creator><dc:creator>English, Lauren</dc:creator><dc:creator>Humphreys, Jennifer</dc:creator><dc:creator>Kalderon-Asael, Boriana</dc:creator><dc:creator>McKibben, Michael</dc:creator><dc:creator>Millstein, Dev</dc:creator><dc:creator>Nakata, Nori</dc:creator><dc:creator>O'Sullivan, John</dc:creator><dc:creator>Planavsky, Noah</dc:creator><dc:creator>Popineau, Joris</dc:creator><dc:creator>Renaud, Theo</dc:creator><dc:creator>Riffault, Jeremy</dc:creator><dc:creator>Slattery, Margaret</dc:creator><dc:creator>Sonnenthal, Eric</dc:creator><dc:creator>Spycher, Nicolas</dc:creator><dc:creator>Stokes-Draut, Jennifer</dc:creator><dc:creator>Stringfellow, William</dc:creator><dc:creator>White, Malcolm</dc:creator><dc:date>2023-11-22</dc:date><dc:description>The energy transition towards a more sustainable and renewable future is a pivotal global endeavor. Central to this shift for the United States is the critical role of domestically sourced lithium, a key mineral in the production of high-performance batteries essential for electric vehicles and renewable energy storage systems. This has driven the United States to invest heavily in a domestic supply chain for battery-grade lithium to enhance energy security, reduce supply chain vulnerabilities, and foster economic growth by tapping into local resources. A notable example is the Biden Administration’s “American Battery Materials Initiative,” which was included in the $2.8-billion Bipartisan Infrastructure Law (The White House, 2022). 
The “Salton Sea Known Geothermal Resource Area” in Imperial County, California has been identified as a potential domestic U.S. resource of lithium due to the brine-hosted lithium in the deep subsurface geothermal reservoir. An analysis funded by the U.S. Department of Energy provides an overview of opportunities and challenges associated with developing the lithium resource in the Salton Sea geothermal reservoir, as well as potential environmental and societal impacts to the county and surrounding region. 
The geologic history of the region suggests that lithium in the subsurface brines could have come from multiple sources, including water and sediments from the Colorado River, which have been periodically deposited over the past several million years; rocks from the mountain ranges surrounding the Imperial Valley; and lithium-bearing volcanic rocks and igneous intrusions from past geologic events. Further, several processes may have concentrated lithium in the brine over time, including evaporative concentration of lithium-bearing water that flowed into the basin and leaching of lithium from the sediments and rocks by the circulating geothermal brines. 
Geothermal brine production at the Salton Sea Geothermal Field, the area with existing geothermal power plants, has averaged just over 120 million metric tons per year since 2004. Using an approximate lithium brine concentration of 198 parts per million (ppm), the amount of dissolved lithium contained in these produced brines is estimated to be 127,000 metric tons of lithium carbonate equivalent (LCE) per year. The total dissolved lithium content in the well-characterized portion of the Salton Sea Geothermal Reservoir is estimated at 4.1 million metric tons of LCE, and the estimated total resource increases to 18 million metric tons of LCE if assumptions for porosity and total reservoir size are increased to reflect the probable resource extent. 
Analysts measured lithium concentrations in the reservoir rocks, which were shown to vary with depth and mineralogy. These data were used to help refine conceptual and computer models of the reservoir; specifically, two complementary computer models of the reservoir were developed. Analysts used the first model to simulate the approximate 30-year history of geothermal power production in the area using historical production and reinjection data, then used that model to simulate a 30-year forecasting period. This forecast assumed continued production and reinjection rates at current levels but removes 95% of the lithium from the produced geothermal brine starting January 1, 2024. The model found that lithium recovery declines by more than half, from 0.8 to 0.3 kilograms per second (kg/s). Forecast scenarios that are optimized to both recover lithium and harness geothermal energy are expected to sustain lithium production rates much more effectively.
The second model included more detailed simulations of the movement of brine and chemical reactivity of lithium within the reservoir. It showed that the reactions of relatively stable lithium-bearing minerals are slow, and that the primary replenishment mechanism for lithium in the brines is the upward flux of convecting lithium-rich brine from below the producing reservoir. However, these replenishment rates are not fast enough to produce significant increases in lithium, which could limit the long-term sustainability of the lithium resource. It is important to note that these models are preliminary and are based on current understanding of fluid replenishment rates, the minerals present in the geothermal system, and their chemical properties and reactivity. Further work should be undertaken to improve them and the associated predictions. 
The report also considered potential impacts on regional water resources, air quality, chemical use, and solid waste disposal needs, as well as the seismic risk associated with geothermal power production and lithium extraction activity. These investigations highlighted the need to proceed with good monitoring and verification systems and with appropriate mitigation technologies. However, the analysis illustrates that if these things are done properly, lithium development is not likely to create significant negative environmental impacts.
Specifically, expanding geothermal energy production and lithium extraction will have a modest impact on water availability in the region. Initial estimates suggested that ~3% of historically available water supply for the region would be needed for currently proposed geothermal energy and lithium recovery operations; the majority of current water usage is for agriculture. It is not anticipated that expanding geothermal capacity or lithium production would impact the availability or quality of water used for human consumption and will not directly affect the water quality of the Salton Sea. However, the long-term drought conditions in the western United States may restrict future availability of water to the region, which is sourced from the Colorado River.
In terms of regional air emissions of all pollutants identified in the analysis (particulate matter, hydrogen sulfide, ammonia, and benzene, expanding geothermal energy and adding lithium extraction overall have a small impact. Chemical use involved in geothermal power production and lithium extraction is consistent with chemical use in industrial settings, and the analysis did not identify any persistent organic pollutants or acutely toxic chemicals among those currently being used. 
Moving fluids within the subsurface can impact subsurface pressures and stresses, potentially triggering seismic activity. Early in geothermal energy production, increasing seismicity rates in the Salton Sea Geothermal Field correlated strongly with energy production activity; however, that correlation weakened after 1996. Even following the onset of geothermal energy production, seismic hazard in the Salton Sea Geothermal Field has not increased beyond that of the surrounding region.
In addition to technical outcomes from the analysis, the report describes an initial effort to incorporate community engagement into lithium research by understanding the local context and priorities and identifying how to effectively communicate to share information and gather feedback. The report includes information about the social and historical context of the region to enable a more holistic understanding of the resource and its potential impact, and identifies key community questions by observing public meetings, visiting the region, and consulting with local organizations. The report provides recommendations about how future research efforts can address community concerns and implement more community-engaged practices. These include developing formal partnerships with local organizations and establishing a community advisory board to facilitate ongoing dialogue and opportunities for feedback. The future work will build on and further refine the models and scenarios presented in the report and strive to deepen engagement with local communities.</dc:description><dc:subject>Lithium</dc:subject><dc:subject>Geothermal</dc:subject><dc:subject>Environmental impacts</dc:subject><dc:subject>Reservoir model</dc:subject><dc:subject>Water use</dc:subject><dc:subject>Induced seismicity</dc:subject><dc:subject>Community outreach</dc:subject><dc:subject>Air emissions</dc:subject><dc:subject>Chemical use</dc:subject><dc:subject>Solid waste disposal</dc:subject><dc:subject>Resource assessment</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4x8868mf</dc:identifier><dc:identifier>https://escholarship.org/content/qt4x8868mf/qt4x8868mf.pdf</dc:identifier><dc:identifier>info:doi/10.2172/2222403</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt67m7r7vn</identifier><datestamp>2026-09-15T23:43:29Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt67m7r7vn</dc:identifier><dc:title>Petawatt Laser Guiding and Electron Beam Acceleration to 8 GeV in a Laser-Heated Capillary Discharge Waveguide</dc:title><dc:creator>Gonsalves, AJ</dc:creator><dc:creator>Nakamura, K</dc:creator><dc:creator>Daniels, J</dc:creator><dc:creator>Benedetti, C</dc:creator><dc:creator>Pieronek, C</dc:creator><dc:creator>de Raadt, TCH</dc:creator><dc:creator>Steinke, S</dc:creator><dc:creator>Bin, JH</dc:creator><dc:creator>Bulanov, SS</dc:creator><dc:creator>van Tilborg, J</dc:creator><dc:creator>Geddes, CGR</dc:creator><dc:creator>Schroeder, CB</dc:creator><dc:creator>Tóth, Cs</dc:creator><dc:creator>Esarey, E</dc:creator><dc:creator>Swanson, K</dc:creator><dc:creator>Fan-Chiang, L</dc:creator><dc:creator>Bagdasarov, G</dc:creator><dc:creator>Bobrova, N</dc:creator><dc:creator>Gasilov, V</dc:creator><dc:creator>Korn, G</dc:creator><dc:creator>Sasorov, P</dc:creator><dc:creator>Leemans, WP</dc:creator><dc:date>2019-03-01</dc:date><dc:description>Guiding of relativistically intense laser pulses with peak power of 0.85 PW over 15 diffraction lengths was demonstrated by increasing the focusing strength of a capillary discharge waveguide using laser inverse bremsstrahlung heating. This allowed for the production of electron beams with quasimonoenergetic peaks up to 7.8&amp;nbsp;GeV, double the energy that was previously demonstrated. Charge was 5&amp;nbsp;pC at 7.8&amp;nbsp;GeV and up to 62&amp;nbsp;pC in 6&amp;nbsp;GeV peaks, and typical beam divergence was 0.2&amp;nbsp;mrad.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>01 Mathematical Sciences (for)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/67m7r7vn</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1103/physrevlett.122.084801</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review Letters, vol 122, iss 8</dc:source><dc:coverage>084801</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3rm3m38c</identifier><datestamp>2026-09-15T23:39:25Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3rm3m38c</dc:identifier><dc:title>Early career Latinas in STEM: Challenges and solutions</dc:title><dc:creator>Werner Washburne, Maggie</dc:creator><dc:creator>Trejo, JoAnn</dc:creator><dc:creator>Zambrana, Ruth Enid</dc:creator><dc:creator>Zavala, Maria Elena</dc:creator><dc:creator>Martinic, Alice</dc:creator><dc:creator>Riestra, Angelica</dc:creator><dc:creator>Delgado, Tracie</dc:creator><dc:creator>Edwards, Staci</dc:creator><dc:creator>Escobar, Thelma</dc:creator><dc:creator>Jamison-McClung, Denneal</dc:creator><dc:creator>Vazquez, Mariel</dc:creator><dc:creator>Vera, Iset</dc:creator><dc:creator>Guerra, Michelle</dc:creator><dc:creator>Marinez, Diana I</dc:creator><dc:creator>Gonzalez, Elma</dc:creator><dc:creator>Rodriguez, Raymond L</dc:creator><dc:date>2023-11-01</dc:date><dc:description>Mexican, Puerto Rican, and Central American Ancestry (MPRCA) individuals represent 82% of US Latinos. An intergenerational group of MPRCA women and allies met to discuss persistent underrepresentation of MPRCA women in STEM, identifying multi-level challenges and solutions. Implementation of these solutions is important and will benefit MPRCA women and the entire academic community.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Stem Cell Research - Nonembryonic - Human (rcdc)</dc:subject><dc:subject>Stem Cell Research (rcdc)</dc:subject><dc:subject>Minority Health (rcdc)</dc:subject><dc:subject>Stem Cell Research - Nonembryonic - Non-Human (rcdc)</dc:subject><dc:subject>5 Gender Equality (sdg)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Hispanic or Latino (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Science (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Science (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Hispanic or Latino (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Hispanic or Latino (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Science (mesh)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>Developmental Biology (science-metrix)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3rm3m38c</dc:identifier><dc:identifier>https://escholarship.org/content/qt3rm3m38c/qt3rm3m38c.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.cell.2023.10.016</dc:identifier><dc:type>article</dc:type><dc:source>Cell, vol 186, iss 23</dc:source><dc:coverage>4985 - 4991</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3590t7qc</identifier><datestamp>2026-09-15T23:38:31Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3590t7qc</dc:identifier><dc:title>Carbon Depletion of Ices by Diamond Precipitation in Sub-Neptune Exoplanets</dc:title><dc:creator>Zhou, Albert</dc:creator><dc:creator>Edmund, Eric</dc:creator><dc:creator>Glenzer, Siegfried H</dc:creator><dc:creator>Frost, Mungo</dc:creator><dc:date>2026-09-16</dc:date><dc:description>Hydrocarbons are observed on the surfaces of many icy moons and planets. At high-pressure high-temperature conditions, such as occur in larger planets, they are known to dissociate to form diamond and hydrogen. Within our solar system Uranus and Neptune easily reach the requisite 10 GPa and 2000 K for this process, while icy moons do not. &amp;nbsp;Densities indicative of icy compositions are commonly observed for exoplanets, many of which have radii intermediate between the local icy moons and icy planets. These so-called 'mini-neptunes' are a common class of exoplanet and, where hydrocarbons are incorporated within their ices, are candidates for diamond formation. Here we simulate model icy exoplanets to investigate the size required to induce diamond formation. &amp;nbsp;Where the conditions are met, the denser diamond will sink through the ices deeper into the planet under gravity. This provides a source of internal heating, and will sequester the carbon deep within the planet. As a consequence, exoplanets with deep ice layers likely have shallow regions depleted in carbon.</dc:description><dc:subject>Exoplanets</dc:subject><dc:subject>Mini-neptune</dc:subject><dc:subject>diamond</dc:subject><dc:subject>habitability</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3590t7qc</dc:identifier><dc:identifier>https://escholarship.org/content/qt3590t7qc/qt3590t7qc.pdf</dc:identifier><dc:identifier>info:doi/10.5070/F3.49013</dc:identifier><dc:type>article</dc:type><dc:source>Geodynamica, vol 1, iss 1</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9fg8k5xh</identifier><datestamp>2026-09-15T23:35:58Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9fg8k5xh</dc:identifier><dc:title>ESnet Requirements Review Program Through the IRI Lens: A Meta-Analysis of Workflow Patterns Across DOE Office of Science Programs (Final Report)</dc:title><dc:creator>Dart, Eli</dc:creator><dc:creator>Zurawski, Jason</dc:creator><dc:creator>Hawk, Carol</dc:creator><dc:creator>Brown, Benjamin</dc:creator><dc:creator>Monga, Inder</dc:creator><dc:date>2023-11-09</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9fg8k5xh</dc:identifier><dc:identifier>https://escholarship.org/content/qt9fg8k5xh/qt9fg8k5xh.pdf</dc:identifier><dc:identifier>info:doi/10.2172/2008205</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2md1k1ss</identifier><datestamp>2026-09-15T23:35:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2md1k1ss</dc:identifier><dc:title>Coupling plant litter quantity to a novel metric for litter quality explains C storage changes in a thawing permafrost peatland</dc:title><dc:creator>Hough, Moira</dc:creator><dc:creator>McCabe, Samantha</dc:creator><dc:creator>Vining, S Rose</dc:creator><dc:creator>Pedersen, Emily Pickering</dc:creator><dc:creator>Wilson, Rachel M</dc:creator><dc:creator>Lawrence, Ryan</dc:creator><dc:creator>Chang, Kuang‐Yu</dc:creator><dc:creator>Bohrer, Gil</dc:creator><dc:creator>Frolking, Steve</dc:creator><dc:creator>Hodgkins, Suzanne B</dc:creator><dc:creator>McCalley, Carmody K</dc:creator><dc:creator>Cooper, William T</dc:creator><dc:creator>Chanton, Jeffrey P</dc:creator><dc:creator>Sullivan, Matthew B</dc:creator><dc:creator>Tyson, Gene W</dc:creator><dc:creator>Brodie, Eoin L</dc:creator><dc:creator>Woodcroft, Ben J</dc:creator><dc:creator>Dominguez, Sky</dc:creator><dc:creator>Riley, William J</dc:creator><dc:creator>Crill, Patrick M</dc:creator><dc:creator>Varner, Ruth K</dc:creator><dc:creator>Blazewicz, Steven J</dc:creator><dc:creator>Dorrepaal, Ellen</dc:creator><dc:creator>Tfaily, Malak M</dc:creator><dc:creator>Saleska, Scott R</dc:creator><dc:creator>Rich, Virginia I</dc:creator><dc:date>2022-02-01</dc:date><dc:description>Permafrost thaw is a major potential feedback source to climate change as it can drive the increased release of greenhouse gases carbon dioxide (CO2 ) and methane (CH4 ). This carbon release from the decomposition of thawing soil organic material can be mitigated by increased net primary productivity (NPP) caused by warming, increasing atmospheric CO2 , and plant community transition. However, the net effect on C storage also depends on how these plant community changes alter plant litter quantity, quality, and decomposition rates. Predicting decomposition rates based on litter quality remains challenging, but a promising new way forward is to incorporate measures of the energetic favorability to soil microbes of plant biomass decomposition. We asked how the variation in one such measure, the nominal oxidation state of carbon (NOSC), interacts with changing quantities of plant material inputs to influence the net C balance of a thawing permafrost peatland. We found: (1) Plant productivity (NPP) increased post-thaw, but instead of contributing to increased standing biomass, it increased plant biomass turnover via increased litter inputs to soil; (2) Plant litter thermodynamic favorability (NOSC) and decomposition rate both increased post-thaw, despite limited changes in bulk C:N ratios; (3) these increases caused the higher NPP to cycle more rapidly&amp;nbsp;through both plants and soil, contributing to higher CO2 and CH4 &amp;nbsp;fluxes from decomposition. Thus, the increased C-storage expected from higher productivity was limited and the high global warming potential of CH4 contributed a net positive warming effect. Although post-thaw peatlands are currently C sinks due to high NPP offsetting high CO2 release, this status is very sensitive to the plant community's litter input rate and quality. Integration of novel bioavailability metrics based on litter chemistry, including NOSC, into studies of ecosystem dynamics, is needed to improve the understanding of controls on arctic C stocks under continued ecosystem transition.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>Arctic Regions (mesh)</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Permafrost (mesh)</dc:subject><dc:subject>Plants (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>C storage</dc:subject><dc:subject>decomposition</dc:subject><dc:subject>litter chemistry</dc:subject><dc:subject>NOSC</dc:subject><dc:subject>peat</dc:subject><dc:subject>permafrost thaw</dc:subject><dc:subject>plant community change</dc:subject><dc:subject>Stordalen Mire</dc:subject><dc:subject>IsoGenie Coordinators</dc:subject><dc:subject>Plants (mesh)</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Arctic Regions (mesh)</dc:subject><dc:subject>Permafrost (mesh)</dc:subject><dc:subject>C storage</dc:subject><dc:subject>NOSC</dc:subject><dc:subject>Stordalen Mire</dc:subject><dc:subject>decomposition</dc:subject><dc:subject>litter chemistry</dc:subject><dc:subject>peat</dc:subject><dc:subject>permafrost thaw</dc:subject><dc:subject>plant community change</dc:subject><dc:subject>Arctic Regions (mesh)</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Permafrost (mesh)</dc:subject><dc:subject>Plants (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>05 Environmental Sciences (for)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>Ecology (science-metrix)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>37 Earth sciences (for-2020)</dc:subject><dc:subject>41 Environmental sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2md1k1ss</dc:identifier><dc:identifier>https://escholarship.org/content/qt2md1k1ss/qt2md1k1ss.pdf</dc:identifier><dc:identifier>info:doi/10.1111/gcb.15970</dc:identifier><dc:type>article</dc:type><dc:source>Global Change Biology, vol 28, iss 3</dc:source><dc:coverage>950 - 968</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt41r662pm</identifier><datestamp>2026-09-15T23:31:07Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt41r662pm</dc:identifier><dc:title>Virus diversity and activity is driven by snowmelt and host dynamics in a high-altitude watershed soil ecosystem</dc:title><dc:creator>Coclet, Clement</dc:creator><dc:creator>Sorensen, Patrick O</dc:creator><dc:creator>Karaoz, Ulas</dc:creator><dc:creator>Wang, Shi</dc:creator><dc:creator>Brodie, Eoin L</dc:creator><dc:creator>Eloe-Fadrosh, Emiley A</dc:creator><dc:creator>Roux, Simon</dc:creator><dc:date>2023-10-27</dc:date><dc:description>BackgroundViruses impact nearly all organisms on Earth, including microbial communities and their associated biogeochemical processes. In soils, highly diverse viral communities have been identified, with a global distribution seemingly driven by multiple biotic and abiotic factors, especially soil temperature and moisture. However, our current understanding of the stability of soil viral communities across time and their response to strong seasonal changes in environmental parameters remains limited. Here, we investigated the diversity and activity of environmental soil DNA and RNA viruses, focusing especially on bacteriophages, across dynamics’ seasonal changes in a snow-dominated mountainous watershed by examining paired metagenomes and metatranscriptomes.ResultsWe identified a large number of DNA and RNA viruses taxonomically divergent from existing environmental viruses, including a significant proportion of fungal RNA viruses, and a large and unsuspected diversity of positive single-stranded RNA phages (Leviviricetes), highlighting the under-characterization of the global soil virosphere. Among these, we were able to distinguish subsets of active DNA and RNA phages that changed across seasons, consistent with a “seed-bank” viral community structure in which new phage activity, for example, replication and host lysis, is sequentially triggered by changes in environmental conditions. At the population level, we further identified virus-host dynamics matching two existing ecological models: “Kill-The-Winner” which proposes that lytic phages are actively infecting abundant bacteria, and “Piggyback-The-Persistent” which argues that when the host is growing slowly, it is more beneficial to remain in a dormant state. The former was associated with summer months of high and rapid microbial activity, and the latter with winter months of limited and slow host growth.ConclusionTaken together, these results suggest that the high diversity of viruses in soils is likely associated with a broad range of host interaction types each adapted to specific host ecological strategies and environmental conditions. As our understanding of how environmental and host factors drive viral activity in soil ecosystems progresses, integrating these viral impacts in complex natural microbiome models will be key to accurately predict ecosystem biogeochemistry.2RJdjcjTGzDNGfvgvrWr_YVideo Abstract</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>Infectious Diseases (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Emerging Infectious Diseases (rcdc)</dc:subject><dc:subject>Infection (hrcs-hc)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Altitude (mesh)</dc:subject><dc:subject>Viruses (mesh)</dc:subject><dc:subject>Bacteriophages (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>Phages</dc:subject><dc:subject>Viruses</dc:subject><dc:subject>Metagenomics and metatranscriptomics</dc:subject><dc:subject>Virus activity</dc:subject><dc:subject>Virus-host interactions</dc:subject><dc:subject>Mountainous watershed</dc:subject><dc:subject>Soils</dc:subject><dc:subject>Seasonal dynamics</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Viruses (mesh)</dc:subject><dc:subject>Bacteriophages (mesh)</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Altitude (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Metagenomics and metatranscriptomics</dc:subject><dc:subject>Mountainous watershed</dc:subject><dc:subject>Phages</dc:subject><dc:subject>Seasonal dynamics</dc:subject><dc:subject>Soils</dc:subject><dc:subject>Virus activity</dc:subject><dc:subject>Virus-host interactions</dc:subject><dc:subject>Viruses</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Altitude (mesh)</dc:subject><dc:subject>Viruses (mesh)</dc:subject><dc:subject>Bacteriophages (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>0602 Ecology (for)</dc:subject><dc:subject>0605 Microbiology (for)</dc:subject><dc:subject>1108 Medical Microbiology (for)</dc:subject><dc:subject>3104 Evolutionary biology (for-2020)</dc:subject><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/41r662pm</dc:identifier><dc:identifier>https://escholarship.org/content/qt41r662pm/qt41r662pm.pdf</dc:identifier><dc:identifier>info:doi/10.1186/s40168-023-01666-z</dc:identifier><dc:type>article</dc:type><dc:source>Microbiome, vol 11, iss 1</dc:source><dc:coverage>237</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1ds6v8ww</identifier><datestamp>2026-09-15T23:30:38Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1ds6v8ww</dc:identifier><dc:title>Challenging problems of quality assurance and quality control (QA/QC) of meteorological time series data</dc:title><dc:creator>Faybishenko, B</dc:creator><dc:creator>Versteeg, R</dc:creator><dc:creator>Pastorello, G</dc:creator><dc:creator>Dwivedi, D</dc:creator><dc:creator>Varadharajan, C</dc:creator><dc:creator>Agarwal, D</dc:creator><dc:date>2022-04-01</dc:date><dc:description>Representativeness and quality of collected meteorological data impact accuracy and precision of climate, hydrological, and biogeochemical analyses and predictions. We developed a comprehensive Quality Assurance (QA) and Quality Control (QC) statistical framework, consisting of three major phases: Phase I—Preliminary data exploration, i.e., processing of raw datasets, with the challenging problems of time formatting and combining datasets of different lengths and different time intervals; Phase II—QA of the datasets, including detecting and flagging of duplicates, outliers, and extreme data; and Phase III—the development of time series of a desired frequency, imputation of missing values, visualization and a final statistical summary. The paper includes two use cases based on the time series data collected at the Billy Barr meteorological station (East River Watershed, Colorado), and the Barro Colorado Island (BCI, Panama) meteorological station. The developed statistical framework is suitable for both real-time and post-data-collection QA/QC analysis of meteorological datasets.</dc:description><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>49 Mathematical Sciences (for-2020)</dc:subject><dc:subject>QA</dc:subject><dc:subject>QC</dc:subject><dc:subject>Statistical methods</dc:subject><dc:subject>Time series</dc:subject><dc:subject>Meteorological data</dc:subject><dc:subject>01 Mathematical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Strategic</dc:subject><dc:subject>Defence &amp; Security Studies (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1ds6v8ww</dc:identifier><dc:identifier>https://escholarship.org/content/qt1ds6v8ww/qt1ds6v8ww.pdf</dc:identifier><dc:identifier>info:doi/10.1007/s00477-021-02106-w</dc:identifier><dc:type>article</dc:type><dc:source>Stochastic Environmental Research and Risk Assessment, vol 36, iss 4</dc:source><dc:coverage>1049 - 1062</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt26x646nc</identifier><datestamp>2026-09-15T23:23:01Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt26x646nc</dc:identifier><dc:title>Search for the Chiral Magnetic Effect via Charge-Dependent Azimuthal Correlations Relative to Spectator and Participant Planes in Au+Au Collisions at sNN=200 GeV</dc:title><dc:creator>Abdallah, MS</dc:creator><dc:creator>Adam, J</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, JR</dc:creator><dc:creator>Adkins, JK</dc:creator><dc:creator>Agakishiev, G</dc:creator><dc:creator>Aggarwal, I</dc:creator><dc:creator>Aggarwal, MM</dc:creator><dc:creator>Ahammed, Z</dc:creator><dc:creator>Alekseev, I</dc:creator><dc:creator>Anderson, DM</dc:creator><dc:creator>Aparin, A</dc:creator><dc:creator>Aschenauer, EC</dc:creator><dc:creator>Ashraf, MU</dc:creator><dc:creator>Atetalla, FG</dc:creator><dc:creator>Attri, A</dc:creator><dc:creator>Averichev, GS</dc:creator><dc:creator>Bairathi, V</dc:creator><dc:creator>Baker, W</dc:creator><dc:creator>Ball, JG</dc:creator><dc:creator>Barish, K</dc:creator><dc:creator>Behera, A</dc:creator><dc:creator>Bellwied, R</dc:creator><dc:creator>Bhagat, P</dc:creator><dc:creator>Bhasin, A</dc:creator><dc:creator>Bielcik, J</dc:creator><dc:creator>Bielcikova, J</dc:creator><dc:creator>Bordyuzhin, IG</dc:creator><dc:creator>Brandenburg, JD</dc:creator><dc:creator>Brandin, AV</dc:creator><dc:creator>Bunzarov, I</dc:creator><dc:creator>Butterworth, J</dc:creator><dc:creator>Cai, XZ</dc:creator><dc:creator>Caines, H</dc:creator><dc:creator>de la Barca Sánchez, M Calderón</dc:creator><dc:creator>Cebra, D</dc:creator><dc:creator>Chakaberia, I</dc:creator><dc:creator>Chaloupka, P</dc:creator><dc:creator>Chan, BK</dc:creator><dc:creator>Chang, F-H</dc:creator><dc:creator>Chang, Z</dc:creator><dc:creator>Chankova-Bunzarova, N</dc:creator><dc:creator>Chatterjee, A</dc:creator><dc:creator>Chattopadhyay, S</dc:creator><dc:creator>Chen, D</dc:creator><dc:creator>Chen, J</dc:creator><dc:creator>Chen, JH</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Chen, Z</dc:creator><dc:creator>Cheng, J</dc:creator><dc:creator>Chevalier, M</dc:creator><dc:creator>Choudhury, S</dc:creator><dc:creator>Christie, W</dc:creator><dc:creator>Chu, X</dc:creator><dc:creator>Crawford, HJ</dc:creator><dc:creator>Csanád, M</dc:creator><dc:creator>Daugherity, M</dc:creator><dc:creator>Dedovich, TG</dc:creator><dc:creator>Deppner, IM</dc:creator><dc:creator>Derevschikov, AA</dc:creator><dc:creator>Dhamija, A</dc:creator><dc:creator>Di Carlo, L</dc:creator><dc:creator>Didenko, L</dc:creator><dc:creator>Dong, X</dc:creator><dc:creator>Drachenberg, JL</dc:creator><dc:creator>Dunlop, JC</dc:creator><dc:creator>Elsey, N</dc:creator><dc:creator>Engelage, J</dc:creator><dc:creator>Eppley, G</dc:creator><dc:creator>Esumi, S</dc:creator><dc:creator>Ewigleben, A</dc:creator><dc:creator>Eyser, O</dc:creator><dc:creator>Fatemi, R</dc:creator><dc:creator>Fawzi, FM</dc:creator><dc:creator>Fazio, S</dc:creator><dc:creator>Federic, P</dc:creator><dc:creator>Fedorisin, J</dc:creator><dc:creator>Feng, CJ</dc:creator><dc:creator>Feng, Y</dc:creator><dc:creator>Filip, P</dc:creator><dc:creator>Finch, E</dc:creator><dc:creator>Fisyak, Y</dc:creator><dc:creator>Francisco, A</dc:creator><dc:creator>Fu, C</dc:creator><dc:creator>Fulek, L</dc:creator><dc:creator>Gagliardi, CA</dc:creator><dc:creator>Galatyuk, T</dc:creator><dc:creator>Geurts, F</dc:creator><dc:creator>Ghimire, N</dc:creator><dc:creator>Gibson, A</dc:creator><dc:creator>Gopal, K</dc:creator><dc:creator>Gou, X</dc:creator><dc:creator>Grosnick, D</dc:creator><dc:creator>Gupta, A</dc:creator><dc:creator>Guryn, W</dc:creator><dc:creator>Hamad, AI</dc:creator><dc:creator>Hamed, A</dc:creator><dc:creator>Han, Y</dc:creator><dc:creator>Harabasz, S</dc:creator><dc:creator>Harasty, MD</dc:creator><dc:date>2022-03-04</dc:date><dc:description>The chiral magnetic effect (CME) refers to charge separation along a strong magnetic field due to imbalanced chirality of quarks in local parity and charge-parity violating domains in quantum chromodynamics. The experimental measurement of the charge separation is made difficult by the presence of a major background from elliptic azimuthal anisotropy. This background and the CME signal have different sensitivities to the spectator and participant planes, and could thus be determined by measurements with respect to these planes. We report such measurements in Au+Au collisions at a nucleon-nucleon center-of-mass energy of 200&amp;nbsp;GeV at the Relativistic Heavy-Ion Collider. It is found that the charge separation, with the flow background removed, is consistent with zero in peripheral (large impact parameter) collisions. Some indication of finite CME signals is seen in midcentral (intermediate impact parameter) collisions. Significant residual background effects may, however, still be present.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>STAR Collaboration</dc:subject><dc:subject>NSD-Relativistic Nuclear Collisions (c-lbnl-label)</dc:subject><dc:subject>01 Mathematical Sciences (for)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/26x646nc</dc:identifier><dc:identifier>https://escholarship.org/content/qt26x646nc/qt26x646nc.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevlett.128.092301</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review Letters, vol 128, iss 9</dc:source><dc:coverage>092301</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1mx4126v</identifier><datestamp>2026-09-15T23:19:56Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1mx4126v</dc:identifier><dc:title>Introduction to Territories issue on Gastrodiplomacy</dc:title><dc:creator>Rockower, Paul</dc:creator><dc:date>2025-12-31</dc:date><dc:subject>Gastrodiplomacy</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1mx4126v</dc:identifier><dc:identifier>https://escholarship.org/content/qt1mx4126v/qt1mx4126v.pdf</dc:identifier><dc:identifier>info:doi/10.5070/T2.61874</dc:identifier><dc:type>article</dc:type><dc:source>Territories: A Trans-Cultural Journal of Regional Studies, vol 4, iss 1</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt80c2f4q1</identifier><datestamp>2026-09-15T23:19:49Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt80c2f4q1</dc:identifier><dc:title>Review: Levine, Jill&amp;nbsp;Unfaithful. A Translator's Memoir (2025)</dc:title><dc:creator>Felman-Panagotacos, Madison</dc:creator><dc:date>2025-12-31</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/80c2f4q1</dc:identifier><dc:identifier>https://escholarship.org/content/qt80c2f4q1/qt80c2f4q1.pdf</dc:identifier><dc:identifier>info:doi/10.5070/T2.61920</dc:identifier><dc:type>article</dc:type><dc:source>Territories: A Trans-Cultural Journal of Regional Studies, vol 4, iss 1</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt99p1t8tt</identifier><datestamp>2026-09-15T23:19:44Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt99p1t8tt</dc:identifier><dc:title>Korean War POWs’ Individual Gastrodiplomacy: Comparing Morris R. Wills and Clarence Adams’ Odyssey&amp;nbsp;</dc:title><dc:creator>He, Yanli</dc:creator><dc:date>2025-12-31</dc:date><dc:description>How does food operate as a medium for informal diplomacy between individuals and nations? In what ways do citizen culinary diplomacy and individual gastrodiplomacy diverge from official or state-sponsored culinary exchanges? This article examines these questions through the experiences of two American POWs from the Korean War, Morris R. Wills and Clarence Adams, focusing on food as a site of private, people-to-people interaction. As POWs in Korea and later as foreign guests in China, Adams and Wills navigated identities suspended between official representation and personal agency, granting them unique access to Chinese diplomats and political elites. How did their trajectories evolve after returning to the United States during the Cultural Revolution? Wills attained a prestigious position at Harvard in the late 1960s, while Adams became the first African American millionaire through his ownership of a Chinese restaurant chain in the 1970s. While Wills prioritized survival—securing basic livelihood—Adams leveraged culinary entrepreneurship as a means of self-empowerment. Adams’ story, in particular, illuminates the role of semi-official food diplomacy and citizen culinary diplomacy in fostering cross-cultural understanding during a critical phase of U.S.-China relations.</dc:description><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/99p1t8tt</dc:identifier><dc:identifier>https://escholarship.org/content/qt99p1t8tt/qt99p1t8tt.pdf</dc:identifier><dc:identifier>info:doi/10.5070/T2.48539</dc:identifier><dc:type>article</dc:type><dc:source>Territories: A Trans-Cultural Journal of Regional Studies, vol 4, iss 1</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6cs404vr</identifier><datestamp>2026-09-15T23:19:40Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6cs404vr</dc:identifier><dc:title>Thinking gastrodiplomacy through a gastrological reading of conflict</dc:title><dc:creator>Sorondo Salazar, Dennis</dc:creator><dc:date>2025-12-31</dc:date><dc:description>The combination of the fields of study of gastronomy and diplomacy is generating a number of highly valuable academic works that cover multiple dimensions of knowledge and social spheres. However, the potential of gastrodiplomacy to explore conflict (or the possibility of it) has not been fully explored. This article aims to fill this gap by complementing the concept of gastrodiplomacy with that of gastrology. In this way, it aims to consider the relationship between gastronomy, diplomacy and conflict, understanding the latter as the conflict zones that emerge between communities, identities, worldviews or even different ways of understanding the value and uses of gastronomy. Based on this analysis, and assuming that gastronomy is part of every culture and, therefore, is open to a multiplicity of meanings giving rise to ambivalences, paradoxes and tensions, it will be argued that gastronomy (and gastrodiplomacy) as a tool, practice and discourse of mediation (and expansion) of estrangement tends to oscillate between the ordinary, the sublime and the grotesque. To this end, the article will refer to violent conflicts between minority and majority national groups. The aim is not to analyse each case in depth, but rather to explore the interrelationship between diplomacy and gastronomy and these conflicts. In doing so, the article will contribute to a better understanding of the potential of gastronomy and diplomacy to think about and work on difference, estrangement and conflict.</dc:description><dc:subject>Gastrodiplomacy</dc:subject><dc:subject>gastrology</dc:subject><dc:subject>Diplomacy</dc:subject><dc:subject>Conflict</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6cs404vr</dc:identifier><dc:identifier>https://escholarship.org/content/qt6cs404vr/qt6cs404vr.pdf</dc:identifier><dc:identifier>info:doi/10.5070/T2.39905</dc:identifier><dc:type>article</dc:type><dc:source>Territories: A Trans-Cultural Journal of Regional Studies, vol 4, iss 1</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5mq2s8nk</identifier><datestamp>2026-09-15T23:19:21Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5mq2s8nk</dc:identifier><dc:title>Food as a vehicle for successful inter-cultural communication among college students: Collaborative Online International Learning (COIL) in food and nutrition courses</dc:title><dc:creator>Goto, Keiko</dc:creator><dc:creator>Navas, Sebastian</dc:creator><dc:creator>Mead, Sally</dc:creator><dc:date>2025-12-31</dc:date><dc:description>This case study examines how food may play a role in enhancing inter-cultural communication and collaboration through a food-related COIL project among students who are enrolled in food and nutrition courses in two different countries. Students taking a semester-long nutrition course at a university in California and students in a culinary art course in Ecuador worked in groups to complete a Food Product Analysis and Development project. The project focused on Ecuadorian food products, and most of the COIL activities involved examination of food. A qualitative evaluation revealed that food played an important role in enhancing inter-cultural communication and collaboration in different ways. First, food was an effective ice breaker and a tool for team building. Second, food also played a role in learning about culture and identifying similarities between the two cultures in a unique way. The project gave Ecuadorian students the opportunity to showcase their own culture, which provided them with a sense of pride. Among American students, learning about the history and consumption of food that was foreign to them sparked their curiosity about Ecuador. Finally, experiential learning through food, such as cooking and tasting food, appeared to help students keep motivated about the project and make the group project more enjoyable. Our findings suggest that food may be used as a vehicle for inter-cultural communication and global competency in higher education. Further research is needed to effectively evaluate learning outcomes of food-related COIL projects. The importance of developing interdisciplinary, community-based food-related COIL projects is also discussed.</dc:description><dc:subject>COIL</dc:subject><dc:subject>Higher education</dc:subject><dc:subject>Food</dc:subject><dc:subject>Culture</dc:subject><dc:subject>experiential learning</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5mq2s8nk</dc:identifier><dc:identifier>https://escholarship.org/content/qt5mq2s8nk/qt5mq2s8nk.pdf</dc:identifier><dc:identifier>info:doi/10.5070/T2.39901</dc:identifier><dc:type>article</dc:type><dc:source>Territories: A Trans-Cultural Journal of Regional Studies, vol 4, iss 1</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7g349671</identifier><datestamp>2026-09-15T23:02:25Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7g349671</dc:identifier><dc:title>First detection of the BAO signal from early DESI data</dc:title><dc:creator>Moon, Jeongin</dc:creator><dc:creator>Valcin, David</dc:creator><dc:creator>Rashkovetskyi, Michael</dc:creator><dc:creator>Saulder, Christoph</dc:creator><dc:creator>Aguilar, Jessica Nicole</dc:creator><dc:creator>Ahlen, Steven</dc:creator><dc:creator>Alam, Shadab</dc:creator><dc:creator>Bailey, Stephen</dc:creator><dc:creator>Baltay, Charles</dc:creator><dc:creator>Blum, Robert</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>Burtin, Etienne</dc:creator><dc:creator>Chaussidon, Edmond</dc:creator><dc:creator>Dawson, Kyle</dc:creator><dc:creator>de la Macorra, Axel</dc:creator><dc:creator>de M attia, Arnaud</dc:creator><dc:creator>Dhungana, Govinda</dc:creator><dc:creator>Eisenstein, Daniel</dc:creator><dc:creator>Flaugher, Brenna</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>Forero-Romero, Jaime E</dc:creator><dc:creator>Garcia-Quintero, Cristhian</dc:creator><dc:creator>Gontcho, Satya Gontcho A</dc:creator><dc:creator>Guy, Julien</dc:creator><dc:creator>Hanif, Malik Muhammad Sikandar</dc:creator><dc:creator>Honscheid, Klaus</dc:creator><dc:creator>Ishak, Mustapha</dc:creator><dc:creator>Kehoe, Robert</dc:creator><dc:creator>Kim, Sumi</dc:creator><dc:creator>Kisner, Theodore</dc:creator><dc:creator>Kremin, Anthony</dc:creator><dc:creator>Landriau, Martin</dc:creator><dc:creator>Le Guillou, Laurent</dc:creator><dc:creator>Levi, Michael</dc:creator><dc:creator>Manera, Marc</dc:creator><dc:creator>Martini, Paul</dc:creator><dc:creator>McDonald, Patrick</dc:creator><dc:creator>Meisner, Aaron</dc:creator><dc:creator>Miquel, Ramon</dc:creator><dc:creator>Moustakas, John</dc:creator><dc:creator>Myers, Adam</dc:creator><dc:creator>Nadathur, Seshadri</dc:creator><dc:creator>Neveux, Richard</dc:creator><dc:creator>Newman, Jeffrey A</dc:creator><dc:creator>Nie, Jundan</dc:creator><dc:creator>Padmanabhan, Nikhil</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Percival, Will</dc:creator><dc:creator>Fernández, Alejandro Pérez</dc:creator><dc:creator>Poppett, Claire</dc:creator><dc:creator>Prada, Francisco</dc:creator><dc:creator>Raichoor, Anand</dc:creator><dc:creator>Ross, Ashley J</dc:creator><dc:creator>Rossi, Graziano</dc:creator><dc:creator>Samushia, Lado</dc:creator><dc:creator>Schlegel, David</dc:creator><dc:creator>Seo, Hee-Jong</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Magana, Mariana Vargas</dc:creator><dc:creator>Variu, Andrei</dc:creator><dc:creator>Weaver, Benjamin Alan</dc:creator><dc:creator>White, Martin J</dc:creator><dc:creator>Yèche, Christophe</dc:creator><dc:creator>Yuan, Sihan</dc:creator><dc:creator>Zhao, Cheng</dc:creator><dc:creator>Zhou, Rongpu</dc:creator><dc:creator>Zhou, Zhimin</dc:creator><dc:creator>Zou, Hu</dc:creator><dc:date>2023-09-11</dc:date><dc:description>ABSTRACT We present the first detection of the baryon acoustic oscillations (BAOs) signal obtained using unblinded data collected during the initial 2 months of operations of the Stage-IV ground-based Dark Energy Spectroscopic Instrument (DESI). From a selected sample of 261 291 luminous red galaxies spanning the redshift interval 0.4 &amp;lt; z &amp;lt; 1.1 and covering 1651 square degrees with a 57.9 &amp;nbsp;per cent completeness level, we report a ∼5σ level BAO detection and the measurement of the BAO location at a precision of 1.7 &amp;nbsp;per cent. Using a bright galaxy sample of 109 523 galaxies in the redshift range 0.1 &amp;lt; z &amp;lt; 0.5, over 3677 square degrees with a 50.0 &amp;nbsp;per cent completeness, we also detect the BAO feature at ∼3σ significance with a 2.6 &amp;nbsp;per cent precision. These first BAO measurements represent an important milestone, acting as a quality control on the optimal performance of the complex robotically actuated, fibre-fed DESI spectrograph, as well as an early validation of the DESI spectroscopic pipeline and data management system. Based on these first promising results, we forecast that DESI is on target to achieve a high-significance BAO detection at sub-per cent precision with the completed 5-yr survey data, meeting the top-level science requirements on BAO measurements. This exquisite level of precision will set new standards in cosmology and confirm DESI as the most competitive BAO experiment for the remainder of this decade.</dc:description><dc:subject>5109 Space Sciences (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>galaxies: statistics</dc:subject><dc:subject>cosmology: large-scale structure of Universe</dc:subject><dc:subject>observations</dc:subject><dc:subject>dark energy</dc:subject><dc:subject>methods: data analysis</dc:subject><dc:subject>statistical</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7g349671</dc:identifier><dc:identifier>https://escholarship.org/content/qt7g349671/qt7g349671.pdf</dc:identifier><dc:identifier>info:doi/10.1093/mnras/stad2618</dc:identifier><dc:type>article</dc:type><dc:source>Monthly Notices of the Royal Astronomical Society, vol 525, iss 4</dc:source><dc:coverage>5406 - 5422</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7fr1n7hf</identifier><datestamp>2026-09-15T23:02:17Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7fr1n7hf</dc:identifier><dc:title>symPACK: A GPU-Capable Fan-Out Sparse Cholesky Solver</dc:title><dc:creator>Bellavita, Julian</dc:creator><dc:creator>Jacquelin, Mathias</dc:creator><dc:creator>Ng, Esmond G</dc:creator><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Corbino, Johnny</dc:creator><dc:creator>Hargrove, Paul H</dc:creator><dc:date>2023-11-12</dc:date><dc:description>Sparse symmetric positive definite systems of equations are ubiquitous in scientific workloads and applications. Parallel sparse Cholesky factorization is the method of choice for solving such linear systems. Therefore, the development of parallel sparse Cholesky codes that can efficiently run on today’s large-scale heterogeneous distributed-memory platforms is of vital importance. Modern supercomputers offer nodes that contain a mix of CPUs and GPUs. To fully utilize the computing power of these nodes, scientific codes must be adapted to offload expensive computations to GPUs. We present symPACK, a GPU-capable parallel sparse Cholesky solver that uses one-sided communication primitives and remote procedure calls provided by the UPC++ library. We also utilize the UPC++ “memory kinds” feature to enable efficient communication of GPU-resident data. We show that on a number of large problems, symPACK outperforms comparable state-of-the-art GPU-capable Cholesky factorization codes by up to 14x on the NERSC Perlmutter supercomputer.</dc:description><dc:subject>46 Information and Computing Sciences (for-2020)</dc:subject><dc:subject>4601 Applied Computing (for-2020)</dc:subject><dc:subject>Distributed programming models</dc:subject><dc:subject>Hybrid symbolic-numeric methods</dc:subject><dc:subject>Linear algebra algorithms</dc:subject><dc:subject>Mathematics of computing</dc:subject><dc:subject>Parallel programming models</dc:subject><dc:subject>Sparse Cholesky Solvers</dc:subject><dc:subject>UPC++</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7fr1n7hf</dc:identifier><dc:identifier>https://escholarship.org/content/qt7fr1n7hf/qt7fr1n7hf.pdf</dc:identifier><dc:identifier>info:doi/10.1145/3624062.3624600</dc:identifier><dc:type>article</dc:type><dc:source>PROCEEDINGS OF 2023 SC23 WORKSHOPS OF THE INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING, NETWORK, STORAGE, AND ANALYSIS, SC-W 2023</dc:source><dc:coverage>1171 - 1184</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4fj9n31r</identifier><datestamp>2026-09-15T23:02:03Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4fj9n31r</dc:identifier><dc:title>Reference genome of the bicolored carpenter ant, Camponotus vicinus</dc:title><dc:creator>Ward, Philip S</dc:creator><dc:creator>Cash, Elizabeth I</dc:creator><dc:creator>Ferger, Kailey</dc:creator><dc:creator>Escalona, Merly</dc:creator><dc:creator>Sahasrabudhe, Ruta</dc:creator><dc:creator>Miller, Courtney</dc:creator><dc:creator>Toffelmier, Erin</dc:creator><dc:creator>Fairbairn, Colin</dc:creator><dc:creator>Seligmann, William</dc:creator><dc:creator>Shaffer, H Bradley</dc:creator><dc:creator>Tsutsui, Neil D</dc:creator><dc:contributor>Sethuraman, Arun</dc:contributor><dc:date>2024-02-03</dc:date><dc:description>Carpenter ants in the genus Camponotus are large, conspicuous ants that are abundant and ecologically influential in many terrestrial ecosystems. The bicolored carpenter ant, Camponotus vicinus Mayr, is distributed across a wide range of elevations and latitudes in western North America, where it is a prominent scavenger and predator. Here, we present a high-quality genome assembly of C. vicinus from a sample collected in Sonoma County, California, near the type locality of the species. This genome assembly consists of 38 scaffolds spanning 302.74 Mb, with contig N50 of 15.9 Mb, scaffold N50 of 19.9 Mb, and BUSCO completeness of 99.2%. This genome sequence will be a valuable resource for exploring the evolutionary ecology of C. vicinus and carpenter ants generally. It also provides an important tool for clarifying cryptic diversity within the C. vicinus species complex, a genetically diverse set of populations, some of which are quite localized and of conservation interest.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>3104 Evolutionary Biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Symbiosis (mesh)</dc:subject><dc:subject>Ants (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Blochmannia</dc:subject><dc:subject>Camponotini</dc:subject><dc:subject>California Conservation Genomics Project</dc:subject><dc:subject>endosymbiont</dc:subject><dc:subject>Formicidae</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Ants (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Symbiosis (mesh)</dc:subject><dc:subject>Blochmannia</dc:subject><dc:subject>California Conservation Genomics Project</dc:subject><dc:subject>Camponotini</dc:subject><dc:subject>Formicidae</dc:subject><dc:subject>endosymbiont</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Symbiosis (mesh)</dc:subject><dc:subject>Ants (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>Evolutionary Biology (science-metrix)</dc:subject><dc:subject>3104 Evolutionary biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4fj9n31r</dc:identifier><dc:identifier>https://escholarship.org/content/qt4fj9n31r/qt4fj9n31r.pdf</dc:identifier><dc:identifier>info:doi/10.1093/jhered/esad055</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Heredity, vol 115, iss 1</dc:source><dc:coverage>120 - 129</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5217c2bm</identifier><datestamp>2026-09-15T23:01:35Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5217c2bm</dc:identifier><dc:title>Laser-heated capillary discharge waveguides as tunable structures for laser-plasma acceleration</dc:title><dc:creator>Pieronek, CV</dc:creator><dc:creator>Gonsalves, AJ</dc:creator><dc:creator>Benedetti, C</dc:creator><dc:creator>Bulanov, SS</dc:creator><dc:creator>van Tilborg, J</dc:creator><dc:creator>Bin, JH</dc:creator><dc:creator>Swanson, KK</dc:creator><dc:creator>Daniels, J</dc:creator><dc:creator>Bagdasarov, GA</dc:creator><dc:creator>Bobrova, NA</dc:creator><dc:creator>Gasilov, VA</dc:creator><dc:creator>Korn, G</dc:creator><dc:creator>Sasorov, PV</dc:creator><dc:creator>Geddes, CGR</dc:creator><dc:creator>Schroeder, CB</dc:creator><dc:creator>Leemans, WP</dc:creator><dc:creator>Esarey, E</dc:creator><dc:date>2020-09-01</dc:date><dc:description>Laser-heated capillary discharge waveguides are novel, low plasma density guiding structures able to guide intense laser pulses over many diffraction lengths and have recently enabled the acceleration of electrons to 7.8 GeV by using a laser-plasma accelerator (LPA). These devices represent an improvement over conventional capillary discharge waveguides, as the channel matched spot size and plasma density can be tuned independently of the capillary radius. This has allowed the guiding of petawatt-scale pulses focused to small spot sizes within large diameter capillaries, preventing laser damage of the capillary structure. High performance channel-guided LPAs require control of matched spot size and density, which experiments and simulations reported here show can be tuned over a wide range via initial discharge and laser parameters. In this paper, measurements of the matched spot size and plasma density in laser-heated capillary discharges are presented, which are found to be in excellent agreement with simulations performed using the MHD code MARPLE. Strategies for optimizing accelerator performance are identified based on these results.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0203 Classical Physics (for)</dc:subject><dc:subject>Fluids &amp; Plasmas (science-metrix)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5217c2bm</dc:identifier><dc:identifier>https://escholarship.org/content/qt5217c2bm/qt5217c2bm.pdf</dc:identifier><dc:identifier>info:doi/10.1063/5.0014961</dc:identifier><dc:type>article</dc:type><dc:source>Physics of Plasmas, vol 27, iss 9</dc:source><dc:coverage>093101</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3mw1t43b</identifier><datestamp>2026-09-15T22:58:36Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3mw1t43b</dc:identifier><dc:title>Student-Generated Knowledge Graphs about Sustainability</dc:title><dc:creator>Freedman, Hayden</dc:creator><dc:creator>Van Der Hoek, Adriaan</dc:creator><dc:creator>Tomlinson, William</dc:creator><dc:date>2021-06-21</dc:date><dc:description>Knowledge graphs---interconnected networks of concepts and relationships---form the foundation for many computational efforts around the world.  Google, Netflix, Facebook, and other major corporations maintain their own knowledge graphs.  However, sustainability efforts are not always aligned with corporate goals; as such, organizational incentives may not be sufficient for the creation of knowledge graphs well-suited to support sustainability.   A free and open platform called Wikidata run by the Wikimedia Foundation does exist, but it is currently sparsely populated with sustainability-related content.
We propose that there is a need for a free and open knowledge graph richly populated with sustainability knowledge, to support computational initiatives that seek to serve the public good.  While there may be a lack of a corporate work force to generate such a sustainability knowledge graph, there are many thousands of students at universities around the world who are engaged in learning about sustainability.  We see an opportunity for the work that these students do in their assignments to contribute to a sustainability knowledge graph, effectively crowdsourcing the effort.
As a first step, we conducted a study with 10 undergraduate students at the University of California, Irvine who recently completed an introductory sustainability-related course. These students were asked to individually create sustainability knowledge graphs. Participants were given 90 minutes to build a fully connected graph with at least 20 concepts and 19 relationships. We asked them to begin with the concept of “Sustainability” but gave no further instructions on what concepts to include. To ensure a controlled vocabulary of concepts, participants were limited to the use of Wikipedia article titles as possible concepts. We did not provide a controlled vocabulary for relationship labels, allowing participants to freely make associations.
After collecting students’ individual graphs, we aggregated them into a single, integrated knowledge graph, which we then assessed for accuracy, relevance, and connectivity. We then compared the unified knowledge graph to the relevant subsection of Wikidata, assessing both how similar the students’ work was to what is already known and what new relationships could potentially be contributed to Wikidata.
Results indicate that each participant was able to effectively create a knowledge graph with the required number of concepts and relationships.  Participants collectively generated 172 unique concepts that spanned many different disciplines. Moreover, we found that the connectivity of the student-generated knowledge graph (270 relationships) was higher than the connectivity between the same concepts in Wikidata (86 relationships). However, the students used a relatively large set of relationship labels, employing 190 distinct labels for the 270 relationships. This indicates that limiting students to a controlled vocabulary of relationship labels may help students create stronger and more consistent associations that are better suited for incorporation into a larger knowledge resource. This study provides evidence that, when properly guided, undergraduate students may be able to contribute useful content to a shared data resource of sustainability knowledge. We envision the possibility of future software-supported curricula enabling students around the world to make many more contributions to shared public resources.</dc:description><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3mw1t43b</dc:identifier><dc:identifier>https://escholarship.org/content/qt3mw1t43b/qt3mw1t43b.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt600139fw</identifier><datestamp>2026-09-15T22:58:32Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt600139fw</dc:identifier><dc:title>A Metric of Species’ Charisma</dc:title><dc:creator>Freedman, Hayden</dc:creator><dc:creator>Tomlinson, William</dc:creator><dc:creator>Torrance, Andrew</dc:creator><dc:creator>Van Der Hoek, Adriaan</dc:creator><dc:date>2021-08-02</dc:date><dc:description>Species are often targeted for conservation based on their “charisma”. A comprehensive, quantitative metric for species charisma could improve conservation efforts and help ensure that even low-charisma species are protected. We investigated whether metrics based on Wikipedia (species article length, links to and from each species page, and Google’s PageRank) could be used to assess the charisma of endangered species, evaluated using prior work on species charisma (Albert et al. 2018). We evaluated three Wikipedia-based metrics based on their ability to assess endangered species charisma. We found highly significant correlations for all three metrics, with article length the most significant (rpb=0.57; p &amp;lt; .00001**).</dc:description><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/600139fw</dc:identifier><dc:identifier>https://escholarship.org/content/qt600139fw/qt600139fw.pdf</dc:identifier><dc:type>non_textual</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt87f4478m</identifier><datestamp>2026-09-15T22:57:30Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt87f4478m</dc:identifier><dc:title>Shaping coherent x-rays with binary optics.</dc:title><dc:creator>Marchesini, Stefano</dc:creator><dc:creator>Sakdinawat, Anne</dc:creator><dc:date>2019-01-21</dc:date><dc:description>Diffractive lenses fabricated by lithographic methods are one of the most popular image forming optics in the x-ray regime. Most commonly, binary diffractive optics, such as Fresnel zone plates, are used due to their ability to focus at high resolution and to manipulate the x-ray wavefront. We report here a binary zone plate design strategy to form arbitrary illuminations for coherent multiplexing, structured illumination, and wavefront shaping experiments. Given a desired illumination, we adjust the duty cycle, harmonic order, and zone placement to vary both the amplitude and phase of the wavefront at the lens. This enables the binary lithographic pattern to generate arbitrary structured illumination optimized for a variety of applications such as holography, interferometry, ptychography, imaging, and others.</dc:description><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>4009 Electronics</dc:subject><dc:subject>Sensors and Digital Hardware (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>physics.optics</dc:subject><dc:subject>physics.optics</dc:subject><dc:subject>physics.app-ph</dc:subject><dc:subject>0205 Optical Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>1005 Communications Technologies (for)</dc:subject><dc:subject>Optics (science-metrix)</dc:subject><dc:subject>4006 Communications engineering (for-2020)</dc:subject><dc:subject>4009 Electronics</dc:subject><dc:subject>sensors and digital hardware (for-2020)</dc:subject><dc:subject>5102 Atomic</dc:subject><dc:subject>molecular and optical physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/87f4478m</dc:identifier><dc:identifier>https://escholarship.org/content/qt87f4478m/qt87f4478m.pdf</dc:identifier><dc:identifier>info:doi/10.1364/oe.27.000907</dc:identifier><dc:type>article</dc:type><dc:source>Optics Express, vol 27, iss 2</dc:source><dc:coverage>907 - 917</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt027191bc</identifier><datestamp>2026-09-15T22:54:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt027191bc</dc:identifier><dc:title>Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines</dc:title><dc:creator>Ellrott, Kyle</dc:creator><dc:creator>Bailey, Matthew H</dc:creator><dc:creator>Saksena, Gordon</dc:creator><dc:creator>Covington, Kyle R</dc:creator><dc:creator>Kandoth, Cyriac</dc:creator><dc:creator>Stewart, Chip</dc:creator><dc:creator>Hess, Julian</dc:creator><dc:creator>Ma</dc:creator><dc:creator>Chiotti, Kami E</dc:creator><dc:creator>McLellan, Michael</dc:creator><dc:creator>Sofia, Heidi J</dc:creator><dc:creator>Hutter, Carolyn</dc:creator><dc:creator>Getz, Gad</dc:creator><dc:creator>Wheeler, David</dc:creator><dc:creator>Ding, Li</dc:creator><dc:creator>Group, MC3 Working</dc:creator><dc:creator>Network, The Cancer Genome Atlas Research</dc:creator><dc:creator>Caesar-Johnson, Samantha J</dc:creator><dc:creator>Demchok, John A</dc:creator><dc:creator>Felau, Ina</dc:creator><dc:creator>Kasapi, Melpomeni</dc:creator><dc:creator>Ferguson, Martin L</dc:creator><dc:creator>Hutter, Carolyn M</dc:creator><dc:creator>Sofia, Heidi J</dc:creator><dc:creator>Tarnuzzer, Roy</dc:creator><dc:creator>Wang, Zhining</dc:creator><dc:creator>Yang, Liming</dc:creator><dc:creator>Zenklusen, Jean C</dc:creator><dc:creator>Zhang, Jiashan</dc:creator><dc:creator>Chudamani, Sudha</dc:creator><dc:creator>Liu, Jia</dc:creator><dc:creator>Lolla, Laxmi</dc:creator><dc:creator>Naresh, Rashi</dc:creator><dc:creator>Pihl, Todd</dc:creator><dc:creator>Sun, Qiang</dc:creator><dc:creator>Wan, Yunhu</dc:creator><dc:creator>Wu, Ye</dc:creator><dc:creator>Cho, Juok</dc:creator><dc:creator>DeFreitas, Timothy</dc:creator><dc:creator>Frazer, Scott</dc:creator><dc:creator>Gehlenborg, Nils</dc:creator><dc:creator>Getz, Gad</dc:creator><dc:creator>Heiman, David I</dc:creator><dc:creator>Kim, Jaegil</dc:creator><dc:creator>Lawrence, Michael S</dc:creator><dc:creator>Lin, Pei</dc:creator><dc:creator>Meier, Sam</dc:creator><dc:creator>Noble, Michael S</dc:creator><dc:creator>Saksena, Gordon</dc:creator><dc:creator>Voet, Doug</dc:creator><dc:creator>Zhang, Hailei</dc:creator><dc:creator>Bernard, Brady</dc:creator><dc:creator>Chambwe, Nyasha</dc:creator><dc:creator>Dhankani, Varsha</dc:creator><dc:creator>Knijnenburg, Theo</dc:creator><dc:creator>Kramer, Roger</dc:creator><dc:creator>Leinonen, Kalle</dc:creator><dc:creator>Liu, Yuexin</dc:creator><dc:creator>Miller, Michael</dc:creator><dc:creator>Reynolds, Sheila</dc:creator><dc:creator>Shmulevich, Ilya</dc:creator><dc:creator>Thorsson, Vesteinn</dc:creator><dc:creator>Zhang, Wei</dc:creator><dc:creator>Akbani, Rehan</dc:creator><dc:creator>Broom, Bradley M</dc:creator><dc:creator>Hegde, Apurva M</dc:creator><dc:creator>Ju, Zhenlin</dc:creator><dc:creator>Kanchi, Rupa S</dc:creator><dc:creator>Korkut, Anil</dc:creator><dc:creator>Li, Jun</dc:creator><dc:creator>Liang, Han</dc:creator><dc:creator>Ling, Shiyun</dc:creator><dc:creator>Liu, Wenbin</dc:creator><dc:creator>Lu, Yiling</dc:creator><dc:creator>Mills, Gordon B</dc:creator><dc:creator>Ng, Kwok-Shing</dc:creator><dc:creator>Rao, Arvind</dc:creator><dc:creator>Ryan, Michael</dc:creator><dc:creator>Wang, Jing</dc:creator><dc:creator>Weinstein, John N</dc:creator><dc:creator>Zhang, Jiexin</dc:creator><dc:creator>Abeshouse, Adam</dc:creator><dc:creator>Armenia, Joshua</dc:creator><dc:creator>Chakravarty, Debyani</dc:creator><dc:creator>Chatila, Walid K</dc:creator><dc:creator>de Bruijn, Ino</dc:creator><dc:creator>Gao, Jianjiong</dc:creator><dc:creator>Gross, Benjamin E</dc:creator><dc:creator>Heins, Zachary J</dc:creator><dc:creator>Kundra, Ritika</dc:creator><dc:creator>La, Konnor</dc:creator><dc:creator>Ladanyi, Marc</dc:creator><dc:creator>Luna, Augustin</dc:creator><dc:creator>Nissan, Moriah G</dc:creator><dc:creator>Ochoa, Angelica</dc:creator><dc:creator>Phillips, Sarah M</dc:creator><dc:creator>Reznik, Ed</dc:creator><dc:creator>Sanchez-Vega, Francisco</dc:creator><dc:creator>Sander, Chris</dc:creator><dc:creator>Schultz, Nikolaus</dc:creator><dc:date>2018-03-01</dc:date><dc:description>The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total &amp;gt;400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and&amp;nbsp;batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is the&amp;nbsp;result of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3102 Bioinformatics and Computational Biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Cancer (rcdc)</dc:subject><dc:subject>Rare Diseases (rcdc)</dc:subject><dc:subject>Cancer Genomics (rcdc)</dc:subject><dc:subject>Biotechnology (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Networking and Information Technology R&amp;D (NITRD) (rcdc)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Genetic Testing (rcdc)</dc:subject><dc:subject>2.1 Biological and endogenous factors (hrcs-rac)</dc:subject><dc:subject>Cancer (hrcs-hc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Algorithms (mesh)</dc:subject><dc:subject>Exome (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>High-Throughput Nucleotide Sequencing (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Information Dissemination (mesh)</dc:subject><dc:subject>Mutation (mesh)</dc:subject><dc:subject>Neoplasms (mesh)</dc:subject><dc:subject>Sequence Analysis</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>Software (mesh)</dc:subject><dc:subject>Exome Sequencing (mesh)</dc:subject><dc:subject>MC3 Working Group</dc:subject><dc:subject>Cancer Genome Atlas Research Network</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Neoplasms (mesh)</dc:subject><dc:subject>Sequence Analysis</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>Information Dissemination (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>Mutation (mesh)</dc:subject><dc:subject>Algorithms (mesh)</dc:subject><dc:subject>Software (mesh)</dc:subject><dc:subject>High-Throughput Nucleotide Sequencing (mesh)</dc:subject><dc:subject>Exome (mesh)</dc:subject><dc:subject>Exome Sequencing (mesh)</dc:subject><dc:subject>PanCanAtlas project</dc:subject><dc:subject>TCGA</dc:subject><dc:subject>large-scale</dc:subject><dc:subject>open science</dc:subject><dc:subject>pan-cancer</dc:subject><dc:subject>reproducible computing</dc:subject><dc:subject>somatic mutation calling</dc:subject><dc:subject>Algorithms (mesh)</dc:subject><dc:subject>Exome (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>High-Throughput Nucleotide Sequencing (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Information Dissemination (mesh)</dc:subject><dc:subject>Mutation (mesh)</dc:subject><dc:subject>Neoplasms (mesh)</dc:subject><dc:subject>Sequence Analysis</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>Software (mesh)</dc:subject><dc:subject>Exome Sequencing (mesh)</dc:subject><dc:subject>0601 Biochemistry and Cell Biology (for)</dc:subject><dc:subject>3101 Biochemistry and cell biology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/027191bc</dc:identifier><dc:identifier>https://escholarship.org/content/qt027191bc/qt027191bc.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.cels.2018.03.002</dc:identifier><dc:type>article</dc:type><dc:source>Cell Systems, vol 6, iss 3</dc:source><dc:coverage>271 - 281.e7</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6vp0b9zp</identifier><datestamp>2026-09-15T22:53:38Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6vp0b9zp</dc:identifier><dc:title>A reference genome assembly for the continentally distributed ring-necked snake, Diadophis punctatus</dc:title><dc:creator>Westeen, Erin P</dc:creator><dc:creator>Escalona, Merly</dc:creator><dc:creator>Beraut, Eric</dc:creator><dc:creator>Marimuthu, Mohan PA</dc:creator><dc:creator>Nguyen, Oanh</dc:creator><dc:creator>Fisher, Robert N</dc:creator><dc:creator>Toffelmier, Erin</dc:creator><dc:creator>Shaffer, H Bradley</dc:creator><dc:creator>Wang, Ian J</dc:creator><dc:contributor>Ruane, Sara</dc:contributor><dc:date>2023-11-15</dc:date><dc:description>Snakes in the family Colubridae include more than 2,000 currently recognized species, and comprise roughly 75% of the global snake species diversity on Earth. For such a spectacular radiation, colubrid snakes remain poorly understood ecologically and genetically. Two subfamilies, Colubrinae (788 species) and Dipsadinae (833 species), comprise the bulk of colubrid species richness. Dipsadines are a speciose and diverse group of snakes that largely inhabit Central and South America, with a handful of small-body-size genera that have invaded North America. Among them, the ring-necked snake, Diadophis punctatus, has an incredibly broad distribution with 14 subspecies. Given its continental distribution and high degree of variation in coloration, diet, feeding ecology, and behavior, the ring-necked snake is an excellent species for the study of genetic diversity and trait evolution. Within California, six subspecies form a continuously distributed "ring species" around the Central Valley, while a seventh, the regal ring-necked snake, Diadophis punctatus regalis is a disjunct outlier and Species of Special Concern in the state. Here, we report a new reference genome assembly for the San Diego ring-necked snake, D. p. similis, as part of the California Conservation Genomics Project. This assembly comprises a total of 444 scaffolds spanning 1,783 Mb and has a contig N50 of 8.0 Mb, scaffold N50 of 83 Mb, and BUSCO completeness score of 94.5%. This reference genome will be a valuable resource for studies of the taxonomy, conservation, and evolution of the ring-necked snake across its broad, continental distribution.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>14 Life Below Water (sdg)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Colubridae (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>North America (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>California Conservation Genomics Project</dc:subject><dc:subject>CCGP</dc:subject><dc:subject>conservation genetics</dc:subject><dc:subject>Dipsadinae</dc:subject><dc:subject>reference genome</dc:subject><dc:subject>snake</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Colubridae (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>North America (mesh)</dc:subject><dc:subject>CCGP</dc:subject><dc:subject>California Conservation Genomics Project</dc:subject><dc:subject>Dipsadinae</dc:subject><dc:subject>conservation genetics</dc:subject><dc:subject>reference genome</dc:subject><dc:subject>snake</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Colubridae (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>North America (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>Evolutionary Biology (science-metrix)</dc:subject><dc:subject>3104 Evolutionary biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6vp0b9zp</dc:identifier><dc:identifier>https://escholarship.org/content/qt6vp0b9zp/qt6vp0b9zp.pdf</dc:identifier><dc:identifier>info:doi/10.1093/jhered/esad051</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Heredity, vol 114, iss 6</dc:source><dc:coverage>690 - 697</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt78f799np</identifier><datestamp>2026-09-15T22:53:31Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt78f799np</dc:identifier><dc:title>Target selection for the DESI Peculiar Velocity Survey</dc:title><dc:creator>Saulder, Christoph</dc:creator><dc:creator>Howlett, Cullan</dc:creator><dc:creator>Douglass, Kelly A</dc:creator><dc:creator>Said, Khaled</dc:creator><dc:creator>BenZvi, Segev</dc:creator><dc:creator>Ahlen, Steven</dc:creator><dc:creator>Aldering, Greg</dc:creator><dc:creator>Bailey, Stephen</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>Davis, Tamara M</dc:creator><dc:creator>de la Macorra, Axel</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>Forero-Romero, Jaime E</dc:creator><dc:creator>Gontcho, Satya Gontcho A</dc:creator><dc:creator>Honscheid, Klaus</dc:creator><dc:creator>Kim, Alex G</dc:creator><dc:creator>Kisner, Theodore</dc:creator><dc:creator>Kremin, Anthony</dc:creator><dc:creator>Landriau, Martin</dc:creator><dc:creator>Levi, Michael E</dc:creator><dc:creator>Lucey, John</dc:creator><dc:creator>Meisner, Aaron M</dc:creator><dc:creator>Miquel, Ramon</dc:creator><dc:creator>Moustakas, John</dc:creator><dc:creator>Myers, Adam D</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Percival, Will</dc:creator><dc:creator>Poppett, Claire</dc:creator><dc:creator>Prada, Francisco</dc:creator><dc:creator>Qin, Fei</dc:creator><dc:creator>Schubnell, Michael</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Magaña, Mariana Vargas</dc:creator><dc:creator>Weaver, Benjamin Alan</dc:creator><dc:creator>Zhou, Rongpu</dc:creator><dc:creator>Zhou, Zhimin</dc:creator><dc:creator>Zou, Hu</dc:creator><dc:date>2023-08-09</dc:date><dc:description>ABSTRACT We describe the target selection and characteristics of the DESI Peculiar Velocity Survey, the largest survey of peculiar velocities (PVs) using both the fundamental plane (FP) and the Tully–Fisher (TF) relationship planned to date. We detail how we identify suitable early-type galaxies (ETGs) for the FP and suitable late-type galaxies (LTGs) for the TF relation using the photometric data provided by the DESI Legacy Imaging Survey DR9. Subsequently, we provide targets for 373 533 ETGs and 118 637 LTGs within the Dark Energy Spectroscopic Instrument (DESI) 5-yr footprint. We validate these photometric selections using existing morphological classifications. Furthermore, we demonstrate using survey validation data that DESI is able to measure the spectroscopic properties to sufficient precision to obtain PVs for our targets. Based on realistic DESI fibre assignment simulations and spectroscopic success rates, we predict the final DESI PV Survey will obtain ∼133 000 FP-based and ∼53 000 TF-based PV measurements over an area of 14 000&amp;nbsp;deg2. We forecast the ability of using these data to measure the clustering of galaxy positions and PVs from the combined DESI PV and Bright Galaxy Surveys (BGS), which allows for cancellation of cosmic variance at low redshifts. With these forecasts, we anticipate a 4 per cent statistical measurement on the growth rate of structure at z &amp;lt; 0.15. This is over two times better than achievable with redshifts from the BGS alone. The combined DESI PV and BGS will enable the most precise tests to date of the time and scale dependence of large-scale structure growth at z &amp;lt; 0.15.</dc:description><dc:subject>5109 Space Sciences (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>surveys</dc:subject><dc:subject>galaxies: distances and redshifts</dc:subject><dc:subject>cosmology: observations</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/78f799np</dc:identifier><dc:identifier>https://escholarship.org/content/qt78f799np/qt78f799np.pdf</dc:identifier><dc:identifier>info:doi/10.1093/mnras/stad2200</dc:identifier><dc:type>article</dc:type><dc:source>Monthly Notices of the Royal Astronomical Society, vol 525, iss 1</dc:source><dc:coverage>1106 - 1125</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5x69z7g2</identifier><datestamp>2026-09-15T22:52:51Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5x69z7g2</dc:identifier><dc:title>Molecular Nature of Mineral-Organic Associations within Redox-Active Mountainous Floodplain Sediments</dc:title><dc:creator>Anderson, Cam G</dc:creator><dc:creator>Goebel, Genevieve M</dc:creator><dc:creator>Tfaily, Malak M</dc:creator><dc:creator>Fox, Patricia M</dc:creator><dc:creator>Nico, Peter S</dc:creator><dc:creator>Fendorf, Scott</dc:creator><dc:creator>Keiluweit, Marco</dc:creator><dc:date>2023-09-21</dc:date><dc:description>Floodplains are critical terrestrial–aquatic interfaces that act as hotspots of organic carbon (OC) cycling, regulating ecosystem carbon storage as well as export to riverine systems. Within floodplain sediments, regular flooding and textural gradients interact to create dynamic redox conditions. While anaerobic protection of OC upon burial is a well-recognized carbon storage mechanism in redox-active floodplain sediments, the impact of protective mineral-organic associations is relatively unknown. Here we determined the quantitative importance and chemical composition of mineral-organic associations along well-defined redox gradients emerging from textural variations and depth within meander sediments of the subalpine East River watershed (Gothic, CO). We characterized mineral-organic associations using a combination of sequential extractions, physical fractionation, and high-resolution mass spectrometry. Across the meander, we found that mineral-associated OC constitutes a significant fraction of total OC, and that extractable iron (Fe) and aluminum (Al) phases as well as high-density isolates were strongly correlated with total OC content, suggesting that mineral-organic associations are quantitatively important for floodplain sediment OC protection. Our mass spectrometry results showed OC associated with increasingly ordered Fe and Al phases are relatively enriched in low-molecular weight, oxidized, aromatic compounds. Surprisingly, however, total OC content showed weak or no correlation with indicators of anaerobic protection, such as relatively bioavailable OC pools (water-extractable and particulate OC) or the molecular weight and oxidation state of OC. Overall, this work highlights that protection of OC bound to reactive mineral phasesin addition to anaerobic protectioncan play a quantitatively important role in controlling soil carbon storage in redox-active floodplain sediments.</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>3703 Geochemistry (for-2020)</dc:subject><dc:subject>34 Chemical Sciences (for-2020)</dc:subject><dc:subject>3705 Geology (for-2020)</dc:subject><dc:subject>Soil organic carbon</dc:subject><dc:subject>Floodplains</dc:subject><dc:subject>Redox gradients</dc:subject><dc:subject>Mineral-organic associations</dc:subject><dc:subject>Climate change</dc:subject><dc:subject>34 Chemical sciences (for-2020)</dc:subject><dc:subject>37 Earth sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5x69z7g2</dc:identifier><dc:identifier>https://escholarship.org/content/qt5x69z7g2/qt5x69z7g2.pdf</dc:identifier><dc:identifier>info:doi/10.1021/acsearthspacechem.3c00037</dc:identifier><dc:type>article</dc:type><dc:source>ACS Earth and Space Chemistry, vol 7, iss 9</dc:source><dc:coverage>1623 - 1634</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5r335408</identifier><datestamp>2026-09-15T22:49:58Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5r335408</dc:identifier><dc:title>Translating community-based participatory research into broadscale sociopolitical change: insights from a coalition of women firefighters, scientists, and environmental health advocates</dc:title><dc:creator>Ohayon, Jennifer Liss</dc:creator><dc:creator>Rasanayagam, Sharima</dc:creator><dc:creator>Rudel, Ruthann A</dc:creator><dc:creator>Patton, Sharyle</dc:creator><dc:creator>Buren, Heather</dc:creator><dc:creator>Stefani, Tony</dc:creator><dc:creator>Trowbridge, Jessica</dc:creator><dc:creator>Clarity, Cassidy</dc:creator><dc:creator>Brody, Julia Green</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:date>2023-08-30</dc:date><dc:description>BackgroundWe report on community-based participatory research (CBPR) initiated by women firefighters in order to share successful elements that can be instructive for other community-engaged research. This CBPR initiative, known as the Women Worker Biomonitoring Collaborative (WWBC) is the first we are aware of to investigate links between occupational exposures and health outcomes, including breast cancer, for a cohort of exclusively women firefighters.MethodsIn order to be reflective of the experiences and knowledge of those most intimately involved, this article is co-authored by leaders of the research initiative. We collected leaders’ input via recorded meeting sessions, emails, and a shared online document. We also conducted interviews (N = 10) with key research participants and community leaders to include additional perspectives.ResultsFactors contributing to the initiative’s success in enacting broadscale social change and advancing scientific knowledge include (1) forming a diverse coalition of impacted community leaders, labor unions, scientists, and advocacy organizations, (2) focusing on impacts at multiple scales of action and nurturing different, yet mutually supportive, goals among partners, (3) adopting innovative communication strategies for study participants, research partners, and the broader community, (4) cultivating a prevention-based ethos in the scientific research, including taking early action to reduce community exposures based on existing evidence of harm, and (5) emphasizing co-learning through all the study stages. Furthermore, we discuss external factors that contribute to success, including funding programs that elevate scientist-community-advocacy partnerships and allow flexibility to respond to emerging science-policy opportunities, as well as institutional structures responsive to worker concerns.ConclusionsWhile WWBC shares characteristics with other successful CBPR partnerships, it also advances approaches that increase the ability for CBPR to translate into change at multiple levels. This includes incorporating partners with particular skills and resources beyond the traditional researcher-community partnerships that are the focus of much CBPR practice and scholarly attention, and designing studies so they support community action in the initial stages of research. Moreover, we emphasize external structural factors that can be critical for CBPR success. This demonstrates the importance of critically examining and advocating for institutional factors that better support this research.</dc:description><dc:subject>4203 Health Services and Systems (for-2020)</dc:subject><dc:subject>4206 Public Health (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Health Services (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Cancer (rcdc)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Community-Based Participatory Research (mesh)</dc:subject><dc:subject>Firefighters (mesh)</dc:subject><dc:subject>Biological Monitoring (mesh)</dc:subject><dc:subject>Breast Neoplasms (mesh)</dc:subject><dc:subject>Environmental Health (mesh)</dc:subject><dc:subject>Community-based participatory research</dc:subject><dc:subject>CBPR</dc:subject><dc:subject>Firefighters</dc:subject><dc:subject>Breast cancer</dc:subject><dc:subject>Biomonitoring</dc:subject><dc:subject>Occupational health</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Breast Neoplasms (mesh)</dc:subject><dc:subject>Environmental Health (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Community-Based Participatory Research (mesh)</dc:subject><dc:subject>Firefighters (mesh)</dc:subject><dc:subject>Biological Monitoring (mesh)</dc:subject><dc:subject>Biomonitoring</dc:subject><dc:subject>Breast cancer</dc:subject><dc:subject>CBPR</dc:subject><dc:subject>Community-based participatory research</dc:subject><dc:subject>Firefighters</dc:subject><dc:subject>Occupational health</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Community-Based Participatory Research (mesh)</dc:subject><dc:subject>Firefighters (mesh)</dc:subject><dc:subject>Biological Monitoring (mesh)</dc:subject><dc:subject>Breast Neoplasms (mesh)</dc:subject><dc:subject>Environmental Health (mesh)</dc:subject><dc:subject>1117 Public Health and Health Services (for)</dc:subject><dc:subject>Toxicology (science-metrix)</dc:subject><dc:subject>4202 Epidemiology (for-2020)</dc:subject><dc:subject>4206 Public health (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5r335408</dc:identifier><dc:identifier>https://escholarship.org/content/qt5r335408/qt5r335408.pdf</dc:identifier><dc:identifier>info:doi/10.1186/s12940-023-01005-7</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Health, vol 22, iss 1</dc:source><dc:coverage>60</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8qb0p7j7</identifier><datestamp>2026-09-15T22:49:02Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8qb0p7j7</dc:identifier><dc:title>Distributed Acoustic Sensing Using Dark Fiber for Near-Surface Characterization and Broadband Seismic Event Detection</dc:title><dc:creator>Ajo-Franklin, Jonathan B</dc:creator><dc:creator>Dou, Shan</dc:creator><dc:creator>Lindsey, Nathaniel J</dc:creator><dc:creator>Monga, Inder</dc:creator><dc:creator>Tracy, Chris</dc:creator><dc:creator>Robertson, Michelle</dc:creator><dc:creator>Rodriguez Tribaldos, Veronica</dc:creator><dc:creator>Ulrich, Craig</dc:creator><dc:creator>Freifeld, Barry</dc:creator><dc:creator>Daley, Thomas</dc:creator><dc:creator>Li, Xiaoye</dc:creator><dc:date>2019-02-04</dc:date><dc:description>We present one of the first case studies demonstrating the use of distributed acoustic sensing deployed on regional unlit fiber-optic telecommunication infrastructure (dark fiber) for broadband seismic monitoring of both near-surface soil properties and earthquake seismology. We recorded 7 months of passive seismic data on a 27 km section of dark fiber stretching from West Sacramento, CA to Woodland, CA, densely sampled at 2 m spacing. This dataset was processed to extract surface wave velocity information using ambient noise interferometry techniques; the resulting VS profiles were used to map both shallow structural profiles and groundwater depth, thus demonstrating that basin-scale variations in hydrological state could be resolved using this technique. The same array was utilized for detection of regional and teleseismic earthquakes and evaluated for long period response using records from the M8.1 Chiapas, Mexico 2017, Sep 8th event. The combination of these two sets of observations conclusively demonstrates that regionally extensive fiber-optic networks can effectively be utilized for a host of geoscience observation tasks at a combination of scale and resolution previously inaccessible.</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>46 Information and Computing Sciences (for-2020)</dc:subject><dc:subject>3705 Geology (for-2020)</dc:subject><dc:subject>3706 Geophysics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8qb0p7j7</dc:identifier><dc:identifier>https://escholarship.org/content/qt8qb0p7j7/qt8qb0p7j7.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41598-018-36675-8</dc:identifier><dc:type>article</dc:type><dc:source>Scientific Reports, vol 9, iss 1</dc:source><dc:coverage>1328</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5823k370</identifier><datestamp>2026-09-15T22:48:58Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5823k370</dc:identifier><dc:title>The LUX-ZEPLIN (LZ) experiment</dc:title><dc:creator>Akerib, DS</dc:creator><dc:creator>Akerlof, CW</dc:creator><dc:creator>Akimov, D Yu</dc:creator><dc:creator>Alquahtani, A</dc:creator><dc:creator>Alsum, SK</dc:creator><dc:creator>Anderson, TJ</dc:creator><dc:creator>Angelides, N</dc:creator><dc:creator>Araújo, HM</dc:creator><dc:creator>Arbuckle, A</dc:creator><dc:creator>Armstrong, JE</dc:creator><dc:creator>Arthurs, M</dc:creator><dc:creator>Auyeung, H</dc:creator><dc:creator>Bai, X</dc:creator><dc:creator>Bailey, AJ</dc:creator><dc:creator>Balajthy, J</dc:creator><dc:creator>Balashov, S</dc:creator><dc:creator>Bang, J</dc:creator><dc:creator>Barry, MJ</dc:creator><dc:creator>Barthel, J</dc:creator><dc:creator>Bauer, D</dc:creator><dc:creator>Bauer, P</dc:creator><dc:creator>Baxter, A</dc:creator><dc:creator>Belle, J</dc:creator><dc:creator>Beltrame, P</dc:creator><dc:creator>Bensinger, J</dc:creator><dc:creator>Benson, T</dc:creator><dc:creator>Bernard, EP</dc:creator><dc:creator>Bernstein, A</dc:creator><dc:creator>Bhatti, A</dc:creator><dc:creator>Biekert, A</dc:creator><dc:creator>Biesiadzinski, TP</dc:creator><dc:creator>Birrittella, B</dc:creator><dc:creator>Boast, KE</dc:creator><dc:creator>Bolozdynya, AI</dc:creator><dc:creator>Boulton, EM</dc:creator><dc:creator>Boxer, B</dc:creator><dc:creator>Bramante, R</dc:creator><dc:creator>Branson, S</dc:creator><dc:creator>Brás, P</dc:creator><dc:creator>Breidenbach, M</dc:creator><dc:creator>Buckley, JH</dc:creator><dc:creator>Bugaev, VV</dc:creator><dc:creator>Bunker, R</dc:creator><dc:creator>Burdin, S</dc:creator><dc:creator>Busenitz, JK</dc:creator><dc:creator>Campbell, JS</dc:creator><dc:creator>Carels, C</dc:creator><dc:creator>Carlsmith, DL</dc:creator><dc:creator>Carlson, B</dc:creator><dc:creator>Carmona-Benitez, MC</dc:creator><dc:creator>Cascella, M</dc:creator><dc:creator>Chan, C</dc:creator><dc:creator>Cherwinka, JJ</dc:creator><dc:creator>Chiller, AA</dc:creator><dc:creator>Chiller, C</dc:creator><dc:creator>Chott, NI</dc:creator><dc:creator>Cole, A</dc:creator><dc:creator>Coleman, J</dc:creator><dc:creator>Colling, D</dc:creator><dc:creator>Conley, RA</dc:creator><dc:creator>Cottle, A</dc:creator><dc:creator>Coughlen, R</dc:creator><dc:creator>Craddock, WW</dc:creator><dc:creator>Curran, D</dc:creator><dc:creator>Currie, A</dc:creator><dc:creator>Cutter, JE</dc:creator><dc:creator>da Cunha, JP</dc:creator><dc:creator>Dahl, CE</dc:creator><dc:creator>Dardin, S</dc:creator><dc:creator>Dasu, S</dc:creator><dc:creator>Davis, J</dc:creator><dc:creator>Davison, TJR</dc:creator><dc:creator>de Viveiros, L</dc:creator><dc:creator>Decheine, N</dc:creator><dc:creator>Dobi, A</dc:creator><dc:creator>Dobson, JEY</dc:creator><dc:creator>Druszkiewicz, E</dc:creator><dc:creator>Dushkin, A</dc:creator><dc:creator>Edberg, TK</dc:creator><dc:creator>Edwards, WR</dc:creator><dc:creator>Edwards, BN</dc:creator><dc:creator>Edwards, J</dc:creator><dc:creator>Elnimr, MM</dc:creator><dc:creator>Emmet, WT</dc:creator><dc:creator>Eriksen, SR</dc:creator><dc:creator>Faham, CH</dc:creator><dc:creator>Fan, A</dc:creator><dc:creator>Fayer, S</dc:creator><dc:creator>Fiorucci, S</dc:creator><dc:creator>Flaecher, H</dc:creator><dc:creator>Florang, IM Fogarty</dc:creator><dc:creator>Ford, P</dc:creator><dc:creator>Francis, VB</dc:creator><dc:creator>Froborg, F</dc:creator><dc:creator>Fruth, T</dc:creator><dc:creator>Gaitskell, RJ</dc:creator><dc:creator>Gantos, NJ</dc:creator><dc:creator>Garcia, D</dc:creator><dc:creator>Geffre, A</dc:creator><dc:creator>Gehman, VM</dc:creator><dc:date>2020-02-01</dc:date><dc:description>We describe the design and assembly of the LUX-ZEPLIN experiment, a direct detection search for cosmic WIMP dark matter particles. The centerpiece of the experiment is a large liquid xenon time projection chamber sensitive to low energy nuclear recoils. Rejection of backgrounds is enhanced by a Xe skin veto detector and by a liquid scintillator Outer Detector loaded with gadolinium for efficient neutron capture and tagging. LZ is located in the Davis Cavern at the 4850’ level of the Sanford Underground Research Facility in Lead, South Dakota, USA. We describe the major subsystems of the experiment and its key design features and requirements.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Dark matter detector</dc:subject><dc:subject>Liquid xenon</dc:subject><dc:subject>Time projection chamber</dc:subject><dc:subject>Underground</dc:subject><dc:subject>physics.ins-det</dc:subject><dc:subject>physics.ins-det</dc:subject><dc:subject>astro-ph.IM</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0299 Other Physical Sciences (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5823k370</dc:identifier><dc:identifier>https://escholarship.org/content/qt5823k370/qt5823k370.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.nima.2019.163047</dc:identifier><dc:type>article</dc:type><dc:source>Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, vol 953</dc:source><dc:coverage>163047</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt26k5w58q</identifier><datestamp>2026-09-15T22:44:41Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt26k5w58q</dc:identifier><dc:title>Using payment for ecosystem services to meet national reforestation commitments: impacts of 20+ years of forestry incentives in Guatemala</dc:title><dc:creator>Patrick, Evan</dc:creator><dc:creator>Butsic, Van</dc:creator><dc:creator>Potts, Matthew D</dc:creator><dc:date>2023-10-01</dc:date><dc:description>International environmental initiatives, such as the Bonn Challenge and the UN Decade on Restoration, have prompted countries to put the management and restoration of forest landscapes at the center of their land use and climate policies. To support these goals, many governments are promoting forest landscape restoration and management through financial forestry incentives, a form of payment for ecosystem services. Since 1996, Guatemala has implemented a series of forestry incentives that promote active forest landscape restoration and management on private and communal lands. These programs have been widely hailed as a success with nearly 600 000 ha enrolled since 1998. However, there has been no systematic assessment of the effectiveness of these programs on preserving and restoring Guatemalan forests. This study evaluates the impacts of over 16 000 individual PES projects funded through two incentive programs using a synthetic control counterfactual. Overall, a program for smallholders resulted in lower rates of forest loss, while a program for industrial timber owners led to greater gains in forest cover. Across policies, we found dramatically higher forest cover increases from restoration projects (15% forest cover increase) compared to plantation and agroforestry projects (3%–6% increase in forest cover). Projects that protected natural forest also showed a 6% reduction in forest loss. We found forest cover increases to be under 10% of total enrolled area, although positive local spillovers suggest this is an underestimate. Restoration projects show the most promise at promoting forest landscape restoration, but these benefits need to be weighed against priorities like resilience and rural development, which may be better served by other projects.</dc:description><dc:subject>30 Agricultural</dc:subject><dc:subject>Veterinary and Food Sciences (for-2020)</dc:subject><dc:subject>4102 Ecological Applications (for-2020)</dc:subject><dc:subject>38 Economics (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>3007 Forestry Sciences (for-2020)</dc:subject><dc:subject>15 Life on Land (sdg)</dc:subject><dc:subject>payment for ecosystem services</dc:subject><dc:subject>synthetic controls</dc:subject><dc:subject>reforestation</dc:subject><dc:subject>forest landscape restoration</dc:subject><dc:subject>smallholders</dc:subject><dc:subject>plantations</dc:subject><dc:subject>forest management</dc:subject><dc:subject>Meteorology &amp; Atmospheric Sciences (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/26k5w58q</dc:identifier><dc:identifier>https://escholarship.org/content/qt26k5w58q/qt26k5w58q.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1748-9326/acf602</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Research Letters, vol 18, iss 10</dc:source><dc:coverage>104030</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9474w7zh</identifier><datestamp>2026-09-15T22:40:09Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9474w7zh</dc:identifier><dc:title>Search for higgsinos in compressed mass spectra using low-momentum tracks in pp collisions at s=13 TeV with the ATLAS detector</dc:title><dc:creator>Aad, G</dc:creator><dc:creator>Aakvaag, E</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdelhameed, S</dc:creator><dc:creator>Abeling, K</dc:creator><dc:creator>Abicht, NJ</dc:creator><dc:creator>Abidi, SH</dc:creator><dc:creator>Aboelela, M</dc:creator><dc:creator>Aboulhorma, A</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Ackermann, A</dc:creator><dc:creator>Adam Bourdarios, C</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Addepalli, SV</dc:creator><dc:creator>Addison, MJ</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adiguzel, A</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Afik, Y</dc:creator><dc:creator>Agaras, MN</dc:creator><dc:creator>Aggarwal, A</dc:creator><dc:creator>Agheorghiesei, C</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Ahuja, S</dc:creator><dc:creator>Ai, X</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Aikot, A</dc:creator><dc:creator>Ait Tamlihat, M</dc:creator><dc:creator>Aitbenchikh, B</dc:creator><dc:creator>Akbiyik, M</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Akiyama, D</dc:creator><dc:creator>Akolkar, NN</dc:creator><dc:creator>Aktas, S</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Alberti, U</dc:creator><dc:creator>Albicocco, P</dc:creator><dc:creator>Albouy, GL</dc:creator><dc:creator>Alderweireldt, S</dc:creator><dc:creator>Alegria, ZL</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alfonsi, F</dc:creator><dc:creator>Algren, M</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Ali, B</dc:creator><dc:creator>Ali, HMJ</dc:creator><dc:creator>Ali, S</dc:creator><dc:creator>Alibocus, SW</dc:creator><dc:creator>Aliev, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alkakhi, W</dc:creator><dc:creator>Allaire, C</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allen, JS</dc:creator><dc:creator>Allen, JF</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Alsolami, ZMK</dc:creator><dc:creator>Alvarez Fernandez, A</dc:creator><dc:creator>Alves Cardoso, M</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Aly, M</dc:creator><dc:creator>Amaral Coutinho, Y</dc:creator><dc:creator>Ambler, A</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amerl, M</dc:creator><dc:creator>Ames, CG</dc:creator><dc:creator>Amezza, T</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Amini, B</dc:creator><dc:creator>Amirie, K</dc:creator><dc:creator>Amirkhanov, A</dc:creator><dc:creator>Amor Dos Santos, SP</dc:creator><dc:creator>Amos, KR</dc:creator><dc:creator>Amperiadou, D</dc:creator><dc:creator>An, S</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Anderson, AC</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antel, C</dc:creator><dc:creator>Antipov, E</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:date>2026-06-08</dc:date><dc:description>This paper presents two searches for the electroweak production of higgsinos with compressed mass spectra using 140 fb−1 of s=13$$ \sqrt{s}=13 $$ TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider. Events are required to feature an energetic jet, large missing transverse momentum, and at least one low-momentum charged particle that serves as a candidate higgsino decay product. In the first search, targeting higgsino mass splittings in the range of 0.3–1 GeV, the higgsinos are expected to predominantly decay into pions that are identified as low-momentum charged particles with large transverse impact parameters due to the long higgsino lifetime (cτ ≈ ?(0.1–10 mm)), and neural networks are used to discriminate between signal and background processes. The second search targets larger mass splittings in the range of 1–3 GeV, where the higgsinos are expected to decay promptly into low-momentum leptons, one of which is identified by dedicated low-momentum electron or muon taggers based on neural networks utilising tracking and calorimeter information. No significant excess above the Standard Model prediction is observed in either search and the results are interpreted within simplified models, to set lower limits on the masses of the higgsino-like charginos and neutralinos. Together, these searches exclude chargino masses below 126 GeV at 95% confidence level for mass splittings between the chargino and lightest neutralino in the range of 0.3–2 GeV. This represents the first ATLAS constraints in a portion of this parameter space and surpasses the limits previously set by other experiments.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Hadron-Hadron Scattering</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>4902 Mathematical physics (for-2020)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9474w7zh</dc:identifier><dc:identifier>https://escholarship.org/content/qt9474w7zh/qt9474w7zh.pdf</dc:identifier><dc:identifier>info:doi/10.1007/jhep06(2026)094</dc:identifier><dc:type>article</dc:type><dc:source>Journal of High Energy Physics, vol 2026, iss 6</dc:source><dc:coverage>94</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0158h3rb</identifier><datestamp>2026-09-15T22:39:26Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0158h3rb</dc:identifier><dc:title>Search for a resonance decaying into a scalar particle and a Higgs boson in the final state with two bottom quarks and two photons with 199 fb − 1 of data collected at s =13 and 13.6 TeV with the ATLAS detector</dc:title><dc:creator>Aad, G</dc:creator><dc:creator>Aakvaag, E</dc:creator><dc:creator>Abbott, B</dc:creator><dc:creator>Abdelhameed, S</dc:creator><dc:creator>Abeling, K</dc:creator><dc:creator>Abicht, NJ</dc:creator><dc:creator>Abidi, SH</dc:creator><dc:creator>Aboelela, M</dc:creator><dc:creator>Aboulhorma, A</dc:creator><dc:creator>Abramowicz, H</dc:creator><dc:creator>Abulaiti, Y</dc:creator><dc:creator>Acharya, BS</dc:creator><dc:creator>Ackermann, A</dc:creator><dc:creator>Bourdarios, C Adam</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Addepalli, SV</dc:creator><dc:creator>Addison, MJ</dc:creator><dc:creator>Adelman, J</dc:creator><dc:creator>Adiguzel, A</dc:creator><dc:creator>Adye, T</dc:creator><dc:creator>Affolder, AA</dc:creator><dc:creator>Afik, Y</dc:creator><dc:creator>Agaras, MN</dc:creator><dc:creator>Aggarwal, A</dc:creator><dc:creator>Agheorghiesei, C</dc:creator><dc:creator>Ahmadov, F</dc:creator><dc:creator>Ahuja, S</dc:creator><dc:creator>Ai, X</dc:creator><dc:creator>Aielli, G</dc:creator><dc:creator>Aikot, A</dc:creator><dc:creator>Tamlihat, M Ait</dc:creator><dc:creator>Aitbenchikh, B</dc:creator><dc:creator>Akbiyik, M</dc:creator><dc:creator>Åkesson, TPA</dc:creator><dc:creator>Akimov, AV</dc:creator><dc:creator>Akiyama, D</dc:creator><dc:creator>Akolkar, NN</dc:creator><dc:creator>Aktas, S</dc:creator><dc:creator>Alberghi, GL</dc:creator><dc:creator>Albert, J</dc:creator><dc:creator>Alberti, U</dc:creator><dc:creator>Albicocco, P</dc:creator><dc:creator>Albouy, GL</dc:creator><dc:creator>Alderweireldt, S</dc:creator><dc:creator>Alegria, ZL</dc:creator><dc:creator>Aleksa, M</dc:creator><dc:creator>Aleksandrov, IN</dc:creator><dc:creator>Alexa, C</dc:creator><dc:creator>Alexopoulos, T</dc:creator><dc:creator>Alfonsi, F</dc:creator><dc:creator>Algren, M</dc:creator><dc:creator>Alhroob, M</dc:creator><dc:creator>Ali, B</dc:creator><dc:creator>Ali, HMJ</dc:creator><dc:creator>Ali, S</dc:creator><dc:creator>Alibocus, SW</dc:creator><dc:creator>Aliev, M</dc:creator><dc:creator>Alimonti, G</dc:creator><dc:creator>Alkakhi, W</dc:creator><dc:creator>Allaire, C</dc:creator><dc:creator>Allbrooke, BMM</dc:creator><dc:creator>Allen, JS</dc:creator><dc:creator>Allen, JF</dc:creator><dc:creator>Allport, PP</dc:creator><dc:creator>Aloisio, A</dc:creator><dc:creator>Alonso, F</dc:creator><dc:creator>Alpigiani, C</dc:creator><dc:creator>Alsolami, ZMK</dc:creator><dc:creator>Fernandez, A Alvarez</dc:creator><dc:creator>Cardoso, M Alves</dc:creator><dc:creator>Alviggi, MG</dc:creator><dc:creator>Aly, M</dc:creator><dc:creator>Coutinho, Y Amaral</dc:creator><dc:creator>Ambler, A</dc:creator><dc:creator>Amelung, C</dc:creator><dc:creator>Amerl, M</dc:creator><dc:creator>Ames, CG</dc:creator><dc:creator>Amezza, T</dc:creator><dc:creator>Amidei, D</dc:creator><dc:creator>Amini, B</dc:creator><dc:creator>Amirie, K</dc:creator><dc:creator>Amirkhanov, A</dc:creator><dc:creator>Dos Santos, SP Amor</dc:creator><dc:creator>Amos, KR</dc:creator><dc:creator>Amperiadou, D</dc:creator><dc:creator>An, S</dc:creator><dc:creator>Anastopoulos, C</dc:creator><dc:creator>Andeen, T</dc:creator><dc:creator>Anders, JK</dc:creator><dc:creator>Anderson, AC</dc:creator><dc:creator>Andreazza, A</dc:creator><dc:creator>Angelidakis, S</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Anisenkov, AV</dc:creator><dc:creator>Annovi, A</dc:creator><dc:creator>Antel, C</dc:creator><dc:creator>Antipov, E</dc:creator><dc:creator>Antonelli, M</dc:creator><dc:creator>Anulli, F</dc:creator><dc:creator>Aoki, M</dc:creator><dc:date>2026-06-01</dc:date><dc:description>A search for the resonant production of a heavy scalar X decaying into a lighter scalar S and a Higgs boson, through the process X → S ( → b b ¯ ) H ( → γ γ ) , where the two photons are consistent with the Higgs boson decay, is performed. The search is conducted using integrated luminosities of 140 and 59 fb − 1 of proton–proton collision data at centre-of-mass energies of 13 and 13.6 TeV, respectively, recorded with the ATLAS detector at the LHC. The search is performed over the mass ranges of 170  ≤  mX  ≤  1000 GeV and 15  ≤  mS  ≤  500 GeV. No significant excess over the Standard Model background predictions is observed and limits at 95% confidence level are set on the product of cross section and branching fraction for the process X → S ( → b b ¯ ) H ( → γ γ ) at 13 TeV, ranging from 9 fb to 0.06 fb.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0158h3rb</dc:identifier><dc:identifier>https://escholarship.org/content/qt0158h3rb/qt0158h3rb.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.physletb.2026.140425</dc:identifier><dc:type>article</dc:type><dc:source>Physics Letters B, vol 877</dc:source><dc:coverage>140425</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt79h346xf</identifier><datestamp>2026-09-15T22:30:49Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt79h346xf</dc:identifier><dc:title>β decay of Mg36 and Al36: Identification of a β-decaying isomer in Al36</dc:title><dc:creator>Lubna, RS</dc:creator><dc:creator>Liddick, SN</dc:creator><dc:creator>Ogunbeku, TH</dc:creator><dc:creator>Chester, A</dc:creator><dc:creator>Allmond, JM</dc:creator><dc:creator>Bhattacharya, Soumik</dc:creator><dc:creator>Campbell, CM</dc:creator><dc:creator>Carpenter, MP</dc:creator><dc:creator>Childers, KL</dc:creator><dc:creator>Chowdhury, P</dc:creator><dc:creator>Christie, J</dc:creator><dc:creator>Clark, BR</dc:creator><dc:creator>Clark, RM</dc:creator><dc:creator>Cox, I</dc:creator><dc:creator>Crawford, HL</dc:creator><dc:creator>Crider, BP</dc:creator><dc:creator>Doetsch, AA</dc:creator><dc:creator>Fallon, P</dc:creator><dc:creator>Frotscher, A</dc:creator><dc:creator>Gaballah, T</dc:creator><dc:creator>Gray, TJ</dc:creator><dc:creator>Grzywacz, R</dc:creator><dc:creator>Harke, JT</dc:creator><dc:creator>Hartley, AC</dc:creator><dc:creator>Jain, R</dc:creator><dc:creator>King, TT</dc:creator><dc:creator>Kitamura, N</dc:creator><dc:creator>Kolos, K</dc:creator><dc:creator>Kondev, FG</dc:creator><dc:creator>Lamere, E</dc:creator><dc:creator>Lewis, R</dc:creator><dc:creator>Longfellow, B</dc:creator><dc:creator>Lyons, S</dc:creator><dc:creator>Luitel, S</dc:creator><dc:creator>Madurga, M</dc:creator><dc:creator>Mahajan, R</dc:creator><dc:creator>Mogannam, MJ</dc:creator><dc:creator>Morse, C</dc:creator><dc:creator>Neupane, SK</dc:creator><dc:creator>Ong, W-J</dc:creator><dc:creator>Perez-Loureiro, D</dc:creator><dc:creator>Porzio, C</dc:creator><dc:creator>Prokop, CJ</dc:creator><dc:creator>Richard, AL</dc:creator><dc:creator>Ronning, EK</dc:creator><dc:creator>Rubino, E</dc:creator><dc:creator>Rykaczewski, K</dc:creator><dc:creator>Seweryniak, D</dc:creator><dc:creator>Siegl, K</dc:creator><dc:creator>Silwal, U</dc:creator><dc:creator>Singh, M</dc:creator><dc:creator>Siwakoti, DP</dc:creator><dc:creator>Smith, DC</dc:creator><dc:creator>Smith, MK</dc:creator><dc:creator>Tabor, SL</dc:creator><dc:creator>Tang, TL</dc:creator><dc:creator>Tripathi, Vandana</dc:creator><dc:creator>Volya, A</dc:creator><dc:creator>Wheeler, T</dc:creator><dc:creator>Xiao, Y</dc:creator><dc:creator>Xu, Z</dc:creator><dc:date>2023-07-01</dc:date><dc:description>The level structure of Al36 has been studied via β decay of Mg36 at the Facility for Rare Isotope Beams (FRIB) and the National Superconducting Cyclotron Laboratory (NSCL). A long-lived isomer in Al36 was identified which decays by β to an excited state of Si36. The ground state and the isomeric state of Al36 were found to populate different energy levels of Si36. The results from the two data sets in the present work complement each other. Configuration interaction calculations performed with the FSU shell-model Hamiltonians provide reasonable descriptions to the experimental observations and offer insight into future improvements of the theoretical interpretation.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>NSD-Low Energy Nuclear Physics (c-lbnl-label)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/79h346xf</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1103/physrevc.108.014329</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review C, vol 108, iss 1</dc:source><dc:coverage>014329</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt113230xt</identifier><datestamp>2026-09-15T22:26:48Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt113230xt</dc:identifier><dc:title>Evidence for large baryonic feedback at low and intermediate redshifts from kinematic Sunyaev-Zel’dovich observations with ACT and DESI photometric galaxies</dc:title><dc:creator>Hadzhiyska, B</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Guachalla, B Ried</dc:creator><dc:creator>Schaan, E</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Battaglia, N</dc:creator><dc:creator>Bond, JR</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Calabrese, E</dc:creator><dc:creator>Choi, SK</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Coulton, WR</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>Devlin, M</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Duivenvoorden, AJ</dc:creator><dc:creator>Dunkley, J</dc:creator><dc:creator>Farren, GS</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gallardo, PA</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho</dc:creator><dc:creator>Gralla, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hill, JC</dc:creator><dc:creator>Hložek, R</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Liu, RH</dc:creator><dc:creator>Louis, T</dc:creator><dc:creator>MacCrann, N</dc:creator><dc:creator>de Macorra, A</dc:creator><dc:creator>Madhavacheril, M</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moodley, K</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Mroczkowski, T</dc:creator><dc:creator>Naess, S</dc:creator><dc:creator>Newman, J</dc:creator><dc:creator>Niemack, MD</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Page, L</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Partridge, B</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Qu, FJ</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Sherwin, B</dc:creator><dc:creator>Sehgal, N</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Sifón, C</dc:creator><dc:creator>Spergel, D</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Staggs, S</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Vargas, C</dc:creator><dc:creator>Vavagiakis, EM</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Wollack, EJ</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-10-15</dc:date><dc:description>Recent advances in cosmological observations have provided an unprecedented opportunity to investigate the distribution of baryons relative to the underlying matter. In this work, we show that the gas is more extended than the dark matter, and the amount of baryonic feedback at z≲1 disfavors low-feedback models such as that of state-of-the-art hydrodynamical simulation IllustrisTNG compared with high-feedback models such as that of the original Illustris simulation. This has important implications for bridging the gap between theory and observations and understanding galaxy formation and evolution. Furthermore, a better grasp of the baryon-dark matter link is critical to future cosmological analyses, which are currently impeded by our limited knowledge of baryonic feedback. Here, we measure the kinematic Sunyaev-Zel’dovich (kSZ) effect from the Atacama Cosmology Telescope, stacked on the luminous red galaxy sample of the Dark Energy Spectroscopic Instrument (DESI) imaging survey. This is the first analysis to use photometric redshifts for reconstructing galaxy velocities. Due to the large number of galaxies comprising the DESI imaging survey, this is the highest signal-to-noise stacked kSZ measurement to date; we detect the signal at 13σ, finding strong evidence that the gas is more spread out than the dark matter, as well as a preference for larger feedback compared to some commonly used state-of-the-art hydrodynamical simulations. Our work opens up the possibility of recalibrating large hydrodynamical simulations using the kSZ effect. In addition, our findings highlight the importance of properly accounting for baryonic feedback with future surveys such as LSST through direct probes such as the kSZ, and shed light on long-standing enigmas in astrophysics, such as the “missing baryon” problem.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:rights>CC-BY-SA</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/113230xt</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1103/kclp-x5j1</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 112, iss 8</dc:source><dc:coverage>083509</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt65s4w5fv</identifier><datestamp>2026-09-15T22:23:06Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt65s4w5fv</dc:identifier><dc:title>Analyzing Transatlantic Network Traffic over Scientific Data Caches</dc:title><dc:creator>Deng, Ziyue</dc:creator><dc:creator>Sim, Alex</dc:creator><dc:creator>Wu, Kesheng</dc:creator><dc:creator>Guok, Chin</dc:creator><dc:creator>Hazen, Damian</dc:creator><dc:creator>Monga, Inder</dc:creator><dc:creator>Andrijauskas, Fabio</dc:creator><dc:creator>Würthwein, Frank</dc:creator><dc:creator>Weitzel, Derek</dc:creator><dc:date>2023-07-28</dc:date><dc:description>Large scientific collaborations often share huge volumes of data around the world. Consequently a significant amount of network bandwidth is needed for data replication and data access. Users in the same region may possibly share resources as well as data, especially when they are working on related topics with similar datasets. In this work, we study the network traffic patterns and resource utilization for scientific data caches connecting European networks to the US. We explore the efficiency of resource utilization, especially for network traffic which consists mostly of transatlantic data transfers, and the potential for having more caching node deployments. Our study shows that these data caches reduced network traffic volume by 97% during the study period. This demonstrates that such caching nodes are effective in reducing wide-area network traffic.</dc:description><dc:subject>4005 Civil Engineering (for-2020)</dc:subject><dc:subject>46 Information and Computing Sciences (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/65s4w5fv</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1145/3589012.3594897</dc:identifier><dc:type>article</dc:type><dc:source>Snta 2023 Proceedings of the 2023 on Systems and Network Telemetry and Analytics</dc:source><dc:coverage>19 - 22</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2q56g42q</identifier><datestamp>2026-09-15T22:18:12Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2q56g42q</dc:identifier><dc:title>A genome assembly for the southern Pacific rattlesnake, Crotalus oreganus helleri, in the western rattlesnake species complex</dc:title><dc:creator>Westeen, Erin P</dc:creator><dc:creator>Escalona, Merly</dc:creator><dc:creator>Holding, Matthew L</dc:creator><dc:creator>Beraut, Eric</dc:creator><dc:creator>Fairbairn, Colin</dc:creator><dc:creator>Marimuthu, Mohan PA</dc:creator><dc:creator>Nguyen, Oanh</dc:creator><dc:creator>Perri, Ralph</dc:creator><dc:creator>Fisher, Robert N</dc:creator><dc:creator>Toffelmier, Erin</dc:creator><dc:creator>Shaffer, H Bradley</dc:creator><dc:creator>Wang, Ian J</dc:creator><dc:contributor>Meyer, Rachel</dc:contributor><dc:date>2023-11-15</dc:date><dc:description>Rattlesnakes play important roles in their ecosystems by regulating prey populations, are involved in complex coevolutionary dynamics with their prey, and exhibit a variety of unusual adaptations, including maternal care, heat-sensing pit organs, hinged fangs, and medically-significant venoms. The western rattlesnake (Crotalus oreganus) is one of the widest ranging rattlesnake species, with a distribution from British Columbia, where it is listed as threatened, to Baja California and east across the Great Basin to western Wyoming, Colorado and New Mexico. Here, we report a new reference genome assembly for one of six currently recognized subspecies, C. oreganus helleri, as part of the California Conservation Genomics Project (CCGP). Consistent with the reference genomic sequencing strategy of the CCGP, we used Pacific Biosciences HiFi long reads and Hi-C chromatin-proximity sequencing technology to produce a de novo assembled genome. The assembly comprises a total of 698 scaffolds spanning 1,564,812,557 base pairs, has a contig N50 of 64.7 Mb, a scaffold N50 of 110.8 Mb, and BUSCO complete score of 90.5%. This reference genome will be valuable for studies on the genomic basis of venom evolution and variation within Crotalus, in resolving the taxonomy of C. oreganus and its relatives, and for the conservation and management of rattlesnakes in general.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3102 Bioinformatics and Computational Biology (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Biotechnology (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Generic health relevance (hrcs-hc)</dc:subject><dc:subject>15 Life on Land (sdg)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Mexico (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Crotalus (mesh)</dc:subject><dc:subject>Venomous Snakes (mesh)</dc:subject><dc:subject>California Conservation Genomics Project</dc:subject><dc:subject>conservation genetics</dc:subject><dc:subject>reference genome</dc:subject><dc:subject>snake</dc:subject><dc:subject>Viperidae</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Crotalus (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Mexico (mesh)</dc:subject><dc:subject>Venomous Snakes (mesh)</dc:subject><dc:subject>California Conservation Genomics Project</dc:subject><dc:subject>Viperidae</dc:subject><dc:subject>conservation genetics</dc:subject><dc:subject>reference genome</dc:subject><dc:subject>snake</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Mexico (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Crotalus (mesh)</dc:subject><dc:subject>Venomous Snakes (mesh)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>Evolutionary Biology (science-metrix)</dc:subject><dc:subject>3104 Evolutionary biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2q56g42q</dc:identifier><dc:identifier>https://escholarship.org/content/qt2q56g42q/qt2q56g42q.pdf</dc:identifier><dc:identifier>info:doi/10.1093/jhered/esad045</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Heredity, vol 114, iss 6</dc:source><dc:coverage>681 - 689</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt82c636sw</identifier><datestamp>2026-09-15T22:17:03Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt82c636sw</dc:identifier><dc:title>Temporal associations between circadian sleep and activity patterns in Mexican American children</dc:title><dc:creator>Martinez, SM</dc:creator><dc:creator>Tschann, JM</dc:creator><dc:creator>McCulloch, CE</dc:creator><dc:creator>Sites, E</dc:creator><dc:creator>Butte, NF</dc:creator><dc:creator>Gregorich</dc:creator><dc:creator>Penilla, C</dc:creator><dc:creator>Flores, E</dc:creator><dc:creator>Pasch, LA</dc:creator><dc:creator>Greenspan, LC</dc:creator><dc:creator>Deardorff, J</dc:creator><dc:date>2019-04-01</dc:date><dc:description>OBJECTIVE: This study aimed to examine the relationship between circadian sleep and activity behaviors (sedentary time [SED], light-intensity physical activity [LPA], and moderate- to vigorous-intensity physical activity [MVPA]) across 3 consecutive days.
METHODS: This study included 308 Mexican American children aged 8-10 years from the San Francisco Bay Area. Minutes of sleep duration, SED, LPA, and MVPA were estimated using hip-worn accelerometers from Wednesday night to Saturday night. A cross-lagged panel model was used to estimate paths between sleep duration the prior night and subsequent behaviors, and paths between behaviors to subsequent sleep duration across the 3 days. We adjusted for child age, sex, body mass index, and household income.
RESULTS: Overall, children were 8.9 (SD 0.8) years old; the weighted average for weekday and weekend combined was 9.6 (SD 0.7) hours per night in sleep duration, 483 (SD 74) min/d SED, 288 (SD 61) min/d LPA, and 63 (SD 38) min/d MVPA. Cross-lagged panel analyses showed that, over 3 days, for every 1-hour increase in sleep duration, there were an expected 0.66-hour (40-minute) decrease in SED, 0.37-hour (22-minute) decrease in LPA, and 0.06-hour (4-minute) decrease in MVPA. For every 1-hour increase in LPA, there was an expected 0.25-hour (15-minute) decrease in sleep duration.
CONCLUSION: An additional hour of sleep the night before corresponded to an hour decrease in combined SED and LPA the next day in Mexican American children. For every hour of LPA, there was an associated 15-minute decrease in sleep. Encouraging longer sleep may help to reduce SED and LPA, and help offset LPA's negative predictive effect on sleep.</dc:description><dc:subject>4206 Public Health (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Sleep Research (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Physical Activity (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Basic Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Circadian Rhythm (mesh)</dc:subject><dc:subject>Exercise (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Mexican Americans (mesh)</dc:subject><dc:subject>Sedentary Behavior (mesh)</dc:subject><dc:subject>Sleep (mesh)</dc:subject><dc:subject>Time Factors (mesh)</dc:subject><dc:subject>Sleep duration</dc:subject><dc:subject>Physical activity</dc:subject><dc:subject>Sedentary behavior</dc:subject><dc:subject>Lagged panel model</dc:subject><dc:subject>Latino children</dc:subject><dc:subject>Temporal</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Exercise (mesh)</dc:subject><dc:subject>Sleep (mesh)</dc:subject><dc:subject>Circadian Rhythm (mesh)</dc:subject><dc:subject>Time Factors (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Mexican Americans (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Sedentary Behavior (mesh)</dc:subject><dc:subject>Lagged panel model</dc:subject><dc:subject>Latino children</dc:subject><dc:subject>Physical activity</dc:subject><dc:subject>Sedentary behavior</dc:subject><dc:subject>Sleep duration</dc:subject><dc:subject>Temporal</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Circadian Rhythm (mesh)</dc:subject><dc:subject>Exercise (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Mexican Americans (mesh)</dc:subject><dc:subject>Sedentary Behavior (mesh)</dc:subject><dc:subject>Sleep (mesh)</dc:subject><dc:subject>Time Factors (mesh)</dc:subject><dc:subject>1117 Public Health and Health Services (for)</dc:subject><dc:subject>1701 Psychology (for)</dc:subject><dc:subject>4206 Public health (for-2020)</dc:subject><dc:subject>5201 Applied and developmental psychology (for-2020)</dc:subject><dc:subject>5203 Clinical and health psychology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/82c636sw</dc:identifier><dc:identifier>https://escholarship.org/content/qt82c636sw/qt82c636sw.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.sleh.2018.10.012</dc:identifier><dc:type>article</dc:type><dc:source>Sleep Health, vol 5, iss 2</dc:source><dc:coverage>201 - 207</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt46h13726</identifier><datestamp>2026-09-15T22:14:00Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt46h13726</dc:identifier><dc:title>Linear complexity </dc:title><dc:creator>Boukaram, Wajih</dc:creator><dc:creator>Keyes, David</dc:creator><dc:creator>Li, Xiaoye</dc:creator><dc:creator>Liu, Yang</dc:creator><dc:creator>Turkiyyah, George</dc:creator><dc:date>2026-06-30</dc:date><dc:description>Abstract We present factorization and solution phases for a new linear complexity direct solver designed for concurrent batch operations on fine-grained parallel architectures, for matrices amenable to hierarchical representation. We focus on the strong-admissibility-based $\mathscr{H}^{2}$ format, where strong recursive skeletonization factorization compresses remote interactions. We build upon previous implementations of $\mathscr{H}^{2}$ matrix construction for efficient factorization and solution algorithm design, which are illustrated graphically in stepwise detail. The algorithms are ‘blackbox’ in the sense that the only inputs are the matrix and right-hand side, without analytical or geometrical information about the origin of the system. We demonstrate linear complexity scaling in both time and memory on four representative families of dense matrices up to one million in size. Parallel scaling up to 16 threads is enabled by a multi-level matrix graph coloring and avoidance of dynamic memory allocations thanks to prefix-sum memory management. An experimental backward error analysis is included. We break down the timings of different phases, identify phases that are memory-bandwidth limited, and discuss alternatives for phases that may be sensitive to the trend to employ lower precisions for performance.</dc:description><dc:subject>4901 Applied Mathematics (for-2020)</dc:subject><dc:subject>49 Mathematical Sciences (for-2020)</dc:subject><dc:subject>linear complexity direct linear solver</dc:subject><dc:subject>hierarchically low-rank matrices</dc:subject><dc:subject>fine-grained concurrent implementation</dc:subject><dc:subject>0102 Applied Mathematics (for)</dc:subject><dc:subject>0103 Numerical and Computational Mathematics (for)</dc:subject><dc:subject>Numerical &amp; Computational Mathematics (science-metrix)</dc:subject><dc:subject>4901 Applied mathematics (for-2020)</dc:subject><dc:subject>4903 Numerical and computational mathematics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/46h13726</dc:identifier><dc:identifier>https://escholarship.org/content/qt46h13726/qt46h13726.pdf</dc:identifier><dc:identifier>info:doi/10.1093/imanum/drag030</dc:identifier><dc:type>article</dc:type><dc:source>IMA Journal of Numerical Analysis</dc:source><dc:coverage>drag030</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8775r1mf</identifier><datestamp>2026-09-15T22:09:29Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8775r1mf</dc:identifier><dc:title>3D Mechanical Analysis of a Compact ${\text{Nb}}_{\text{3}}{\text{Sn}}$ IR Quadrupole for EIC</dc:title><dc:creator>Vallone, Giorgio</dc:creator><dc:creator>Anerella, Michael</dc:creator><dc:creator>Parker, Brett</dc:creator><dc:creator>Cozzolino, John</dc:creator><dc:creator>Michalski, Timothy</dc:creator><dc:creator>Plate, Stephen</dc:creator><dc:creator>Prestemon, Soren</dc:creator><dc:creator>Sabbi, GianLuca</dc:creator><dc:creator>Schmalzle, Jesse</dc:creator><dc:date>2021-08-01</dc:date><dc:description>The Electron Ion Collider (EIC) will require large aperture quadrupole magnets for the Hadron beam in the insertion region. Key requirements include high field, compact size, and tight control of the fringe fields. A 120mm aperture, 308.4mm outer diameter actively shielded ${\rm {Nb}}_{3}{\rm {Sn}}$ quadrupole model is under development to support these goals. This work is being carried out by a collaboration of BNL, JLAB and LBNL. A compact shell-based structure preloaded with a bladder and key system was developed for this project. In this paper, the effect of the compact structure on the mechanical behavior was investigated. In particular, the impact of the assembly tolerances and coil size variations on the actual coil stresses and bladder pressures was computed and compared with results from larger bladder and key structures developed for the LHC IR. The longitudinal preload is provided by stainless steel rods. Differently from other bladder and key magnets, the rods are first preloaded axially before coil axial load is applied. This new design aims to increase the overall stiffness of the system and reduce the longitudinal coil displacement during powering. Based on the results of a 3D mechanical analysis, the preliminary pre-load targets for the EIC quadrupole assembly will be reviewed and discussed.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Urologic Diseases (rcdc)</dc:subject><dc:subject>Electron ion collider</dc:subject><dc:subject>Nb8Sn magnet</dc:subject><dc:subject>mechanical performance</dc:subject><dc:subject>Electron ion collider</dc:subject><dc:subject>Nb3Sn magnet</dc:subject><dc:subject>mechanical performance</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>4008 Electrical engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8775r1mf</dc:identifier><dc:identifier>https://escholarship.org/content/qt8775r1mf/qt8775r1mf.pdf</dc:identifier><dc:identifier>info:doi/10.1109/tasc.2021.3062782</dc:identifier><dc:type>article</dc:type><dc:source>IEEE Transactions on Applied Superconductivity, vol 31, iss 5</dc:source><dc:coverage>1 - 5</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3j23j59x</identifier><datestamp>2026-09-15T22:08:40Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3j23j59x</dc:identifier><dc:title>Twelve-crystal prototype of Li2MoO4 scintillating bolometers for CUPID and CROSS experiments</dc:title><dc:creator>Alfonso, K</dc:creator><dc:creator>Armatol, A</dc:creator><dc:creator>Augier, C</dc:creator><dc:creator>Avignone, FT</dc:creator><dc:creator>Azzolini, O</dc:creator><dc:creator>Balata, M</dc:creator><dc:creator>Bandac, IC</dc:creator><dc:creator>Barabash, AS</dc:creator><dc:creator>Bari, G</dc:creator><dc:creator>Barresi, A</dc:creator><dc:creator>Baudin, D</dc:creator><dc:creator>Bellini, F</dc:creator><dc:creator>Benato, G</dc:creator><dc:creator>Berest, V</dc:creator><dc:creator>Beretta, M</dc:creator><dc:creator>Bettelli, M</dc:creator><dc:creator>Biassoni, M</dc:creator><dc:creator>Billard, J</dc:creator><dc:creator>Boldrini, V</dc:creator><dc:creator>Branca, A</dc:creator><dc:creator>Brofferio, C</dc:creator><dc:creator>Bucci, C</dc:creator><dc:creator>Calvo-Mozota, JM</dc:creator><dc:creator>Camilleri, J</dc:creator><dc:creator>Campani, A</dc:creator><dc:creator>Capelli, C</dc:creator><dc:creator>Capelli, S</dc:creator><dc:creator>Cappelli, L</dc:creator><dc:creator>Cardani, L</dc:creator><dc:creator>Carniti, P</dc:creator><dc:creator>Casali, N</dc:creator><dc:creator>Celi, E</dc:creator><dc:creator>Chang, C</dc:creator><dc:creator>Chiesa, D</dc:creator><dc:creator>Clemenza, M</dc:creator><dc:creator>Colantoni, I</dc:creator><dc:creator>Copello, S</dc:creator><dc:creator>Craft, E</dc:creator><dc:creator>Cremonesi, O</dc:creator><dc:creator>Creswick, RJ</dc:creator><dc:creator>Cruciani, A</dc:creator><dc:creator>D'Addabbo, A</dc:creator><dc:creator>D'Imperio, G</dc:creator><dc:creator>Dabagov, S</dc:creator><dc:creator>Dafinei, I</dc:creator><dc:creator>Danevich, FA</dc:creator><dc:creator>De Jesus, M</dc:creator><dc:creator>de Marcillac, P</dc:creator><dc:creator>Dell'Oro, S</dc:creator><dc:creator>Di Domizio, S</dc:creator><dc:creator>Di Lorenzo, S</dc:creator><dc:creator>Dixon, T</dc:creator><dc:creator>Dompé, V</dc:creator><dc:creator>Drobizhev, A</dc:creator><dc:creator>Dumoulin, L</dc:creator><dc:creator>Fantini, G</dc:creator><dc:creator>Faverzani, M</dc:creator><dc:creator>Ferri, E</dc:creator><dc:creator>Ferri, F</dc:creator><dc:creator>Ferroni, F</dc:creator><dc:creator>Figueroa-Feliciano, E</dc:creator><dc:creator>Foggetta, L</dc:creator><dc:creator>Formaggio, J</dc:creator><dc:creator>Franceschi, A</dc:creator><dc:creator>Fu, C</dc:creator><dc:creator>Fu, S</dc:creator><dc:creator>Fujikawa, BK</dc:creator><dc:creator>Gallas, A</dc:creator><dc:creator>Gascon, J</dc:creator><dc:creator>Ghislandi, S</dc:creator><dc:creator>Giachero, A</dc:creator><dc:creator>Gianvecchio, A</dc:creator><dc:creator>Girola, M</dc:creator><dc:creator>Gironi, L</dc:creator><dc:creator>Giuliani, A</dc:creator><dc:creator>Gorla, P</dc:creator><dc:creator>Gotti, C</dc:creator><dc:creator>Grant, C</dc:creator><dc:creator>Gras, P</dc:creator><dc:creator>Guillaumon, PV</dc:creator><dc:creator>Gutierrez, TD</dc:creator><dc:creator>Han, K</dc:creator><dc:creator>Hansen, EV</dc:creator><dc:creator>Heeger, KM</dc:creator><dc:creator>Helis, DL</dc:creator><dc:creator>Huang, HZ</dc:creator><dc:creator>Ianni, A</dc:creator><dc:creator>Imbert, L</dc:creator><dc:creator>Johnston, J</dc:creator><dc:creator>Juillard, A</dc:creator><dc:creator>Karapetrov, G</dc:creator><dc:creator>Keppel, G</dc:creator><dc:creator>Khalife, H</dc:creator><dc:creator>Kobychev, VV</dc:creator><dc:creator>Kolomensky, Yu G</dc:creator><dc:creator>Konovalov, SI</dc:creator><dc:creator>Kowalski, R</dc:creator><dc:creator>Langford, T</dc:creator><dc:creator>Lefevre, M</dc:creator><dc:creator>Liu, R</dc:creator><dc:date>2023-06-01</dc:date><dc:description>An array of twelve 0.28 kg lithium molybdate (LMO) low-temperature bolometers equipped with 16 bolometric Ge light detectors, aiming at optimization of detector structure for CROSS and CUPID double-beta decay experiments, was constructed and tested in a low-background pulse-tube-based cryostat at the Canfranc underground laboratory in Spain. Performance of the scintillating bolometers was studied depending on the size of phonon NTD-Ge sensors glued to both LMO and Ge absorbers, shape of the Ge light detectors (circular vs. square, from two suppliers), in different light collection conditions (with and without reflector, with aluminum coated LMO crystal surface). The scintillating bolometer array was operated over 8 months in the low-background conditions that allowed to probe a very low, μBq/kg, level of the LMO crystals radioactive contamination by 228Th and 226Ra.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Cryogenic detectors</dc:subject><dc:subject>Double-beta decay detectors</dc:subject><dc:subject>Particle identification methods</dc:subject><dc:subject>Scintillators</dc:subject><dc:subject>scintillation and light emission processes (solid</dc:subject><dc:subject>gas and liquid scintillators)</dc:subject><dc:subject>NSD-Neutrinos (c-lbnl-label)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3j23j59x</dc:identifier><dc:identifier>https://escholarship.org/content/qt3j23j59x/qt3j23j59x.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1748-0221/18/06/p06018</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Instrumentation, vol 18, iss 06</dc:source><dc:coverage>p06018</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4hg1p4z5</identifier><datestamp>2026-09-15T22:08:34Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4hg1p4z5</dc:identifier><dc:title>A first test of CUPID prototypal light detectors with NTD-Ge sensors in a pulse-tube cryostat</dc:title><dc:creator>Alfonso, K</dc:creator><dc:creator>Armatol, A</dc:creator><dc:creator>Augier, C</dc:creator><dc:creator>Avignone, FT</dc:creator><dc:creator>Azzolini, O</dc:creator><dc:creator>Balata, M</dc:creator><dc:creator>Barabash, AS</dc:creator><dc:creator>Bari, G</dc:creator><dc:creator>Barresi, A</dc:creator><dc:creator>Baudin, D</dc:creator><dc:creator>Bellini, F</dc:creator><dc:creator>Benato, G</dc:creator><dc:creator>Berest, V</dc:creator><dc:creator>Beretta, M</dc:creator><dc:creator>Bettelli, M</dc:creator><dc:creator>Biassoni, M</dc:creator><dc:creator>Billard, J</dc:creator><dc:creator>Boldrini, V</dc:creator><dc:creator>Branca, A</dc:creator><dc:creator>Brofferio, C</dc:creator><dc:creator>Bucci, C</dc:creator><dc:creator>Camilleri, J</dc:creator><dc:creator>Campani, A</dc:creator><dc:creator>Capelli, C</dc:creator><dc:creator>Capelli, S</dc:creator><dc:creator>Cappelli, L</dc:creator><dc:creator>Cardani, L</dc:creator><dc:creator>Carniti, P</dc:creator><dc:creator>Casali, N</dc:creator><dc:creator>Celi, E</dc:creator><dc:creator>Chang, C</dc:creator><dc:creator>Chiesa, D</dc:creator><dc:creator>Clemenza, M</dc:creator><dc:creator>Colantoni, I</dc:creator><dc:creator>Copello, S</dc:creator><dc:creator>Craft, E</dc:creator><dc:creator>Cremonesi, O</dc:creator><dc:creator>Creswick, RJ</dc:creator><dc:creator>Cruciani, A</dc:creator><dc:creator>D'Addabbo, A</dc:creator><dc:creator>D'Imperio, G</dc:creator><dc:creator>Dabagov, S</dc:creator><dc:creator>Dafinei, I</dc:creator><dc:creator>Danevich, FA</dc:creator><dc:creator>De Jesus, M</dc:creator><dc:creator>de Marcillac, P</dc:creator><dc:creator>Dell'Oro, S</dc:creator><dc:creator>Di Domizio, S</dc:creator><dc:creator>Di Lorenzo, S</dc:creator><dc:creator>Dixon, T</dc:creator><dc:creator>Dompé, V</dc:creator><dc:creator>Drobizhev, A</dc:creator><dc:creator>Dumoulin, L</dc:creator><dc:creator>Fantini, G</dc:creator><dc:creator>Faverzani, M</dc:creator><dc:creator>Ferri, E</dc:creator><dc:creator>Ferri, F</dc:creator><dc:creator>Ferroni, F</dc:creator><dc:creator>Figueroa-Feliciano, E</dc:creator><dc:creator>Foggetta, L</dc:creator><dc:creator>Formaggio, J</dc:creator><dc:creator>Franceschi, A</dc:creator><dc:creator>Fu, C</dc:creator><dc:creator>Fu, S</dc:creator><dc:creator>Fujikawa, BK</dc:creator><dc:creator>Gallas, A</dc:creator><dc:creator>Gascon, J</dc:creator><dc:creator>Ghislandi, S</dc:creator><dc:creator>Giachero, A</dc:creator><dc:creator>Gianvecchio, A</dc:creator><dc:creator>Girola, M</dc:creator><dc:creator>Gironi, L</dc:creator><dc:creator>Giuliani, A</dc:creator><dc:creator>Gorla, P</dc:creator><dc:creator>Gotti, C</dc:creator><dc:creator>Grant, C</dc:creator><dc:creator>Gras, P</dc:creator><dc:creator>Guillaumon, PV</dc:creator><dc:creator>Gutierrez, TD</dc:creator><dc:creator>Han, K</dc:creator><dc:creator>Hansen, EV</dc:creator><dc:creator>Heeger, KM</dc:creator><dc:creator>Helis, DL</dc:creator><dc:creator>Huang, HZ</dc:creator><dc:creator>Imbert, L</dc:creator><dc:creator>Johnston, J</dc:creator><dc:creator>Juillard, A</dc:creator><dc:creator>Karapetrov, G</dc:creator><dc:creator>Keppel, G</dc:creator><dc:creator>Khalife, H</dc:creator><dc:creator>Kobychev, VV</dc:creator><dc:creator>Kolomensky, Yu G</dc:creator><dc:creator>Konovalov, SI</dc:creator><dc:creator>Kowalski, R</dc:creator><dc:creator>Langford, T</dc:creator><dc:creator>Lefevre, M</dc:creator><dc:creator>Liu, R</dc:creator><dc:creator>Liu, Y</dc:creator><dc:creator>Loaiza, P</dc:creator><dc:creator>Ma, L</dc:creator><dc:date>2023-06-01</dc:date><dc:description>CUPID is a next-generation bolometric experiment aiming at searching for neutrinoless double-beta decay with ∼250 kg of isotopic mass of 100Mo. It will operate at ∼10 mK in a cryostat currently hosting a similar-scale bolometric array for the CUORE experiment at the Gran Sasso National Laboratory (Italy). CUPID will be based on large-volume scintillating bolometers consisting of 100Mo-enriched Li2MoO4 crystals, facing thin Ge-wafer-based bolometric light detectors. In the CUPID design, the detector structure is novel and needs to be validated. In particular, the CUORE cryostat presents a high level of mechanical vibrations due to the use of pulse tubes and the effect of vibrations on the detector performance must be investigated. In this paper we report the first test of the CUPID-design bolometric light detectors with NTD-Ge sensors in a dilution refrigerator equipped with a pulse tube in an above-ground lab. Light detectors are characterized in terms of sensitivity, energy resolution, pulse time constants, and noise power spectrum. Despite the challenging noisy environment due to pulse-tube-induced vibrations, we demonstrate that all the four tested light detectors comply with the CUPID goal in terms of intrinsic energy resolution of 100 eV RMS baseline noise. Indeed, we have measured 70–90 eV RMS for the four devices, which show an excellent reproducibility. We have also obtained high energy resolutions at the 356 keV line from a 133Ba source, as good as Ge semiconductor γ detectors in this energy range.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Cryogenic detectors</dc:subject><dc:subject>Gamma detectors (scintillators</dc:subject><dc:subject>CZT</dc:subject><dc:subject>HPGe</dc:subject><dc:subject>HgI etc)</dc:subject><dc:subject>Photon detectors for UV</dc:subject><dc:subject>visible and IR photons (solid-state)</dc:subject><dc:subject>X-ray detectors</dc:subject><dc:subject>Cryogenic detectors</dc:subject><dc:subject>Gamma detectors (scintillators</dc:subject><dc:subject>CZT</dc:subject><dc:subject>HPGe</dc:subject><dc:subject>HgI etc)</dc:subject><dc:subject>Photon detectors for UV</dc:subject><dc:subject>visible and IR photons (solid-state)</dc:subject><dc:subject>X-ray detectors</dc:subject><dc:subject>NSD-Neutrinos (c-lbnl-label)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4hg1p4z5</dc:identifier><dc:identifier>https://escholarship.org/content/qt4hg1p4z5/qt4hg1p4z5.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1748-0221/18/06/p06033</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Instrumentation, vol 18, iss 06</dc:source><dc:coverage>p06033</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt23j7m7xv</identifier><datestamp>2026-09-15T22:01:56Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt23j7m7xv</dc:identifier><dc:title>Net fluxes of broadband shortwave and photosynthetically active radiation complement NDVI and near infrared reflectance of vegetation to explain gross photosynthesis variability across ecosystems and climate</dc:title><dc:creator>Mallick, Kanishka</dc:creator><dc:creator>Verfaillie, Joseph</dc:creator><dc:creator>Wang, Tianxin</dc:creator><dc:creator>Ortiz, Ariane Arias</dc:creator><dc:creator>Szutu, Daphne</dc:creator><dc:creator>Yi, Koong</dc:creator><dc:creator>Kang, Yanghui</dc:creator><dc:creator>Shortt, Robert</dc:creator><dc:creator>Hu, Tian</dc:creator><dc:creator>Sulis, Mauro</dc:creator><dc:creator>Szantoi, Zoltan</dc:creator><dc:creator>Boulet, Gilles</dc:creator><dc:creator>Fisher, Joshua B</dc:creator><dc:creator>Baldocchi, Dennis</dc:creator><dc:date>2024-06-01</dc:date><dc:description>A significant challenge in global change research is understanding how vegetation interacts with the environment to influence ecosystem gross primary productivity (GPP) through carbon assimilation. One emerging objective is to consistently predict GPP fluctuations worldwide by establishing a robust scaling relationship between GPP measured at flux towers and satellite spectral reflectance data. However, a major hurdle in achieving this goal is the discrepancy in spatial resolution between early satellite measurements and eddy flux measurements. By using a large set of growing season data covering 100 site-years in North and Central America, we explored the potential of transforming incident and reflected shortwave (Rg) and photosynthetically active radiation (PAR) measurements into a broadband normalized difference vegetation index (NDVI) and near-infrared (NIR) reflectance of vegetation (NIRv) which simultaneously explains the GPP variability. We found that the broadband NDVI and NIRv derived from Rg and PAR measurements at the daily time scale were highly correlated with Planet Fusion, Landsat-8/9, and Sentinel-2 narrowband NDVI and NIRv across a wide range of climate and ecological gradients. The differences between satellite and broadband NDVI and NIRv were found to be significantly associated with soil background variations, phenological stages, water stress and signal saturation of broadband NIR reflectance at high biomass. The seasonal variability of broadband NDVI and NIRv remarkably captured the seasonality of vegetation phenology, evaporative fraction, GPP and rainfall in different ecosystems. Although saturation of GPP at high NDVI was evident, a linear relationship between broadband NIRv times incident PAR versus GPP indicated the effectiveness of NIRv-based approach to capture the hidden light use efficiency impacts on GPP. Our study concludes that inexpensive measurement of Rg and PAR components can provide reliable information on NDVI, NIRv, and GPP uninterruptedly. This enhances the sensing capability of flux tower sites without requiring additional spectrometer measurements. The proposed in-situ vegetation indices make a compelling case on using radiation signals for handshaking between ecosystem-scale measurements and remote sensing observables relevant to carbon uptake.</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>Spectral reflectance</dc:subject><dc:subject>Broadband vegetation index</dc:subject><dc:subject>NIRv</dc:subject><dc:subject>Gross primary productivity</dc:subject><dc:subject>Photosynthetically active radiation</dc:subject><dc:subject>Ecosystem</dc:subject><dc:subject>Climate</dc:subject><dc:subject>Broadband vegetation index</dc:subject><dc:subject>Climate</dc:subject><dc:subject>Earth sciences</dc:subject><dc:subject>Earth Sciences</dc:subject><dc:subject>Ecosystem</dc:subject><dc:subject>Geological &amp; Geomatics Engineering</dc:subject><dc:subject>Geomatic Engineering</dc:subject><dc:subject>Gross primary productivity</dc:subject><dc:subject>NIRv</dc:subject><dc:subject>Photosynthetically active radiation</dc:subject><dc:subject>Physical Geography and Environmental Geoscience</dc:subject><dc:subject>Spectral reflectance</dc:subject><dc:subject>0406 Physical Geography and Environmental Geoscience (for)</dc:subject><dc:subject>0909 Geomatic Engineering (for)</dc:subject><dc:subject>Geological &amp; Geomatics Engineering (science-metrix)</dc:subject><dc:subject>37 Earth sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/23j7m7xv</dc:identifier><dc:identifier>https://escholarship.org/content/qt23j7m7xv/qt23j7m7xv.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.rse.2024.114123</dc:identifier><dc:type>article</dc:type><dc:source>Remote Sensing of Environment, vol 307</dc:source><dc:coverage>114123</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt30b6q2d1</identifier><datestamp>2026-09-15T22:01:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt30b6q2d1</dc:identifier><dc:title>Modeling of the high column density systems in the Lyman-Alpha forest</dc:title><dc:creator>Tan, T</dc:creator><dc:creator>Rich, J</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Le Goff, JM</dc:creator><dc:creator>Balland, C</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Walther, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-11-01</dc:date><dc:description>The Lyman-α forests observed in the spectra of high-redshift quasars can be used as a tracer of the cosmological matter density to study baryon acoustic oscillations (BAO) and the Alcock-Paczynski effect. Extraction of cosmological information from these studies requires modeling of the forest correlations. While the models depend most importantly on the bias parameters of the intergalactic medium (IGM), they also depend on the numbers and characteristics of high-column-density systems (HCDs) ranging from Lyman-limit systems with column densities log N HI/1cm-2 &amp;gt; 17 to damped Lyman-α systems (DLAs) with log N HI/1cm-2 &amp;gt; 20.2. These HCDs introduce broad damped absorption characteristic of a Voigt profile. Consequently they imprint a component on the power spectrum whose modes in the radial direction are suppressed, leading to a scale-dependent bias. Using mock data sets of known HCD content, we test a model that describes this effect in terms of the distribution of column densities of HCDs, the Fourier transforms of their Voigt profiles and the bias of the halos containing the HCDs. Our results show that this physically well-motivated model describes the effects of HCDs with an accuracy comparable to that of the ad-hoc models used in published forest analyses. We also discuss the problems of applying the model to real data, where the HCD content and their bias is uncertain.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>intergalactic media</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/30b6q2d1</dc:identifier><dc:identifier>https://escholarship.org/content/qt30b6q2d1/qt30b6q2d1.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/11/074</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 11</dc:source><dc:coverage>074</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7d84f2g3</identifier><datestamp>2026-09-15T22:00:48Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7d84f2g3</dc:identifier><dc:title>Polygenic score for C-reactive protein is linked to faster cortical thinning and psychopathology risk in adolescents</dc:title><dc:creator>Zheng, Haixia</dc:creator><dc:creator>Savitz, Jonathan</dc:creator><dc:creator>Haroon, Ebrahim</dc:creator><dc:creator>Ahern, Jonathan</dc:creator><dc:creator>Loughnan, Robert J</dc:creator><dc:creator>Naber, Firas</dc:creator><dc:creator>Xu, Bohan</dc:creator><dc:creator>Forthman, Katherine L</dc:creator><dc:creator>Aupperle, Robin L</dc:creator><dc:creator>Williams, Leanne M</dc:creator><dc:creator>Paulus, Martin P</dc:creator><dc:creator>Fan, Chun Chieh</dc:creator><dc:creator>Thompson, Wesley K</dc:creator><dc:date>2026-01-01</dc:date><dc:description>Adolescence is a sensitive period of brain development marked by rapid cortical thinning and increased risk for psychiatric disorders, yet the biological drivers of atypical trajectories remain unclear. Here, using longitudinal data from the Adolescent Brain Cognitive Development Study, we examined whether genetic predisposition to systemic inflammation, indexed by polygenic scores for C-reactive protein (PGS-CRP), influences brain development and psychopathology. Higher PGS-CRP was associated with accelerated cortical thinning, particularly in medial temporal and insular regions, and with increased externalizing symptoms. Early-life infections independently predicted greater depressive and externalizing symptoms but did not interact with genetic risk. Mediation analyses indicated that cortical thinning partially accounted for the association between PGS-CRP and externalizing psychopathology. Biological annotation further identified the regional similarity between cortical effects of PGS-CRP and several neurotransmitter systems. Together, these findings suggest that genetic susceptibility to inflammation may shape adolescent brain maturation and contribute to mental health vulnerability via neuroimmune pathways.</dc:description><dc:subject>5202 Biological Psychology (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>52 Psychology (for-2020)</dc:subject><dc:subject>Depression (rcdc)</dc:subject><dc:subject>Basic Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Mental Illness (rcdc)</dc:subject><dc:subject>Mental Health (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Brain Disorders (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>2.1 Biological and endogenous factors (hrcs-rac)</dc:subject><dc:subject>Mental health (hrcs-hc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Developmental neurogenesis</dc:subject><dc:subject>Risk factors</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7d84f2g3</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1038/s44220-026-00585-w</dc:identifier><dc:type>article</dc:type><dc:source>Nature Mental Health, vol 4, iss 3</dc:source><dc:coverage>427 - 438</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3hk6g6cm</identifier><datestamp>2026-09-15T21:48:09Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3hk6g6cm</dc:identifier><dc:title>Sex differences in HIV-associated cognitive impairment.</dc:title><dc:creator>Sundermann, Erin E</dc:creator><dc:creator>Heaton, Robert K</dc:creator><dc:creator>Pasipanodya, Elizabeth</dc:creator><dc:creator>Moore, Raeanne C</dc:creator><dc:creator>Paolillo, Emily W</dc:creator><dc:creator>Rubin, Leah H</dc:creator><dc:creator>Ellis, Ronald</dc:creator><dc:creator>Moore, David J</dc:creator><dc:creator>HNRP Group</dc:creator><dc:date>2018-11-01</dc:date><dc:description>ObjectiveWe determined whether there are sex differences in the prevalence and profile of HIV-associated neurocognitive impairment, and whether sex moderates the effect of HIV-serostatus on neurocognitive impairment among HIV-positive and HIV-negative individuals. Secondarily, we assessed whether differences were explained by greater biopsychosocial risk factors in HIV-positive women.DesignAn observational cohort study.MethodsAnalyses included 1361 HIV-positive (204 women) and 702 HIV-negative (214 women) (ages = 18-79 years) participants from the UCSD HIV Neurobehavioral Research Program. Demographically corrected standardized T-scores from 15 neuropsychological tests were used to calculate domain-specific and global deficit scores (GDS). GDS at least 0.5 defined neurocognitive impairment. Biopsychosocial risk factors included low education, low reading level (education quality), lifetime substance use disorders, depressed mood (clinically significant depressive symptoms and/or current major depressive disorder) and a cumulative syndemic count (sum of biopsychosocial risk factors, range = 0-4). Race-stratified analyses were conducted. Analyses were adjusted for relevant demographic and clinical factors.ResultsHIV-associated neurocognitive impairment was more prevalent in women versus men; however, the difference was eliminated after adjustment for reading level. In sex-stratified logistic regressions, the association between HIV-seropositivity and higher likelihood of neurocognitive impairment was stronger in women versus men; however, the association was attenuated in women, but not men, after adjusting for reading level. These results in the overall sample were specific to blacks. Sex differences in the profile of HIV-associated neurocognitive impairment varied by race.ConclusionWomen, particularly black women, were most at-risk for HIV-associated neurocognitive impairment. Higher rates of HIV-associated neurocognitive impairment in women versus men may reflect differences in educational quality.</dc:description><dc:subject>HNRP Group</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>HIV Infections (mesh)</dc:subject><dc:subject>AIDS Dementia Complex (mesh)</dc:subject><dc:subject>Prevalence (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Sex Factors (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Ethnicity (mesh)</dc:subject><dc:subject>AIDS Dementia Complex (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Ethnicity (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>HIV Infections (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Prevalence (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>Sex Factors (mesh)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>17 Psychology and Cognitive Sciences (for)</dc:subject><dc:subject>Virology (science-metrix)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:subject>42 Health sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3hk6g6cm</dc:identifier><dc:identifier>https://escholarship.org/content/qt3hk6g6cm/qt3hk6g6cm.pdf</dc:identifier><dc:identifier>info:doi/10.1097/qad.0000000000002012</dc:identifier><dc:type>article</dc:type><dc:source>AIDS (London, England), vol 32, iss 18</dc:source><dc:coverage>2719 - 2726</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt66x7v3b8</identifier><datestamp>2026-09-15T21:44:05Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt66x7v3b8</dc:identifier><dc:title>The environmental controls on efficiency of enhanced rock weathering in soils</dc:title><dc:creator>Deng, Hang</dc:creator><dc:creator>Sonnenthal, Eric</dc:creator><dc:creator>Arora, Bhavna</dc:creator><dc:creator>Breunig, Hanna</dc:creator><dc:creator>Brodie, Eoin</dc:creator><dc:creator>Kleber, Markus</dc:creator><dc:creator>Spycher, Nicolas</dc:creator><dc:creator>Nico, Peter</dc:creator><dc:date>2023-06-16</dc:date><dc:description>Enhanced rock weathering (ERW) in soils is a promising carbon removal technology, but the realistically achievable efficiency, controlled primarily by in situ weathering rates of the applied rocks, is highly uncertain. Here we explored the impacts of coupled biogeochemical and transport processes and a set of primary environmental and operational controls, using forsterite as a proxy mineral in soils and a multiphase multi-component reactive transport model considering microbe-mediated reactions. For a onetime forsterite application of ~ 16&amp;nbsp;kg/m2, complete weathering within five years can be achieved, giving an equivalent carbon removal rate of ~ 2.3 kgCO2/m2/yr. However, the rate is highly variable based on site-specific conditions. We showed that the in situ weathering rate can be enhanced by conditions and operations that maintain high CO2 availability via effective transport of atmospheric CO2 (e.g. in well-drained soils) and/or sufficient biogenic CO2 supply (e.g. stimulated plant–microbe processes). Our results further highlight that the effect of increasing surface area on weathering rate can be significant—so that the energy penalty of reducing the grain size may be justified—only when CO2 supply is nonlimiting. Therefore, for ERW practices to be effective, siting and engineering design (e.g. optimal grain size) need to be co-optimized.</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>3705 Geology (for-2020)</dc:subject><dc:subject>EGD-Carbon Removal and Mineralization (c-lbnl-label)</dc:subject><dc:subject>CESD-Nature-Based Carbon Reduction (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/66x7v3b8</dc:identifier><dc:identifier>https://escholarship.org/content/qt66x7v3b8/qt66x7v3b8.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41598-023-36113-4</dc:identifier><dc:type>article</dc:type><dc:source>Scientific Reports, vol 13, iss 1</dc:source><dc:coverage>9765</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1c6167c8</identifier><datestamp>2026-09-15T21:43:53Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1c6167c8</dc:identifier><dc:title>Mapping gas around massive galaxies: cross-correlation of DES Y3 galaxies and Compton-y maps from SPT and Planck</dc:title><dc:creator>Sánchez, J</dc:creator><dc:creator>Omori, Y</dc:creator><dc:creator>Chang, C</dc:creator><dc:creator>Bleem, LE</dc:creator><dc:creator>Crawford, T</dc:creator><dc:creator>Drlica-Wagner, A</dc:creator><dc:creator>Raghunathan, S</dc:creator><dc:creator>Zacharegkas, G</dc:creator><dc:creator>Abbott, TMC</dc:creator><dc:creator>Aguena, M</dc:creator><dc:creator>Alarcon, A</dc:creator><dc:creator>Allam, S</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Amon, A</dc:creator><dc:creator>Avila, S</dc:creator><dc:creator>Baxter, E</dc:creator><dc:creator>Bechtol, K</dc:creator><dc:creator>Benson, BA</dc:creator><dc:creator>Bernstein, GM</dc:creator><dc:creator>Bertin, E</dc:creator><dc:creator>Bocquet, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Burke, DL</dc:creator><dc:creator>Campos, A</dc:creator><dc:creator>Carlstrom, JE</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Kind, M Carrasco</dc:creator><dc:creator>Carretero, J</dc:creator><dc:creator>Castander, FJ</dc:creator><dc:creator>Cawthon, R</dc:creator><dc:creator>Chang, CL</dc:creator><dc:creator>Chen, A</dc:creator><dc:creator>Choi, A</dc:creator><dc:creator>Chown, R</dc:creator><dc:creator>Costanzi, M</dc:creator><dc:creator>Crites, AT</dc:creator><dc:creator>Crocce, M</dc:creator><dc:creator>da Costa, LN</dc:creator><dc:creator>Pereira, MES</dc:creator><dc:creator>de Haan, T</dc:creator><dc:creator>De Vicente, J</dc:creator><dc:creator>DeRose, J</dc:creator><dc:creator>Desai, S</dc:creator><dc:creator>Diehl, HT</dc:creator><dc:creator>Dobbs, MA</dc:creator><dc:creator>Dodelson, S</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Elvin-Poole, J</dc:creator><dc:creator>Everett, W</dc:creator><dc:creator>Everett, S</dc:creator><dc:creator>Ferrero, I</dc:creator><dc:creator>Flaugher, B</dc:creator><dc:creator>Fosalba, P</dc:creator><dc:creator>Frieman, J</dc:creator><dc:creator>García-Bellido, J</dc:creator><dc:creator>Gatti, M</dc:creator><dc:creator>George, EM</dc:creator><dc:creator>Gerdes, DW</dc:creator><dc:creator>Giannini, G</dc:creator><dc:creator>Gruen, D</dc:creator><dc:creator>Gruendl, RA</dc:creator><dc:creator>Gschwend, J</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Halverson, NW</dc:creator><dc:creator>Hinton, SR</dc:creator><dc:creator>Holder, GP</dc:creator><dc:creator>Hollowood, DL</dc:creator><dc:creator>Holzapfel, WL</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Hrubes, JD</dc:creator><dc:creator>James, DJ</dc:creator><dc:creator>Knox, L</dc:creator><dc:creator>Kuehn, K</dc:creator><dc:creator>Kuropatkin, N</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Lee, AT</dc:creator><dc:creator>Luong-Van, D</dc:creator><dc:creator>MacCrann, N</dc:creator><dc:creator>Marshall, JL</dc:creator><dc:creator>McCullough, J</dc:creator><dc:creator>McMahon, JJ</dc:creator><dc:creator>Melchior, P</dc:creator><dc:creator>Mena-Fernández, J</dc:creator><dc:creator>Menanteau, F</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Mocanu, L</dc:creator><dc:creator>Mohr, JJ</dc:creator><dc:creator>Muir, J</dc:creator><dc:creator>Myles, J</dc:creator><dc:creator>Natoli, T</dc:creator><dc:creator>Padin, S</dc:creator><dc:creator>Palmese, A</dc:creator><dc:creator>Pandey, S</dc:creator><dc:creator>Paz-Chinchón, F</dc:creator><dc:creator>Pieres, A</dc:creator><dc:creator>Malagón, AA Plazas</dc:creator><dc:creator>Porredon, A</dc:creator><dc:creator>Pryke, C</dc:creator><dc:creator>Raveri, M</dc:creator><dc:creator>Reichardt, CL</dc:creator><dc:date>2023-04-21</dc:date><dc:description>ABSTRACT We cross-correlate positions of galaxies measured in data from the first three years of the Dark Energy Survey with Compton-y maps generated using data from the South Pole Telescope (SPT) and the Planck mission. We model this cross-correlation measurement together with the galaxy autocorrelation to constrain the distribution of gas in the Universe. We measure the hydrostatic mass bias or, equivalently, the mean halo bias-weighted electron pressure 〈bhPe 〉, using large-scale information. We find 〈bhPe 〉 to be $[0.16^{+0.03}_{-0.04},0.28^{+0.04}_{-0.05},0.45^{+0.06}_{-0.10},0.54^{+0.08}_{-0.07},0.61^{+0.08}_{-0.06},0.63^{+0.07}_{-0.08}]$ meV cm−3 at redshifts z ∼ [0.30, 0.46, 0.62, 0.77, 0.89, 0.97]. These values are consistent with previous work where measurements exist in the redshift range. We also constrain the mean gas profile using small-scale information, enabled by the high-resolution of the SPT data. We compare our measurements to different parametrized profiles based on the cosmo-OWLS hydrodynamical simulations. We find that our data are consistent with the simulation that assumes an AGN heating temperature of 108.5 K but are incompatible with the model that assumes an AGN heating temperature of 108.0 K. These comparisons indicate that the data prefer a higher value of electron pressure than the simulations within r500c of the galaxies’ haloes.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>galaxies: structure</dc:subject><dc:subject>large-scale structure of Universe</dc:subject><dc:subject>cosmology: observations</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1c6167c8</dc:identifier><dc:identifier>https://escholarship.org/content/qt1c6167c8/qt1c6167c8.pdf</dc:identifier><dc:identifier>info:doi/10.1093/mnras/stad1167</dc:identifier><dc:type>article</dc:type><dc:source>Monthly Notices of the Royal Astronomical Society, vol 522, iss 2</dc:source><dc:coverage>3163 - 3182</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1r9359dj</identifier><datestamp>2026-09-15T21:40:19Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1r9359dj</dc:identifier><dc:title>Assembly of the largest squamate reference genome to date: The western fence lizard, Sceloporus occidentalis</dc:title><dc:creator>Bishop, Anusha P</dc:creator><dc:creator>Westeen, Erin P</dc:creator><dc:creator>Yuan, Michael L</dc:creator><dc:creator>Escalona, Merly</dc:creator><dc:creator>Beraut, Eric</dc:creator><dc:creator>Fairbairn, Colin</dc:creator><dc:creator>Marimuthu, Mohan PA</dc:creator><dc:creator>Nguyen, Oanh</dc:creator><dc:creator>Chumchim, Noravit</dc:creator><dc:creator>Toffelmier, Erin</dc:creator><dc:creator>Fisher, Robert N</dc:creator><dc:creator>Shaffer, H Bradley</dc:creator><dc:creator>Wang, Ian J</dc:creator><dc:contributor>Shapiro, Beth</dc:contributor><dc:date>2023-08-23</dc:date><dc:description>Spiny lizards (genus Sceloporus) have long served as important systems for studies of behavior, thermal physiology, dietary ecology, vector biology, speciation, and biogeography. The western fence lizard, Sceloporus occidentalis, is found across most of the major biogeographical regions in the western United States and northern Baja California, Mexico, inhabiting a wide range of habitats, from grassland to chaparral to open woodlands. As small ectotherms, Sceloporus lizards are particularly vulnerable to climate change, and S. occidentalis has also become an important system for studying the impacts of land use change and urbanization on small vertebrates. Here, we report a new reference genome assembly for S. occidentalis, as part of the California Conservation Genomics Project (CCGP). Consistent with the reference genomics strategy of the CCGP, we used Pacific Biosciences HiFi long reads and Hi-C chromatin-proximity sequencing technology to produce a de novo assembled genome. The assembly comprises a total of 608 scaffolds spanning 2,856 Mb, has a contig N50 of 18.9 Mb, a scaffold N50 of 98.4 Mb, and BUSCO completeness score of 98.1% based on the tetrapod gene set. This reference genome will be valuable for understanding ecological and evolutionary dynamics in S. occidentalis, the species status of the California endemic island fence lizard (S. becki), and the spectacular radiation of Sceloporus lizards.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3102 Bioinformatics and Computational Biology (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>15 Life on Land (sdg)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Mexico (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>Lizards (mesh)</dc:subject><dc:subject>California Conservation Genomics Project</dc:subject><dc:subject>CCGP</dc:subject><dc:subject>de novo genome assembly</dc:subject><dc:subject>Iguania</dc:subject><dc:subject>Phrynosomatidae</dc:subject><dc:subject>reptile</dc:subject><dc:subject>Squamata</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Lizards (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>Mexico (mesh)</dc:subject><dc:subject>CCGP</dc:subject><dc:subject>California Conservation Genomics Project</dc:subject><dc:subject>Iguania</dc:subject><dc:subject>Phrynosomatidae</dc:subject><dc:subject>Squamata</dc:subject><dc:subject>de novo genome assembly</dc:subject><dc:subject>reptile</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Mexico (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>Lizards (mesh)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>Evolutionary Biology (science-metrix)</dc:subject><dc:subject>3104 Evolutionary biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1r9359dj</dc:identifier><dc:identifier>https://escholarship.org/content/qt1r9359dj/qt1r9359dj.pdf</dc:identifier><dc:identifier>info:doi/10.1093/jhered/esad037</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Heredity, vol 114, iss 5</dc:source><dc:coverage>521 - 528</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9b55h7tv</identifier><datestamp>2026-09-15T21:36:50Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9b55h7tv</dc:identifier><dc:title>Biome-scale temperature sensitivity of ecosystem respiration revealed by atmospheric CO2 observations</dc:title><dc:creator>Sun, Wu</dc:creator><dc:creator>Luo, Xiangzhong</dc:creator><dc:creator>Fang, Yuanyuan</dc:creator><dc:creator>Shiga, Yoichi P</dc:creator><dc:creator>Zhang, Yao</dc:creator><dc:creator>Fisher, Joshua B</dc:creator><dc:creator>Keenan, Trevor F</dc:creator><dc:creator>Michalak, Anna M</dc:creator><dc:date>2023-08-01</dc:date><dc:description>The temperature sensitivity of ecosystem respiration regulates how the terrestrial carbon sink responds to a warming climate but has been difficult to constrain observationally beyond the plot scale. Here we use observations of atmospheric CO2 concentrations from a network of towers together with carbon flux estimates from state-of-the-art terrestrial biosphere models to characterize the temperature sensitivity of ecosystem respiration, as represented by the Arrhenius activation energy, over various North American biomes. We infer activation energies of 0.43 eV for North America and 0.38 eV to 0.53 eV for major biomes therein, which are substantially below those reported for plot-scale studies (approximately 0.65 eV). This discrepancy suggests that sparse plot-scale observations do not capture the spatial-scale dependence and biome specificity of the temperature sensitivity. We further show that adjusting the apparent temperature sensitivity in model estimates markedly improves their ability to represent observed atmospheric CO2 variability. This study provides observationally constrained estimates of the temperature sensitivity of ecosystem respiration directly at the biome scale and reveals that temperature sensitivities at this scale are lower than those based on earlier plot-scale studies. These findings call for additional work to assess the resilience of large-scale carbon sinks to warming.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Temperature (mesh)</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>Carbon Cycle (mesh)</dc:subject><dc:subject>Respiration (mesh)</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Temperature (mesh)</dc:subject><dc:subject>Respiration (mesh)</dc:subject><dc:subject>Carbon Cycle (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Temperature (mesh)</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>Carbon Cycle (mesh)</dc:subject><dc:subject>Respiration (mesh)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>3104 Evolutionary biology (for-2020)</dc:subject><dc:subject>4104 Environmental management (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9b55h7tv</dc:identifier><dc:identifier>https://escholarship.org/content/qt9b55h7tv/qt9b55h7tv.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41559-023-02093-x</dc:identifier><dc:type>article</dc:type><dc:source>Nature Ecology &amp; Evolution, vol 7, iss 8</dc:source><dc:coverage>1199 - 1210</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7pz1f4n5</identifier><datestamp>2026-09-15T21:36:25Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7pz1f4n5</dc:identifier><dc:title>A genome assembly of the speckled dace, Rhinichthys osculus</dc:title><dc:creator>Baker, Henry K</dc:creator><dc:creator>Escalona, Merly</dc:creator><dc:creator>Kinziger, Andrew P</dc:creator><dc:creator>Rodzen, Jeff</dc:creator><dc:creator>Parmenter, Steve</dc:creator><dc:creator>Marimuthu, Mohan PA</dc:creator><dc:creator>Nguyen, Oanh</dc:creator><dc:creator>Chumchim, Noravit</dc:creator><dc:creator>Beraut, Eric</dc:creator><dc:creator>Sacco, Samuel</dc:creator><dc:creator>Seligmann, William</dc:creator><dc:creator>Fairbairn, Colin W</dc:creator><dc:creator>Cooper, Robert D</dc:creator><dc:creator>Miller, Courtney</dc:creator><dc:creator>Toffelmier, Erin</dc:creator><dc:creator>Garza, J Carlos</dc:creator><dc:creator>Shaffer, H Bradley</dc:creator><dc:creator>Shurin, Jonathan B</dc:creator><dc:creator>Rennison, Diana J</dc:creator><dc:date>2026-05-26</dc:date><dc:description>The speckled dace, Rhinichtyhs osculus, is a cyprinoid fish species complex (family: Leuciscidae) with one of the widest native ranges of any freshwater fish in western North America. It occupies a variety of freshwater habitats and exhibits considerable morphological and genetic variation across its range. Several endemic taxa within the species complex are imperiled, four of which are protected under the US Endangered Species Act, with two more proposed for listing. Here, we present an annotated, scaffold-level assembly of the speckled dace genome as part of the California Conservation Genomics Project (CCGP). Consistent with the CCGP genome assembly strategy, we used Pacific Biosciences HiFi long reads and Omni-C data for our de novo genome assembly and performed genome annotations on NCBI Eukaryotic Genome Annotation Pipeline using novel, species-specific RNA-Seq reads generated from five tissue types. The assembly consists of 490 scaffolds totaling approximately 1.15 Gb, with a contig N50 of 10.9&amp;nbsp;Mb and a scaffold N50 of 44.5&amp;nbsp;Mb. A BUSCO score of 97.7% reflects the assembly's strong completeness. The genome of Rhinichthys osculus is estimated to consist of 25 chromosomes. This is the first scaffold-level genome assembly within the genus Rhinichthys. We annotated a total of 39,919 genes with a BUSCO completeness score of 98.3%. This reference genome will be a valuable resource for understanding the phylogeography and evolution of speckled dace and informing its conservation.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3102 Bioinformatics and Computational Biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Biotechnology (rcdc)</dc:subject><dc:subject>15 Life on Land (sdg)</dc:subject><dc:subject>California conservation genomics project</dc:subject><dc:subject>ccgp</dc:subject><dc:subject>conservation genetics</dc:subject><dc:subject>cypriniformes</dc:subject><dc:subject>leuciscidae</dc:subject><dc:subject>freshwater fish</dc:subject><dc:subject>California conservation genomics project</dc:subject><dc:subject>ccgp</dc:subject><dc:subject>conservation genetics</dc:subject><dc:subject>cypriniformes</dc:subject><dc:subject>freshwater fish</dc:subject><dc:subject>leuciscidae</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>Evolutionary Biology (science-metrix)</dc:subject><dc:subject>3104 Evolutionary biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7pz1f4n5</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1093/jhered/esag041</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Heredity</dc:source><dc:coverage>esag041</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt64j537n0</identifier><datestamp>2026-09-15T21:32:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt64j537n0</dc:identifier><dc:title>Intrinsic alignment as an RSD contaminant in the DESI survey</dc:title><dc:creator>Lamman, Claire</dc:creator><dc:creator>Eisenstein, Daniel</dc:creator><dc:creator>Aguilar, Jessica Nicole</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>de la Macorra, Axel</dc:creator><dc:creator>Doel, Peter</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>Gontcho, Satya Gontcho A</dc:creator><dc:creator>Honscheid, Klaus</dc:creator><dc:creator>Kehoe, Robert</dc:creator><dc:creator>Kisner, Theodore</dc:creator><dc:creator>Kremin, Anthony</dc:creator><dc:creator>Landriau, Martin</dc:creator><dc:creator>Levi, Michael</dc:creator><dc:creator>Miquel, Ramon</dc:creator><dc:creator>Moustakas, John</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Poppett, Claire</dc:creator><dc:creator>Schubnell, Michael</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:date>2023-04-13</dc:date><dc:description>ABSTRACT We measure the tidal alignment of the major axes of luminous red galaxies (LRGs) from the Legacy Imaging Survey and use it to infer the artificial redshift-space distortion signature that will arise from an orientation-dependent, surface-brightness selection in the Dark Energy Spectroscopic Instrument (DESI) survey. Using photometric redshifts to downweight the shape–density correlations due to weak lensing, we measure the intrinsic tidal alignment of LRGs. Separately, we estimate the net polarization of LRG orientations from DESI’s fibre-magnitude target selection to be of order 10−2 along the line of sight. Using these measurements and a linear tidal model, we forecast a 0.5 per cent fractional decrease on the quadrupole of the two-point correlation function for projected separations of 40–80 h−1 Mpc. We also use a halo catalogue from the Abacussummit cosmological simulation suite to reproduce this false quadrupole.</dc:description><dc:subject>5109 Space Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>methods: data analysis</dc:subject><dc:subject>dark energy</dc:subject><dc:subject>large-scale structure of Universe</dc:subject><dc:subject>cosmology: observations</dc:subject><dc:subject>methods: data analysis</dc:subject><dc:subject>dark energy</dc:subject><dc:subject>large-scale structure of Universe</dc:subject><dc:subject>cosmology: observations</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/64j537n0</dc:identifier><dc:identifier>https://escholarship.org/content/qt64j537n0/qt64j537n0.pdf</dc:identifier><dc:identifier>info:doi/10.1093/mnras/stad950</dc:identifier><dc:type>article</dc:type><dc:source>Monthly Notices of the Royal Astronomical Society, vol 522, iss 1</dc:source><dc:coverage>117 - 129</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5wr6j7w1</identifier><datestamp>2026-09-15T21:31:34Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5wr6j7w1</dc:identifier><dc:title>A Natural ≳100× Telescope: Discovery of the Strongly Lensed Type II SN 2025mkn at z = 1.37</dc:title><dc:creator>Lemon, Cameron</dc:creator><dc:creator>Goobar, Ariel</dc:creator><dc:creator>Johansson, Joel</dc:creator><dc:creator>Mörtsell, Edvard</dc:creator><dc:creator>Schulze, Steve</dc:creator><dc:creator>Andreoni, Igor</dc:creator><dc:creator>Bochenek, Aleksandra</dc:creator><dc:creator>Brennan, Seán J</dc:creator><dc:creator>Busmann, Malte</dc:creator><dc:creator>Coughlin, Michael</dc:creator><dc:creator>Das, Kaustav K</dc:creator><dc:creator>Dhawan, Suhail</dc:creator><dc:creator>Fremling, Christoffer</dc:creator><dc:creator>Gangopadhyay, Anjasha</dc:creator><dc:creator>Gruen, Daniel</dc:creator><dc:creator>Hall, Xander J</dc:creator><dc:creator>Ho, Anna YQ</dc:creator><dc:creator>Kasliwal, Mansi M</dc:creator><dc:creator>Perley, Daniel A</dc:creator><dc:creator>Rigault, Mickael</dc:creator><dc:creator>Schroeder, Genevieve</dc:creator><dc:creator>Smith, Mathew</dc:creator><dc:creator>Sollerman, Jesper</dc:creator><dc:creator>Somalwar, Jean J</dc:creator><dc:creator>Stein, Robert</dc:creator><dc:creator>Thorp, Stephen</dc:creator><dc:creator>Townsend, Alice</dc:creator><dc:creator>Wise, Jacob L</dc:creator><dc:creator>Yan, Lin</dc:creator><dc:creator>Arendse, Nikki</dc:creator><dc:creator>Bellm, Eric C</dc:creator><dc:creator>Chen, Tracy X</dc:creator><dc:creator>Drake, Andrew</dc:creator><dc:creator>Masci, Frank J</dc:creator><dc:creator>Purdum, Josiah</dc:creator><dc:creator>Smith, Roger</dc:creator><dc:creator>Hinkle, Jason T</dc:creator><dc:creator>Rivera-Thorsen, T Emil</dc:creator><dc:creator>Shappee, Benjamin J</dc:creator><dc:creator>Tucker, Michael A</dc:creator><dc:creator>Aguilar, Jessica</dc:creator><dc:creator>Ahlen, Steven</dc:creator><dc:creator>Aldering, Greg</dc:creator><dc:creator>BenZvi, Segev</dc:creator><dc:creator>Bianchi, Davide</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>Claybaugh, Todd</dc:creator><dc:creator>de la Macorra, Axel</dc:creator><dc:creator>Della Costa, John</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Doel, Peter</dc:creator><dc:creator>Flaugher, Brenna</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>Forero-Romero, Jaime E</dc:creator><dc:creator>Gaztañaga, Enrique</dc:creator><dc:creator>Gontcho, Satya Gontcho A</dc:creator><dc:creator>Gutierrez, Gaston</dc:creator><dc:creator>Huterer, Dragan</dc:creator><dc:creator>Ishak, Mustapha</dc:creator><dc:creator>Jimenez, Jorge</dc:creator><dc:creator>Joyce, Dick</dc:creator><dc:creator>Juneau, Stephanie</dc:creator><dc:creator>Kehoe, Robert</dc:creator><dc:creator>Kim, Alex G</dc:creator><dc:creator>Kirkby, David</dc:creator><dc:creator>Kisner, Theodore</dc:creator><dc:creator>Kremin, Anthony</dc:creator><dc:creator>Lahav, Ofer</dc:creator><dc:creator>Landriau, Martin</dc:creator><dc:creator>Le Guillou, Laurent</dc:creator><dc:creator>Levi, Michael E</dc:creator><dc:creator>Manera, Marc</dc:creator><dc:creator>Meisner, Aaron</dc:creator><dc:creator>Miquel, Ramon</dc:creator><dc:creator>Moustakas, John</dc:creator><dc:creator>Nadathur, Seshadri</dc:creator><dc:creator>O’Connor, Brendan</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Palmese, Antonella</dc:creator><dc:creator>Percival, Will J</dc:creator><dc:creator>Pérez-Ràfols, Ignasi</dc:creator><dc:creator>Poppett, Claire</dc:creator><dc:creator>Prada, Francisco</dc:creator><dc:creator>Rossi, Graziano</dc:creator><dc:creator>Sanchez, Eusebio</dc:creator><dc:creator>Schlegel, David</dc:creator><dc:creator>Schubnell, Michael</dc:creator><dc:creator>Shafieloo, Arman</dc:creator><dc:creator>Silber, Joseph</dc:creator><dc:creator>Sprayberry, David</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Weaver, Benjamin A</dc:creator><dc:creator>Zou, Hu</dc:creator><dc:date>2026-06-01</dc:date><dc:description>We present the discovery of SN 2025mkn, a gravitationally lensed Type II supernova. First detected as a blue transient in Zwicky Transient Facility (ZTF), 0 .″ 83 from a z = 0.42 elliptical galaxy, the follow-up SNIFS/UH2.2 m and LRIS/Keck spectra revealed absorption lines at z = 1.371. Later JWST NIRCam imaging shows that the bright transient is a close pair of point sources separated by ∼0.″07 , and a 30 times fainter counterimage opposite the lens, for which NIRSpec reveals strong Hα emission also at z = 1.371. The lightcurves and spectra are consistent with the Type II supernova source being magnified ≳100 times, with ∼250 required to reconcile its luminosity with that of nearby events such as SN 2023ixf. Lens models are consistent with such high magnifications, and always show that the faint image arrived first (undetected in earlier ZTF imaging), consistent with the later spectral phase of this fainter image. A fourth image is also predicted and possibly detected in the NIRSpec data. Lightcurve-based time-delay measurements are not possible due to the first image being the faintest; however, the resolved NIRSpec spectra offer a future opportunity for time-delay cosmography through supernova phase measurements.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5wr6j7w1</dc:identifier><dc:identifier>https://escholarship.org/content/qt5wr6j7w1/qt5wr6j7w1.pdf</dc:identifier><dc:identifier>info:doi/10.3847/2041-8213/ae6780</dc:identifier><dc:type>article</dc:type><dc:source>The Astrophysical Journal Letters, vol 1003, iss 2</dc:source><dc:coverage>l47</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3fs7f4rp</identifier><datestamp>2026-09-15T21:31:19Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3fs7f4rp</dc:identifier><dc:title>A comparison of effective field theory models of redshift space galaxy power spectra for DESI 2024 and future surveys</dc:title><dc:creator>Maus, M</dc:creator><dc:creator>Lai, Y</dc:creator><dc:creator>Noriega, HE</dc:creator><dc:creator>Ramirez-Solano, S</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Fromenteau, S</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>White, M</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>Icaza-Lizaola, M</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Findlay, N</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Rezaie, M</dc:creator><dc:creator>Rocher, A</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Yuan, S</dc:creator><dc:creator>Zhao, R</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>In preparation for the next generation of galaxy redshift surveys, and in particular the year-one data release from the Dark Energy Spectroscopic Instrument (DESI), we investigate the consistency of a variety of effective field theory models that describe the galaxy-galaxy power spectra in redshift space into the quasi-linear regime using 1-loop perturbation theory. These models are employed in the pipelines velocileptors, PyBird, and Folpsν . While these models have been validated independently, a detailed comparison with consistent choices has not been attempted. After briefly discussing the theoretical differences between the models we describe how to provide a more apples-to-apples comparison between them. We present the results of fitting mock spectra from the AbacusSummit suite of N-body simulations provided in three redshift bins to mimic the types of dark time tracers targeted by the DESI survey. We show that the theories behave similarly and give consistent constraints in both the forward-modeling and ShapeFit compressed fitting approaches. We additionally generate (noiseless) synthetic data from each pipeline to be fit by the others, varying the scale cuts in order to show that the models agree within the range of scales for which we expect 1-loop perturbation theory to be applicable. This work lays the foundation of Full-Shape analysis with DESI Y1 galaxy samples where in the tests we performed, we found no systematic error associated with the modeling of the galaxy redshift space power spectrum for this volume.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3fs7f4rp</dc:identifier><dc:identifier>https://escholarship.org/content/qt3fs7f4rp/qt3fs7f4rp.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/134</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>134</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7gx7q4zn</identifier><datestamp>2026-09-15T21:27:02Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7gx7q4zn</dc:identifier><dc:title>Advanced monitoring of soil-vegetation co-dynamics reveals the successive controls of snowmelt on soil moisture and on plant seasonal dynamics in a mountainous watershed</dc:title><dc:creator>Dafflon, Baptiste</dc:creator><dc:creator>Léger, Emmanuel</dc:creator><dc:creator>Falco, Nicola</dc:creator><dc:creator>Wainwright, Haruko M</dc:creator><dc:creator>Peterson, John</dc:creator><dc:creator>Chen, Jiancong</dc:creator><dc:creator>Williams, Kenneth H</dc:creator><dc:creator>Hubbard, Susan S</dc:creator><dc:date>2023-05-12</dc:date><dc:description>Evaluating the interactions between above- and below-ground processes is important to understand and quantify how ecosystems respond differently to atmospheric forcings and/or perturbations and how this depends on their intrinsic characteristics and heterogeneity. Improving such understanding is particularly needed in snow-impacted mountainous systems where the complexity in water and carbon storage and release arises from strong heterogeneity in meteorological forcing and terrain, vegetation and soil characteristics. This study investigates spatial and temporal interactions between terrain, soil moisture, and plant seasonal dynamics at the intra- and inter-annual scale along a 160 m long mountainous, non-forested hillslope-to-floodplain system in the upper East River Watershed in the upper Colorado River Basin. To this end, repeated UAV-based multi-spectral aerial imaging, ground-based soil electrical resistivity imaging, and soil moisture sensors were used to quantify the interactions between above and below-ground compartments. Results reveal significant soil-plant co-dynamics. The spatial variation and dynamics of soil water content and electrical conductivity, driven by topographic and soil intrinsic characteristics, correspond to distinct plant types, with highest plant productivity in convergent areas. Plant productivity in heavy snow years benefited from more water infiltration as well as a shallow groundwater table depth. In comparison, low snowpack years with an early first bare-ground date, which are linked to an early increase in plant greenness, imply a short period of saturated conditions that leads to lower average and maximum greenness values during the growing season. Overall, these results emphasize the strong impact of snowpack dynamics, and terrain and subsurface characteristics on the heterogeneity in plant type and seasonal dynamics.</dc:description><dc:subject>3707 Hydrology (for-2020)</dc:subject><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>hillslope</dc:subject><dc:subject>snow impact</dc:subject><dc:subject>soil moisture</dc:subject><dc:subject>vegetation growth</dc:subject><dc:subject>seasonal dynamic</dc:subject><dc:subject>0403 Geology (for)</dc:subject><dc:subject>0404 Geophysics (for)</dc:subject><dc:subject>0406 Physical Geography and Environmental Geoscience (for)</dc:subject><dc:subject>3705 Geology (for-2020)</dc:subject><dc:subject>3706 Geophysics (for-2020)</dc:subject><dc:subject>3709 Physical geography and environmental geoscience (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7gx7q4zn</dc:identifier><dc:identifier>https://escholarship.org/content/qt7gx7q4zn/qt7gx7q4zn.pdf</dc:identifier><dc:identifier>info:doi/10.3389/feart.2023.976227</dc:identifier><dc:type>article</dc:type><dc:source>Frontiers in Earth Science, vol 11</dc:source><dc:coverage>976227</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3hq8m5gg</identifier><datestamp>2026-09-15T21:23:42Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3hq8m5gg</dc:identifier><dc:title>Effect of methamphetamine dependence on inhibitory deficits in a novel human open-field paradigm</dc:title><dc:creator>Henry, Brook L</dc:creator><dc:creator>Minassian, Arpi</dc:creator><dc:creator>van Rhenen, Mandy</dc:creator><dc:creator>Young, Jared W</dc:creator><dc:creator>Geyer, Mark A</dc:creator><dc:creator>Perry, William</dc:creator><dc:creator>Translational Methamphetamine AIDS Research Center (TMARC) Group</dc:creator><dc:date>2011-06-01</dc:date><dc:description>RationaleMethamphetamine (MA) is an addictive psychostimulant associated with neurocognitive impairment, including inhibitory deficits characterized by a reduced ability to control responses to stimuli. While various domains of inhibition such as exaggerated novelty seeking and perseveration have been assessed in rodents by quantifying activity in open-field tests, similar models have not been utilized in human substance abusers. We recently developed a cross-species translational human open-field paradigm, the human behavior pattern monitor (hBPM), consisting of an unfamiliar room containing novel and engaging objects. Previous work demonstrated that manic bipolar subjects exhibit a disinhibited pattern of behavior in the hBPM characterized by increased object interactions.ObjectivesIn the current study, we examined the effect of MA dependence on inhibitory deficits using this paradigm. hBPM activity and object interactions were quantified in 16 abstinent MA-dependent individuals and 18 matched drug-free comparison subjects. The Wisconsin card sorting task (WCST) and the positive and negative syndrome scale (PANSS) were administered to assess executive function and psychopathology.ResultsMA-dependent participants exhibited a significant increase in total object interactions, time spent with objects, and perseverative object interactions relative to comparison subjects. Greater object interaction was associated with impaired performance on the WCST, higher PANSS scores, and more frequent MA use in the past year.ConclusionsAbstinent MA-dependent individuals exhibited impaired inhibition in the hBPM, displaying increased interaction with novel stimuli. Utilization of this measure may enable assessment of inhibitory deficits relevant to drug-seeking behavior and facilitate development of intervention methods to reduce high-risk conduct in this population.</dc:description><dc:subject>5202 Biological Psychology (for-2020)</dc:subject><dc:subject>52 Psychology (for-2020)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Brain Disorders (rcdc)</dc:subject><dc:subject>Substance Misuse (rcdc)</dc:subject><dc:subject>Basic Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Methamphetamine (rcdc)</dc:subject><dc:subject>Drug Abuse (NIDA only) (rcdc)</dc:subject><dc:subject>Stimulant Use and Misuse (rcdc)</dc:subject><dc:subject>Mental Health (rcdc)</dc:subject><dc:subject>Mental health (hrcs-hc)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Amphetamine-Related Disorders (mesh)</dc:subject><dc:subject>Case-Control Studies (mesh)</dc:subject><dc:subject>Data Interpretation</dc:subject><dc:subject>Statistical (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Inhibition</dc:subject><dc:subject>Psychological (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Methamphetamine (mesh)</dc:subject><dc:subject>Neuropsychological Tests (mesh)</dc:subject><dc:subject>Methamphetamine</dc:subject><dc:subject>Inhibition</dc:subject><dc:subject>Human behavior pattern monitor</dc:subject><dc:subject>Exploration</dc:subject><dc:subject>Prefrontal cortex</dc:subject><dc:subject>Cognitive deficits</dc:subject><dc:subject>Translational Methamphetamine AIDS Research Center (TMARC) Group</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Amphetamine-Related Disorders (mesh)</dc:subject><dc:subject>Methamphetamine (mesh)</dc:subject><dc:subject>Data Interpretation</dc:subject><dc:subject>Statistical (mesh)</dc:subject><dc:subject>Case-Control Studies (mesh)</dc:subject><dc:subject>Neuropsychological Tests (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Inhibition</dc:subject><dc:subject>Psychological (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Amphetamine-Related Disorders (mesh)</dc:subject><dc:subject>Case-Control Studies (mesh)</dc:subject><dc:subject>Data Interpretation</dc:subject><dc:subject>Statistical (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Inhibition</dc:subject><dc:subject>Psychological (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Methamphetamine (mesh)</dc:subject><dc:subject>Neuropsychological Tests (mesh)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>17 Psychology and Cognitive Sciences (for)</dc:subject><dc:subject>Psychiatry (science-metrix)</dc:subject><dc:subject>5202 Biological psychology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3hq8m5gg</dc:identifier><dc:identifier>https://escholarship.org/content/qt3hq8m5gg/qt3hq8m5gg.pdf</dc:identifier><dc:identifier>info:doi/10.1007/s00213-011-2170-2</dc:identifier><dc:type>article</dc:type><dc:source>Psychopharmacology, vol 215, iss 4</dc:source><dc:coverage>697 - 707</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4x2923j4</identifier><datestamp>2026-09-15T21:23:19Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4x2923j4</dc:identifier><dc:title>Inference of the linear matter power spectrum at z = 0 using DESI DR1 Full-Shape data</dc:title><dc:creator>Cereskaite, R</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Davis, Tamara M</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Castander, FJ</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Huterer, D</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Joyce, R</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Lambert, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:creator>collaboration, The DESI</dc:creator><dc:date>2026-04-01</dc:date><dc:description>Measurements of galaxy distributions at large cosmic distances capture clustering from the past. In this study, we use a cosmological model to translate these observations into the present-day galaxy distribution. Specifically, we reconstruct the 3D linear matter power spectrum at redshift z = 0 using Dark Energy Spectroscopic Instrument (DESI) Year 1 (DR1) galaxy clustering data and Cosmic Microwave Background (CMB) observations, assuming the ΛCDM model, and compare it to the result assuming the w 0 wa CDM model. Building on previous state-of-the-art methods, we apply Effective Field Theory (EFT) modelling of the galaxy power spectrum to account for small-scale effects in the 2-point statistics of galaxy data. Implementation of the EFT approach improves the modelling of the galaxy power spectrum, providing a more robust consistency test of the assumed cosmological model. By casting both CMB and galaxy clustering observations, spanning distinct redshift regimes, into k-space, we can identify discrepancies between the datasets of different redshifts, which would indicate potential inaccuracies in the assumed expansion history. While previous studies have shown consistency with ΛCDM, this work extends the analysis with higher-quality data to further test the expansion histories of both ΛCDM and w 0 wa CDM. Our findings show that both ΛCDM and w 0 wa CDM provide consistent fits to the linear matter power spectrum recovered from DESI DR1 data.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>galaxy clustering</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4x2923j4</dc:identifier><dc:identifier>https://escholarship.org/content/qt4x2923j4/qt4x2923j4.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2026/04/080</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2026, iss 04</dc:source><dc:coverage>080</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9x73w5pk</identifier><datestamp>2026-09-15T21:23:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9x73w5pk</dc:identifier><dc:title>DESI DR1 Lyα 1D power spectrum: Validation of estimators</dc:title><dc:creator>Karaçaylı, Naim Göksel</dc:creator><dc:creator>Ravoux, Corentin</dc:creator><dc:creator>Martini, Paul</dc:creator><dc:creator>Le Goff, Jean-Marc</dc:creator><dc:creator>Armengaud, Eric</dc:creator><dc:creator>Abdul-Karim, M</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Anand, A</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Herrera-Alcantar, HK</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Jimenez, J</dc:creator><dc:creator>Joyce, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Lahav, O</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Silber, J</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tan, T</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Walther, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2026-04-01</dc:date><dc:description>The Data Release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI) is the largest sample to date for small-scale Lyα forest cosmology, accessed through its one-dimensional power spectrum (P 1D). The Lyα forest P 1D is extracted from quasar spectra that are highly inhomogeneous (both in wavelength and between quasars) in noise properties due to intrinsic properties of the quasar, atmospheric and astrophysical contamination, and also sensitive to low-level details of the spectral extraction pipeline. We employ two estimators in DR1 analysis to measure P 1D: the optimal estimator and the fast Fourier transform (FFT) estimator. To ensure robustness of our DR1 measurements, we validate these two power spectrum and covariance matrix estimation methodologies against the challenging aspects of the data. First, using a set of 20 synthetic 1D realizations of DR1, we derive the masking bias corrections needed for the FFT estimator and the continuum fitting bias needed for both estimators. We demonstrate that both estimators, including their covariances, are unbiased with these corrections using the Kolmogorov-Smirnov test. Second, we substantially extend our previous suite of CCD image simulations to include 675,000 quasars, allowing us to accurately quantify the pipeline's performance. This set of simulations reveals biases at the highest k values, corresponding to a resolution error of a few percent. We base the resolution systematics error budget of DR1 P 1D on these values, but do not derive corrections from them since the simulation fidelity is insufficient for precise corrections.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Lyman alpha forest</dc:subject><dc:subject>power spectrum</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9x73w5pk</dc:identifier><dc:identifier>https://escholarship.org/content/qt9x73w5pk/qt9x73w5pk.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2026/04/048</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2026, iss 04</dc:source><dc:coverage>048</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4gk0m0b7</identifier><datestamp>2026-09-15T21:18:56Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4gk0m0b7</dc:identifier><dc:title>Responsible research in health disparities using the Adolescent Brain Cognitive DevelopmentSM (ABCD) study</dc:title><dc:creator>Gonzalez</dc:creator><dc:creator>Cardenas-Iniguez, C</dc:creator><dc:creator>Linares, DE</dc:creator><dc:creator>Wonnum, S</dc:creator><dc:creator>Bagot, K</dc:creator><dc:creator>White, EJ</dc:creator><dc:creator>Cuan, A</dc:creator><dc:creator>DiMatteo, S</dc:creator><dc:creator>Akiel, YD</dc:creator><dc:creator>Lindsley, P</dc:creator><dc:creator>Harris, JC</dc:creator><dc:creator>Perez-Amparan, E</dc:creator><dc:creator>Powell, TD</dc:creator><dc:creator>de City Heights, Comité Organizador Latino</dc:creator><dc:creator>Dowling, G</dc:creator><dc:creator>Alkire, D</dc:creator><dc:creator>Thompson, WK</dc:creator><dc:creator>Murray, TM</dc:creator><dc:date>2025-01-01</dc:date><dc:description>PURPOSE: The Adolescent Brain Cognitive DevelopmentSM (ABCD) Study is the largest longitudinal study on brain development and adolescent health in the United States. The study includes a sociodemographically diverse cohort of nearly 12,000 youth born 2005-2009, with an open science model of making data rapidly available to the scientific community. The ABCD Study® data has been used in over 1100 peer-reviewed publications since its first data release in 2018. The dataset contains a broad scope and comprehensive set of measures of youths' behavioral, health, and brain outcomes, as well as extensive contextual and environmental measures that map onto the social determinants of health (SDOH). Understanding the impact of SDOH on the developmental trajectories of youth will help to address early lifecourse health inequities that lead to disparities later in life. However, the open science model and extensive use of ABCD data highlight the need for guidance on appropriate, responsible, and equitable use of the data.
DESIGN METHODS: Our conceptual framework integrates the National Institute on Minority Health and Health Disparities (NIMHD) Research Framework with strength-based and data equity perspectives. We use this framework to articulate best practices and methods for investigations that aim to identify the multilevel pathways by which structural and systemic inequities impact adolescent health trajectories.
RESULTS: Using our conceptual model, we provide recommendations for equitable health disparities research using ABCD Study data. We identify over fifty ABCD measures that can encompass SDOH across five levels of influence: individual, interpersonal, school, community, and societal. We expand the societal level to acknowledge structural discrimination as the root cause of systemic and structural inequities resulting in health disparities among marginalized youth. We apply the methodological recommendations in an example data analysis using a multi-level approach that integrates strength-based and data equity perspectives to elucidate pathways by which social and structural inequities may influence cognitive decision making in youth. We conclude with recommendations for strengthening the utility of ABCD data for health disparities research now and in the future.
CONCLUSION: Adolescence is a critical period of development with subsequent ramifications for health outcomes across the lifespan. Thus, understanding SDOH among diverse youth can inform prevention interventions before the emergence of health disparities in adulthood.</dc:description><dc:subject>3213 Paediatrics (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>Basic Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Minority Health (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>11 Sustainable Cities and Communities (sdg)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Adolescent (mesh)</dc:subject><dc:subject>Longitudinal Studies (mesh)</dc:subject><dc:subject>Adolescent Development (mesh)</dc:subject><dc:subject>Health Status Disparities (mesh)</dc:subject><dc:subject>Social Determinants of Health (mesh)</dc:subject><dc:subject>Cognition (mesh)</dc:subject><dc:subject>Brain (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Adolescent Health (mesh)</dc:subject><dc:subject>Brain (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Longitudinal Studies (mesh)</dc:subject><dc:subject>Adolescent Development (mesh)</dc:subject><dc:subject>Cognition (mesh)</dc:subject><dc:subject>Adolescent (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Health Status Disparities (mesh)</dc:subject><dc:subject>Social Determinants of Health (mesh)</dc:subject><dc:subject>Adolescent Health (mesh)</dc:subject><dc:subject>Adolescent health</dc:subject><dc:subject>Health disparities research</dc:subject><dc:subject>Responsible data use</dc:subject><dc:subject>Social determinants of health</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Adolescent (mesh)</dc:subject><dc:subject>Longitudinal Studies (mesh)</dc:subject><dc:subject>Adolescent Development (mesh)</dc:subject><dc:subject>Health Status Disparities (mesh)</dc:subject><dc:subject>Social Determinants of Health (mesh)</dc:subject><dc:subject>Cognition (mesh)</dc:subject><dc:subject>Brain (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Adolescent Health (mesh)</dc:subject><dc:subject>1103 Clinical Sciences (for)</dc:subject><dc:subject>1109 Neurosciences (for)</dc:subject><dc:subject>1702 Cognitive Sciences (for)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:subject>5202 Biological psychology (for-2020)</dc:subject><dc:subject>5203 Clinical and health psychology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4gk0m0b7</dc:identifier><dc:identifier>https://escholarship.org/content/qt4gk0m0b7/qt4gk0m0b7.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.dcn.2024.101497</dc:identifier><dc:type>article</dc:type><dc:source>Developmental Cognitive Neuroscience, vol 71</dc:source><dc:coverage>101497</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4cb1n525</identifier><datestamp>2026-09-15T21:18:30Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4cb1n525</dc:identifier><dc:title>Structural classification of locally stationary time series based on second-order characteristics</dc:title><dc:creator>Qian, Chen</dc:creator><dc:creator>Ding, Xiucai</dc:creator><dc:creator>Li, Lexin</dc:creator><dc:date>2026-06-23</dc:date><dc:description>Abstract Time series classification is crucial for numerous scientific and engineering applications. In this article, we present a numerically efficient, practically competitive, and theoretically rigorous classification method for distinguishing between two classes of locally stationary time series based on their time-domain, second-order characteristics. Our approach builds on the autoregressive approximation for locally stationary time series, imposes no requirement on the training sample size, and is shown to achieve zero misclassification error rate asymptotically when the underlying time series differ only mildly in their second-order characteristics. The new method is demonstrated to outperform a variety of state-of-the-art solutions, including wavelet-based, tree-based, convolution-based methods, as well as modern deep learning methods, through intensive numerical simulations and a real electroencephalography data analysis for epilepsy classification.</dc:description><dc:subject>38 Economics (for-2020)</dc:subject><dc:subject>4905 Statistics (for-2020)</dc:subject><dc:subject>3802 Econometrics (for-2020)</dc:subject><dc:subject>49 Mathematical Sciences (for-2020)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>Networking and Information Technology R&amp;D (NITRD) (rcdc)</dc:subject><dc:subject>autocovariance function</dc:subject><dc:subject>autoregressive approximation</dc:subject><dc:subject>electroencephalogram</dc:subject><dc:subject>locally stationary time series</dc:subject><dc:subject>time series classification</dc:subject><dc:subject>0102 Applied Mathematics (for)</dc:subject><dc:subject>0104 Statistics (for)</dc:subject><dc:subject>1403 Econometrics (for)</dc:subject><dc:subject>Statistics &amp; Probability (science-metrix)</dc:subject><dc:subject>3802 Econometrics (for-2020)</dc:subject><dc:subject>4905 Statistics (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4cb1n525</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1093/jrsssb/qkag083</dc:identifier><dc:type>article</dc:type><dc:source>Journal of the Royal Statistical Society Series B Statistical Methodology</dc:source><dc:coverage>qkag083</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8mm2r79m</identifier><datestamp>2026-09-15T21:14:55Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8mm2r79m</dc:identifier><dc:title>Sponge diversification in marine lakes: Implications for phylogeography and population genomic studies on sponges</dc:title><dc:creator>Maas, Diede L</dc:creator><dc:creator>Prost, Stefan</dc:creator><dc:creator>de Leeuw, Christiaan A</dc:creator><dc:creator>Bi, Ke</dc:creator><dc:creator>Smith, Lydia L</dc:creator><dc:creator>Purwanto, Purwanto</dc:creator><dc:creator>Aji, Ludi P</dc:creator><dc:creator>Tapilatu, Ricardo F</dc:creator><dc:creator>Gillespie, Rosemary G</dc:creator><dc:creator>Becking, Leontine E</dc:creator><dc:date>2023-04-01</dc:date><dc:description>The relative influence of geography, currents, and environment on gene flow within sessile marine species remains an open question. Detecting subtle genetic differentiation at small scales is challenging in benthic populations due to large effective population sizes, general lack of resolution in genetic markers, and because barriers to dispersal often remain elusive. Marine lakes can circumvent confounding factors by providing discrete and replicated ecosystems. Using high-resolution double digest restriction-site-associated DNA sequencing (4826 Single Nucleotide Polymorphisms, SNPs), we genotyped populations of the sponge Suberites diversicolor (n = 125) to test the relative importance of spatial scales (1-1400 km), local environmental conditions, and permeability of seascape barriers in shaping population genomic structure. With the SNP dataset, we show strong intralineage population structure, even at scales &amp;lt;10 km (average F ST = 0.63), which was not detected previously using single markers. Most variation was explained by differentiation between populations (AMOVA: 48.8%) with signatures of population size declines and bottlenecks per lake. Although the populations were strongly structured, we did not detect significant effects of geographic distance, local environments, or degree of connection to the sea on population structure, suggesting mechanisms such as founder events with subsequent priority effects may be at play. We show that the inclusion of morphologically cryptic lineages that can be detected with the COI marker can reduce the obtained SNP set by around 90%. Future work on sponge genomics should confirm that only one lineage is included. Our results call for a reassessment of poorly dispersing benthic organisms that were previously assumed to be highly connected based on low-resolution markers.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Biotechnology (rcdc)</dc:subject><dc:subject>1.1 Normal biological development and functioning (hrcs-rac)</dc:subject><dc:subject>14 Life Below Water (sdg)</dc:subject><dc:subject>genetic resolution</dc:subject><dc:subject>marine biodiversity</dc:subject><dc:subject>Porifera</dc:subject><dc:subject>RADseq</dc:subject><dc:subject>seascape genomics</dc:subject><dc:subject>Suberites diversicolor</dc:subject><dc:subject>Porifera</dc:subject><dc:subject>RADseq</dc:subject><dc:subject>Suberites diversicolor</dc:subject><dc:subject>genetic resolution</dc:subject><dc:subject>marine biodiversity</dc:subject><dc:subject>seascape genomics</dc:subject><dc:subject>0602 Ecology (for)</dc:subject><dc:subject>0603 Evolutionary Biology (for)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>3104 Evolutionary biology (for-2020)</dc:subject><dc:subject>4102 Ecological applications (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8mm2r79m</dc:identifier><dc:identifier>https://escholarship.org/content/qt8mm2r79m/qt8mm2r79m.pdf</dc:identifier><dc:identifier>info:doi/10.1002/ece3.9945</dc:identifier><dc:type>article</dc:type><dc:source>Ecology and Evolution, vol 13, iss 4</dc:source><dc:coverage>e9945</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8hq913tm</identifier><datestamp>2026-09-15T21:09:04Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8hq913tm</dc:identifier><dc:title>Forward Introduction: Interior Empire</dc:title><dc:creator>Takeuchi-Demirci, Aiko</dc:creator><dc:creator>Kim, Sabine</dc:creator><dc:date>2026-09-05</dc:date><dc:description>Editors' introduction to a curated selection of excerpts from recent thought-provoking work in the field of transnational American studies.</dc:description><dc:subject>US empire</dc:subject><dc:subject>transnational American studies</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8hq913tm</dc:identifier><dc:identifier>https://escholarship.org/content/qt8hq913tm/qt8hq913tm.pdf</dc:identifier><dc:identifier>info:doi/10.5070/T8.69030</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Transnational American Studies, vol 17, iss 1</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8r71f7zg</identifier><datestamp>2026-09-15T21:00:05Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8r71f7zg</dc:identifier><dc:title>Reference genome of the black rail, Laterallus jamaicensis</dc:title><dc:creator>Hall, Laurie A</dc:creator><dc:creator>Wang, Ian J</dc:creator><dc:creator>Escalona, Merly</dc:creator><dc:creator>Beraut, Eric</dc:creator><dc:creator>Sacco, Samuel</dc:creator><dc:creator>Sahasrabudhe, Ruta</dc:creator><dc:creator>Nguyen, Oanh</dc:creator><dc:creator>Toffelmier, Erin</dc:creator><dc:creator>Shaffer, H Bradley</dc:creator><dc:creator>Beissinger, Steven R</dc:creator><dc:contributor>Shapiro, Beth</dc:contributor><dc:date>2023-06-22</dc:date><dc:description>The black rail, Laterallus jamaicensis, is one of the most secretive and poorly understood birds in the Americas. Two of its five subspecies breed in North America: the Eastern black rail (L. j. jamaicensis), found primarily in the southern and mid-Atlantic states, and the California black rail (L. j. coturniculus), inhabiting California and Arizona, are recognized across the highly disjunct distribution. Population declines, due primarily to wetland loss and degradation, have resulted in conservation status listings for both subspecies. To help advance understanding of the phylogeography, biology, and ecology of this elusive species, we report the first reference genome assembly for the black rail, produced as part of the California Conservation Genomics Project (CCGP). We produced a de novo genome assembly using Pacific Biosciences HiFi long reads and Hi-C chromatin-proximity sequencing technology with an estimated sequencing error rate of 0.182%. The assembly consists of 964 scaffolds spanning 1.39 Gb, with a contig N50 of 7.4 Mb, scaffold N50 of 21.4 Mb, largest contig of 44.8 Mb, and largest scaffold of 101.2 Mb. The assembly has a high BUSCO completeness score of 96.8% and represents the first genome assembly available for the genus Laterallus. This genome assembly can help resolve questions about the complex evolutionary history of rails, assess black rail vagility and population connectivity, estimate effective population sizes, and evaluate the potential of rails for adaptive evolution in the face of growing threats from climate change, habitat loss and fragmentation, and disease.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>15 Life on Land (sdg)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>Birds (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>Ecology (mesh)</dc:subject><dc:subject>Chromosomes (mesh)</dc:subject><dc:subject>California Conservation Genomics Project</dc:subject><dc:subject>CCGP</dc:subject><dc:subject>conservation genetics</dc:subject><dc:subject>Gruiformes</dc:subject><dc:subject>Rallidae</dc:subject><dc:subject>Chromosomes (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Birds (mesh)</dc:subject><dc:subject>Ecology (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>CCGP</dc:subject><dc:subject>California Conservation Genomics Project</dc:subject><dc:subject>Gruiformes</dc:subject><dc:subject>Rallidae</dc:subject><dc:subject>conservation genetics</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>Birds (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Genomics (mesh)</dc:subject><dc:subject>Ecology (mesh)</dc:subject><dc:subject>Chromosomes (mesh)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>Evolutionary Biology (science-metrix)</dc:subject><dc:subject>3104 Evolutionary biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8r71f7zg</dc:identifier><dc:identifier>https://escholarship.org/content/qt8r71f7zg/qt8r71f7zg.pdf</dc:identifier><dc:identifier>info:doi/10.1093/jhered/esad025</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Heredity, vol 114, iss 4</dc:source><dc:coverage>436 - 443</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt66x0511j</identifier><datestamp>2026-09-15T20:56:53Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt66x0511j</dc:identifier><dc:title>Data Release 1 of the Dark Energy Spectroscopic Instrument</dc:title><dc:creator>Collaboration, DESI</dc:creator><dc:creator>Karim, M Abdul</dc:creator><dc:creator>Adame, AG</dc:creator><dc:creator>Aguado, D</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alam, S</dc:creator><dc:creator>Aldering, G</dc:creator><dc:creator>Alexander, DM</dc:creator><dc:creator>Alfarsy, R</dc:creator><dc:creator>Allen, L</dc:creator><dc:creator>Prieto, C Allende</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Anand, A</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Avila, S</dc:creator><dc:creator>Aviles, A</dc:creator><dc:creator>Awan, H</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Lizancos, A Baleato</dc:creator><dc:creator>Ballester, O</dc:creator><dc:creator>Bault, A</dc:creator><dc:creator>Bautista, J</dc:creator><dc:creator>Bean, R</dc:creator><dc:creator>Behera, J</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Silva, L Beraldo E</dc:creator><dc:creator>Bermejo-Climent, JR</dc:creator><dc:creator>Beutler, F</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Blake, C</dc:creator><dc:creator>Blum, R</dc:creator><dc:creator>Bolton, AS</dc:creator><dc:creator>Bonici, M</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Buckley-Geer, E</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Byström, A</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Carr, A</dc:creator><dc:creator>Carrilho, P</dc:creator><dc:creator>Casas, L</dc:creator><dc:creator>Castander, FJ</dc:creator><dc:creator>Cereskaite, R</dc:creator><dc:creator>Cervantes-Cota, JL</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Chaves-Montero, J</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Circosta, C</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Cooper, AP</dc:creator><dc:creator>Cousinou, M-C</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Davis, TM</dc:creator><dc:creator>Dawson, KS</dc:creator><dc:creator>de Belsunce, R</dc:creator><dc:creator>de la Cruz, R</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Deiosso, N</dc:creator><dc:creator>Della Costa, J</dc:creator><dc:creator>Demina, R</dc:creator><dc:creator>Demirbozan, U</dc:creator><dc:creator>DeRose, J</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Ding, J</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Douglass, K</dc:creator><dc:creator>Dowicz, M</dc:creator><dc:creator>Ebina, H</dc:creator><dc:creator>Edelstein, J</dc:creator><dc:creator>Eisenstein, DJ</dc:creator><dc:creator>Elbers, W</dc:creator><dc:creator>Emas, N</dc:creator><dc:creator>Escoffier, S</dc:creator><dc:creator>Fagrelius, P</dc:creator><dc:creator>Fan, X</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Favole, G</dc:creator><dc:creator>Fawcett, VA</dc:creator><dc:creator>Fernández-García, E</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Findlay, N</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Forero-Sánchez, D</dc:creator><dc:creator>Frenk, CS</dc:creator><dc:creator>Gänsicke, BT</dc:creator><dc:creator>Galbany, L</dc:creator><dc:creator>García-Bellido, J</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Garrison, LH</dc:creator><dc:date>2026-05-01</dc:date><dc:description>In 2021 May the Dark Energy Spectroscopic Instrument (DESI) collaboration began a 5 yr spectroscopic redshift survey to produce a detailed map of the evolving three-dimensional structure of the Universe between z = 0 and z ≈ 4. DESI’s principal scientific objectives are to place precise constraints on the equation of state of dark energy, the gravitationally driven growth of large-scale structure, and the sum of the neutrino masses, and to explore the observational signatures of primordial inflation. We present DESI DR1, which consists of all data acquired during the first 13 months of the DESI main survey, as well as a uniform reprocessing of the DESI Survey Validation data, which were previously made public in the DESI Early Data Release. The DR1 main survey includes high-confidence redshifts for 18.7M objects, of which 13.1M are spectroscopically classified as galaxies, 1.6M as quasars, and 4M as stars, making DR1 the largest sample of extragalactic redshifts ever assembled. We summarize the DR1 observations, the spectroscopic data-reduction pipeline and data products, large-scale structure catalogs, value-added catalogs, and describe how to access and interact with the data. In addition to fulfilling its core cosmological objectives with unprecedented precision, we expect DR1 to enable a wide range of transformational astrophysical studies and discoveries.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/66x0511j</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.3847/1538-3881/ae4c43</dc:identifier><dc:type>article</dc:type><dc:source>The Astronomical Journal, vol 171, iss 5</dc:source><dc:coverage>285</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3dh4j155</identifier><datestamp>2026-09-15T20:55:55Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3dh4j155</dc:identifier><dc:title>River thorium concentrations can record bedrock fracture processes including some triggered by distant seismic events</dc:title><dc:creator>Gilbert, Benjamin</dc:creator><dc:creator>Carrero, Sergio</dc:creator><dc:creator>Dong, Wenming</dc:creator><dc:creator>Joe-Wong, Claresta</dc:creator><dc:creator>Arora, Bhavna</dc:creator><dc:creator>Fox, Patricia</dc:creator><dc:creator>Nico, Peter</dc:creator><dc:creator>Williams, Kenneth H</dc:creator><dc:date>2023-04-26</dc:date><dc:description>Fractures are integral to the hydrology and geochemistry of watersheds, but our understanding of fracture dynamics is very limited because of the challenge of monitoring the subsurface. Here we provide evidence that long-term, high-frequency measurements of the river concentration of the ultra-trace element thorium (Th) can provide a signature of bedrock fracture processes spanning neighboring watersheds in Colorado. River Th concentrations show abrupt (subdaily) excursions and biexponential decay with approximately 1-day and 1-week time constants, concentration patterns that are distinct from all other solutes except beryllium and arsenic. The patterns are uncorrelated with daily precipitation records or seasonal trends in atmospheric deposition. Groundwater Th analyses are consistent with bedrock release and dilution upon mixing with river water. Most Th excursions have no seismic signatures that are detectable 50 km from the site, suggesting the Th concentrations can reveal aseismic fracture or fault events. We find, however, a weak statistical correlation between Th and seismic motion caused by distant earthquakes, possibly the first chemical signature of dynamic earthquake triggering, a phenomenon previously identified only through geophysical methods.</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>3703 Geochemistry (for-2020)</dc:subject><dc:subject>3705 Geology (for-2020)</dc:subject><dc:subject>3706 Geophysics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3dh4j155</dc:identifier><dc:identifier>https://escholarship.org/content/qt3dh4j155/qt3dh4j155.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41467-023-37784-3</dc:identifier><dc:type>article</dc:type><dc:source>Nature Communications, vol 14, iss 1</dc:source><dc:coverage>2395</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2qm6h6tp</identifier><datestamp>2026-09-15T20:52:35Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2qm6h6tp</dc:identifier><dc:title>COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data</dc:title><dc:creator>Bond‐Lamberty, Ben</dc:creator><dc:creator>Christianson, Danielle S</dc:creator><dc:creator>Malhotra, Avni</dc:creator><dc:creator>Pennington, Stephanie C</dc:creator><dc:creator>Sihi, Debjani</dc:creator><dc:creator>AghaKouchak, Amir</dc:creator><dc:creator>Anjileli, Hassan</dc:creator><dc:creator>Arain, M Altaf</dc:creator><dc:creator>Armesto, Juan J</dc:creator><dc:creator>Ashraf, Samaneh</dc:creator><dc:creator>Ataka, Mioko</dc:creator><dc:creator>Baldocchi, Dennis</dc:creator><dc:creator>Black, Thomas Andrew</dc:creator><dc:creator>Buchmann, Nina</dc:creator><dc:creator>Carbone, Mariah S</dc:creator><dc:creator>Chang, Shih‐Chieh</dc:creator><dc:creator>Crill, Patrick</dc:creator><dc:creator>Curtis, Peter S</dc:creator><dc:creator>Davidson, Eric A</dc:creator><dc:creator>Desai, Ankur R</dc:creator><dc:creator>Drake, John E</dc:creator><dc:creator>El‐Madany, Tarek S</dc:creator><dc:creator>Gavazzi, Michael</dc:creator><dc:creator>Görres, Carolyn‐Monika</dc:creator><dc:creator>Gough, Christopher M</dc:creator><dc:creator>Goulden, Michael</dc:creator><dc:creator>Gregg, Jillian</dc:creator><dc:creator>del Arroyo, Omar Gutiérrez</dc:creator><dc:creator>He, Jin‐Sheng</dc:creator><dc:creator>Hirano, Takashi</dc:creator><dc:creator>Hopple, Anya</dc:creator><dc:creator>Hughes, Holly</dc:creator><dc:creator>Järveoja, Järvi</dc:creator><dc:creator>Jassal, Rachhpal</dc:creator><dc:creator>Jian, Jinshi</dc:creator><dc:creator>Kan, Haiming</dc:creator><dc:creator>Kaye, Jason</dc:creator><dc:creator>Kominami, Yuji</dc:creator><dc:creator>Liang, Naishen</dc:creator><dc:creator>Lipson, David</dc:creator><dc:creator>Macdonald, Catriona A</dc:creator><dc:creator>Maseyk, Kadmiel</dc:creator><dc:creator>Mathes, Kayla</dc:creator><dc:creator>Mauritz, Marguerite</dc:creator><dc:creator>Mayes, Melanie A</dc:creator><dc:creator>McNulty, Steve</dc:creator><dc:creator>Miao, Guofang</dc:creator><dc:creator>Migliavacca, Mirco</dc:creator><dc:creator>Miller, Scott</dc:creator><dc:creator>Miniat, Chelcy F</dc:creator><dc:creator>Nietz, Jennifer G</dc:creator><dc:creator>Nilsson, Mats B</dc:creator><dc:creator>Noormets, Asko</dc:creator><dc:creator>Norouzi, Hamidreza</dc:creator><dc:creator>O’Connell, Christine S</dc:creator><dc:creator>Osborne, Bruce</dc:creator><dc:creator>Oyonarte, Cecilio</dc:creator><dc:creator>Pang, Zhuo</dc:creator><dc:creator>Peichl, Matthias</dc:creator><dc:creator>Pendall, Elise</dc:creator><dc:creator>Perez‐Quezada, Jorge F</dc:creator><dc:creator>Phillips, Claire L</dc:creator><dc:creator>Phillips, Richard P</dc:creator><dc:creator>Raich, James W</dc:creator><dc:creator>Renchon, Alexandre A</dc:creator><dc:creator>Ruehr, Nadine K</dc:creator><dc:creator>Sánchez‐Cañete, Enrique P</dc:creator><dc:creator>Saunders, Matthew</dc:creator><dc:creator>Savage, Kathleen E</dc:creator><dc:creator>Schrumpf, Marion</dc:creator><dc:creator>Scott, Russell L</dc:creator><dc:creator>Seibt, Ulli</dc:creator><dc:creator>Silver, Whendee L</dc:creator><dc:creator>Sun, Wu</dc:creator><dc:creator>Szutu, Daphne</dc:creator><dc:creator>Takagi, Kentaro</dc:creator><dc:creator>Takagi, Masahiro</dc:creator><dc:creator>Teramoto, Munemasa</dc:creator><dc:creator>Tjoelker, Mark G</dc:creator><dc:creator>Trumbore, Susan</dc:creator><dc:creator>Ueyama, Masahito</dc:creator><dc:creator>Vargas, Rodrigo</dc:creator><dc:creator>Varner, Ruth K</dc:creator><dc:creator>Verfaillie, Joseph</dc:creator><dc:creator>Vogel, Christoph</dc:creator><dc:creator>Wang, Jinsong</dc:creator><dc:creator>Winston, Greg</dc:creator><dc:creator>Wood, Tana E</dc:creator><dc:creator>Wu, Juying</dc:creator><dc:creator>Wutzler, Thomas</dc:creator><dc:creator>Zeng, Jiye</dc:creator><dc:creator>Zha, Tianshan</dc:creator><dc:creator>Zhang, Quan</dc:creator><dc:creator>Zou, Junliang</dc:creator><dc:date>2020-12-01</dc:date><dc:description>Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil-to-atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS ), is one of the largest carbon fluxes in the Earth system. An increasing number of high-frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open-source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long-term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS , the database design accommodates other soil-atmosphere measurements (e.g. ecosystem respiration, chamber-measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.</dc:description><dc:subject>4101 Climate Change Impacts and Adaptation (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>2.6 Resources and infrastructure (aetiology) (hrcs-rac)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>Atmosphere (mesh)</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Greenhouse Gases (mesh)</dc:subject><dc:subject>Methane (mesh)</dc:subject><dc:subject>Nitrous Oxide (mesh)</dc:subject><dc:subject>Reproducibility of Results (mesh)</dc:subject><dc:subject>Respiration (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>carbon dioxide</dc:subject><dc:subject>greenhouse gases</dc:subject><dc:subject>methane</dc:subject><dc:subject>open data</dc:subject><dc:subject>open science</dc:subject><dc:subject>soil respiration</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>Nitrous Oxide (mesh)</dc:subject><dc:subject>Methane (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>Reproducibility of Results (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Atmosphere (mesh)</dc:subject><dc:subject>Respiration (mesh)</dc:subject><dc:subject>Greenhouse Gases (mesh)</dc:subject><dc:subject>carbon dioxide</dc:subject><dc:subject>greenhouse gases</dc:subject><dc:subject>methane</dc:subject><dc:subject>open data</dc:subject><dc:subject>open science</dc:subject><dc:subject>soil respiration</dc:subject><dc:subject>Atmosphere (mesh)</dc:subject><dc:subject>Carbon Dioxide (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Greenhouse Gases (mesh)</dc:subject><dc:subject>Methane (mesh)</dc:subject><dc:subject>Nitrous Oxide (mesh)</dc:subject><dc:subject>Reproducibility of Results (mesh)</dc:subject><dc:subject>Respiration (mesh)</dc:subject><dc:subject>Soil (mesh)</dc:subject><dc:subject>05 Environmental Sciences (for)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>Ecology (science-metrix)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>37 Earth sciences (for-2020)</dc:subject><dc:subject>41 Environmental sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2qm6h6tp</dc:identifier><dc:identifier>https://escholarship.org/content/qt2qm6h6tp/qt2qm6h6tp.pdf</dc:identifier><dc:identifier>info:doi/10.1111/gcb.15353</dc:identifier><dc:type>article</dc:type><dc:source>Global Change Biology, vol 26, iss 12</dc:source><dc:coverage>7268 - 7283</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1507s9df</identifier><datestamp>2026-09-15T20:51:43Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1507s9df</dc:identifier><dc:title>Effectiveness and predictability of in-network storage cache for Scientific Workflows</dc:title><dc:creator>Sim, Caitlin</dc:creator><dc:creator>Wu, Kesheng</dc:creator><dc:creator>Sim, Alex</dc:creator><dc:creator>Monga, Inder</dc:creator><dc:creator>Guok, Chin</dc:creator><dc:creator>Würthwein, Frank</dc:creator><dc:creator>Davila, Diego</dc:creator><dc:creator>Newman, Harvey</dc:creator><dc:creator>Balcas, Justas</dc:creator><dc:date>2023-02-22</dc:date><dc:description>Large scientific collaborations often have multiple scientists accessing the same set of files while doing different analyses, which create repeated accesses to the large amounts of shared data located far away. These data accesses have long latency due to distance and occupy the limited bandwidth available over the wide-area network. To reduce the wide-area network traffic and the data access latency, regional data storage caches have been installed as a new networking service. To study the effectiveness of such a cache system in scientific applications, we examine the Southern California Petabyte Scale Cache for a high-energy physics experiment. By examining about 3TB of operational logs, we show that this cache removed 67.6% of file requests from the wide-area network and reduced the traffic volume on wide-area network by 12. 3TB (or 35.4%) an average day. The reduction in the traffic volume (35.4%) is less than the reduction in file counts (67.6%) because the larger files are less likely to be reused. Due to this difference in data access patterns, the cache system has implemented a policy to avoid evicting smaller files when processing larger files. We also build a machine learning model to study the predictability of the cache behavior. Tests show that this model is able to accurately predict the cache accesses, cache misses, and network throughput, making the model useful for future studies on resource provisioning and planning.</dc:description><dc:subject>33 Built Environment and Design (for-2020)</dc:subject><dc:subject>3301 Architecture (for-2020)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>in-network caching</dc:subject><dc:subject>data throughput</dc:subject><dc:subject>transfer performance</dc:subject><dc:subject>data access trends</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1507s9df</dc:identifier><dc:identifier>https://escholarship.org/content/qt1507s9df/qt1507s9df.pdf</dc:identifier><dc:identifier>info:doi/10.1109/icnc57223.2023.10074058</dc:identifier><dc:type>article</dc:type><dc:source>2023 INTERNATIONAL CONFERENCE ON COMPUTING, NETWORKING AND COMMUNICATIONS, ICNC, vol 00</dc:source><dc:coverage>226 - 230</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6b99h996</identifier><datestamp>2026-09-15T20:48:44Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6b99h996</dc:identifier><dc:title>Using Field-Metered Data to Characterize Consumer Usage Patterns of Residential Dishwashers</dc:title><dc:creator>Sun, Qingyi</dc:creator><dc:creator>Ke, Jing</dc:creator><dc:creator>Dunham, Camilla</dc:creator><dc:creator>Sim, Joong Hoon</dc:creator><dc:creator>Chen, Yuting</dc:creator><dc:date>2023-04-14</dc:date><dc:description>Pecan Street’s field-metered data offer an opportunity to track actual appliance usage patterns and energy consumption over multiple years, and can supplement data from the US Energy Information Administration’s Residential Energy Consumption Survey (RECS).  This report is based on dishwasher metering data collected from more than 500 households located in Texas, California, New York, and Colorado from 2012 to 2021. The historical dishwasher usage frequency, the COVID-19 period usage change, and the potential seasonal trend in usage were investigated. Dishwasher cycle features such as cycle duration, quick cycle usage frequency, and average per cycle dishwasher energy consumption were observed and characterized. Due to the sample size, the lack of demographic data, and the limited geographic locations of the participating households, the results are not nationally representative. However, when compared with the usage frequency reported by RECS, the field-obtained average annual cycle counts per household are 164 in 2015 and 197 in 2020 for selected households which are consistent with the RECS annual cycle counts of 181 and 191 respectively in 2015 and 2020 for the same geographic locations. Our findings support the use of RECS data to approximate field dishwasher usage. The field data usage frequency for households with infrequent dishwasher use could supplement the RECS information to better characterize the national usage distribution of different cycle selections.</dc:description><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6b99h996</dc:identifier><dc:identifier>https://escholarship.org/content/qt6b99h996/qt6b99h996.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7n45d71z</identifier><datestamp>2026-09-15T20:44:29Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7n45d71z</dc:identifier><dc:title>Pre-treatment bone mineral density and the benefit of pharmacologic treatment on fracture risk and BMD change: analysis from the FNIH-ASBMR SABRE project</dc:title><dc:creator>Schini, Marian</dc:creator><dc:creator>Vilaca, Tatiane</dc:creator><dc:creator>Lui, Li-Yung</dc:creator><dc:creator>Ewing, Susan K</dc:creator><dc:creator>Thompson, Austin</dc:creator><dc:creator>Vittinghoff, Eric</dc:creator><dc:creator>Bauer, Douglas C</dc:creator><dc:creator>Bouxsein, Mary L</dc:creator><dc:creator>Black, Dennis M</dc:creator><dc:creator>Eastell, Richard</dc:creator><dc:date>2024-08-05</dc:date><dc:description>Some osteoporosis drug trials have suggested that treatment is more effective in those with low BMD measured by DXA. This study used data from a large set of randomized controlled trials (RCTs) to determine whether the anti-fracture efficacy of treatments differs according to baseline BMD. We used individual patient data from 25 RCTs (103 086 subjects) of osteoporosis medications collected as part of the FNIH-ASBMR SABRE project. Participants were stratified into FN BMD T-score subgroups (≤-2.5, &amp;gt; -2.5). We used Cox proportional hazard regression to estimate treatment effect for clinical fracture outcomes and logistic regression for the radiographic vertebral fracture outcome. We also performed analyses based on BMD quintiles. Overall, 42% had a FN BMD T-score ≤ -2.5. Treatment with anti-osteoporosis drugs led to significant reductions in fractures in both T-score ≤ -2.5 and &amp;gt; -2.5 subgroups. Compared to those with FN BMD T-score &amp;gt; -2.5, the risk reduction for each fracture outcome was greater in those with T-score ≤ -2.5, but only the all-fracture outcome reached statistical significance (interaction P = .001). Results were similar when limited to bisphosphonate trials. In the quintile analysis, there was significant anti-fracture efficacy across all quintiles for vertebral fractures and with greater effects on fracture risk reduction for non-vertebral, all, and all clinical fractures in the lower BMD quintiles (all interaction P ≤ .03). In summary, anti-osteoporotic medications reduced the risk of fractures regardless of baseline BMD. Significant fracture risk reduction with treatment for 4 of the 5 fracture endpoints was seen in participants with T-scores above -2.5, though effects tended to be larger and more significant in those with baseline T-scores &amp;lt;-2.5.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>Physical Injury - Accidents and Adverse Effects (rcdc)</dc:subject><dc:subject>Aging (rcdc)</dc:subject><dc:subject>Clinical Trials and Supportive Activities (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Precision Medicine (rcdc)</dc:subject><dc:subject>Osteoporosis (rcdc)</dc:subject><dc:subject>5.1 Pharmaceuticals (hrcs-rac)</dc:subject><dc:subject>Musculoskeletal (hrcs-hc)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Bone Density (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>Fractures</dc:subject><dc:subject>Bone (mesh)</dc:subject><dc:subject>Bone Density Conservation Agents (mesh)</dc:subject><dc:subject>Randomized Controlled Trials as Topic (mesh)</dc:subject><dc:subject>Spinal Fractures (mesh)</dc:subject><dc:subject>Osteoporosis (mesh)</dc:subject><dc:subject>osteoporosis</dc:subject><dc:subject>BMD</dc:subject><dc:subject>T-score</dc:subject><dc:subject>treatment</dc:subject><dc:subject>SABRE</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Osteoporosis (mesh)</dc:subject><dc:subject>Spinal Fractures (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>Bone Density (mesh)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Bone Density Conservation Agents (mesh)</dc:subject><dc:subject>Fractures</dc:subject><dc:subject>Bone (mesh)</dc:subject><dc:subject>Randomized Controlled Trials as Topic (mesh)</dc:subject><dc:subject>BMD</dc:subject><dc:subject>SABRE</dc:subject><dc:subject>T-score</dc:subject><dc:subject>osteoporosis</dc:subject><dc:subject>treatment</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Bone Density (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>Fractures</dc:subject><dc:subject>Bone (mesh)</dc:subject><dc:subject>Bone Density Conservation Agents (mesh)</dc:subject><dc:subject>Randomized Controlled Trials as Topic (mesh)</dc:subject><dc:subject>Spinal Fractures (mesh)</dc:subject><dc:subject>Osteoporosis (mesh)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>Anatomy &amp; Morphology (science-metrix)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7n45d71z</dc:identifier><dc:identifier>https://escholarship.org/content/qt7n45d71z/qt7n45d71z.pdf</dc:identifier><dc:identifier>info:doi/10.1093/jbmr/zjae068</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Bone and Mineral Research, vol 39, iss 7</dc:source><dc:coverage>867 - 876</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt04j9g55j</identifier><datestamp>2026-09-15T20:44:04Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt04j9g55j</dc:identifier><dc:title>Investigating the eco‐evolutionary response of microbiomes to environmental change</dc:title><dc:creator>Martiny, Jennifer BH</dc:creator><dc:creator>Martiny, Adam C</dc:creator><dc:creator>Brodie, Eoin</dc:creator><dc:creator>Chase, Alexander B</dc:creator><dc:creator>Rodríguez‐Verdugo, Alejandra</dc:creator><dc:creator>Treseder, Kathleen K</dc:creator><dc:creator>Allison, Steven D</dc:creator><dc:date>2023-09-01</dc:date><dc:description>Microorganisms are the primary engines of biogeochemical processes and foundational to the provisioning of ecosystem services to human society. Free-living microbial communities (microbiomes) and their functioning are now known to be highly sensitive to environmental change. Given microorganisms' capacity for rapid evolution, evolutionary processes could play a role in this response. Currently, however, few models of biogeochemical processes explicitly consider how microbial evolution will affect biogeochemical responses to environmental change. Here, we propose a conceptual framework for explicitly integrating evolution into microbiome-functioning relationships. We consider how microbiomes respond simultaneously to environmental change via four interrelated processes that affect overall microbiome functioning (physiological acclimation, demography, dispersal and evolution). Recent evidence in both the laboratory and the field suggests that ecological and evolutionary dynamics occur simultaneously within microbiomes; however, the implications for biogeochemistry under environmental change will depend on the timescales over which these processes contribute to a microbiome's response. Over the long term, evolution may play an increasingly important role for microbially driven biogeochemical responses to environmental change, particularly to conditions without recent historical precedent.</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>4101 Climate Change Impacts and Adaptation (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>Microbiome (rcdc)</dc:subject><dc:subject>14 Life Below Water (sdg)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Biological Evolution (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>Acclimatization (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Biological (mesh)</dc:subject><dc:subject>bacteria</dc:subject><dc:subject>eco-evolutionary feedbacks</dc:subject><dc:subject>fungi</dc:subject><dc:subject>global change</dc:subject><dc:subject>rapid evolution</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Acclimatization (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Biological (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>Biological Evolution (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>bacteria</dc:subject><dc:subject>eco-evolutionary feedbacks</dc:subject><dc:subject>fungi</dc:subject><dc:subject>global change</dc:subject><dc:subject>rapid evolution</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Biological Evolution (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>Acclimatization (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Biological (mesh)</dc:subject><dc:subject>0501 Ecological Applications (for)</dc:subject><dc:subject>0602 Ecology (for)</dc:subject><dc:subject>0603 Evolutionary Biology (for)</dc:subject><dc:subject>Ecology (science-metrix)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>4102 Ecological applications (for-2020)</dc:subject><dc:subject>4104 Environmental management (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/04j9g55j</dc:identifier><dc:identifier>https://escholarship.org/content/qt04j9g55j/qt04j9g55j.pdf</dc:identifier><dc:identifier>info:doi/10.1111/ele.14209</dc:identifier><dc:type>article</dc:type><dc:source>Ecology Letters, vol 26, iss S1</dc:source><dc:coverage>s81 - s90</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1kp9k0f7</identifier><datestamp>2026-09-15T20:43:51Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1kp9k0f7</dc:identifier><dc:title>The Environmental Influences on Child Health Outcomes (ECHO)-Wide Cohort</dc:title><dc:creator>Knapp, Emily A</dc:creator><dc:creator>Kress, Amii M</dc:creator><dc:creator>Parker, Corette B</dc:creator><dc:creator>Page, Grier P</dc:creator><dc:creator>McArthur, Kristen</dc:creator><dc:creator>Gachigi, Kennedy K</dc:creator><dc:creator>Alshawabkeh, Akram N</dc:creator><dc:creator>Aschner, Judy L</dc:creator><dc:creator>Bastain, Theresa M</dc:creator><dc:creator>Breton, Carrie V</dc:creator><dc:creator>Bendixsen, Casper G</dc:creator><dc:creator>Brennan, Patricia A</dc:creator><dc:creator>Bush, Nicole R</dc:creator><dc:creator>Buss, Claudia</dc:creator><dc:creator>Camargo, Carlos A</dc:creator><dc:creator>Catellier, Diane</dc:creator><dc:creator>Cordero, José F</dc:creator><dc:creator>Croen, Lisa</dc:creator><dc:creator>Dabelea, Dana</dc:creator><dc:creator>Deoni, Sean</dc:creator><dc:creator>D’Sa, Viren</dc:creator><dc:creator>Duarte, Cristiane S</dc:creator><dc:creator>Dunlop, Anne L</dc:creator><dc:creator>Elliott, Amy J</dc:creator><dc:creator>Farzan, Shohreh F</dc:creator><dc:creator>Ferrara, Assiamira</dc:creator><dc:creator>Ganiban, Jody M</dc:creator><dc:creator>Gern, James E</dc:creator><dc:creator>Giardino, Angelo P</dc:creator><dc:creator>Towe-Goodman, Nissa R</dc:creator><dc:creator>Gold, Diane R</dc:creator><dc:creator>Habre, Rima</dc:creator><dc:creator>Hamra, Ghassan B</dc:creator><dc:creator>Hartert, Tina</dc:creator><dc:creator>Herbstman, Julie B</dc:creator><dc:creator>Hertz-Picciotto, Irva</dc:creator><dc:creator>Hipwell, Alison E</dc:creator><dc:creator>Karagas, Margaret R</dc:creator><dc:creator>Karr, Catherine J</dc:creator><dc:creator>Keenan, Kate</dc:creator><dc:creator>Kerver, Jean M</dc:creator><dc:creator>Koinis-Mitchell, Daphne</dc:creator><dc:creator>Lau, Bryan</dc:creator><dc:creator>Lester, Barry M</dc:creator><dc:creator>Leve, Leslie D</dc:creator><dc:creator>Leventhal, Bennett</dc:creator><dc:creator>LeWinn, Kaja Z</dc:creator><dc:creator>Lewis, Johnnye</dc:creator><dc:creator>Litonjua, Augusto A</dc:creator><dc:creator>Lyall, Kristen</dc:creator><dc:creator>Madan, Juliette C</dc:creator><dc:creator>McEvoy, Cindy T</dc:creator><dc:creator>McGrath, Monica</dc:creator><dc:creator>Meeker, John D</dc:creator><dc:creator>Miller, Rachel L</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Neiderhiser, Jenae M</dc:creator><dc:creator>O’Connor, Thomas G</dc:creator><dc:creator>Oken, Emily</dc:creator><dc:creator>O’Shea, Michael</dc:creator><dc:creator>Paneth, Nigel</dc:creator><dc:creator>Porucznik, Christina A</dc:creator><dc:creator>Sathyanarayana, Sheela</dc:creator><dc:creator>Schantz, Susan L</dc:creator><dc:creator>Spindel, Eliot R</dc:creator><dc:creator>Stanford, Joseph B</dc:creator><dc:creator>Stroustrup, Annemarie</dc:creator><dc:creator>Teitelbaum, Susan L</dc:creator><dc:creator>Trasande, Leonardo</dc:creator><dc:creator>Volk, Heather</dc:creator><dc:creator>Wadhwa, Pathik D</dc:creator><dc:creator>Weiss, Scott T</dc:creator><dc:creator>Woodruff, Tracey J</dc:creator><dc:creator>Wright, Rosalind J</dc:creator><dc:creator>Zhao, Qi</dc:creator><dc:creator>Jacobson, Lisa P</dc:creator><dc:creator>Outcomes, on behalf of program collaborators for Environmental Influences on Child Health</dc:creator><dc:date>2023-08-04</dc:date><dc:description>The Environmental Influences on Child Health Outcomes (ECHO)-Wide Cohort Study (EWC), a collaborative research design comprising 69 cohorts in 31 consortia, was funded by the National Institutes of Health (NIH) in 2016 to improve children's health in the United States. The EWC harmonizes extant data and collects new data using a standardized protocol, the ECHO-Wide Cohort Data Collection Protocol (EWCP). EWCP visits occur at least once per life stage, but the frequency and timing of the visits vary across cohorts. As of March 4, 2022, the EWC cohorts contributed data from 60,553 children and consented 29,622 children for new EWCP data and biospecimen collection. The median (interquartile range) age of EWCP-enrolled children was 7.5 years (3.7-11.1). Surveys, interviews, standardized examinations, laboratory analyses, and medical record abstraction are used to obtain information in 5 main outcome areas: pre-, peri-, and postnatal outcomes; neurodevelopment; obesity; airways; and positive health. Exposures include factors at the level of place (e.g., air pollution, neighborhood socioeconomic status), family (e.g., parental mental health), and individuals (e.g., diet, genomics).</dc:description><dc:subject>4206 Public Health (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Nutrition (rcdc)</dc:subject><dc:subject>Childhood Obesity (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Obesity (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>2.4 Surveillance and distribution (hrcs-rac)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Child Health (mesh)</dc:subject><dc:subject>Air Pollution (mesh)</dc:subject><dc:subject>Outcome Assessment</dc:subject><dc:subject>Health Care (mesh)</dc:subject><dc:subject>adolescent</dc:subject><dc:subject>child</dc:subject><dc:subject>child development</dc:subject><dc:subject>child health</dc:subject><dc:subject>child well-being</dc:subject><dc:subject>cohort studies</dc:subject><dc:subject>environmental exposure</dc:subject><dc:subject>epidemiologic methods</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Air Pollution (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Child Health (mesh)</dc:subject><dc:subject>Outcome Assessment</dc:subject><dc:subject>Health Care (mesh)</dc:subject><dc:subject>adolescent</dc:subject><dc:subject>child</dc:subject><dc:subject>child development</dc:subject><dc:subject>child health</dc:subject><dc:subject>child well-being</dc:subject><dc:subject>cohort studies</dc:subject><dc:subject>environmental exposure</dc:subject><dc:subject>epidemiologic methods</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Child Health (mesh)</dc:subject><dc:subject>Air Pollution (mesh)</dc:subject><dc:subject>Outcome Assessment</dc:subject><dc:subject>Health Care (mesh)</dc:subject><dc:subject>01 Mathematical Sciences (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>Epidemiology (science-metrix)</dc:subject><dc:subject>4202 Epidemiology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1kp9k0f7</dc:identifier><dc:identifier>https://escholarship.org/content/qt1kp9k0f7/qt1kp9k0f7.pdf</dc:identifier><dc:identifier>info:doi/10.1093/aje/kwad071</dc:identifier><dc:type>article</dc:type><dc:source>American Journal of Epidemiology, vol 192, iss 8</dc:source><dc:coverage>1249 - 1263</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2400c76b</identifier><datestamp>2026-09-15T20:40:45Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2400c76b</dc:identifier><dc:title>The Spectroscopic Data Processing Pipeline for the Dark Energy Spectroscopic Instrument</dc:title><dc:creator>Guy, J</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Alam, Shadab</dc:creator><dc:creator>Alexander, DM</dc:creator><dc:creator>Prieto, C Allende</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Bolton, AS</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Cooper, AP</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Dhungana, G</dc:creator><dc:creator>Eisenstein, DJ</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Green, D</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kirkby, D</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Koposov, Sergey E</dc:creator><dc:creator>Lan, Ting-Wen</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, Michael E</dc:creator><dc:creator>Magneville, C</dc:creator><dc:creator>Manser, Christopher J</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, Aaron M</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Myers, Adam D</dc:creator><dc:creator>Newman, Jeffrey A</dc:creator><dc:creator>Nie, Jundan</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Raichoor, A</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Schlafly, EF</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Sharples, Ray M</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yéche, Christophe</dc:creator><dc:creator>Zhou, Rongpu</dc:creator><dc:creator>Zhou, Zhimin</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2023-04-01</dc:date><dc:description>We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4 m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the universe with the baryon acoustic oscillation technique and the growth rate of structure with redshift space distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near-UV to near-infrared (3600–9800 Å) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline’s algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project’s requirements for redshift performance, with high efficiency and a purity greater than 99% for all target classes.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2400c76b</dc:identifier><dc:identifier>https://escholarship.org/content/qt2400c76b/qt2400c76b.pdf</dc:identifier><dc:identifier>info:doi/10.3847/1538-3881/acb212</dc:identifier><dc:type>article</dc:type><dc:source>The Astronomical Journal, vol 165, iss 4</dc:source><dc:coverage>144</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5c7729r0</identifier><datestamp>2026-09-15T20:36:40Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5c7729r0</dc:identifier><dc:title>UPC++ v1.0 Programmer’s Guide, Revision 2023.3.0</dc:title><dc:creator>Bachan, John</dc:creator><dc:creator>Baden, Scott B</dc:creator><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Corbino, Johnny</dc:creator><dc:creator>Grossman, Jonathan</dc:creator><dc:creator>Hargrove, Paul H</dc:creator><dc:creator>Hofmeyr, Steven</dc:creator><dc:creator>Jacquelin, Mathias</dc:creator><dc:creator>Kamil, Amir</dc:creator><dc:creator>Van Straalen, Brian</dc:creator><dc:creator>Waters, Daniel</dc:creator><dc:date>2023-03-30</dc:date><dc:description>UPC++ is a C++ library that supports Partitioned Global Address Space (PGAS) programming. It is designed for writing efficient, scalable parallel programs on distributed-memory parallel computers. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). The UPC++ control model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. The PGAS memory model additionally provides one-sided RMA communication to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ also features Remote Procedure Call (RPC) communication, making it easy to move computation to operate on data that resides on remote processes.

UPC++ was designed to support exascale high-performance computing, and the library interfaces and implementation are focused on maximizing scalability. In UPC++, all communication operations are syntactically explicit, which encourages programmers to consider the costs associated with communication and data movement. Moreover, all communication operations are asynchronous by default, encouraging programmers to seek opportunities for overlapping communication latencies with other useful work. UPC++ provides expressive and composable abstractions designed for efficiently managing aggressive use of asynchrony in programs. Together, these design principles are intended to enable programmers to write applications using UPC++ that perform well even on hundreds of thousands of cores.</dc:description><dc:subject>Exascale Computing</dc:subject><dc:subject>GASNet</dc:subject><dc:subject>Library Programmer's Guide</dc:subject><dc:subject>parallel distributed programming</dc:subject><dc:subject>PGAS</dc:subject><dc:subject>scientific computing</dc:subject><dc:subject>UPC++</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5c7729r0</dc:identifier><dc:identifier>https://escholarship.org/content/qt5c7729r0/qt5c7729r0.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S43591</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8g68q0w0</identifier><datestamp>2026-09-15T20:36:33Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8g68q0w0</dc:identifier><dc:title>Bedroom Concentrations and Emissions of Volatile Organic Compounds during Sleep</dc:title><dc:creator>Molinier, Betty</dc:creator><dc:creator>Arata, Caleb</dc:creator><dc:creator>Katz, Erin F</dc:creator><dc:creator>Lunderberg, David M</dc:creator><dc:creator>Ofodile, Jennifer</dc:creator><dc:creator>Singer, Brett C</dc:creator><dc:creator>Nazaroff, William W</dc:creator><dc:creator>Goldstein, Allen H</dc:creator><dc:date>2024-05-07</dc:date><dc:description>Because humans spend about one-third of their time asleep in their bedrooms and are themselves emission sources of volatile organic compounds (VOCs), it is important to specifically characterize the composition of the bedroom air that they experience during sleep. This work uses real-time indoor and outdoor measurements of volatile organic compounds (VOCs) to examine concentration enhancements in bedroom air during sleep and to calculate VOC emission rates associated with sleeping occupants. Gaseous VOCs were measured with proton-transfer reaction time-of-flight mass spectrometry during a multiweek residential monitoring campaign under normal occupancy conditions. Results indicate high emissions of nearly 100 VOCs and other species in the bedroom during sleeping periods as compared to the levels in other rooms of the same residence. Air change rates for the bedroom and, correspondingly, emission rates of sleeping-associated VOCs were determined for two bounding conditions: (1) air exchange between the bedroom and outdoors only and (2) air exchange between the bedroom and other indoor spaces only (as represented by measurements in the kitchen). VOCs from skin oil oxidation and personal care products were present, revealing that many emission pathways can be important occupant-associated emission factors affecting bedroom air composition in addition to direct emissions from building materials and furnishings.</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>3701 Atmospheric Sciences (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>4105 Pollution and Contamination (for-2020)</dc:subject><dc:subject>Health Effects of Indoor Air Pollution (rcdc)</dc:subject><dc:subject>Sleep Research (rcdc)</dc:subject><dc:subject>Volatile Organic Compounds (mesh)</dc:subject><dc:subject>Air Pollution</dc:subject><dc:subject>Indoor (mesh)</dc:subject><dc:subject>Sleep (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Environmental Monitoring (mesh)</dc:subject><dc:subject>Housing (mesh)</dc:subject><dc:subject>Air Pollutants (mesh)</dc:subject><dc:subject>indoor air</dc:subject><dc:subject>VOC composition</dc:subject><dc:subject>residentialmicroenvironments</dc:subject><dc:subject>CO2</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Air Pollutants (mesh)</dc:subject><dc:subject>Sleep (mesh)</dc:subject><dc:subject>Housing (mesh)</dc:subject><dc:subject>Air Pollution</dc:subject><dc:subject>Indoor (mesh)</dc:subject><dc:subject>Environmental Monitoring (mesh)</dc:subject><dc:subject>Volatile Organic Compounds (mesh)</dc:subject><dc:subject>CO2</dc:subject><dc:subject>VOC composition</dc:subject><dc:subject>indoor air</dc:subject><dc:subject>residential microenvironments</dc:subject><dc:subject>Volatile Organic Compounds (mesh)</dc:subject><dc:subject>Air Pollution</dc:subject><dc:subject>Indoor (mesh)</dc:subject><dc:subject>Sleep (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Environmental Monitoring (mesh)</dc:subject><dc:subject>Housing (mesh)</dc:subject><dc:subject>Air Pollutants (mesh)</dc:subject><dc:subject>Environmental Sciences (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8g68q0w0</dc:identifier><dc:identifier>https://escholarship.org/content/qt8g68q0w0/qt8g68q0w0.pdf</dc:identifier><dc:identifier>info:doi/10.1021/acs.est.3c10841</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Science and Technology, vol 58, iss 18</dc:source><dc:coverage>7958 - 7967</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt66b3m2rd</identifier><datestamp>2026-09-15T20:35:38Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt66b3m2rd</dc:identifier><dc:title>Applied Metrology for the Assembly of the Nb3Sn MQXFA Quadrupole Magnets for the HL-LHC AUP</dc:title><dc:creator>Ray, Katherine L</dc:creator><dc:creator>Ambrosio, Giorgio</dc:creator><dc:creator>Cheng, Daniel W</dc:creator><dc:creator>Ferracin, Paolo</dc:creator><dc:creator>Prestemon, Soren</dc:creator><dc:creator>Solis, Michael J</dc:creator><dc:date>2023-08-01</dc:date><dc:description>The US HL-LHC Accelerator Upgrade Project (AUP) is building Nb3Sn quadrupole magnets, called MQXFA, with plans to install 16 of them in the HL-LHC Interaction Regions. Variability in coil size must be dealt with at the assembly level, which requires timely and repeatable measurement of each coil. In this paper we will present the methodology used for coil measurements and the geometrical size data for the coils that have been measured thus far. We will also show the coil measurements of 8 coils before and after cold test. The Leica AT960-MR laser tracker with Spatial Analyzer software acquired to achieve these measurements has been used elsewhere in the project to great effect.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>Accelerator magnets</dc:subject><dc:subject>geometrical measurements</dc:subject><dc:subject>high luminosity LHC</dc:subject><dc:subject>metrology</dc:subject><dc:subject>Nb3Sn magnets</dc:subject><dc:subject>ATAP-2023 (c-lbnl-label)</dc:subject><dc:subject>ATAP-SMP (c-lbnl-label)</dc:subject><dc:subject>ATAP-GENERAL (c-lbnl-label)</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>4008 Electrical engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-SA</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/66b3m2rd</dc:identifier><dc:identifier>https://escholarship.org/content/qt66b3m2rd/qt66b3m2rd.pdf</dc:identifier><dc:identifier>info:doi/10.1109/tasc.2023.3243876</dc:identifier><dc:type>article</dc:type><dc:source>IEEE Transactions on Applied Superconductivity, vol 33, iss 5</dc:source><dc:coverage>1 - 6</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2h77g82w</identifier><datestamp>2026-09-15T20:32:27Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2h77g82w</dc:identifier><dc:title>Relationship of Estimated GFR and Albuminuria to Concurrent Laboratory Abnormalities: An Individual Participant Data Meta-analysis in a Global Consortium</dc:title><dc:creator>Inker, Lesley A</dc:creator><dc:creator>Grams, Morgan E</dc:creator><dc:creator>Levey, Andrew S</dc:creator><dc:creator>Coresh, Josef</dc:creator><dc:creator>Cirillo, Massimo</dc:creator><dc:creator>Collins, John F</dc:creator><dc:creator>Gansevoort, Ron T</dc:creator><dc:creator>Gutierrez, Orlando M</dc:creator><dc:creator>Hamano, Takayuki</dc:creator><dc:creator>Heine, Gunnar H</dc:creator><dc:creator>Ishikawa, Shizukiyo</dc:creator><dc:creator>Jee, Sun Ha</dc:creator><dc:creator>Kronenberg, Florian</dc:creator><dc:creator>Landray, Martin J</dc:creator><dc:creator>Miura, Katsuyuki</dc:creator><dc:creator>Nadkarni, Girish N</dc:creator><dc:creator>Peralta, Carmen A</dc:creator><dc:creator>Rothenbacher, Dietrich</dc:creator><dc:creator>Schaeffner, Elke</dc:creator><dc:creator>Sedaghat, Sanaz</dc:creator><dc:creator>Shlipak, Michael G</dc:creator><dc:creator>Zhang, Luxia</dc:creator><dc:creator>van Zuilen, Arjan D</dc:creator><dc:creator>Hallan, Stein I</dc:creator><dc:creator>Kovesdy, Csaba P</dc:creator><dc:creator>Woodward, Mark</dc:creator><dc:creator>Levin, Adeera</dc:creator><dc:creator>Astor, Brad</dc:creator><dc:creator>Appel, Larry</dc:creator><dc:creator>Greene, Tom</dc:creator><dc:creator>Chen, Teresa</dc:creator><dc:creator>Chalmers, John</dc:creator><dc:creator>Woodward, Mark</dc:creator><dc:creator>Arima, Hisatomi</dc:creator><dc:creator>Perkovic, Vlado</dc:creator><dc:creator>Yatsuya, Hiroshi</dc:creator><dc:creator>Tamakoshi, Koji</dc:creator><dc:creator>Li, Yuanying</dc:creator><dc:creator>Hirakawa, Yoshihisa</dc:creator><dc:creator>Coresh, Josef</dc:creator><dc:creator>Matsushita, Kunihiro</dc:creator><dc:creator>Grams, Morgan</dc:creator><dc:creator>Sang, Yingying</dc:creator><dc:creator>Polkinghorne, Kevan</dc:creator><dc:creator>Chadban, Steven</dc:creator><dc:creator>Atkins, Robert</dc:creator><dc:creator>Levin, Adeera</dc:creator><dc:creator>Djurdjev, Ognjenka</dc:creator><dc:creator>Zhang, Luxia</dc:creator><dc:creator>Liu, Lisheng</dc:creator><dc:creator>Zhao, Minghui</dc:creator><dc:creator>Wang, Fang</dc:creator><dc:creator>Wang, Jinwei</dc:creator><dc:creator>Schaeffner, Elke</dc:creator><dc:creator>Ebert, Natalie</dc:creator><dc:creator>Martus, Peter</dc:creator><dc:creator>Levin, Adeera</dc:creator><dc:creator>Djurdjev, Ognjenka</dc:creator><dc:creator>Tang, Mila</dc:creator><dc:creator>Heine, Gunnar</dc:creator><dc:creator>Emrich, Insa</dc:creator><dc:creator>Seiler, Sarah</dc:creator><dc:creator>Zawada, Adam</dc:creator><dc:creator>Nally, Joseph</dc:creator><dc:creator>Navaneethan, Sankar</dc:creator><dc:creator>Schold, Jesse</dc:creator><dc:creator>Zhang, Luxia</dc:creator><dc:creator>Zhao, Minghui</dc:creator><dc:creator>Wang, Fang</dc:creator><dc:creator>Wang, Jinwei</dc:creator><dc:creator>Shlipak, Michael</dc:creator><dc:creator>Sarnak, Mark</dc:creator><dc:creator>Katz, Ronit</dc:creator><dc:creator>Hiramoto, Jade</dc:creator><dc:creator>Iso, Hiroyasu</dc:creator><dc:creator>Yamagishi, Kazumasa</dc:creator><dc:creator>Umesawa, Mitsumasa</dc:creator><dc:creator>Muraki, Isao</dc:creator><dc:creator>Fukagawa, Masafumi</dc:creator><dc:creator>Maruyama, Shoichi</dc:creator><dc:creator>Hamano, Takayuki</dc:creator><dc:creator>Hasegawa, Takeshi</dc:creator><dc:creator>Fujii, Naohiko</dc:creator><dc:creator>Wheeler, David</dc:creator><dc:creator>Emberson, John</dc:creator><dc:creator>Townend, John</dc:creator><dc:creator>Landray, Martin</dc:creator><dc:creator>Brenner, Hermann</dc:creator><dc:creator>Schöttker, Ben</dc:creator><dc:creator>Saum, Kai-Uwe</dc:creator><dc:creator>Rothenbacher, Dietrich</dc:creator><dc:creator>Fox, Caroline</dc:creator><dc:creator>Hwang, Shih-Jen</dc:creator><dc:creator>Köttgen, Anna</dc:creator><dc:creator>Kronenberg, Florian</dc:creator><dc:creator>Schneider, Markus P</dc:creator><dc:creator>Eckardt, Kai-Uwe</dc:creator><dc:creator>Green, Jamie</dc:creator><dc:creator>Kirchner, H Lester</dc:creator><dc:creator>Chang, Alex R</dc:creator><dc:date>2019-02-01</dc:date><dc:description>RATIONALE &amp;amp; OBJECTIVE: Chronic kidney disease (CKD) is complicated by abnormalities that reflect disruption in filtration, tubular, and endocrine functions of the kidney. Our aim was to explore the relationship of specific laboratory result abnormalities and hypertension with the estimated glomerular filtration rate (eGFR) and albuminuria CKD staging framework.
STUDY DESIGN: Cross-sectional individual participant-level analyses in a global consortium.
SETTING &amp;amp; STUDY POPULATIONS: 17 CKD and 38 general population and high-risk cohorts.
SELECTION CRITERIA FOR STUDIES: Cohorts in the CKD Prognosis Consortium with data for eGFR and albuminuria, as well as a measurement of hemoglobin, bicarbonate, phosphorus, parathyroid hormone, potassium, or calcium, or hypertension.
DATA EXTRACTION: Data were obtained and analyzed between July 2015 and January&amp;nbsp;2018.
ANALYTICAL APPROACH: We modeled the association of eGFR and albuminuria with hemoglobin, bicarbonate, phosphorus, parathyroid hormone, potassium, and calcium values using linear regression and with hypertension and categorical definitions of each abnormality using logistic regression. Results were pooled using random-effects meta-analyses.
RESULTS: The CKD cohorts (n=254,666 participants) were 27% women and 10% black, with a mean age of 69 (SD, 12) years. The general population/high-risk cohorts (n=1,758,334) were 50% women and 2% black, with a mean age of 50 (16) years. There was a strong graded association between lower eGFR and all laboratory result abnormalities (ORs ranging from 3.27 [95% CI, 2.68-3.97] to 8.91 [95% CI, 7.22-10.99] comparing eGFRs of 15 to 29 with eGFRs of 45 to 59mL/min/1.73m2), whereas albuminuria had equivocal or weak associations with abnormalities (ORs ranging from 0.77 [95% CI, 0.60-0.99] to 1.92 [95% CI, 1.65-2.24] comparing urinary albumin-creatinine ratio &amp;gt; 300 vs&amp;nbsp;&amp;lt; 30mg/g).
LIMITATIONS: Variations in study era, health care delivery system, typical diet, and laboratory assays.
CONCLUSIONS: Lower eGFR was strongly associated with higher odds of multiple laboratory result abnormalities. Knowledge of risk associations might help guide management in the heterogeneous group of patients with CKD.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>Hypertension (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Kidney Disease (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Renal and urogenital (hrcs-hc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Albuminuria (mesh)</dc:subject><dc:subject>Blood Chemical Analysis (mesh)</dc:subject><dc:subject>Creatinine (mesh)</dc:subject><dc:subject>Cross-Sectional Studies (mesh)</dc:subject><dc:subject>Disease Progression (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Global Health (mesh)</dc:subject><dc:subject>Glomerular Filtration Rate (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Hypertension</dc:subject><dc:subject>Renal (mesh)</dc:subject><dc:subject>Internationality (mesh)</dc:subject><dc:subject>Kidney Function Tests (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Predictive Value of Tests (mesh)</dc:subject><dc:subject>Renal Insufficiency</dc:subject><dc:subject>Chronic (mesh)</dc:subject><dc:subject>Retrospective Studies (mesh)</dc:subject><dc:subject>Sensitivity and Specificity (mesh)</dc:subject><dc:subject>Severity of Illness Index (mesh)</dc:subject><dc:subject>Urinalysis (mesh)</dc:subject><dc:subject>CKD Prognosis Consortium</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Hypertension</dc:subject><dc:subject>Renal (mesh)</dc:subject><dc:subject>Albuminuria (mesh)</dc:subject><dc:subject>Disease Progression (mesh)</dc:subject><dc:subject>Creatinine (mesh)</dc:subject><dc:subject>Kidney Function Tests (mesh)</dc:subject><dc:subject>Glomerular Filtration Rate (mesh)</dc:subject><dc:subject>Urinalysis (mesh)</dc:subject><dc:subject>Blood Chemical Analysis (mesh)</dc:subject><dc:subject>Severity of Illness Index (mesh)</dc:subject><dc:subject>Sensitivity and Specificity (mesh)</dc:subject><dc:subject>Retrospective Studies (mesh)</dc:subject><dc:subject>Cross-Sectional Studies (mesh)</dc:subject><dc:subject>Predictive Value of Tests (mesh)</dc:subject><dc:subject>Internationality (mesh)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Renal Insufficiency</dc:subject><dc:subject>Chronic (mesh)</dc:subject><dc:subject>Global Health (mesh)</dc:subject><dc:subject>CKD Prognosis Consortium</dc:subject><dc:subject>CKD stage</dc:subject><dc:subject>Chronic kidney disease (CKD)</dc:subject><dc:subject>albuminuria</dc:subject><dc:subject>anemia</dc:subject><dc:subject>diabetes</dc:subject><dc:subject>glomerular filtration rate (GFR)</dc:subject><dc:subject>hematocrit</dc:subject><dc:subject>hemoglobin</dc:subject><dc:subject>hyperparathyroidism</dc:subject><dc:subject>hypertension</dc:subject><dc:subject>individual-level meta-analysis</dc:subject><dc:subject>kidney function</dc:subject><dc:subject>laboratory abnormality</dc:subject><dc:subject>laboratory tests</dc:subject><dc:subject>meta-analysis</dc:subject><dc:subject>serum bicarbonate</dc:subject><dc:subject>serum calcium</dc:subject><dc:subject>serum intact parathyroid hormone</dc:subject><dc:subject>serum phosphorus</dc:subject><dc:subject>serum potassium</dc:subject><dc:subject>staging system</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Albuminuria (mesh)</dc:subject><dc:subject>Blood Chemical Analysis (mesh)</dc:subject><dc:subject>Creatinine (mesh)</dc:subject><dc:subject>Cross-Sectional Studies (mesh)</dc:subject><dc:subject>Disease Progression (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Global Health (mesh)</dc:subject><dc:subject>Glomerular Filtration Rate (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Hypertension</dc:subject><dc:subject>Renal (mesh)</dc:subject><dc:subject>Internationality (mesh)</dc:subject><dc:subject>Kidney Function Tests (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Predictive Value of Tests (mesh)</dc:subject><dc:subject>Renal Insufficiency</dc:subject><dc:subject>Chronic (mesh)</dc:subject><dc:subject>Retrospective Studies (mesh)</dc:subject><dc:subject>Sensitivity and Specificity (mesh)</dc:subject><dc:subject>Severity of Illness Index (mesh)</dc:subject><dc:subject>Urinalysis (mesh)</dc:subject><dc:subject>1103 Clinical Sciences (for)</dc:subject><dc:subject>1117 Public Health and Health Services (for)</dc:subject><dc:subject>Urology &amp; Nephrology (science-metrix)</dc:subject><dc:subject>3202 Clinical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2h77g82w</dc:identifier><dc:identifier>https://escholarship.org/content/qt2h77g82w/qt2h77g82w.pdf</dc:identifier><dc:identifier>info:doi/10.1053/j.ajkd.2018.08.013</dc:identifier><dc:type>article</dc:type><dc:source>American Journal of Kidney Diseases, vol 73, iss 2</dc:source><dc:coverage>206 - 217</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9dr9395k</identifier><datestamp>2026-09-15T20:31:59Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9dr9395k</dc:identifier><dc:title>Birth Outcomes in Relation to Prenatal Exposure to Per- and Polyfluoroalkyl Substances and Stress in the Environmental Influences on Child Health Outcomes (ECHO) Program</dc:title><dc:creator>Padula, Amy M</dc:creator><dc:creator>Ning, Xuejuan</dc:creator><dc:creator>Bakre, Shivani</dc:creator><dc:creator>Barrett, Emily S</dc:creator><dc:creator>Bastain, Tracy</dc:creator><dc:creator>Bennett, Deborah H</dc:creator><dc:creator>Bloom, Michael S</dc:creator><dc:creator>Breton, Carrie V</dc:creator><dc:creator>Dunlop, Anne L</dc:creator><dc:creator>Eick, Stephanie M</dc:creator><dc:creator>Ferrara, Assiamira</dc:creator><dc:creator>Fleisch, Abby</dc:creator><dc:creator>Geiger, Sarah</dc:creator><dc:creator>Goin, Dana E</dc:creator><dc:creator>Kannan, Kurunthachalam</dc:creator><dc:creator>Karagas, Margaret R</dc:creator><dc:creator>Korrick, Susan</dc:creator><dc:creator>Meeker, John D</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>O’Connor, Thomas G</dc:creator><dc:creator>Oken, Emily</dc:creator><dc:creator>Robinson, Morgan</dc:creator><dc:creator>Romano, Megan E</dc:creator><dc:creator>Schantz, Susan L</dc:creator><dc:creator>Schmidt, Rebecca J</dc:creator><dc:creator>Starling, Anne P</dc:creator><dc:creator>Zhu, Yeyi</dc:creator><dc:creator>Hamra, Ghassan B</dc:creator><dc:creator>Woodruff, Tracey J</dc:creator><dc:creator>Outcomes, the program collaborators for Environmental influences on Child Health</dc:creator><dc:date>2023-03-01</dc:date><dc:description>BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are persistent and ubiquitous chemicals associated with risk of adverse birth outcomes. Results of previous studies have been inconsistent. Associations between PFAS and birth outcomes may be affected by psychosocial stress.
OBJECTIVES: We estimated risk of adverse birth outcomes in relation to prenatal PFAS concentrations and evaluate whether maternal stress modifies those relationships.
METHODS: We included 3,339 participants from 11 prospective prenatal cohorts in the Environmental influences on the Child Health Outcomes (ECHO) program to estimate the associations of five PFAS and birth outcomes. We stratified by perceived stress scale scores to examine effect modification and used Bayesian Weighted Sums to estimate mixtures of PFAS.
RESULTS: We observed reduced birth size with increased concentrations of all PFAS. For a 1-unit higher log-normalized exposure to perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), perfluorononanoic acid (PFNA), and perfluorohexane sulfonic acid (PFHxS), we observed lower birthweight-for-gestational-age z-scores of  [95% confidence interval (CI): , ],  (95% CI: , ),  (95% CI: , ),  (95% CI: , 0.06), and  (95% CI: , ), respectively. We observed a lower odds ratio (OR) for large-for-gestational-age:  (95% CI: 0.38, 0.83),  (95% CI: 0.35, 0.77). For a 1-unit increase in log-normalized concentration of summed PFAS, we observed a lower birthweight-for-gestational-age z-score [; 95% highest posterior density (HPD): , ] and decreased odds of large-for-gestational-age (; 95% HPD: 0.29, 0.82). Perfluorodecanoic acid (PFDA) explained the highest percentage (40%) of the summed effect in both models. Associations were not modified by maternal perceived stress.
DISCUSSION: Our large, multi-cohort study of PFAS and adverse birth outcomes found a negative association between prenatal PFAS and birthweight-for-gestational-age, and the associations were not different in groups with high vs. low perceived stress. This study can help inform policy to reduce exposures in the environment and humans. https://doi.org/10.1289/EHP10723.</dc:description><dc:subject>4204 Midwifery (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Endocrine Disruptors (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Conditions Affecting the Embryonic and Fetal Periods (rcdc)</dc:subject><dc:subject>Perinatal Period - Conditions Originating in Perinatal Period (rcdc)</dc:subject><dc:subject>Mental Health (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>2.2 Factors relating to the physical environment (hrcs-rac)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Prenatal Exposure Delayed Effects (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Birth Weight (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>Bayes Theorem (mesh)</dc:subject><dc:subject>Fluorocarbons (mesh)</dc:subject><dc:subject>Alkanesulfonic Acids (mesh)</dc:subject><dc:subject>Outcome Assessment</dc:subject><dc:subject>Health Care (mesh)</dc:subject><dc:subject>Fatty Acids (mesh)</dc:subject><dc:subject>Decanoic Acids (mesh)</dc:subject><dc:subject>program collaborators for Environmental influences on Child Health Outcomes</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Prenatal Exposure Delayed Effects (mesh)</dc:subject><dc:subject>Birth Weight (mesh)</dc:subject><dc:subject>Alkanesulfonic Acids (mesh)</dc:subject><dc:subject>Fluorocarbons (mesh)</dc:subject><dc:subject>Fatty Acids (mesh)</dc:subject><dc:subject>Decanoic Acids (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Bayes Theorem (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Outcome Assessment</dc:subject><dc:subject>Health Care (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Prenatal Exposure Delayed Effects (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Birth Weight (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>Bayes Theorem (mesh)</dc:subject><dc:subject>Fluorocarbons (mesh)</dc:subject><dc:subject>Alkanesulfonic Acids (mesh)</dc:subject><dc:subject>Outcome Assessment</dc:subject><dc:subject>Health Care (mesh)</dc:subject><dc:subject>Fatty Acids (mesh)</dc:subject><dc:subject>Decanoic Acids (mesh)</dc:subject><dc:subject>05 Environmental Sciences (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>Toxicology (science-metrix)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:subject>41 Environmental sciences (for-2020)</dc:subject><dc:subject>42 Health sciences (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9dr9395k</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1289/ehp10723</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Health Perspectives, vol 131, iss 3</dc:source><dc:coverage>037006</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2207k15c</identifier><datestamp>2026-09-15T20:31:45Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2207k15c</dc:identifier><dc:title>Association of Mitochondrial DNA Copy Number With Brain MRI Markers and Cognitive Function</dc:title><dc:creator>Zhang, Yuankai</dc:creator><dc:creator>Liu, Xue</dc:creator><dc:creator>Wiggins, Kerri L</dc:creator><dc:creator>Kurniansyah, Nuzulul</dc:creator><dc:creator>Guo, Xiuqing</dc:creator><dc:creator>Rodrigue, Amanda L</dc:creator><dc:creator>Zhao, Wei</dc:creator><dc:creator>Yanek, Lisa R</dc:creator><dc:creator>Ratliff, Scott M</dc:creator><dc:creator>Pitsillides, Achilleas</dc:creator><dc:creator>Aguirre Patiño, Juan Sebastian</dc:creator><dc:creator>Sofer, Tamar</dc:creator><dc:creator>Arking, Dan E</dc:creator><dc:creator>Austin, Thomas R</dc:creator><dc:creator>Beiser, Alexa S</dc:creator><dc:creator>Blangero, John</dc:creator><dc:creator>Boerwinkle, Eric</dc:creator><dc:creator>Bressler, Jan</dc:creator><dc:creator>Curran, Joanne E</dc:creator><dc:creator>Hou, Lifang</dc:creator><dc:creator>Hughes, Timothy M</dc:creator><dc:creator>Kardia, Sharon LR</dc:creator><dc:creator>Launer, Lenore J</dc:creator><dc:creator>Levy, Daniel</dc:creator><dc:creator>Mosley, Thomas H</dc:creator><dc:creator>Nasrallah, Ilya M</dc:creator><dc:creator>Rich, Stephen S</dc:creator><dc:creator>Rotter, Jerome I</dc:creator><dc:creator>Seshadri, Sudha</dc:creator><dc:creator>Tarraf, Wassim</dc:creator><dc:creator>González, Kevin A</dc:creator><dc:creator>Ramachandran, Vasan</dc:creator><dc:creator>Yaffe, Kristine</dc:creator><dc:creator>Nyquist, Paul A</dc:creator><dc:creator>Psaty, Bruce M</dc:creator><dc:creator>DeCarli, Charles S</dc:creator><dc:creator>Smith, Jennifer A</dc:creator><dc:creator>Glahn, David C</dc:creator><dc:creator>González, Hector M</dc:creator><dc:creator>Bis, Joshua C</dc:creator><dc:creator>Fornage, Myriam</dc:creator><dc:creator>Heckbert, Susan R</dc:creator><dc:creator>Fitzpatrick, Annette L</dc:creator><dc:creator>Liu, Chunyu</dc:creator><dc:creator>Satizabal, Claudia L</dc:creator><dc:creator>Aguilera, Norma</dc:creator><dc:creator>Ament, Seth</dc:creator><dc:creator>Ammous, Farah</dc:creator><dc:creator>Arnett, Donna K</dc:creator><dc:creator>Becker, Diane</dc:creator><dc:creator>Bis, Joshua</dc:creator><dc:creator>Blue, Elizabeth</dc:creator><dc:creator>Boerwinkle, Eric</dc:creator><dc:creator>Breaux, Camille</dc:creator><dc:creator>Bressler, Jan</dc:creator><dc:creator>Chaar, Dima</dc:creator><dc:creator>MHI</dc:creator><dc:creator>Clarkson-Townsend, Danielle</dc:creator><dc:creator>Cooper, Brigidann</dc:creator><dc:creator>Coresh, Josef</dc:creator><dc:creator>Correa, Adolfo</dc:creator><dc:creator>DeStefano, Anita</dc:creator><dc:creator>Ding, Jingzhong</dc:creator><dc:creator>Fardo, David</dc:creator><dc:creator>Fitzpatrick, Annette</dc:creator><dc:creator>Fornage, Myriam</dc:creator><dc:creator>French, Jennifer</dc:creator><dc:creator>Glahn, David</dc:creator><dc:creator>Gonzalez, Hector</dc:creator><dc:creator>Granot-Hershkovitz, Einat</dc:creator><dc:creator>Hanly, Patrick</dc:creator><dc:creator>Hayden, Kathleen</dc:creator><dc:creator>Heckbert, Susan</dc:creator><dc:creator>Heemann, Scott</dc:creator><dc:creator>Horvath, Steve</dc:creator><dc:creator>Hoth, Karin</dc:creator><dc:creator>Hughes, Timothy</dc:creator><dc:creator>Jaiswal, Sidd</dc:creator><dc:creator>Jian, Xueqiu</dc:creator><dc:creator>Katsumata, Yuriko</dc:creator><dc:creator>Kho, Minjung</dc:creator><dc:creator>Kooperberg, Charles</dc:creator><dc:creator>Launer, Lenore</dc:creator><dc:creator>Lin, Honghuang</dc:creator><dc:creator>Litkowski, Elizabeth</dc:creator><dc:creator>Longstreth, Will</dc:creator><dc:creator>Martin, Alexandra</dc:creator><dc:creator>Mayeux, Richard</dc:creator><dc:creator>Mikulla, Julie</dc:creator><dc:creator>Miller, Amy</dc:creator><dc:creator>Misra, Biswapriya</dc:creator><dc:creator>Mosley, Thomas</dc:creator><dc:creator>Nyquist, Paul</dc:creator><dc:creator>O'Connell, Jeff</dc:creator><dc:creator>Olivier, Michael</dc:creator><dc:creator>Peloso, Gina</dc:creator><dc:creator>Perry, James</dc:creator><dc:creator>Psaty, Bruce</dc:creator><dc:creator>Purcell, Shaun</dc:creator><dc:creator>Raffield, Laura</dc:creator><dc:date>2023-05-02</dc:date><dc:description>BACKGROUND AND OBJECTIVES: Previous studies suggest that lower mitochondrial DNA (mtDNA) copy number (CN) is associated with neurodegenerative diseases. However, whether mtDNA CN in whole blood is related to endophenotypes of Alzheimer disease (AD) and AD-related dementia (AD/ADRD) needs further investigation. We assessed the association of mtDNA CN with cognitive function and MRI measures in community-based samples of middle-aged to older adults.
METHODS: We included dementia-free participants from 9 diverse community-based cohorts with whole-genome sequencing in the Trans-Omics for Precision Medicine (TOPMed) program. Circulating mtDNA CN was estimated as twice the ratio of the average coverage of mtDNA to nuclear DNA. Brain MRI markers included total brain, hippocampal, and white matter hyperintensity volumes. General cognitive function was derived from distinct cognitive domains. We performed cohort-specific association analyses of mtDNA CN with AD/ADRD endophenotypes assessed within ±5 years (i.e., cross-sectional analyses) or 5-20 years after blood draw (i.e., prospective analyses) adjusting for potential confounders. We further explored associations stratified by sex and age (&amp;lt;60 vs ≥60 years). Fixed-effects or sample size-weighted meta-analyses were performed to combine results. Finally, we performed mendelian randomization (MR) analyses to assess causality.
RESULTS: We included up to 19,152 participants (mean age 59 years, 57% women). Higher mtDNA CN was cross-sectionally associated with better general cognitive function (β = 0.04; 95% CI 0.02-0.06) independent of age, sex, batch effects, race/ethnicity, time between blood draw and cognitive evaluation, cohort-specific variables, and education. Additional adjustment for blood cell counts or cardiometabolic traits led to slightly attenuated results. We observed similar significant associations with cognition in prospective analyses, although of reduced magnitude. We found no significant associations between mtDNA CN and brain MRI measures in meta-analyses. MR analyses did not reveal a causal relation between mtDNA CN in blood and cognition.
DISCUSSION: Higher mtDNA CN in blood is associated with better current and future general cognitive function in large and diverse communities across the United States. Although MR analyses did not support a causal role, additional research is needed to assess causality. Circulating mtDNA CN could serve nevertheless as a biomarker of current and future cognitive function in the community.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Dementia (rcdc)</dc:subject><dc:subject>Basic Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Alzheimer's Disease (rcdc)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>Acquired Cognitive Impairment (rcdc)</dc:subject><dc:subject>Neurodegenerative (rcdc)</dc:subject><dc:subject>Alzheimer's Disease Related Dementias (ADRD) (rcdc)</dc:subject><dc:subject>Aging (rcdc)</dc:subject><dc:subject>Precision Medicine (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Brain Disorders (rcdc)</dc:subject><dc:subject>Minority Health (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Biomedical Imaging (rcdc)</dc:subject><dc:subject>Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) (rcdc)</dc:subject><dc:subject>4.1 Discovery and preclinical testing of markers and technologies (hrcs-rac)</dc:subject><dc:subject>2.1 Biological and endogenous factors (hrcs-rac)</dc:subject><dc:subject>Mental health (hrcs-hc)</dc:subject><dc:subject>Neurological (hrcs-hc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>DNA</dc:subject><dc:subject>Mitochondrial (mesh)</dc:subject><dc:subject>DNA Copy Number Variations (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>Cross-Sectional Studies (mesh)</dc:subject><dc:subject>Alzheimer Disease (mesh)</dc:subject><dc:subject>Magnetic Resonance Imaging (mesh)</dc:subject><dc:subject>Cognition (mesh)</dc:subject><dc:subject>Brain (mesh)</dc:subject><dc:subject>NHLBI Trans-Omics for Precision Medicine (TOPMed) program</dc:subject><dc:subject>Mitochondrial and Neurocognitive Working Groups</dc:subject><dc:subject>Brain (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Alzheimer Disease (mesh)</dc:subject><dc:subject>DNA</dc:subject><dc:subject>Mitochondrial (mesh)</dc:subject><dc:subject>Magnetic Resonance Imaging (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>Cross-Sectional Studies (mesh)</dc:subject><dc:subject>Cognition (mesh)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>DNA Copy Number Variations (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>DNA</dc:subject><dc:subject>Mitochondrial (mesh)</dc:subject><dc:subject>DNA Copy Number Variations (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>Cross-Sectional Studies (mesh)</dc:subject><dc:subject>Alzheimer Disease (mesh)</dc:subject><dc:subject>Magnetic Resonance Imaging (mesh)</dc:subject><dc:subject>Cognition (mesh)</dc:subject><dc:subject>Brain (mesh)</dc:subject><dc:subject>1103 Clinical Sciences (for)</dc:subject><dc:subject>1109 Neurosciences (for)</dc:subject><dc:subject>1702 Cognitive Sciences (for)</dc:subject><dc:subject>Neurology &amp; Neurosurgery (science-metrix)</dc:subject><dc:subject>3202 Clinical sciences (for-2020)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2207k15c</dc:identifier><dc:identifier>https://escholarship.org/content/qt2207k15c/qt2207k15c.pdf</dc:identifier><dc:identifier>info:doi/10.1212/wnl.0000000000207157</dc:identifier><dc:type>article</dc:type><dc:source>Neurology, vol 100, iss 18</dc:source><dc:coverage>e1930 - e1943</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1xj6b0n5</identifier><datestamp>2026-09-15T20:31:35Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1xj6b0n5</dc:identifier><dc:title>K*0 production in Au+Au collisions at sNN=7.7, 11.5, 14.5, 19.6, 27, and 39 GeV from the RHIC beam energy scan</dc:title><dc:creator>Abdallah, MS</dc:creator><dc:creator>Aboona, BE</dc:creator><dc:creator>Adam, J</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, JR</dc:creator><dc:creator>Adkins, JK</dc:creator><dc:creator>Aggarwal, I</dc:creator><dc:creator>Aggarwal, MM</dc:creator><dc:creator>Ahammed, Z</dc:creator><dc:creator>Anderson, DM</dc:creator><dc:creator>Aschenauer, EC</dc:creator><dc:creator>Atchison, J</dc:creator><dc:creator>Bairathi, V</dc:creator><dc:creator>Baker, W</dc:creator><dc:creator>Ball, JG</dc:creator><dc:creator>Barish, K</dc:creator><dc:creator>Bellwied, R</dc:creator><dc:creator>Bhagat, P</dc:creator><dc:creator>Bhasin, A</dc:creator><dc:creator>Bhatta, S</dc:creator><dc:creator>Bielcik, J</dc:creator><dc:creator>Bielcikova, J</dc:creator><dc:creator>Brandenburg, JD</dc:creator><dc:creator>Cai, XZ</dc:creator><dc:creator>Caines, H</dc:creator><dc:creator>de la Barca Sánchez, M Calderón</dc:creator><dc:creator>Cebra, D</dc:creator><dc:creator>Chakaberia, I</dc:creator><dc:creator>Chaloupka, P</dc:creator><dc:creator>Chan, BK</dc:creator><dc:creator>Chang, Z</dc:creator><dc:creator>Chatterjee, A</dc:creator><dc:creator>Chen, D</dc:creator><dc:creator>Chen, J</dc:creator><dc:creator>Chen, JH</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Chen, Z</dc:creator><dc:creator>Cheng, J</dc:creator><dc:creator>Cheng, Y</dc:creator><dc:creator>Choudhury, S</dc:creator><dc:creator>Christie, W</dc:creator><dc:creator>Chu, X</dc:creator><dc:creator>Crawford, HJ</dc:creator><dc:creator>Csanád, M</dc:creator><dc:creator>Dale-Gau, G</dc:creator><dc:creator>Daugherity, M</dc:creator><dc:creator>Deppner, IM</dc:creator><dc:creator>Dhamija, A</dc:creator><dc:creator>Di Carlo, L</dc:creator><dc:creator>Didenko, L</dc:creator><dc:creator>Dixit, P</dc:creator><dc:creator>Dong, X</dc:creator><dc:creator>Drachenberg, JL</dc:creator><dc:creator>Duckworth, E</dc:creator><dc:creator>Dunlop, JC</dc:creator><dc:creator>Engelage, J</dc:creator><dc:creator>Eppley, G</dc:creator><dc:creator>Esumi, S</dc:creator><dc:creator>Evdokimov, O</dc:creator><dc:creator>Ewigleben, A</dc:creator><dc:creator>Eyser, O</dc:creator><dc:creator>Fatemi, R</dc:creator><dc:creator>Fawzi, FM</dc:creator><dc:creator>Fazio, S</dc:creator><dc:creator>Feng, CJ</dc:creator><dc:creator>Feng, Y</dc:creator><dc:creator>Finch, E</dc:creator><dc:creator>Fisyak, Y</dc:creator><dc:creator>Fu, C</dc:creator><dc:creator>Gagliardi, CA</dc:creator><dc:creator>Galatyuk, T</dc:creator><dc:creator>Geurts, F</dc:creator><dc:creator>Ghimire, N</dc:creator><dc:creator>Gibson, A</dc:creator><dc:creator>Gopal, K</dc:creator><dc:creator>Gou, X</dc:creator><dc:creator>Grosnick, D</dc:creator><dc:creator>Gupta, A</dc:creator><dc:creator>Guryn, W</dc:creator><dc:creator>Hamed, A</dc:creator><dc:creator>Han, Y</dc:creator><dc:creator>Harabasz, S</dc:creator><dc:creator>Harasty, MD</dc:creator><dc:creator>Harris, JW</dc:creator><dc:creator>Harrison, H</dc:creator><dc:creator>He, S</dc:creator><dc:creator>He, W</dc:creator><dc:creator>He, XH</dc:creator><dc:creator>He, Y</dc:creator><dc:creator>Heppelmann, S</dc:creator><dc:creator>Herrmann, N</dc:creator><dc:creator>Hoffman, E</dc:creator><dc:creator>Holub, L</dc:creator><dc:creator>Hu, C</dc:creator><dc:creator>Hu, Q</dc:creator><dc:creator>Hu, Y</dc:creator><dc:creator>Huang, H</dc:creator><dc:creator>Huang, HZ</dc:creator><dc:creator>Huang, SL</dc:creator><dc:creator>Huang, T</dc:creator><dc:date>2023-03-01</dc:date><dc:description>We report the measurement of K*0 meson at midrapidity (|y|&amp;lt; 1.0) in Au+Au collisions at sNN=7.7, 11.5, 14.5, 19.6, 27, and 39 GeV collected by the STAR experiment during the Relativistic Heavy Ion Collider (RHIC) beam energy scan program. The transverse momentum spectra, yield, and average transverse momentum of K*0 are presented as functions of collision centrality and beam energy. The K*0/K yield ratios are presented for different collision centrality intervals and beam energies. The K*0/K ratio in heavy-ion collisions are observed to be smaller than that in small-system collisions (e+e and p+p). The K*0/K ratio follows a similar centrality dependence to that observed in previous RHIC and Large Hadron Collider measurements. The data favor the scenario of the dominance of hadronic rescattering over regeneration for K*0 production in the hadronic phase of the medium.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>NSD-Relativistic Nuclear Collisions (c-lbnl-label)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1xj6b0n5</dc:identifier><dc:identifier>https://escholarship.org/content/qt1xj6b0n5/qt1xj6b0n5.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevc.107.034907</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review C, vol 107, iss 3</dc:source><dc:coverage>034907</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2jp2w0zf</identifier><datestamp>2026-09-15T20:31:15Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2jp2w0zf</dc:identifier><dc:title>Status of the High Field Cable Test Facility at Fermilab</dc:title><dc:creator>Velev, GV</dc:creator><dc:creator>Arbelaez, D</dc:creator><dc:creator>Arcola, C</dc:creator><dc:creator>Bruce, R</dc:creator><dc:creator>Kashikhin, V</dc:creator><dc:creator>Koshelev, S</dc:creator><dc:creator>Makulski, A</dc:creator><dc:creator>Marinozzi, V</dc:creator><dc:creator>Nikolic, V</dc:creator><dc:creator>Orris, D</dc:creator><dc:creator>Prestemon, S</dc:creator><dc:creator>Sabbi, G</dc:creator><dc:creator>Tope, T</dc:creator><dc:creator>Yuan, X</dc:creator><dc:date>2023-08-01</dc:date><dc:description>Fermi National Accelerator Laboratory (FNAL) and Lawrence Berkeley National Laboratory (LBNL) are building a new High Field Vertical Magnet Test Facility (HFVMTF) for testing superconducting cables in high magnetic field. The background magnetic field of 15 T in the HFVMTF will be produced by a magnet provided by LBNL. The HFVMTF is jointly funded by the US DOE Offices of Science, High Energy Physics (HEP), and Fusion Energy Sciences (FES), and will serve as a superconducting cable test facility in high magnetic fields and a wide range of temperatures for HEP and FES communities. This facility will also be used to test high-field superconducting magnet models and demonstrators, including hybrid magnets, produced by the US Magnet Development Program (MDP). The paper describes the status of the facility, including construction, cryostat designs, top and lambda plates, and systems for powering, and quench protection and monitoring.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>Superconducting magnets</dc:subject><dc:subject>Helium</dc:subject><dc:subject>Heating systems</dc:subject><dc:subject>Valves</dc:subject><dc:subject>Test facilities</dc:subject><dc:subject>Magnetic shielding</dc:subject><dc:subject>Magnetic noise</dc:subject><dc:subject>High-temperature superconductors</dc:subject><dc:subject>super- conducting magnets</dc:subject><dc:subject>superconducting materials</dc:subject><dc:subject>test facilities</dc:subject><dc:subject>High-temperature superconductors</dc:subject><dc:subject>superconducting magnets</dc:subject><dc:subject>superconducting materials</dc:subject><dc:subject>test facilities</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>4008 Electrical engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2jp2w0zf</dc:identifier><dc:identifier>https://escholarship.org/content/qt2jp2w0zf/qt2jp2w0zf.pdf</dc:identifier><dc:identifier>info:doi/10.1109/tasc.2023.3242853</dc:identifier><dc:type>article</dc:type><dc:source>IEEE Transactions on Applied Superconductivity, vol 33, iss 5</dc:source><dc:coverage>1 - 6</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0778b8vd</identifier><datestamp>2026-09-15T20:28:07Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0778b8vd</dc:identifier><dc:title>Target Selection and Validation of DESI Quasars</dc:title><dc:creator>Chaussidon, Edmond</dc:creator><dc:creator>Yèche, Christophe</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Alexander, David M</dc:creator><dc:creator>Yang, Jinyi</dc:creator><dc:creator>Ahlen, Steven</dc:creator><dc:creator>Bailey, Stephen</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>Cai, Zheng</dc:creator><dc:creator>Chabanier, Solène</dc:creator><dc:creator>Davis, Tamara M</dc:creator><dc:creator>Dawson, Kyle</dc:creator><dc:creator>de laMacorra, Axel</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Eftekharzadeh, Sarah</dc:creator><dc:creator>Eisenstein, Daniel J</dc:creator><dc:creator>Fanning, Kevin</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>Gaztañaga, Enrique</dc:creator><dc:creator>Gontcho, Satya Gontcho A</dc:creator><dc:creator>Gonzalez-Morales, Alma X</dc:creator><dc:creator>Guy, Julien</dc:creator><dc:creator>Herrera-Alcantar, Hiram K</dc:creator><dc:creator>Honscheid, Klaus</dc:creator><dc:creator>Ishak, Mustapha</dc:creator><dc:creator>Jiang, Linhua</dc:creator><dc:creator>Juneau, Stephanie</dc:creator><dc:creator>Kehoe, Robert</dc:creator><dc:creator>Kisner, Theodore</dc:creator><dc:creator>Kovács, Andras</dc:creator><dc:creator>Kremin, Anthony</dc:creator><dc:creator>Lan, Ting-Wen</dc:creator><dc:creator>Landriau, Martin</dc:creator><dc:creator>Le Guillou, Laurent</dc:creator><dc:creator>Levi, Michael E</dc:creator><dc:creator>Magneville, Christophe</dc:creator><dc:creator>Martini, Paul</dc:creator><dc:creator>Meisner, Aaron M</dc:creator><dc:creator>Moustakas, John</dc:creator><dc:creator>Muñoz-Gutiérrez, Andrea</dc:creator><dc:creator>Myers, Adam D</dc:creator><dc:creator>Newman, Jeffrey A</dc:creator><dc:creator>Nie, Jundan</dc:creator><dc:creator>Percival, Will J</dc:creator><dc:creator>Poppett, Claire</dc:creator><dc:creator>Prada, Francisco</dc:creator><dc:creator>Raichoor, Anand</dc:creator><dc:creator>Ravoux, Corentin</dc:creator><dc:creator>Ross, Ashley J</dc:creator><dc:creator>Schlafly, Edward</dc:creator><dc:creator>Schlegel, David</dc:creator><dc:creator>Tan, Ting</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Zhou, Rongpu</dc:creator><dc:creator>Zhou, Zhimin</dc:creator><dc:creator>Zou, Hu</dc:creator><dc:date>2023-02-01</dc:date><dc:description>The Dark Energy Spectroscopic Instrument (DESI) survey will measure large-scale structures using quasars as direct tracers of dark matter in the redshift range 0.9 &amp;lt; z &amp;lt; 2.1 and using Lyα forests in quasar spectra at z &amp;gt; 2.1. We present several methods to select candidate quasars for DESI, using input photometric imaging in three optical bands (g, r, z) from the DESI Legacy Imaging Surveys and two infrared bands (W1, W2) from the Wide-field Infrared Survey Explorer. These methods were extensively tested during the Survey Validation of DESI. In this paper, we report on the results obtained with the different methods and present the selection we optimized for the DESI main survey. The final quasar target selection is based on a random forest algorithm and selects quasars in the magnitude range of 16.5 &amp;lt; r &amp;lt; 23. Visual selection of ultra-deep observations indicates that the main selection consists of 71% quasars, 16% galaxies, 6% stars, and 7% inconclusive spectra. Using the spectra based on this selection, we build an automated quasar catalog that achieves a fraction of true QSOs higher than 99% for a nominal effective exposure time of ∼1000 s. With a 310 deg−2 target density, the main selection allows DESI to select more than 200 deg−2 quasars (including 60 deg−2 quasars with z &amp;gt; 2.1), exceeding the project requirements by 20%. The redshift distribution of the selected quasars is in excellent agreement with quasar luminosity function predictions.</dc:description><dc:subject>5109 Space Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0306 Physical Chemistry (incl. Structural) (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0778b8vd</dc:identifier><dc:identifier>https://escholarship.org/content/qt0778b8vd/qt0778b8vd.pdf</dc:identifier><dc:identifier>info:doi/10.3847/1538-4357/acb3c2</dc:identifier><dc:type>article</dc:type><dc:source>The Astrophysical Journal, vol 944, iss 1</dc:source><dc:coverage>107</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2321d436</identifier><datestamp>2026-09-15T20:27:36Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2321d436</dc:identifier><dc:title>ClimateNet: an expert-labeled open dataset and deep learning architecture for enabling high-precision analyses of extreme weather</dc:title><dc:creator>Prabhat</dc:creator><dc:creator>Kashinath, Karthik</dc:creator><dc:creator>Mudigonda, Mayur</dc:creator><dc:creator>Kim, Sol</dc:creator><dc:creator>Kapp-Schwoerer, Lukas</dc:creator><dc:creator>Graubner, Andre</dc:creator><dc:creator>Karaismailoglu, Ege</dc:creator><dc:creator>von Kleist, Leo</dc:creator><dc:creator>Kurth, Thorsten</dc:creator><dc:creator>Greiner, Annette</dc:creator><dc:creator>Mahesh, Ankur</dc:creator><dc:creator>Yang, Kevin</dc:creator><dc:creator>Lewis, Colby</dc:creator><dc:creator>Chen, Jiayi</dc:creator><dc:creator>Lou, Andrew</dc:creator><dc:creator>Chandran, Sathyavat</dc:creator><dc:creator>Toms, Ben</dc:creator><dc:creator>Chapman, Will</dc:creator><dc:creator>Dagon, Katherine</dc:creator><dc:creator>Shields, Christine A</dc:creator><dc:creator>O'Brien, Travis</dc:creator><dc:creator>Wehner, Michael</dc:creator><dc:creator>Collins, William</dc:creator><dc:date>2021-01-08</dc:date><dc:description>Abstract. Identifying, detecting, and localizing extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Pattern recognition tasks such as classification, object detection, and segmentation (i.e., pixel-level classification) have remained challenging problems in the weather and climate sciences. While there exist many empirical heuristics for detecting extreme events, the disparities between the output of these different methods even for a single event are large and often difficult to reconcile. Given the success of deep learning (DL) in tackling similar problems in computer vision, we advocate a DL-based approach. DL, however, works best in the context of supervised learning – when labeled datasets are readily available. Reliable labeled training data for extreme weather and climate events is scarce. We create “ClimateNet” – an open, community-sourced human-expert-labeled curated dataset that captures tropical cyclones (TCs) and atmospheric rivers (ARs) in high-resolution climate model output from a simulation of a recent historical period. We use the curated ClimateNet dataset to train a state-of-the-art DL model for pixel-level identification – i.e., segmentation – of TCs and ARs. We then apply the trained DL model to historical and climate change scenarios simulated by the Community Atmospheric Model (CAM5.1) and show that the DL model accurately segments the data into TCs, ARs, or “the background” at a pixel level. Further, we show how the segmentation results can be used to conduct spatially and temporally precise analytics by quantifying distributions of extreme precipitation conditioned on event types (TC or AR) at regional scales. The key contribution of this work is that it paves the way for DL-based automated, high-fidelity, and highly precise analytics of climate data using a curated expert-labeled dataset – ClimateNet. ClimateNet and the DL-based segmentation method provide several unique capabilities: (i) they can be used to calculate a variety of TC and AR statistics at a fine-grained level; (ii) they can be applied to different climate scenarios and different datasets without tuning as they do not rely on threshold conditions; and (iii) the proposed DL method is suitable for rapidly analyzing large amounts of climate model output. While our study has been conducted for two important extreme weather patterns (TCs and ARs) in simulation datasets, we believe that this methodology can be applied to a much broader class of patterns and applied to observational and reanalysis data products via transfer learning.</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>3701 Atmospheric Sciences (for-2020)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>Networking and Information Technology R&amp;D (NITRD) (rcdc)</dc:subject><dc:subject>Climate-Related Exposures and Conditions (rcdc)</dc:subject><dc:subject>Data Science (rcdc)</dc:subject><dc:subject>Climate Change (rcdc)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>04 Earth Sciences (for)</dc:subject><dc:subject>37 Earth sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2321d436</dc:identifier><dc:identifier>https://escholarship.org/content/qt2321d436/qt2321d436.pdf</dc:identifier><dc:identifier>info:doi/10.5194/gmd-14-107-2021</dc:identifier><dc:type>article</dc:type><dc:source>Geoscientific Model Development, vol 14, iss 1</dc:source><dc:coverage>107 - 124</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7wf5k89s</identifier><datestamp>2026-09-15T20:23:47Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7wf5k89s</dc:identifier><dc:title>Concordant and opposing effects of climate and land-use change on avian assemblages in California’s most transformed landscapes</dc:title><dc:creator>Beissinger, Steven R</dc:creator><dc:creator>MacLean, Sarah A</dc:creator><dc:creator>Iknayan, Kelly J</dc:creator><dc:creator>de Valpine, Perry</dc:creator><dc:date>2023-02-24</dc:date><dc:description>Climate and land-use change could exhibit concordant effects that favor or disfavor the same species, which would amplify their impacts, or species may respond to each threat in a divergent manner, causing opposing effects that moderate their impacts in isolation. We used early 20th century surveys of birds conducted by Joseph Grinnell paired with modern resurveys and land-use change reconstructed from historic maps to examine avian change in Los Angeles and California's Central Valley (and their surrounding foothills). Occupancy and species richness declined greatly in Los Angeles from urbanization, strong warming (+1.8°C), and drying (-77.2&amp;nbsp;millimeters) but remained stable in the Central Valley, despite large-scale agricultural development, average warming (+0.9°C), and increased precipitation (+11.2&amp;nbsp;millimeters). While climate was the main driver of species distributions a century ago, the combined impacts of land-use and climate change drove temporal changes in occupancy, with similar numbers of species experiencing concordant and opposing effects.</dc:description><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>4102 Ecological Applications (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>15 Life on Land (sdg)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Environment (mesh)</dc:subject><dc:subject>Birds (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>Urbanization (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Birds (mesh)</dc:subject><dc:subject>Environment (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:subject>Urbanization (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Environment (mesh)</dc:subject><dc:subject>Birds (mesh)</dc:subject><dc:subject>Climate Change (mesh)</dc:subject><dc:subject>Urbanization (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7wf5k89s</dc:identifier><dc:identifier>https://escholarship.org/content/qt7wf5k89s/qt7wf5k89s.pdf</dc:identifier><dc:identifier>info:doi/10.1126/sciadv.abn0250</dc:identifier><dc:type>article</dc:type><dc:source>Science Advances, vol 9, iss 8</dc:source><dc:coverage>eabn0250</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8xn4v0s5</identifier><datestamp>2026-09-15T20:23:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8xn4v0s5</dc:identifier><dc:title>Dynamical dark energy in light of the DESI DR2 baryonic acoustic oscillations measurements</dc:title><dc:creator>Gu, Gan</dc:creator><dc:creator>Wang, Xiaoma</dc:creator><dc:creator>Wang, Yuting</dc:creator><dc:creator>Zhao, Gong-Bo</dc:creator><dc:creator>Pogosian, Levon</dc:creator><dc:creator>Koyama, Kazuya</dc:creator><dc:creator>Peacock, John A</dc:creator><dc:creator>Cai, Zheng</dc:creator><dc:creator>Cervantes-Cota, Jorge L</dc:creator><dc:creator>Ishak, Mustapha</dc:creator><dc:creator>Shafieloo, Arman</dc:creator><dc:creator>Zhao, Ruiyang</dc:creator><dc:creator>Ahlen, Steven</dc:creator><dc:creator>Bianchi, Davide</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>Claybaugh, Todd</dc:creator><dc:creator>Cole, Shaun</dc:creator><dc:creator>de la Macorra, Axel</dc:creator><dc:creator>de Mattia, Arnaud</dc:creator><dc:creator>Doel, Peter</dc:creator><dc:creator>Ferraro, Simone</dc:creator><dc:creator>Forero-Romero, Jaime E</dc:creator><dc:creator>Gaztañaga, Enrique</dc:creator><dc:creator>Gontcho A Gontcho, Satya</dc:creator><dc:creator>Gutierrez, Gaston</dc:creator><dc:creator>Hahn, ChangHoon</dc:creator><dc:creator>Howlett, Cullan</dc:creator><dc:creator>Kehoe, Robert</dc:creator><dc:creator>Kirkby, David</dc:creator><dc:creator>Kneib, Jean-Paul</dc:creator><dc:creator>Kremin, Anthony</dc:creator><dc:creator>Lahav, Ofer</dc:creator><dc:creator>Landriau, Martin</dc:creator><dc:creator>Le Guillou, Laurent</dc:creator><dc:creator>Leauthaud, Alexie</dc:creator><dc:creator>Levi, Michael</dc:creator><dc:creator>Manera, Marc</dc:creator><dc:creator>Meisner, Aaron</dc:creator><dc:creator>Miquel, Ramon</dc:creator><dc:creator>Moustakas, John</dc:creator><dc:creator>Muñoz-Gutiérrez, Andrea</dc:creator><dc:creator>Nadathur, Seshadri</dc:creator><dc:creator>Newman, Jeffrey A</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Percival, Will</dc:creator><dc:creator>Prada, Francisco</dc:creator><dc:creator>Pérez-Ràfols, Ignasi</dc:creator><dc:creator>Rossi, Graziano</dc:creator><dc:creator>Samushia, Lado</dc:creator><dc:creator>Sanchez, Eusebio</dc:creator><dc:creator>Schlegel, David</dc:creator><dc:creator>Seo, Hee-Jong</dc:creator><dc:creator>Sprayberry, David</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Walther, Michael</dc:creator><dc:creator>Weaver, Benjamin Alan</dc:creator><dc:creator>Zarrouk, Pauline</dc:creator><dc:creator>Zhao, Cheng</dc:creator><dc:creator>Zhou, Rongpu</dc:creator><dc:creator>Zou, Hu</dc:creator><dc:date>2025-01-01</dc:date><dc:description>Understanding whether cosmic acceleration arises from a cosmological constant or a dynamical component is a central goal of cosmology, and the Dark Energy Spectroscopic Instrument (DESI) enables stringent tests with high-precision distance measurements. Here we analyse measurements of baryon acoustic oscillations in DESI Data Release 1 and Data Release 2 and consider type Ia supernovae and a distance prior for the cosmic microwave background. With the larger statistical power and wider redshift coverage of Data Release 2, the preference for dynamical dark energy does not diminish relative to Data Release 1. Using both a shape-function reconstruction and non-parametric approaches with a Horndeski-motivated correlation prior, we find that the equation of state for dark energy w(z) varies with redshift. Baryon acoustic oscillation data alone yield modest constraints, but in combination with independent supernova compilations and the prior for the cosmic microwave background, they strengthen the evidence for dynamics. A Bayesian comparison of models shows moderate support for departures from Λ cold dark matter (ΛCDM) when several degrees of freedom in w(z) are allowed, corresponding to ~3σ tension with ΛCDM (and higher for some datasets). Despite methodological differences, our results are consistent with companion DESI papers, underscoring the complementarity of the approaches. Possible systematics remain under study; forthcoming DESI, Euclid and next-generation cosmic microwave background data will provide decisive tests.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Cosmology</dc:subject><dc:subject>Dark energy and dark matter</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8xn4v0s5</dc:identifier><dc:identifier>https://escholarship.org/content/qt8xn4v0s5/qt8xn4v0s5.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41550-025-02669-6</dc:identifier><dc:type>article</dc:type><dc:source>Nature Astronomy, vol 9, iss 12</dc:source><dc:coverage>1879 - 1889</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt06v28277</identifier><datestamp>2026-09-15T20:19:52Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt06v28277</dc:identifier><dc:title>Computation of the Strain Induced Critical Current Reduction in the 16 T Nb3Sn Test Facility Dipole</dc:title><dc:creator>Vallone, G</dc:creator><dc:creator>Anderssen, E</dc:creator><dc:creator>Arbelaez, D</dc:creator><dc:creator>Cheggour, N</dc:creator><dc:creator>Ferracin, P</dc:creator><dc:creator>Sabbi, GL</dc:creator><dc:creator>Turrioni, D</dc:creator><dc:date>2023-08-01</dc:date><dc:description>A test facility dipole is being developed at LBNL, targeting a 16 T field in a 144 mm wide aperture. The magnet uses a block design, with two double-pancake coils. In order to minimize motion under the large Lorentz forces, the coils are preloaded against a thick aluminum shell and iron yoke using bladder and key technology. It is then crucial to verify that the performance of the magnet is not degraded due to strain induced on the Nb3Sn conductor during assembly, cool-down and powering. The critical current of extracted strands was measured in a varying background magnetic field and as a function of the applied longitudinal strain. Finite element analysis was used to extract the strain state inside the superconducting strands during magnet assembly and operation. This strain was then compared to the measurements to evaluate potential reversible and irreversible effects on the magnet performances. The results suggest that the magnet can reach 16 T with sufficient margin, with no irreversible degradation in the high field region.</dc:description><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>4008 Electrical Engineering (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Nb3Sn</dc:subject><dc:subject>test facility</dc:subject><dc:subject>critical current</dc:subject><dc:subject>dipole</dc:subject><dc:subject>strain sensitivity</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>4008 Electrical engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/06v28277</dc:identifier><dc:identifier>https://escholarship.org/content/qt06v28277/qt06v28277.pdf</dc:identifier><dc:identifier>info:doi/10.1109/tasc.2023.3247690</dc:identifier><dc:type>article</dc:type><dc:source>IEEE Transactions on Applied Superconductivity, vol 33, iss 5</dc:source><dc:coverage>1 - 5</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4bw178sj</identifier><datestamp>2026-09-15T20:19:30Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4bw178sj</dc:identifier><dc:title>The DESI Survey Validation: Results from Visual Inspection of the Quasar Survey Spectra</dc:title><dc:creator>Alexander, David M</dc:creator><dc:creator>Davis, Tamara M</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Fawcett, VA</dc:creator><dc:creator>Gonzalez-Morales, Alma X</dc:creator><dc:creator>Lan, Ting-Wen</dc:creator><dc:creator>Yèche, Christophe</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Aguilar, JN</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Cai, Z</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Carr, A</dc:creator><dc:creator>Chabanier, S</dc:creator><dc:creator>Cousinou, Marie-Claude</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Dhungana, G</dc:creator><dc:creator>Edge, AC</dc:creator><dc:creator>Eftekharzadeh, S</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Farr, James</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Garcia-Bellido, J</dc:creator><dc:creator>Garrison, Lehman</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, Satya Gontcho A</dc:creator><dc:creator>Gordon, C</dc:creator><dc:creator>Gonzalez, Stefany Guadalupe Medellin</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Herrera-Alcantar, Hiram K</dc:creator><dc:creator>Jiang, L</dc:creator><dc:creator>Juneau, S</dc:creator><dc:creator>Karaçaylı, NG</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kovács, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Levi, Michael E</dc:creator><dc:creator>Magneville, C</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, Aaron M</dc:creator><dc:creator>Mezcua, M</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Camacho, P Montero</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Muñoz-Gutiérrez, Andrea</dc:creator><dc:creator>Myers, Adam D</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Napolitano, L</dc:creator><dc:creator>Nie, JD</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Pan, Z</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Pérez-Ràfols, I</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Ramírez-Pérez, César</dc:creator><dc:creator>Ravoux, C</dc:creator><dc:creator>Rosario, DJ</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Walther, M</dc:creator><dc:creator>Weiner, B</dc:creator><dc:creator>Youles, S</dc:creator><dc:creator>Zhou, Zhimin</dc:creator><dc:creator>Zou, H</dc:creator><dc:creator>Zou, Siwei</dc:creator><dc:date>2023-03-01</dc:date><dc:description>A key component of the Dark Energy Spectroscopic Instrument (DESI) survey validation (SV) is a detailed visual inspection (VI) of the optical spectroscopic data to quantify key survey metrics. In this paper we present results from VI of the quasar survey using deep coadded SV spectra. We show that the majority (≈70%) of the main-survey targets are spectroscopically confirmed as quasars, with ≈16% galaxies, ≈6% stars, and ≈8% low-quality spectra lacking reliable features. A nonnegligible fraction of the quasars are misidentified by the standard spectroscopic pipeline, but we show that the majority can be recovered using post-pipeline “afterburner” quasar-identification approaches. We combine these “afterburners” with our standard pipeline to create a modified pipeline to increase the overall quasar yield. At the depth of the main DESI survey, both pipelines achieve a good-redshift purity (reliable redshifts measured within 3000 km s−1) of ≈99%; however, the modified pipeline recovers ≈94% of the visually inspected quasars, as compared to ≈86% from the standard pipeline. We demonstrate that both pipelines achieve a median redshift precision and accuracy of ≈100 km s−1 and ≈70 km s−1, respectively. We constructed composite spectra to investigate why some quasars are missed by the standard pipeline and find that they are more host-galaxy dominated (i.e., distant analogs of “Seyfert galaxies”) and/or more dust reddened than the standard-pipeline quasars. We also show example spectra to demonstrate the overall diversity of the DESI quasar sample and provide strong-lensing candidates where two targets contribute to a single spectrum.</dc:description><dc:subject>5109 Space Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4bw178sj</dc:identifier><dc:identifier>https://escholarship.org/content/qt4bw178sj/qt4bw178sj.pdf</dc:identifier><dc:identifier>info:doi/10.3847/1538-3881/acacfc</dc:identifier><dc:type>article</dc:type><dc:source>The Astronomical Journal, vol 165, iss 3</dc:source><dc:coverage>124</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3jd3278g</identifier><datestamp>2026-09-15T20:19:26Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3jd3278g</dc:identifier><dc:title>Target Selection and Validation of DESI Emission Line Galaxies</dc:title><dc:creator>Raichoor, A</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Newman, Jeffrey A</dc:creator><dc:creator>Karim, T</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alam, Shadab</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Dhungana, G</dc:creator><dc:creator>Eftekharzadeh, S</dc:creator><dc:creator>Eisenstein, DJ</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>García-Bellido, J</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, Anthony</dc:creator><dc:creator>Lan, Ting-Wen</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, Michael E</dc:creator><dc:creator>Magneville, C</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, Aaron M</dc:creator><dc:creator>Myers, Adam D</dc:creator><dc:creator>Nie, Jundan</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Ruhlmann-Kleider, V</dc:creator><dc:creator>Sabiu, CG</dc:creator><dc:creator>Schlafly, EF</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yèche, Christophe</dc:creator><dc:creator>Zhou, Rongpu</dc:creator><dc:creator>Zhou, Zhimin</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2023-03-01</dc:date><dc:description>The Dark Energy Spectroscopic Instrument (DESI) will precisely constrain cosmic expansion and the growth of structure by collecting ∼40 million extragalactic redshifts across ∼80% of cosmic history and one-third of the sky. The Emission Line galaxy (ELG) sample, which will comprise about one-third of all DESI tracers, will be used to probe the universe over the 0.6 &amp;lt; z &amp;lt; 1.6 range, including the 1.1 &amp;lt; z &amp;lt; 1.6 range, which is expected to provide the tightest constraints. We present the target selection for the DESI Survey Validation (SV) and Main Survey ELG samples, which relies on the imaging of the Legacy Surveys. The Main ELG selection consists of a g-band magnitude cut and a (g − r) versus (r − z) color box, while the SV selection explores extensions of the Main selection boundaries. The Main ELG sample is composed of two disjoint subsamples, which have target densities of about 1940 deg−2 and 460 deg−2, respectively. We first characterize their photometric properties and density variations across the footprint. We then analyze the DESI spectroscopic data that have been obtained from 2020 December to 2021 December in the SV and Main Survey. We establish a preliminary criterion for selecting reliable redshifts, based on the [O ii] flux measurement, and assess its performance. Using this criterion, we are able to present the spectroscopic efficiency of the Main ELG selection, along with its redshift distribution. We thus demonstrate that the Main selection 1940 deg−2 subsample alone should provide 400 deg−2 and 460 deg−2 reliable redshifts in the 0.6 &amp;lt; z &amp;lt; 1.1 and the 1.1 &amp;lt; z &amp;lt; 1.6 ranges, respectively.</dc:description><dc:subject>5109 Space Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3jd3278g</dc:identifier><dc:identifier>https://escholarship.org/content/qt3jd3278g/qt3jd3278g.pdf</dc:identifier><dc:identifier>info:doi/10.3847/1538-3881/acb213</dc:identifier><dc:type>article</dc:type><dc:source>The Astronomical Journal, vol 165, iss 3</dc:source><dc:coverage>126</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9hp3t8hx</identifier><datestamp>2026-09-15T20:12:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9hp3t8hx</dc:identifier><dc:title>Measurements of W and Z/γ* cross sections and their ratios in p+p collisions at RHIC</dc:title><dc:creator>Adam, J</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, JR</dc:creator><dc:creator>Adkins, JK</dc:creator><dc:creator>Agakishiev, G</dc:creator><dc:creator>Aggarwal, MM</dc:creator><dc:creator>Ahammed, Z</dc:creator><dc:creator>Alekseev, I</dc:creator><dc:creator>Anderson, DM</dc:creator><dc:creator>Aparin, A</dc:creator><dc:creator>Aschenauer, EC</dc:creator><dc:creator>Ashraf, MU</dc:creator><dc:creator>Atetalla, FG</dc:creator><dc:creator>Attri, A</dc:creator><dc:creator>Averichev, GS</dc:creator><dc:creator>Bairathi, V</dc:creator><dc:creator>Barish, K</dc:creator><dc:creator>Behera, A</dc:creator><dc:creator>Bellwied, R</dc:creator><dc:creator>Bhasin, A</dc:creator><dc:creator>Bielcik, J</dc:creator><dc:creator>Bielcikova, J</dc:creator><dc:creator>Bland, LC</dc:creator><dc:creator>Bordyuzhin, IG</dc:creator><dc:creator>Brandenburg, JD</dc:creator><dc:creator>Brandin, AV</dc:creator><dc:creator>Butterworth, J</dc:creator><dc:creator>Caines, H</dc:creator><dc:creator>de la Barca Sánchez, M Calderón</dc:creator><dc:creator>Cebra, D</dc:creator><dc:creator>Chakaberia, I</dc:creator><dc:creator>Chaloupka, P</dc:creator><dc:creator>Chan, BK</dc:creator><dc:creator>Chang, F-H</dc:creator><dc:creator>Chang, Z</dc:creator><dc:creator>Chankova-Bunzarova, N</dc:creator><dc:creator>Chatterjee, A</dc:creator><dc:creator>Chen, D</dc:creator><dc:creator>Chen, J</dc:creator><dc:creator>Chen, JH</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Chen, Z</dc:creator><dc:creator>Cheng, J</dc:creator><dc:creator>Cherney, M</dc:creator><dc:creator>Chevalier, M</dc:creator><dc:creator>Choudhury, S</dc:creator><dc:creator>Christie, W</dc:creator><dc:creator>Chu, X</dc:creator><dc:creator>Crawford, HJ</dc:creator><dc:creator>Csanád, M</dc:creator><dc:creator>Daugherity, M</dc:creator><dc:creator>Dedovich, TG</dc:creator><dc:creator>Deppner, IM</dc:creator><dc:creator>Derevschikov, AA</dc:creator><dc:creator>Didenko, L</dc:creator><dc:creator>Dong, X</dc:creator><dc:creator>Drachenberg, JL</dc:creator><dc:creator>Dunlop, JC</dc:creator><dc:creator>Edmonds, T</dc:creator><dc:creator>Elsey, N</dc:creator><dc:creator>Engelage, J</dc:creator><dc:creator>Eppley, G</dc:creator><dc:creator>Esumi, S</dc:creator><dc:creator>Evdokimov, O</dc:creator><dc:creator>Ewigleben, A</dc:creator><dc:creator>Eyser, O</dc:creator><dc:creator>Fatemi, R</dc:creator><dc:creator>Fazio, S</dc:creator><dc:creator>Federic, P</dc:creator><dc:creator>Fedorisin, J</dc:creator><dc:creator>Feng, CJ</dc:creator><dc:creator>Feng, Y</dc:creator><dc:creator>Filip, P</dc:creator><dc:creator>Finch, E</dc:creator><dc:creator>Fisyak, Y</dc:creator><dc:creator>Francisco, A</dc:creator><dc:creator>Fulek, L</dc:creator><dc:creator>Gagliardi, CA</dc:creator><dc:creator>Galatyuk, T</dc:creator><dc:creator>Geurts, F</dc:creator><dc:creator>Gibson, A</dc:creator><dc:creator>Gopal, K</dc:creator><dc:creator>Gou, X</dc:creator><dc:creator>Grosnick, D</dc:creator><dc:creator>Guryn, W</dc:creator><dc:creator>Hamad, AI</dc:creator><dc:creator>Hamed, A</dc:creator><dc:creator>Harabasz, S</dc:creator><dc:creator>Harris, JW</dc:creator><dc:creator>He, S</dc:creator><dc:creator>He, W</dc:creator><dc:creator>He, XH</dc:creator><dc:creator>He, Y</dc:creator><dc:creator>Heppelmann, S</dc:creator><dc:creator>Heppelmann, S</dc:creator><dc:creator>Herrmann, N</dc:creator><dc:creator>Hoffman, E</dc:creator><dc:creator>Holub, L</dc:creator><dc:creator>Hong, Y</dc:creator><dc:creator>Horvat, S</dc:creator><dc:date>2021-01-01</dc:date><dc:description>We report on the W and Z/γ* differential and total cross sections as well as the W+/W- and (W++W-)/(Z/γ*) cross section ratios measured by the STAR experiment at RHIC in p+p collisions at s=500 GeV and 510 GeV. The cross sections and their ratios are sensitive to quark and antiquark parton distribution functions. In particular, at leading order, the W cross section ratio is sensitive to the d¯/u¯ ratio. These measurements were taken at high Q2∼MW2,MZ2 and can serve as input into global analyses to provide constraints on the sea quark distributions. The results presented here combine three STAR datasets from 2011, 2012, and 2013, accumulating an integrated luminosity of 350 pb-1. We also assess the expected impact that our W+/W- cross section ratios will have on various quark distributions, and find sensitivity to the u¯-d¯ and d¯/u¯ distributions.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>nucl-ex</dc:subject><dc:subject>nucl-ex</dc:subject><dc:subject>hep-ex</dc:subject><dc:subject>NSD-Relativistic Nuclear Collisions (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9hp3t8hx</dc:identifier><dc:identifier>https://escholarship.org/content/qt9hp3t8hx/qt9hp3t8hx.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevd.103.012001</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 103, iss 1</dc:source><dc:coverage>012001</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt17j9r8qg</identifier><datestamp>2026-09-15T20:11:13Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt17j9r8qg</dc:identifier><dc:title>Understanding the I/O Performance Gap Between Cori KNL and Haswell</dc:title><dc:creator>Liu, J</dc:creator><dc:creator>Koziol</dc:creator><dc:creator>Tang, H</dc:creator><dc:creator>Tessier, F</dc:creator><dc:creator>Bhimji</dc:creator><dc:creator>Cook, B</dc:creator><dc:creator>Byna, S</dc:creator><dc:creator>Austin, B</dc:creator><dc:creator>Thakur, B</dc:creator><dc:creator>lockwood</dc:creator><dc:creator>Deslippe</dc:creator><dc:creator>prabhat</dc:creator><dc:date>2017-05-07</dc:date><dc:description>The Cori system at NERSC has two compute
partitions with different CPU architectures: a 2,004 node
Haswell partition and a 9,688 node KNL partition, which
ranked as the 5th most powerful and fastest supercomputer
on the November 2016 Top 500 list. The compute partitions
share a common storage configuration, and understanding the
IO performance gap between them is important, impacting
not only to NERSC/LBNL users and other national labs, but
also to the relevant hardware vendors and software developers.
In this paper, we have analyzed performance of single core
and single node IO comprehensively on the Haswell and KNL
partitions, and have discovered the major bottlenecks, which
include CPU frequencies and memory copy performance. We
have also extended our performance tests to multi-node IO
and revealed the IO cost difference caused by network latency,
buffer size, and communication cost. Overall, we have developed
a strong understanding of the IO gap between Haswell and KNL
nodes and the lessons learned from this exploration will guide
us in designing optimal IO solutions in many-core era.</dc:description><dc:subject>I/O performance</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/17j9r8qg</dc:identifier><dc:identifier/><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0r52x292</identifier><datestamp>2026-09-15T20:07:04Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0r52x292</dc:identifier><dc:title>Extrahepatic Anomalies in Infants With Biliary Atresia: Results of a Large Prospective North American Multicenter Study</dc:title><dc:creator>Schwarz, Kathleen B</dc:creator><dc:creator>Haber, Barbara H</dc:creator><dc:creator>Rosenthal, Philip</dc:creator><dc:creator>Mack, Cara L</dc:creator><dc:creator>Moore, Jeffrey</dc:creator><dc:creator>Bove, Kevin</dc:creator><dc:creator>Bezerra, Jorge A</dc:creator><dc:creator>Karpen, Saul J</dc:creator><dc:creator>Kerkar, Nanda</dc:creator><dc:creator>Shneider, Benjamin L</dc:creator><dc:creator>Turmelle, Yumirle P</dc:creator><dc:creator>Whitington, Peter F</dc:creator><dc:creator>Molleston, Jean P</dc:creator><dc:creator>Murray, Karen F</dc:creator><dc:creator>Ng, Vicky L</dc:creator><dc:creator>Romero, René</dc:creator><dc:creator>Wang, Kasper S</dc:creator><dc:creator>Sokol, Ronald J</dc:creator><dc:creator>Magee, John C</dc:creator><dc:creator>Network, Childhood Liver Disease Research and Education</dc:creator><dc:date>2013-11-01</dc:date><dc:description>The etiology of biliary atresia (BA) is unknown. Given that patterns of anomalies might provide etiopathogenetic clues, we used data from the North American Childhood Liver Disease Research and Education Network to analyze patterns of anomalies in infants with BA. In all, 289 infants who were enrolled in the prospective database prior to surgery at any of 15 participating centers were evaluated. Group 1 was nonsyndromic, isolated BA (without major malformations) (n = 242, 84%), Group 2 was BA and at least one malformation considered major as defined by the National Birth Defects Prevention Study but without laterality defects (n = 17, 6%). Group 3 was syndromic, with laterality defects (n = 30, 10%). In the population as a whole, anomalies (either major or minor) were most prevalent in the cardiovascular (16%) and gastrointestinal (14%) systems. Group 3 patients accounted for the majority of subjects with cardiac, gastrointestinal, and splenic anomalies. Group 2 subjects also frequently displayed cardiovascular (71%) and gastrointestinal (24%) anomalies; interestingly, this group had genitourinary anomalies more frequently (47%) compared to Group 3 subjects (10%).
CONCLUSION: This study identified a group of BA (Group 2) that differed from the classical syndromic and nonsyndromic groups and that was defined by multiple malformations without laterality defects. Careful phenotyping of the patterns of anomalies may be critical to the interpretation of both genetic and environmental risk factors associated with BA, allowing new insight into pathogenesis and/or outcome.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>Liver Disease (rcdc)</dc:subject><dc:subject>Clinical Trials and Supportive Activities (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Perinatal Period - Conditions Originating in Perinatal Period (rcdc)</dc:subject><dc:subject>Chronic Liver Disease and Cirrhosis (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Congenital Structural Anomalies (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Cardiovascular (rcdc)</dc:subject><dc:subject>Rare Diseases (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Digestive Diseases (rcdc)</dc:subject><dc:subject>Abnormalities</dc:subject><dc:subject>Multiple (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Biliary Atresia (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Childhood Liver Disease Research and Education Network</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Biliary Atresia (mesh)</dc:subject><dc:subject>Abnormalities</dc:subject><dc:subject>Multiple (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Abnormalities</dc:subject><dc:subject>Multiple (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Biliary Atresia (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Prospective Studies (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>1101 Medical Biochemistry and Metabolomics (for)</dc:subject><dc:subject>1103 Clinical Sciences (for)</dc:subject><dc:subject>1107 Immunology (for)</dc:subject><dc:subject>Gastroenterology &amp; Hepatology (science-metrix)</dc:subject><dc:subject>3202 Clinical sciences (for-2020)</dc:subject><dc:subject>3204 Immunology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0r52x292</dc:identifier><dc:identifier>https://escholarship.org/content/qt0r52x292/qt0r52x292.pdf</dc:identifier><dc:identifier>info:doi/10.1002/hep.26512</dc:identifier><dc:type>article</dc:type><dc:source>Hepatology, vol 58, iss 5</dc:source><dc:coverage>1724 - 1731</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4td0p2vq</identifier><datestamp>2026-09-15T19:58:25Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4td0p2vq</dc:identifier><dc:title>Disparities in Drinking Water Manganese Concentrations in Domestic Wells and Community Water Systems in the Central Valley, CA, USA</dc:title><dc:creator>Aiken, Miranda L</dc:creator><dc:creator>Pace, Clare E</dc:creator><dc:creator>Ramachandran, Maithili</dc:creator><dc:creator>Schwabe, Kurt A</dc:creator><dc:creator>Ajami, Hoori</dc:creator><dc:creator>Link, Bruce G</dc:creator><dc:creator>Ying, Samantha C</dc:creator><dc:date>2023-02-07</dc:date><dc:description>Over 1.3 million Californians rely on unmonitored domestic wells. Existing probability estimates of groundwater Mn concentrations, population estimates, and sociodemographic data were integrated with spatial data delineating domestic well communities (DWCs) to predict the probability of high Mn concentrations in extracted groundwater within DWCs in California's Central Valley. Additional Mn concentration data of water delivered by community water systems (CWSs) were used to estimate Mn in public water supply. We estimate that 0.4% of the DWC population (2342 users) rely on groundwater with predicted Mn &amp;gt; 300 μg L-1. In CWSs, 2.4% of the population (904 users) served by small CWSs and 0.4% of the population (3072 users) served by medium CWS relied on drinking water with mean point-of-entry Mn concentration &amp;gt;300 μg L-1. Small CWSs were less likely to report Mn concentrations relative to large CWSs, yet a higher percentage of small CWSs exceed regulatory standards relative to larger systems. Modeled calculations do not reveal differences in estimated Mn concentration between groundwater from current regional domestic well depth and 33 m deeper. These analyses demonstrate the need for additional well-monitoring programs that evaluate Mn and increased access to point-of-use treatment for domestic well users disproportionately burdened by associated costs of water treatment.</dc:description><dc:subject>3707 Hydrology (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>6 Clean Water and Sanitation (sdg)</dc:subject><dc:subject>Drinking Water (mesh)</dc:subject><dc:subject>Manganese (mesh)</dc:subject><dc:subject>Water Pollutants</dc:subject><dc:subject>Chemical (mesh)</dc:subject><dc:subject>Water Supply (mesh)</dc:subject><dc:subject>Water Wells (mesh)</dc:subject><dc:subject>Groundwater (mesh)</dc:subject><dc:subject>Environmental Monitoring (mesh)</dc:subject><dc:subject>human right to water</dc:subject><dc:subject>secondary data</dc:subject><dc:subject>well depth</dc:subject><dc:subject>redox conditions</dc:subject><dc:subject>community water systems</dc:subject><dc:subject>domestic well communities</dc:subject><dc:subject>Manganese (mesh)</dc:subject><dc:subject>Water Pollutants</dc:subject><dc:subject>Chemical (mesh)</dc:subject><dc:subject>Environmental Monitoring (mesh)</dc:subject><dc:subject>Water Supply (mesh)</dc:subject><dc:subject>Groundwater (mesh)</dc:subject><dc:subject>Drinking Water (mesh)</dc:subject><dc:subject>Water Wells (mesh)</dc:subject><dc:subject>community water systems</dc:subject><dc:subject>domestic well communities</dc:subject><dc:subject>human right to water</dc:subject><dc:subject>redox conditions</dc:subject><dc:subject>secondary data</dc:subject><dc:subject>well depth</dc:subject><dc:subject>Drinking Water (mesh)</dc:subject><dc:subject>Manganese (mesh)</dc:subject><dc:subject>Water Pollutants</dc:subject><dc:subject>Chemical (mesh)</dc:subject><dc:subject>Water Supply (mesh)</dc:subject><dc:subject>Water Wells (mesh)</dc:subject><dc:subject>Groundwater (mesh)</dc:subject><dc:subject>Environmental Monitoring (mesh)</dc:subject><dc:subject>Environmental Sciences (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4td0p2vq</dc:identifier><dc:identifier>https://escholarship.org/content/qt4td0p2vq/qt4td0p2vq.pdf</dc:identifier><dc:identifier>info:doi/10.1021/acs.est.2c08548</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Science and Technology, vol 57, iss 5</dc:source><dc:coverage>1987 - 1996</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6xw0x69d</identifier><datestamp>2026-09-15T19:53:58Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6xw0x69d</dc:identifier><dc:title>Carbon nanotube substrates enhance SARS-CoV-2 spike protein ion yields in matrix-assisted laser desorption–ionization mass spectrometry</dc:title><dc:creator>Schenkel, T</dc:creator><dc:creator>Snijders, AM</dc:creator><dc:creator>Nakamura, K</dc:creator><dc:creator>Seidl, PA</dc:creator><dc:creator>Mak, B</dc:creator><dc:creator>Obst-Huebl, L</dc:creator><dc:creator>Knobel, H</dc:creator><dc:creator>Pong, I</dc:creator><dc:creator>Persaud, A</dc:creator><dc:creator>van Tilborg, J</dc:creator><dc:creator>Ostermayr, T</dc:creator><dc:creator>Steinke, S</dc:creator><dc:creator>Blakely, EA</dc:creator><dc:creator>Ji, Q</dc:creator><dc:creator>Javey, A</dc:creator><dc:creator>Kapadia, R</dc:creator><dc:creator>Geddes, CGR</dc:creator><dc:creator>Esarey, E</dc:creator><dc:date>2023-01-30</dc:date><dc:description>Nanostructured surfaces enhance ion yields in matrix-assisted laser desorption–ionization mass spectrometry (MALDI-MS). The spike protein complex, S1, is one fingerprint signature of Sars-CoV-2 with a mass of 75 kDa. Here, we show that MALDI-MS yields of Sars-CoV-2 spike protein ions in the 100 kDa range are enhanced 50-fold when the matrix–analyte solution is placed on substrates that are coated with a dense forest of multi-walled carbon nanotubes, compared to yields from uncoated substrates. Nanostructured substrates can support the development of mass spectrometry techniques for sensitive pathogen detection and environmental monitoring.</dc:description><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Nanotechnology (rcdc)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>Infectious Diseases (rcdc)</dc:subject><dc:subject>Emerging Infectious Diseases (rcdc)</dc:subject><dc:subject>Coronaviruses (rcdc)</dc:subject><dc:subject>ATAP-FS&amp;IBT (c-lbnl-label)</dc:subject><dc:subject>ATAP-BELLA Center (c-lbnl-label)</dc:subject><dc:subject>ATAP-SMP (c-lbnl-label)</dc:subject><dc:subject>ATAP-GENERAL (c-lbnl-label)</dc:subject><dc:subject>ATAP-2023 (c-lbnl-label)</dc:subject><dc:subject>ATAP-FS-IBT (c-lbnl-label)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>10 Technology (for)</dc:subject><dc:subject>Applied Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6xw0x69d</dc:identifier><dc:identifier>https://escholarship.org/content/qt6xw0x69d/qt6xw0x69d.pdf</dc:identifier><dc:identifier>info:doi/10.1063/5.0128667</dc:identifier><dc:type>article</dc:type><dc:source>Applied Physics Letters, vol 122, iss 5</dc:source><dc:coverage>050601</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt74s593ks</identifier><datestamp>2026-09-15T19:53:53Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt74s593ks</dc:identifier><dc:title>The DESI Survey Validation: Results from Visual Inspection of Bright Galaxies, Luminous Red Galaxies, and Emission-line Galaxies</dc:title><dc:creator>Lan, Ting-Wen</dc:creator><dc:creator>Tojeiro, R</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Prochaska, J Xavier</dc:creator><dc:creator>Davis, TM</dc:creator><dc:creator>Alexander, David M</dc:creator><dc:creator>Raichoor, A</dc:creator><dc:creator>Zhou, Rongpu</dc:creator><dc:creator>Yèche, Christophe</dc:creator><dc:creator>Balland, C</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Berti, A</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Carr, A</dc:creator><dc:creator>Chittenden, H</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Cousinou, M-C</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Douglass, K</dc:creator><dc:creator>Edge, A</dc:creator><dc:creator>Escoffier, S</dc:creator><dc:creator>Glanville, A</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Hwang, Ho Seong</dc:creator><dc:creator>Jiang, L</dc:creator><dc:creator>Kovács, A</dc:creator><dc:creator>Mezcua, M</dc:creator><dc:creator>Moore, S</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Oh, M</dc:creator><dc:creator>Parkinson, D</dc:creator><dc:creator>Rocher, A</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Ruhlmann-Kleider, V</dc:creator><dc:creator>Sabiu, CG</dc:creator><dc:creator>Said, K</dc:creator><dc:creator>Saulder, C</dc:creator><dc:creator>Sierra-Porta, D</dc:creator><dc:creator>Weiner, B</dc:creator><dc:creator>Yu, J</dc:creator><dc:creator>Zarrouk, P</dc:creator><dc:creator>Zhang, Y</dc:creator><dc:creator>Zou, H</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Cooper, AP</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dhungana, G</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Eftekharzadeh, S</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Garrison, L</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Kehoe, R</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, Michael E</dc:creator><dc:creator>Magneville, C</dc:creator><dc:creator>Meisner, Aaron M</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Myers, Adam D</dc:creator><dc:creator>Newman, Jeffrey A</dc:creator><dc:creator>Nie, JD</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Zhang, K</dc:creator><dc:creator>Zhou, Zhimin</dc:creator><dc:date>2023-01-01</dc:date><dc:description>The Dark Energy Spectroscopic Instrument (DESI) Survey has obtained a set of spectroscopic measurements of galaxies to validate the final survey design and target selections. To assist in these tasks, we visually inspect DESI spectra of approximately 2500 bright galaxies, 3500 luminous red galaxies (LRGs), and 10,000 emission-line galaxies (ELGs) to obtain robust redshift identifications. We then utilize the visually inspected redshift information to characterize the performance of the DESI operation. Based on the visual inspection (VI) catalogs, our results show that the final survey design yields samples of bright galaxies, LRGs, and ELGs with purity greater than 99%. Moreover, we demonstrate that the precision of the redshift measurements is approximately 10 km s−1 for bright galaxies and ELGs and approximately 40 km s−1 for LRGs. The average redshift accuracy is within 10 km s−1 for the three types of galaxies. The VI process also helps improve the quality of the DESI data by identifying spurious spectral features introduced by the pipeline. Finally, we show examples of unexpected real astronomical objects, such as Lyα emitters and strong lensing candidates, identified by VI. These results demonstrate the importance and utility of visually inspecting data from incoming and upcoming surveys, especially during their early operation phases.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0306 Physical Chemistry (incl. Structural) (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/74s593ks</dc:identifier><dc:identifier>https://escholarship.org/content/qt74s593ks/qt74s593ks.pdf</dc:identifier><dc:identifier>info:doi/10.3847/1538-4357/aca5fa</dc:identifier><dc:type>article</dc:type><dc:source>The Astrophysical Journal, vol 943, iss 1</dc:source><dc:coverage>68</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0km96259</identifier><datestamp>2026-09-15T19:53:44Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0km96259</dc:identifier><dc:title>An Initial Look at the Magnetic Design of a 150 mm Aperture High-Temperature Superconducting Magnet With a Dipole Field of 8 to 10 T</dc:title><dc:creator>Wang, X</dc:creator><dc:creator>Arbelaez, D</dc:creator><dc:creator>Brouwer, L</dc:creator><dc:creator>Caspi, S</dc:creator><dc:creator>Ferracin, P</dc:creator><dc:creator>Fajardo, L Garcia</dc:creator><dc:creator>Gourlay, S</dc:creator><dc:creator>Higley, H</dc:creator><dc:creator>Juchno, M</dc:creator><dc:creator>Marchevsky, M</dc:creator><dc:creator>Pong, I</dc:creator><dc:creator>Prestemon, S</dc:creator><dc:creator>Fernandez, JL Rudeiros</dc:creator><dc:creator>Sabbi, G</dc:creator><dc:creator>Shen, T</dc:creator><dc:creator>Teyber, R</dc:creator><dc:creator>Vallone, G</dc:creator><dc:creator>van der Laan, D</dc:creator><dc:creator>Weiss, J</dc:creator><dc:date>2023-08-01</dc:date><dc:description>High-temperature superconducting REBa$_{2}$ Cu$_{3}$O$_{7-x}$ (rebco) conductors have the potential to generate a high magnetic field over a broad temperature range. The corresponding accelerator magnet technology, still in its infancy, can be attractive for future energy-frontier particle colliders such as a multi-TeV muon collider. To help develop the technology, we explore the requirements and potential characteristics of a rebco magnet, operating at 4.2 or 20 K, with a dipole field of 810 T in a clear aperture of 150 mm. We use the canted $\cos \theta$ magnet configuration to reduce the electromagnetic stresses on the conductors. We present the resulting dipole fields, field gradients for combined-function cases, conductor stresses, magnet dimensions and conductor lengths. We also discuss the conductor performance that is required to achieve the target dipole field at 4.2 and 20 K. The information can provide useful input to the development of rebco magnet and conductor technology for collider-ring magnets in a muon collider.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Arc magnet</dc:subject><dc:subject>muon collider</dc:subject><dc:subject>REBCO</dc:subject><dc:subject>high-temperature superconducting magnet (c-lbnl-label)</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>4008 Electrical engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0km96259</dc:identifier><dc:identifier>https://escholarship.org/content/qt0km96259/qt0km96259.pdf</dc:identifier><dc:identifier>info:doi/10.1109/tasc.2023.3241833</dc:identifier><dc:type>article</dc:type><dc:source>IEEE Transactions on Applied Superconductivity, vol 33, iss 5</dc:source><dc:coverage>1 - 8</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8ng6c7p0</identifier><datestamp>2026-09-15T19:46:22Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8ng6c7p0</dc:identifier><dc:title>Metagenomic analysis of intertidal hypersaline microbial mats from Elkhorn Slough, California, grown with and without molybdate</dc:title><dc:creator>D’haeseleer, Patrik</dc:creator><dc:creator>Lee, Jackson Z</dc:creator><dc:creator>Prufert-Bebout, Leslie</dc:creator><dc:creator>Burow, Luke C</dc:creator><dc:creator>Detweiler, Angela M</dc:creator><dc:creator>Weber, Peter K</dc:creator><dc:creator>Karaoz, Ulas</dc:creator><dc:creator>Brodie, Eoin L</dc:creator><dc:creator>Glavina del Rio, Tijana</dc:creator><dc:creator>Tringe, Susannah G</dc:creator><dc:creator>Bebout, Brad M</dc:creator><dc:creator>Pett-Ridge, Jennifer</dc:creator><dc:date>2017-11-15</dc:date><dc:description>Cyanobacterial mats are laminated microbial ecosystems which occur in highly diverse environments and which may provide a possible model for early life on Earth. Their ability to produce hydrogen also makes them of interest from a biotechnological and bioenergy perspective. Samples of an intertidal microbial mat from the Elkhorn Slough estuary in Monterey Bay, California, were transplanted to a greenhouse at NASA Ames Research Center to study a 24-h diel cycle, in the presence or absence of molybdate (which inhibits biohydrogen consumption by sulfate reducers). Here, we present metagenomic analyses of four samples that will be used as references for future metatranscriptomic analyses of this diel time series.</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>Microbial mats</dc:subject><dc:subject>Hydrogen</dc:subject><dc:subject>Fermentation</dc:subject><dc:subject>Elkhorn slough</dc:subject><dc:subject>Metagenomics</dc:subject><dc:subject>Elkhorn slough</dc:subject><dc:subject>Fermentation</dc:subject><dc:subject>Hydrogen</dc:subject><dc:subject>Metagenomics</dc:subject><dc:subject>Microbial mats</dc:subject><dc:subject>0601 Biochemistry and Cell Biology (for)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8ng6c7p0</dc:identifier><dc:identifier>https://escholarship.org/content/qt8ng6c7p0/qt8ng6c7p0.pdf</dc:identifier><dc:identifier>info:doi/10.1186/s40793-017-0279-6</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Microbiome, vol 12, iss 1</dc:source><dc:coverage>67</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1261w1xd</identifier><datestamp>2026-09-15T19:46:16Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1261w1xd</dc:identifier><dc:title>Improved genome assembly of American alligator genome reveals conserved architecture of estrogen signaling</dc:title><dc:creator>Rice, Edward S</dc:creator><dc:creator>Kohno, Satomi</dc:creator><dc:creator>St. John, John</dc:creator><dc:creator>Pham, Son</dc:creator><dc:creator>Howard, Jonathan</dc:creator><dc:creator>Lareau, Liana F</dc:creator><dc:creator>O'Connell, Brendan L</dc:creator><dc:creator>Hickey, Glenn</dc:creator><dc:creator>Armstrong, Joel</dc:creator><dc:creator>Deran, Alden</dc:creator><dc:creator>Fiddes, Ian</dc:creator><dc:creator>Platt, Roy N</dc:creator><dc:creator>Gresham, Cathy</dc:creator><dc:creator>McCarthy, Fiona</dc:creator><dc:creator>Kern, Colin</dc:creator><dc:creator>Haan, David</dc:creator><dc:creator>Phan, Tan</dc:creator><dc:creator>Schmidt, Carl</dc:creator><dc:creator>Sanford, Jeremy R</dc:creator><dc:creator>Ray, David A</dc:creator><dc:creator>Paten, Benedict</dc:creator><dc:creator>Guillette, Louis J</dc:creator><dc:creator>Green, Richard E</dc:creator><dc:date>2017-05-01</dc:date><dc:description>The American alligator, Alligator mississippiensis, like all crocodilians, has temperature-dependent sex determination, in which the sex of an embryo is determined by the incubation temperature of the egg during a critical period of development. The lack of genetic differences between male and female alligators leaves open the question of how the genes responsible for sex determination and differentiation are regulated. Insight into this question comes from the fact that exposing an embryo incubated at male-producing temperature to estrogen causes it to develop ovaries. Because estrogen response elements are known to regulate genes over long distances, a contiguous genome assembly is crucial for predicting and understanding their impact. We present an improved assembly of the American alligator genome, scaffolded with in vitro proximity ligation (Chicago) data. We use this assembly to scaffold two other crocodilian genomes based on synteny. We perform RNA sequencing of tissues from American alligator embryos to find genes that are differentially expressed between embryos incubated at male- versus female-producing temperature. Finally, we use the improved contiguity of our assembly along with the current model of CTCF-mediated chromatin looping to predict regions of the genome likely to contain estrogen-responsive genes. We find that these regions are significantly enriched for genes with female-biased expression in developing gonads after the critical period during which sex is determined by incubation temperature. We thus conclude that estrogen signaling is a major driver of female-biased gene expression in the post-temperature sensitive period gonads.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3102 Bioinformatics and Computational Biology (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Estrogen (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Contraception/Reproduction (rcdc)</dc:subject><dc:subject>Biotechnology (rcdc)</dc:subject><dc:subject>1.1 Normal biological development and functioning (hrcs-rac)</dc:subject><dc:subject>Generic health relevance (hrcs-hc)</dc:subject><dc:subject>Alligators and Crocodiles (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>CCCTC-Binding Factor (mesh)</dc:subject><dc:subject>Chromatin (mesh)</dc:subject><dc:subject>Conserved Sequence (mesh)</dc:subject><dc:subject>Contig Mapping (mesh)</dc:subject><dc:subject>Estrogens (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Sequence Analysis</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>Sex Determination Processes (mesh)</dc:subject><dc:subject>Signal Transduction (mesh)</dc:subject><dc:subject>Synteny (mesh)</dc:subject><dc:subject>Chromatin (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Alligators and Crocodiles (mesh)</dc:subject><dc:subject>Estrogens (mesh)</dc:subject><dc:subject>Contig Mapping (mesh)</dc:subject><dc:subject>Sequence Analysis</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>Signal Transduction (mesh)</dc:subject><dc:subject>Conserved Sequence (mesh)</dc:subject><dc:subject>Synteny (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Sex Determination Processes (mesh)</dc:subject><dc:subject>CCCTC-Binding Factor (mesh)</dc:subject><dc:subject>Alligators and Crocodiles (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>CCCTC-Binding Factor (mesh)</dc:subject><dc:subject>Chromatin (mesh)</dc:subject><dc:subject>Conserved Sequence (mesh)</dc:subject><dc:subject>Contig Mapping (mesh)</dc:subject><dc:subject>Estrogens (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Genome (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Sequence Analysis</dc:subject><dc:subject>DNA (mesh)</dc:subject><dc:subject>Sex Determination Processes (mesh)</dc:subject><dc:subject>Signal Transduction (mesh)</dc:subject><dc:subject>Synteny (mesh)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>Bioinformatics (science-metrix)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1261w1xd</dc:identifier><dc:identifier>https://escholarship.org/content/qt1261w1xd/qt1261w1xd.pdf</dc:identifier><dc:identifier>info:doi/10.1101/gr.213595.116</dc:identifier><dc:type>article</dc:type><dc:source>Genome Research, vol 27, iss 5</dc:source><dc:coverage>686 - 696</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8d25027s</identifier><datestamp>2026-09-15T19:45:47Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8d25027s</dc:identifier><dc:title>Height and Body Mass Index as Modifiers of Breast Cancer Risk in BRCA1/2 Mutation Carriers: A Mendelian Randomization Study</dc:title><dc:creator>Qian, Frank</dc:creator><dc:creator>Wang, Shengfeng</dc:creator><dc:creator>Mitchell, Jonathan</dc:creator><dc:creator>McGuffog, Lesley</dc:creator><dc:creator>Barrowdale, Daniel</dc:creator><dc:creator>Leslie, Goska</dc:creator><dc:creator>Oosterwijk, Jan C</dc:creator><dc:creator>Chung, Wendy K</dc:creator><dc:creator>Evans, D Gareth</dc:creator><dc:creator>Engel, Christoph</dc:creator><dc:creator>Kast, Karin</dc:creator><dc:creator>Aalfs, Cora M</dc:creator><dc:creator>Adank, Muriel A</dc:creator><dc:creator>Adlard, Julian</dc:creator><dc:creator>Agnarsson, Bjarni A</dc:creator><dc:creator>Aittomäki, Kristiina</dc:creator><dc:creator>Alducci, Elisa</dc:creator><dc:creator>Andrulis, Irene L</dc:creator><dc:creator>Arun, Banu K</dc:creator><dc:creator>Ausems, Margreet GEM</dc:creator><dc:creator>Azzollini, Jacopo</dc:creator><dc:creator>Barouk-Simonet, Emmanuelle</dc:creator><dc:creator>Barwell, Julian</dc:creator><dc:creator>Belotti, Muriel</dc:creator><dc:creator>Benitez, Javier</dc:creator><dc:creator>Berger, Andreas</dc:creator><dc:creator>Borg, Ake</dc:creator><dc:creator>Bradbury, Angela R</dc:creator><dc:creator>Brunet, Joan</dc:creator><dc:creator>Buys, Saundra S</dc:creator><dc:creator>Caldes, Trinidad</dc:creator><dc:creator>Caligo, Maria A</dc:creator><dc:creator>Campbell, Ian</dc:creator><dc:creator>Caputo, Sandrine M</dc:creator><dc:creator>Chiquette, Jocelyne</dc:creator><dc:creator>Claes, Kathleen BM</dc:creator><dc:creator>Collée, J Margriet</dc:creator><dc:creator>Couch, Fergus J</dc:creator><dc:creator>Coupier, Isabelle</dc:creator><dc:creator>Daly, Mary B</dc:creator><dc:creator>Davidson, Rosemarie</dc:creator><dc:creator>Diez, Orland</dc:creator><dc:creator>Domchek, Susan M</dc:creator><dc:creator>Donaldson, Alan</dc:creator><dc:creator>Dorfling, Cecilia M</dc:creator><dc:creator>Eeles, Ros</dc:creator><dc:creator>Feliubadaló, Lidia</dc:creator><dc:creator>Foretova, Lenka</dc:creator><dc:creator>Fowler, Jeffrey</dc:creator><dc:creator>Friedman, Eitan</dc:creator><dc:creator>Frost, Debra</dc:creator><dc:creator>Ganz, Patricia A</dc:creator><dc:creator>Garber, Judy</dc:creator><dc:creator>Garcia-Barberan, Vanesa</dc:creator><dc:creator>Glendon, Gord</dc:creator><dc:creator>Godwin, Andrew K</dc:creator><dc:creator>Garcia, Encarna B Gómez</dc:creator><dc:creator>Gronwald, Jacek</dc:creator><dc:creator>Hahnen, Eric</dc:creator><dc:creator>Hamann, Ute</dc:creator><dc:creator>Henderson, Alex</dc:creator><dc:creator>Hendricks, Carolyn B</dc:creator><dc:creator>Hopper, John L</dc:creator><dc:creator>Hulick, Peter J</dc:creator><dc:creator>Imyanitov, Evgeny N</dc:creator><dc:creator>Isaacs, Claudine</dc:creator><dc:creator>Izatt, Louise</dc:creator><dc:creator>Izquierdo, Ángel</dc:creator><dc:creator>Jakubowska, Anna</dc:creator><dc:creator>Kaczmarek, Katarzyna</dc:creator><dc:creator>Kang, Eunyoung</dc:creator><dc:creator>Karlan, Beth Y</dc:creator><dc:creator>Kets, Carolien M</dc:creator><dc:creator>Kim, Sung-Won</dc:creator><dc:creator>Kim, Zisun</dc:creator><dc:creator>Kwong, Ava</dc:creator><dc:creator>Laitman, Yael</dc:creator><dc:creator>Lasset, Christine</dc:creator><dc:creator>Lee, Min Hyuk</dc:creator><dc:creator>Lee, Jong Won</dc:creator><dc:creator>Lee, Jihyoun</dc:creator><dc:creator>Lester, Jenny</dc:creator><dc:creator>Lesueur, Fabienne</dc:creator><dc:creator>Loud, Jennifer T</dc:creator><dc:creator>Lubinski, Jan</dc:creator><dc:creator>Mebirouk, Noura</dc:creator><dc:creator>Meijers-Heijboer, Hanne EJ</dc:creator><dc:creator>Meindl, Alfons</dc:creator><dc:creator>Miller, Austin</dc:creator><dc:creator>Montagna, Marco</dc:creator><dc:creator>Mooij, Thea M</dc:creator><dc:creator>Morrison, Patrick J</dc:creator><dc:creator>Mouret-Fourme, Emmanuelle</dc:creator><dc:creator>Nathanson, Katherine L</dc:creator><dc:creator>Neuhausen, Susan L</dc:creator><dc:creator>Nevanlinna, Heli</dc:creator><dc:creator>Niederacher, Dieter</dc:creator><dc:creator>Nielsen, Finn C</dc:creator><dc:creator>Nussbaum, Robert L</dc:creator><dc:creator>Offit, Kenneth</dc:creator><dc:date>2019-04-01</dc:date><dc:description>BACKGROUND: BRCA1/2 mutations confer high lifetime risk of breast cancer, although other factors may modify this risk. Whether height or body mass index (BMI) modifies breast cancer risk in BRCA1/2 mutation carriers remains unclear.
METHODS: We used Mendelian randomization approaches to evaluate the association of height and BMI on breast cancer risk, using data from the Consortium of Investigators of Modifiers of BRCA1/2 with 14 676 BRCA1 and 7912 BRCA2 mutation carriers, including 11 451 cases of breast cancer. We created a height genetic score using 586 height-associated variants and a BMI genetic score using 93 BMI-associated variants. We examined both observed and genetically determined height and BMI with breast cancer risk using weighted Cox models. All statistical tests were two-sided.
RESULTS: Observed height was positively associated with breast cancer risk (HR = 1.09 per 10 cm increase, 95% confidence interval [CI] = 1.0 to 1.17; P = 1.17). Height genetic score was positively associated with breast cancer, although this was not statistically significant (per 10 cm increase in genetically predicted height, HR = 1.04, 95% CI = 0.93 to 1.17; P = .47). Observed BMI was inversely associated with breast cancer risk (per 5 kg/m2 increase, HR = 0.94, 95% CI = 0.90 to 0.98; P = .007). BMI genetic score was also inversely associated with breast cancer risk (per 5 kg/m2 increase in genetically predicted BMI, HR = 0.87, 95% CI = 0.76 to 0.98; P = .02). BMI was primarily associated with premenopausal breast cancer.
CONCLUSION: Height is associated with overall breast cancer and BMI is associated with premenopausal breast cancer in BRCA1/2 mutation carriers. Incorporating height and BMI, particularly genetic score, into risk assessment may improve cancer management.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3211 Oncology and Carcinogenesis (for-2020)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Cancer (rcdc)</dc:subject><dc:subject>Aging (rcdc)</dc:subject><dc:subject>Genetic Testing (rcdc)</dc:subject><dc:subject>Breast Cancer (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>2.1 Biological and endogenous factors (hrcs-rac)</dc:subject><dc:subject>Cancer (hrcs-hc)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>BRCA1 Protein (mesh)</dc:subject><dc:subject>BRCA2 Protein (mesh)</dc:subject><dc:subject>Body Height (mesh)</dc:subject><dc:subject>Body Mass Index (mesh)</dc:subject><dc:subject>Breast Neoplasms (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Genetic Predisposition to Disease (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Mendelian Randomization Analysis (mesh)</dc:subject><dc:subject>Mutation (mesh)</dc:subject><dc:subject>Polymorphism</dc:subject><dc:subject>Single Nucleotide (mesh)</dc:subject><dc:subject>Prognosis (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>GEMO Study Collaborators</dc:subject><dc:subject>HEBON</dc:subject><dc:subject>EMBRACE</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Breast Neoplasms (mesh)</dc:subject><dc:subject>Genetic Predisposition to Disease (mesh)</dc:subject><dc:subject>BRCA1 Protein (mesh)</dc:subject><dc:subject>BRCA2 Protein (mesh)</dc:subject><dc:subject>Body Mass Index (mesh)</dc:subject><dc:subject>Body Height (mesh)</dc:subject><dc:subject>Prognosis (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>Mutation (mesh)</dc:subject><dc:subject>Polymorphism</dc:subject><dc:subject>Single Nucleotide (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Mendelian Randomization Analysis (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>BRCA1 Protein (mesh)</dc:subject><dc:subject>BRCA2 Protein (mesh)</dc:subject><dc:subject>Body Height (mesh)</dc:subject><dc:subject>Body Mass Index (mesh)</dc:subject><dc:subject>Breast Neoplasms (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Genetic Predisposition to Disease (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Mendelian Randomization Analysis (mesh)</dc:subject><dc:subject>Mutation (mesh)</dc:subject><dc:subject>Polymorphism</dc:subject><dc:subject>Single Nucleotide (mesh)</dc:subject><dc:subject>Prognosis (mesh)</dc:subject><dc:subject>Risk Factors (mesh)</dc:subject><dc:subject>1112 Oncology and Carcinogenesis (for)</dc:subject><dc:subject>Oncology &amp; Carcinogenesis (science-metrix)</dc:subject><dc:subject>3211 Oncology and carcinogenesis (for-2020)</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8d25027s</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1093/jnci/djy132</dc:identifier><dc:type>article</dc:type><dc:source>Journal of the National Cancer Institute, vol 111, iss 4</dc:source><dc:coverage>350 - 364</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt11g68175</identifier><datestamp>2026-09-15T19:42:23Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt11g68175</dc:identifier><dc:title>Genetic variants for head size share genes and pathways with cancer</dc:title><dc:creator>Knol, Maria J</dc:creator><dc:creator>Poot, Raymond A</dc:creator><dc:creator>Evans, Tavia E</dc:creator><dc:creator>Satizabal, Claudia L</dc:creator><dc:creator>Mishra, Aniket</dc:creator><dc:creator>Sargurupremraj, Muralidharan</dc:creator><dc:creator>van der Auwera, Sandra</dc:creator><dc:creator>Duperron, Marie-Gabrielle</dc:creator><dc:creator>Jian, Xueqiu</dc:creator><dc:creator>Hostettler, Isabel C</dc:creator><dc:creator>van Dam-Nolen, Dianne HK</dc:creator><dc:creator>Lamballais, Sander</dc:creator><dc:creator>Pawlak, Mikolaj A</dc:creator><dc:creator>Lewis, Cora E</dc:creator><dc:creator>Carrion-Castillo, Amaia</dc:creator><dc:creator>van Erp, Theo GM</dc:creator><dc:creator>Reinbold, Céline S</dc:creator><dc:creator>Shin, Jean</dc:creator><dc:creator>Scholz, Markus</dc:creator><dc:creator>Håberg, Asta K</dc:creator><dc:creator>Kämpe, Anders</dc:creator><dc:creator>Li, Gloria HY</dc:creator><dc:creator>Avinun, Reut</dc:creator><dc:creator>Atkins, Joshua R</dc:creator><dc:creator>Hsu, Fang-Chi</dc:creator><dc:creator>Amod, Alyssa R</dc:creator><dc:creator>Lam, Max</dc:creator><dc:creator>Tsuchida, Ami</dc:creator><dc:creator>Teunissen, Mariël WA</dc:creator><dc:creator>Aygün, Nil</dc:creator><dc:creator>Patel, Yash</dc:creator><dc:creator>Liang, Dan</dc:creator><dc:creator>Beiser, Alexa S</dc:creator><dc:creator>Beyer, Frauke</dc:creator><dc:creator>Bis, Joshua C</dc:creator><dc:creator>Bos, Daniel</dc:creator><dc:creator>Bryan, R Nick</dc:creator><dc:creator>Bülow, Robin</dc:creator><dc:creator>Caspers, Svenja</dc:creator><dc:creator>Catheline, Gwenaëlle</dc:creator><dc:creator>Cecil, Charlotte AM</dc:creator><dc:creator>Dalvie, Shareefa</dc:creator><dc:creator>Dartigues, Jean-François</dc:creator><dc:creator>DeCarli, Charles</dc:creator><dc:creator>Enlund-Cerullo, Maria</dc:creator><dc:creator>Ford, Judith M</dc:creator><dc:creator>Franke, Barbara</dc:creator><dc:creator>Freedman, Barry I</dc:creator><dc:creator>Friedrich, Nele</dc:creator><dc:creator>Green, Melissa J</dc:creator><dc:creator>Haworth, Simon</dc:creator><dc:creator>Helmer, Catherine</dc:creator><dc:creator>Hoffmann, Per</dc:creator><dc:creator>Homuth, Georg</dc:creator><dc:creator>Ikram, M Kamran</dc:creator><dc:creator>Jack, Clifford R</dc:creator><dc:creator>Jahanshad, Neda</dc:creator><dc:creator>Jockwitz, Christiane</dc:creator><dc:creator>Kamatani, Yoichiro</dc:creator><dc:creator>Knodt, Annchen R</dc:creator><dc:creator>Li, Shuo</dc:creator><dc:creator>Lim, Keane</dc:creator><dc:creator>Longstreth, WT</dc:creator><dc:creator>Macciardi, Fabio</dc:creator><dc:creator>Consortium, The Cohorts for Heart and Aging Research in Genomic Epidemiology</dc:creator><dc:creator>Amouyel, Philippe</dc:creator><dc:creator>Arfanakis, Konstantinos</dc:creator><dc:creator>Aribisala, Benjamin S</dc:creator><dc:creator>Bastin, Mark E</dc:creator><dc:creator>Chauhan, Ganesh</dc:creator><dc:creator>Chen, Christopher</dc:creator><dc:creator>Cheng, Ching-Yu</dc:creator><dc:creator>de Jager, Philip L</dc:creator><dc:creator>Deary, Ian J</dc:creator><dc:creator>Fleischman, Debra A</dc:creator><dc:creator>Gottesman, Rebecca F</dc:creator><dc:creator>Gudnason, Vilmundur</dc:creator><dc:creator>Hilal, Saima</dc:creator><dc:creator>Hofer, Edith</dc:creator><dc:creator>Janowitz, Deborah</dc:creator><dc:creator>Jukema, J Wouter</dc:creator><dc:creator>Liewald, David CM</dc:creator><dc:creator>Lopez, Lorna M</dc:creator><dc:creator>Lopez, Oscar</dc:creator><dc:creator>Luciano, Michelle</dc:creator><dc:creator>Martinez, Oliver</dc:creator><dc:creator>Niessen, Wiro J</dc:creator><dc:creator>Nyquist, Paul</dc:creator><dc:creator>Rotter, Jerome I</dc:creator><dc:creator>Rundek, Tatjana</dc:creator><dc:creator>Sacco, Ralph L</dc:creator><dc:creator>Schmidt, Helena</dc:creator><dc:creator>Tiemeier, Henning</dc:creator><dc:creator>Trompet, Stella</dc:creator><dc:creator>van der Grond, Jeroen</dc:creator><dc:creator>Völzke, Henry</dc:creator><dc:creator>Wardlaw, Joanna M</dc:creator><dc:creator>Yanek, Lisa</dc:creator><dc:creator>Yang, Jingyun</dc:creator><dc:creator>Consortium, The Enhancing NeuroImaging Genetics through Meta-Analysis</dc:creator><dc:date>2024-05-01</dc:date><dc:description>The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N&amp;nbsp;= 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>Biotechnology (rcdc)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>Cancer (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Stem Cell Research (rcdc)</dc:subject><dc:subject>2.1 Biological and endogenous factors (hrcs-rac)</dc:subject><dc:subject>1.1 Normal biological development and functioning (hrcs-rac)</dc:subject><dc:subject>Neurological (hrcs-hc)</dc:subject><dc:subject>Cancer (hrcs-hc)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Genome-Wide Association Study (mesh)</dc:subject><dc:subject>Head (mesh)</dc:subject><dc:subject>Neoplasms (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Polymorphism</dc:subject><dc:subject>Single Nucleotide (mesh)</dc:subject><dc:subject>Genetic Variation (mesh)</dc:subject><dc:subject>Organ Size (mesh)</dc:subject><dc:subject>Signal Transduction (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Genetic Predisposition to Disease (mesh)</dc:subject><dc:subject>Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium</dc:subject><dc:subject>Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium</dc:subject><dc:subject>Head (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Neoplasms (mesh)</dc:subject><dc:subject>Genetic Predisposition to Disease (mesh)</dc:subject><dc:subject>Organ Size (mesh)</dc:subject><dc:subject>Signal Transduction (mesh)</dc:subject><dc:subject>Polymorphism</dc:subject><dc:subject>Single Nucleotide (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Genetic Variation (mesh)</dc:subject><dc:subject>Genome-Wide Association Study (mesh)</dc:subject><dc:subject>cancer</dc:subject><dc:subject>genetics</dc:subject><dc:subject>genome-wide association study</dc:subject><dc:subject>head circumference</dc:subject><dc:subject>head size</dc:subject><dc:subject>intracranial volume</dc:subject><dc:subject>meta-analysis</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Genome-Wide Association Study (mesh)</dc:subject><dc:subject>Head (mesh)</dc:subject><dc:subject>Neoplasms (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Polymorphism</dc:subject><dc:subject>Single Nucleotide (mesh)</dc:subject><dc:subject>Genetic Variation (mesh)</dc:subject><dc:subject>Organ Size (mesh)</dc:subject><dc:subject>Signal Transduction (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Genetic Predisposition to Disease (mesh)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/11g68175</dc:identifier><dc:identifier>https://escholarship.org/content/qt11g68175/qt11g68175.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.xcrm.2024.101529</dc:identifier><dc:type>article</dc:type><dc:source>Cell Reports Medicine, vol 5, iss 5</dc:source><dc:coverage>101529</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt495348h9</identifier><datestamp>2026-09-15T19:41:34Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt495348h9</dc:identifier><dc:title>Development of ultralow-background cryogenic calorimeters for the measurement of surface &amp;nbsp; α &amp;nbsp;contamination</dc:title><dc:creator>Benato, G</dc:creator><dc:creator>Biassoni, M</dc:creator><dc:creator>Brofferio, C</dc:creator><dc:creator>Celi, E</dc:creator><dc:creator>Dell'Oro, S</dc:creator><dc:creator>Drobizhev, A</dc:creator><dc:creator>Gianvecchio, A</dc:creator><dc:creator>Girola, M</dc:creator><dc:creator>Ghislandi, S</dc:creator><dc:creator>Kolomensky, Yu G</dc:creator><dc:creator>Nutini, I</dc:creator><dc:creator>Olmi, M</dc:creator><dc:creator>Pagnanini, L</dc:creator><dc:creator>Puiu, A</dc:creator><dc:creator>Quitadamo, S</dc:creator><dc:date>2023-03-01</dc:date><dc:description>Next-generation experiments searching for rare events must satisfy increasingly stringent requirements on the bulk and surface radioactive contamination of their active and structural materials. The measurement of surface contamination is particularly challenging, as no existing technology is capable of separately measuring parts of the 232Th and 238U decay chains that are commonly found to be out of secular equilibrium. We will present the results obtained with a detector prototype consisting of 8 silicon wafers of 150&amp;nbsp;mm diameter instrumented as bolometers and operated in a low-background dilution refrigerator at the Gran Sasso Underground Laboratory of INFN, Italy. The prototype was characterized by a baseline energy resolution of few keV and a background &amp;lt;100&amp;nbsp;nBq/cm2 in the full range of &amp;nbsp;α&amp;nbsp;energies, obtained with simple procedures for cleaning of all employed materials and no specific measures to prevent recontamination. Such performance, together with the modularity of the detector design, demonstrate the possibility to realize an alpha detector capable of separately measuring all alpha emitters of the 232Th and 238U chains, possibly reaching a sensitivity of few nBq/cm2.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>3211 Oncology and Carcinogenesis (for-2020)</dc:subject><dc:subject>Bolometric α detector</dc:subject><dc:subject>Low-radioactivity measurements</dc:subject><dc:subject>Material screening</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0299 Other Physical Sciences (for)</dc:subject><dc:subject>1103 Clinical Sciences (for)</dc:subject><dc:subject>Nuclear Medicine &amp; Medical Imaging (science-metrix)</dc:subject><dc:subject>3202 Clinical sciences (for-2020)</dc:subject><dc:subject>3211 Oncology and carcinogenesis (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/495348h9</dc:identifier><dc:identifier>https://escholarship.org/content/qt495348h9/qt495348h9.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.apradiso.2023.110681</dc:identifier><dc:type>article</dc:type><dc:source>Applied Radiation and Isotopes, vol 193</dc:source><dc:coverage>110681</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1n37d5c5</identifier><datestamp>2026-09-15T19:38:14Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1n37d5c5</dc:identifier><dc:title>Target Selection and Validation of DESI Luminous Red Galaxies</dc:title><dc:creator>Zhou, Rongpu</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Newman, Jeffrey A</dc:creator><dc:creator>Eisenstein, Daniel J</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Berti, A</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Lan, Ting-Wen</dc:creator><dc:creator>Zou, H</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alam, Shadab</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dhungana, G</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Ishak, Mustapha</dc:creator><dc:creator>Kisner, T</dc:creator><dc:creator>Kovács, A</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Levi, Michael E</dc:creator><dc:creator>Magneville, C</dc:creator><dc:creator>Manera, Marc</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, Aaron M</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Myers, Adam D</dc:creator><dc:creator>Nie, Jundan</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Prada, F</dc:creator><dc:creator>Raichoor, A</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Schlafly, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Wechsler, RH</dc:creator><dc:creator>Yéche, Christophe</dc:creator><dc:creator>Zhou, Zhimin</dc:creator><dc:date>2023-02-01</dc:date><dc:description>The Dark Energy Spectroscopic Instrument (DESI) is carrying out a five-year survey that aims to measure the redshifts of tens of millions of galaxies and quasars, including 8 million luminous red galaxies (LRGs) in the redshift range 0.4 &amp;lt; z ≲ 1.0. Here we present the selection of the DESI LRG sample and assess its spectroscopic performance using data from Survey Validation (SV) and the first two months of the Main Survey. The DESI LRG sample, selected using g, r, z, and W1 photometry from the DESI Legacy Imaging Surveys, is highly robust against imaging systematics. The sample has a target density of 605 deg−2 and a comoving number density of 5 × 10−4 h 3 Mpc−3 in 0.4 &amp;lt; z &amp;lt; 0.8; this is a significantly higher density than previous LRG surveys (such as SDSS, BOSS, and eBOSS) while also extending to z ∼ 1. After applying a bright star veto mask developed for the sample, 98.9% of the observed LRG targets yield confident redshifts (with a catastrophic failure rate of 0.2% in the confident redshifts), and only 0.5% of the LRG targets are stellar contamination. The LRG redshift efficiency varies with source brightness and effective exposure time, and we present a simple model that accurately characterizes this dependence. In the appendices, we describe the extended LRG samples observed during SV.</dc:description><dc:subject>5109 Space Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1n37d5c5</dc:identifier><dc:identifier>https://escholarship.org/content/qt1n37d5c5/qt1n37d5c5.pdf</dc:identifier><dc:identifier>info:doi/10.3847/1538-3881/aca5fb</dc:identifier><dc:type>article</dc:type><dc:source>The Astronomical Journal, vol 165, iss 2</dc:source><dc:coverage>58</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7cd794mv</identifier><datestamp>2026-09-15T19:37:48Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7cd794mv</dc:identifier><dc:title>Prenatal Exposure to Per- and Polyfluoroalkyl Substances and Childhood Autism-related Outcomes</dc:title><dc:creator>Ames, Jennifer L</dc:creator><dc:creator>Burjak, Mohamad</dc:creator><dc:creator>Avalos, Lyndsay A</dc:creator><dc:creator>Braun, Joseph M</dc:creator><dc:creator>Bulka, Catherine M</dc:creator><dc:creator>Croen, Lisa A</dc:creator><dc:creator>Dunlop, Anne L</dc:creator><dc:creator>Ferrara, Assiamira</dc:creator><dc:creator>Fry, Rebecca C</dc:creator><dc:creator>Hedderson, Monique M</dc:creator><dc:creator>Karagas, Margaret R</dc:creator><dc:creator>Liang, Donghai</dc:creator><dc:creator>Lin, Pi-I D</dc:creator><dc:creator>Lyall, Kristen</dc:creator><dc:creator>Moore, Brianna</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>O’Connor, Thomas G</dc:creator><dc:creator>Oh, Jiwon</dc:creator><dc:creator>Padula, Amy M</dc:creator><dc:creator>Woodruff, Tracey J</dc:creator><dc:creator>Zhu, Yeyi</dc:creator><dc:creator>Hamra, Ghassan B</dc:creator><dc:creator>Outcomes, on behalf of program collaborators for Environmental influences on Child Health</dc:creator><dc:date>2023-05-01</dc:date><dc:description>BACKGROUND: Epidemiologic evidence linking prenatal exposure to per- and polyfluoroalkyl substances (PFAS) with altered neurodevelopment is inconclusive, and few large studies have focused on autism-related outcomes. We investigated whether blood concentrations of PFAS in pregnancy are associated with child autism-related outcomes.
METHODS: We included 10 cohorts from the National Institutes of Health (NIH)-funded Environmental influences on Child Health Outcomes (ECHO) program (n = 1,429). We measured 14 PFAS analytes in maternal blood collected during pregnancy; eight analytes met detection criteria for analysis. We assessed quantitative autism-related traits in children via parent report on the Social Responsiveness Scale (SRS). In multivariable linear models, we examined relationships of each PFAS (natural log-transformed) with SRS scores. We further modeled PFAS as a complex mixture using Bayesian methods and examined modification of these relationships by child sex.
RESULTS: Most PFAS in maternal blood were not associated with child SRS T-scores. Perfluorononanoic acid (PFNA) showed the strongest and most consistent association: each 1-unit increase in ln-transformed PFNA was associated with greater autism-related traits (adjusted β [95% confidence interval (CI)] = 1.5 [-0.1, 3.0]). The summed mixture, which included six PFAS detected in &amp;gt;70% of participants, was not associated with SRS T-scores (adjusted β [95% highest posterior density interval] = 0.7 [-1.4, 3.0]). We did not observe consistent evidence of sex differences.
CONCLUSIONS: Prenatal blood concentrations of PFNA may be associated with modest increases in child autism-related traits. Future work should continue to examine the relationship between exposures to both legacy and emerging PFAS and additional dimensional, quantitative measures of childhood autism-related outcomes.</dc:description><dc:subject>4206 Public Health (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Mental Health (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Autism (rcdc)</dc:subject><dc:subject>Brain Disorders (rcdc)</dc:subject><dc:subject>Endocrine Disruptors (rcdc)</dc:subject><dc:subject>Intellectual and Developmental Disabilities (IDD) (rcdc)</dc:subject><dc:subject>2.1 Biological and endogenous factors (hrcs-rac)</dc:subject><dc:subject>Reproductive health and childbirth (hrcs-hc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Prenatal Exposure Delayed Effects (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Autistic Disorder (mesh)</dc:subject><dc:subject>Bayes Theorem (mesh)</dc:subject><dc:subject>Fluorocarbons (mesh)</dc:subject><dc:subject>Alkanesulfonic Acids (mesh)</dc:subject><dc:subject>Autism</dc:subject><dc:subject>Fluorocarbon</dc:subject><dc:subject>Mixtures</dc:subject><dc:subject>Per- and polyfluoroalkyl substances</dc:subject><dc:subject>Pregnancy</dc:subject><dc:subject>Prenatal exposure</dc:subject><dc:subject>program collaborators for Environmental influences on Child Health Outcomes</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Prenatal Exposure Delayed Effects (mesh)</dc:subject><dc:subject>Alkanesulfonic Acids (mesh)</dc:subject><dc:subject>Fluorocarbons (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Bayes Theorem (mesh)</dc:subject><dc:subject>Autistic Disorder (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Prenatal Exposure Delayed Effects (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Autistic Disorder (mesh)</dc:subject><dc:subject>Bayes Theorem (mesh)</dc:subject><dc:subject>Fluorocarbons (mesh)</dc:subject><dc:subject>Alkanesulfonic Acids (mesh)</dc:subject><dc:subject>0104 Statistics (for)</dc:subject><dc:subject>1117 Public Health and Health Services (for)</dc:subject><dc:subject>Epidemiology (science-metrix)</dc:subject><dc:subject>4202 Epidemiology (for-2020)</dc:subject><dc:subject>4206 Public health (for-2020)</dc:subject><dc:subject>4905 Statistics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7cd794mv</dc:identifier><dc:identifier>https://escholarship.org/content/qt7cd794mv/qt7cd794mv.pdf</dc:identifier><dc:identifier>info:doi/10.1097/ede.0000000000001587</dc:identifier><dc:type>article</dc:type><dc:source>Epidemiology, vol 34, iss 3</dc:source><dc:coverage>450 - 459</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt88t642wk</identifier><datestamp>2026-09-15T19:34:01Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt88t642wk</dc:identifier><dc:title>iTat transgenic mice exhibit hyper-locomotion in the behavioral pattern monitor after chronic exposure to methamphetamine but are unaffected by Tat expression</dc:title><dc:creator>Ayoub, Samantha</dc:creator><dc:creator>Kenton, Johnny A</dc:creator><dc:creator>Milienne-Petiot, Morgane</dc:creator><dc:creator>Deben, Debbie S</dc:creator><dc:creator>Achim, Cristian</dc:creator><dc:creator>Geyer, Mark A</dc:creator><dc:creator>Perry, William</dc:creator><dc:creator>Grant, Igor E</dc:creator><dc:creator>Young, Jared W</dc:creator><dc:creator>Minassian, Arpi</dc:creator><dc:creator>TMARC</dc:creator><dc:date>2023-01-01</dc:date><dc:description>Although antiretroviral therapy (ART) has increased the quality of life and lifespan in people living with HIV (PWH), millions continue to suffer from the neurobehavioral effects of the virus. Additionally, the abuse of illicit drugs (methamphetamine in particular) is significantly higher in PWH compared to the general population, which may further impact their neurological functions. The HIV regulatory protein, Tat, has been implicated in the neurobehavioral impacts of HIV and is purported to inhibit dopamine transporter (DAT) function in a way similar to methamphetamine. Thus, we hypothesized that a combination of Tat expression and methamphetamine would exert synergistic deleterious effects on behavior and DAT expression. We examined the impact of chronic methamphetamine exposure on exploration in transgenic mice expressing human Tat (iTat) vs. their wildtype littermates using the behavioral pattern monitor (BPM). During baseline, mice exhibited sex-dependent differences in BPM behavior, which persisted through methamphetamine exposure, and Tat activation with doxycycline. We observed a main effect of methamphetamine, wherein exposure, irrespective of genotype, increased locomotor activity and decreased specific exploration. After doxycycline treatment, mice continued to exhibit drug-dependent alterations in locomotion, with no effect of Tat, or methamphetamine interactions. DAT levels were higher in wildtype, saline-exposed males compared to all other groups. These data support stimulant-induced changes of locomotor activity and exploration, and suggest that viral Tat and methamphetamine do not synergistically interact to alter these behaviors in mice. These findings are important for future studies attempting to disentangle the effect of substances that impact DAT on HAND-relevant behaviors using such transgenic animals.</dc:description><dc:subject>3214 Pharmacology and Pharmaceutical Sciences (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>Infectious Diseases (rcdc)</dc:subject><dc:subject>Substance Misuse (rcdc)</dc:subject><dc:subject>Basic Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Mental Health (rcdc)</dc:subject><dc:subject>Methamphetamine (rcdc)</dc:subject><dc:subject>Stimulant Use and Misuse (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>HIV/AIDS (rcdc)</dc:subject><dc:subject>Brain Disorders (rcdc)</dc:subject><dc:subject>Drug Abuse (NIDA only) (rcdc)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Mice</dc:subject><dc:subject>Transgenic (mesh)</dc:subject><dc:subject>Methamphetamine (mesh)</dc:subject><dc:subject>tat Gene Products</dc:subject><dc:subject>Human Immunodeficiency Virus (mesh)</dc:subject><dc:subject>Quality of Life (mesh)</dc:subject><dc:subject>Doxycycline (mesh)</dc:subject><dc:subject>HIV Infections (mesh)</dc:subject><dc:subject>Locomotion (mesh)</dc:subject><dc:subject>iTAT HIV model</dc:subject><dc:subject>Behavioral pattern monitor</dc:subject><dc:subject>Mouse</dc:subject><dc:subject>Movement</dc:subject><dc:subject>Exploration</dc:subject><dc:subject>Dopamine</dc:subject><dc:subject>TMARC</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Mice</dc:subject><dc:subject>Transgenic (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>HIV Infections (mesh)</dc:subject><dc:subject>Methamphetamine (mesh)</dc:subject><dc:subject>Doxycycline (mesh)</dc:subject><dc:subject>Locomotion (mesh)</dc:subject><dc:subject>Quality of Life (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>tat Gene Products</dc:subject><dc:subject>Human Immunodeficiency Virus (mesh)</dc:subject><dc:subject>Behavioral pattern monitor</dc:subject><dc:subject>Dopamine</dc:subject><dc:subject>Exploration</dc:subject><dc:subject>Mouse</dc:subject><dc:subject>Movement</dc:subject><dc:subject>iTAT HIV model</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Mice</dc:subject><dc:subject>Transgenic (mesh)</dc:subject><dc:subject>Methamphetamine (mesh)</dc:subject><dc:subject>tat Gene Products</dc:subject><dc:subject>Human Immunodeficiency Virus (mesh)</dc:subject><dc:subject>Quality of Life (mesh)</dc:subject><dc:subject>Doxycycline (mesh)</dc:subject><dc:subject>HIV Infections (mesh)</dc:subject><dc:subject>Locomotion (mesh)</dc:subject><dc:subject>1115 Pharmacology and Pharmaceutical Sciences (for)</dc:subject><dc:subject>Neurology &amp; Neurosurgery (science-metrix)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:subject>3214 Pharmacology and pharmaceutical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/88t642wk</dc:identifier><dc:identifier>https://escholarship.org/content/qt88t642wk/qt88t642wk.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.pbb.2022.173499</dc:identifier><dc:type>article</dc:type><dc:source>Pharmacology Biochemistry and Behavior, vol 222</dc:source><dc:coverage>173499</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3h14z7bd</identifier><datestamp>2026-09-15T19:33:55Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3h14z7bd</dc:identifier><dc:title>A science-based agenda for health-protective chemical assessments and decisions: overview and consensus statement</dc:title><dc:creator>Woodruff, Tracey J</dc:creator><dc:creator>Rayasam, Swati DG</dc:creator><dc:creator>Axelrad, Daniel A</dc:creator><dc:creator>Koman, Patricia D</dc:creator><dc:creator>Chartres, Nicholas</dc:creator><dc:creator>Bennett, Deborah H</dc:creator><dc:creator>Birnbaum, Linda S</dc:creator><dc:creator>Brown, Phil</dc:creator><dc:creator>Carignan, Courtney C</dc:creator><dc:creator>Cooper, Courtney</dc:creator><dc:creator>Cranor, Carl F</dc:creator><dc:creator>Diamond, Miriam L</dc:creator><dc:creator>Franjevic, Shari</dc:creator><dc:creator>Gartner, Eve C</dc:creator><dc:creator>Hattis, Dale</dc:creator><dc:creator>Hauser, Russ</dc:creator><dc:creator>Heiger-Bernays, Wendy</dc:creator><dc:creator>Joglekar, Rashmi</dc:creator><dc:creator>Lam, Juleen</dc:creator><dc:creator>Levy, Jonathan I</dc:creator><dc:creator>MacRoy, Patrick M</dc:creator><dc:creator>Maffini, Maricel V</dc:creator><dc:creator>Marquez, Emily C</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Nachman, Keeve E</dc:creator><dc:creator>Nielsen, Greylin H</dc:creator><dc:creator>Oksas, Catherine</dc:creator><dc:creator>Abrahamsson, Dimitri Panagopoulos</dc:creator><dc:creator>Patisaul, Heather B</dc:creator><dc:creator>Patton, Sharyle</dc:creator><dc:creator>Robinson, Joshua F</dc:creator><dc:creator>Rodgers, Kathryn M</dc:creator><dc:creator>Rossi, Mark S</dc:creator><dc:creator>Rudel, Ruthann A</dc:creator><dc:creator>Sass, Jennifer B</dc:creator><dc:creator>Sathyanarayana, Sheela</dc:creator><dc:creator>Schettler, Ted</dc:creator><dc:creator>Shaffer, Rachel M</dc:creator><dc:creator>Shamasunder, Bhavna</dc:creator><dc:creator>Shepard, Peggy M</dc:creator><dc:creator>Shrader-Frechette, Kristin</dc:creator><dc:creator>Solomon, Gina M</dc:creator><dc:creator>Subra, Wilma A</dc:creator><dc:creator>Vandenberg, Laura N</dc:creator><dc:creator>Varshavsky, Julia R</dc:creator><dc:creator>White, Roberta F</dc:creator><dc:creator>Zarker, Ken</dc:creator><dc:creator>Zeise, Lauren</dc:creator><dc:date>2023-01-12</dc:date><dc:description>The manufacture and production of industrial chemicals continues to increase, with hundreds of thousands of chemicals and chemical mixtures used worldwide, leading to widespread population exposures and resultant health impacts. Low-wealth communities and communities of color often bear disproportionate burdens of exposure and impact; all compounded by&amp;nbsp;regulatory delays to the detriment of public health. Multiple authoritative bodies and scientific consensus groups have called for actions to prevent harmful exposures via improved policy approaches. We worked across multiple disciplines to develop consensus recommendations for health-protective, scientific approaches to reduce harmful chemical exposures, which can be applied to current US policies governing industrial chemicals and environmental pollutants. This consensus identifies five principles and scientific recommendations for improving how agencies like the US Environmental Protection Agency (EPA) approach and conduct hazard and risk assessment and risk management analyses: (1) the financial burden of data generation for any given chemical on (or to be introduced to) the market should be on the chemical producers that benefit from their production and use; (2) lack of data does not equate to lack of hazard, exposure, or risk; (3) populations at greater risk, including those that are more susceptible or more highly exposed, must be better identified and protected to account for their real-world risks; (4) hazard and risk assessments should not assume existence of a “safe” or “no-risk” level of chemical exposure in the diverse general population; and (5) hazard and risk assessments must evaluate and account for financial conflicts of interest in the body of evidence. While many of these recommendations focus specifically on the EPA, they are general principles for environmental health that could be adopted by any agency or entity engaged in exposure, hazard, and risk assessment. We also detail recommendations for four priority areas in companion papers (exposure assessment methods, human variability assessment, methods for quantifying non-cancer health outcomes, and a framework for defining chemical classes). These recommendations constitute key steps for improved evidence-based environmental health decision-making and public health protection.</dc:description><dc:subject>4202 Epidemiology (for-2020)</dc:subject><dc:subject>4206 Public Health (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Climate-Related Exposures and Conditions (rcdc)</dc:subject><dc:subject>Endocrine Disruptors (rcdc)</dc:subject><dc:subject>2.2 Factors relating to the physical environment (hrcs-rac)</dc:subject><dc:subject>Generic health relevance (hrcs-hc)</dc:subject><dc:subject>15 Life on Land (sdg)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Environmental Health (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Public Health (mesh)</dc:subject><dc:subject>Risk Assessment (mesh)</dc:subject><dc:subject>Consensus Statements as Topic (mesh)</dc:subject><dc:subject>Chemicals</dc:subject><dc:subject>Conflicts of Interest</dc:subject><dc:subject>Environmental Health</dc:subject><dc:subject>Environmental Justice</dc:subject><dc:subject>EPA</dc:subject><dc:subject>Hazard Identification</dc:subject><dc:subject>Health Equity</dc:subject><dc:subject>Risk Assessment</dc:subject><dc:subject>TSCA</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Risk Assessment (mesh)</dc:subject><dc:subject>Environmental Health (mesh)</dc:subject><dc:subject>Public Health (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Consensus Statements as Topic (mesh)</dc:subject><dc:subject>Chemicals</dc:subject><dc:subject>Conflicts of Interest</dc:subject><dc:subject>EPA</dc:subject><dc:subject>Environmental Health</dc:subject><dc:subject>Environmental Justice</dc:subject><dc:subject>Hazard Identification</dc:subject><dc:subject>Health Equity</dc:subject><dc:subject>Risk Assessment</dc:subject><dc:subject>TSCA</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Environmental Health (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Public Health (mesh)</dc:subject><dc:subject>Risk Assessment (mesh)</dc:subject><dc:subject>Consensus Statements as Topic (mesh)</dc:subject><dc:subject>1117 Public Health and Health Services (for)</dc:subject><dc:subject>Toxicology (science-metrix)</dc:subject><dc:subject>4202 Epidemiology (for-2020)</dc:subject><dc:subject>4206 Public health (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3h14z7bd</dc:identifier><dc:identifier>https://escholarship.org/content/qt3h14z7bd/qt3h14z7bd.pdf</dc:identifier><dc:identifier>info:doi/10.1186/s12940-022-00930-3</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Health, vol 21, iss Suppl 1</dc:source><dc:coverage>132</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0xn1d73j</identifier><datestamp>2026-09-15T19:33:37Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0xn1d73j</dc:identifier><dc:title>Erratum: “Adiabatic matching of particle bunches in a plasma-based accelerator in the presence of ion motion” [Phys. Plasmas 28, 053102 (2021)]</dc:title><dc:creator>Benedetti, C</dc:creator><dc:creator>Mehrling, TJ</dc:creator><dc:creator>Schroeder, CB</dc:creator><dc:creator>Geddes, CGR</dc:creator><dc:creator>Esarey, E</dc:creator><dc:date>2023-01-01</dc:date><dc:description>We would like to correct an error affecting the horizontal scale of panels (c) and (d) of Fig. 4 in Ref. 1. A scale factor of kp was neglected when generating the plots. The correct figure is shown below. The authors would like to thank Yujian Zhao for pointing out this issue. We would also like to correct a typo introduced during the preparation of the proofs and affecting Eq. (25); the correct equation reads. (Formula presented).</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0203 Classical Physics (for)</dc:subject><dc:subject>Fluids &amp; Plasmas (science-metrix)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0xn1d73j</dc:identifier><dc:identifier>https://escholarship.org/content/qt0xn1d73j/qt0xn1d73j.pdf</dc:identifier><dc:identifier>info:doi/10.1063/5.0138482</dc:identifier><dc:type>article</dc:type><dc:source>Physics of Plasmas, vol 30, iss 1</dc:source><dc:coverage>019902</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9gt3k403</identifier><datestamp>2026-09-15T19:29:56Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9gt3k403</dc:identifier><dc:title>Longitudinal tapering in gas jets for increased efficiency of 10-GeV class laser plasma accelerators</dc:title><dc:creator>Li, R</dc:creator><dc:creator>Picksley, A</dc:creator><dc:creator>Benedetti, C</dc:creator><dc:creator>Filippi, F</dc:creator><dc:creator>Stackhouse, J</dc:creator><dc:creator>Fan-Chiang, L</dc:creator><dc:creator>Tsai, HE</dc:creator><dc:creator>Nakamura, K</dc:creator><dc:creator>Schroeder, CB</dc:creator><dc:creator>van Tilborg, J</dc:creator><dc:creator>Esarey, E</dc:creator><dc:creator>Geddes, CGR</dc:creator><dc:creator>Gonsalves, AJ</dc:creator><dc:date>2025-04-01</dc:date><dc:description>Modern laser plasma accelerators often require plasma waveguides tens of centimeters long to propagate a high-intensity drive laser pulse. Tapering the longitudinal gas density profile in 10&amp;nbsp;cm scale gas jets could allow for single stage laser plasma acceleration well beyond 10 GeV with current petawatt-class laser systems. Via simulation and interferometry measurements, we show density control by longitudinally adjusting the throat width and jet angle. Density profiles appropriate for tapering were calculated analytically and via particle-in-cell simulations and were matched experimentally. These simulations show that tapering can increase electron beam energy using 19&amp;nbsp;J laser energy from ∼9 GeV to &amp;gt;12 GeV in a 30&amp;nbsp;cm plasma and the accelerated charge by an order of magnitude.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>ATAP-2025 (c-lbnl-label)</dc:subject><dc:subject>ATAP-GENERAL (c-lbnl-label)</dc:subject><dc:subject>ATAP-BELLA Center (c-lbnl-label)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>03 Chemical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Applied Physics (science-metrix)</dc:subject><dc:subject>34 Chemical sciences (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9gt3k403</dc:identifier><dc:identifier>https://escholarship.org/content/qt9gt3k403/qt9gt3k403.pdf</dc:identifier><dc:identifier>info:doi/10.1063/5.0250698</dc:identifier><dc:type>article</dc:type><dc:source>Review of Scientific Instruments, vol 96, iss 4</dc:source><dc:coverage>043306</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt80c2w987</identifier><datestamp>2026-09-15T19:29:46Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt80c2w987</dc:identifier><dc:title>Author Correction: A genomic catalog of Earth’s microbiomes</dc:title><dc:creator>Nayfach, Stephen</dc:creator><dc:creator>Roux, Simon</dc:creator><dc:creator>Seshadri, Rekha</dc:creator><dc:creator>Udwary, Daniel</dc:creator><dc:creator>Varghese, Neha</dc:creator><dc:creator>Schulz, Frederik</dc:creator><dc:creator>Wu, Dongying</dc:creator><dc:creator>Paez-Espino, David</dc:creator><dc:creator>Chen, I-Min</dc:creator><dc:creator>Huntemann, Marcel</dc:creator><dc:creator>Palaniappan, Krishna</dc:creator><dc:creator>Ladau, Joshua</dc:creator><dc:creator>Mukherjee, Supratim</dc:creator><dc:creator>Reddy, TBK</dc:creator><dc:creator>Nielsen, Torben</dc:creator><dc:creator>Kirton, Edward</dc:creator><dc:creator>Faria, José P</dc:creator><dc:creator>Edirisinghe, Janaka N</dc:creator><dc:creator>Henry, Christopher S</dc:creator><dc:creator>Jungbluth, Sean P</dc:creator><dc:creator>Chivian, Dylan</dc:creator><dc:creator>Dehal, Paramvir</dc:creator><dc:creator>Wood-Charlson, Elisha M</dc:creator><dc:creator>Arkin, Adam P</dc:creator><dc:creator>Tringe, Susannah G</dc:creator><dc:creator>Visel, Axel</dc:creator><dc:creator>Woyke, Tanja</dc:creator><dc:creator>Mouncey, Nigel J</dc:creator><dc:creator>Ivanova, Natalia N</dc:creator><dc:creator>Kyrpides, Nikos C</dc:creator><dc:creator>Eloe-Fadrosh, Emiley A</dc:creator><dc:date>2021-04-01</dc:date><dc:description>A Correction to this paper has been published: https://doi.org/10.1038/s41587-021-00898-4.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>IMG/M Data Consortium</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/80c2w987</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1038/s41587-021-00898-4</dc:identifier><dc:type>article</dc:type><dc:source>Nature Biotechnology, vol 39, iss 4</dc:source><dc:coverage>521 - 521</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4zc9j5fr</identifier><datestamp>2026-09-15T19:26:06Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4zc9j5fr</dc:identifier><dc:title>Current distribution monitoring enables quench and damage detection in superconducting fusion magnets</dc:title><dc:creator>Teyber, Reed</dc:creator><dc:creator>Weiss, Jeremy</dc:creator><dc:creator>Marchevsky, Maxim</dc:creator><dc:creator>Prestemon, Soren</dc:creator><dc:creator>van der Laan, Danko</dc:creator><dc:date>2022-12-28</dc:date><dc:description>Fusion magnets made from high temperature superconducting ReBCO CORC®&amp;nbsp;cables are typically protected with quench detection systems that use voltage or temperature measurements to trigger current extraction processes. Although small coils with low inductances have been demonstrated, magnet protection remains a challenge and magnets are typically operated with little knowledge of the intrinsic performance parameters. We propose a protection framework based on current distribution monitoring in fusion cables with limited inter-cable current sharing. By employing inverse Biot-Savart techniques to distributed Hall probe arrays around CORC®&amp;nbsp;Cable-In-Conduit-Conductor (CICC) terminations, individual cable currents are recreated and used to extract the parameters of a predictive model. These parameters are shown to be of value for detecting conductor damage and defining safe magnet operating limits. The trained model is then used to predict cable current distributions in real-time, and departures between predictions and inverse Biot-Savart recreated current distributions are used to generate quench triggers. The methodology shows promise for quality control, operational planning and real-time quench detection in bundled CORC®&amp;nbsp;cables for compact fusion reactors.</dc:description><dc:subject>4605 Data Management and Data Science (for-2020)</dc:subject><dc:subject>46 Information and Computing Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4zc9j5fr</dc:identifier><dc:identifier>https://escholarship.org/content/qt4zc9j5fr/qt4zc9j5fr.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41598-022-26592-2</dc:identifier><dc:type>article</dc:type><dc:source>Scientific Reports, vol 12, iss 1</dc:source><dc:coverage>22503</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt49f6f7v9</identifier><datestamp>2026-09-15T19:25:35Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt49f6f7v9</dc:identifier><dc:title>Identifying Vulnerable Populations through an Examination of the Association Between Multipollutant Profiles and Poverty</dc:title><dc:creator>Molitor, John</dc:creator><dc:creator>Su, Jason G</dc:creator><dc:creator>Molitor, Nuoo-Ting</dc:creator><dc:creator>Rubio, Virgilio Gómez</dc:creator><dc:creator>Richardson, Sylvia</dc:creator><dc:creator>Hastie, David</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Jerrett, Michael</dc:creator><dc:date>2011-09-15</dc:date><dc:description>Recently, concerns have centered on how to expand knowledge on the limited science related to the cumulative impact of multiple air pollution exposures and the potential vulnerability of poor communities to their toxic effects. The highly intercorrelated nature of exposures makes application of standard regression-based methods to these questions problematic due to well-known issues related to multicollinearity. Our paper addresses these problems by using, as its basic unit of inference, a profile consisting of a pattern of exposure values. These profiles are grouped into clusters and associated with a deprivation outcome. Specifically, we examine how profiles of NO(2)-, PM(2.5)-, and diesel- (road and off-road) based exposures are associated with the number of individuals living under poverty in census tracts (CT's) in Los Angeles County. Results indicate that higher levels of pollutants are generally associated with higher poverty counts, though the association is complex and nonlinear. Our approach is set in the Bayesian framework, and as such the entire model can be fit as a unit using modern Bayesian multilevel modeling techniques via the freely available WinBUGS software package, (1) though we have used custom-written C++ code (validated with WinBUGS) to improve computational speed. The modeling approach proposed thus goes beyond single-pollutant models in that it allows us to determine the association between entire multipollutant profiles of exposures with poverty levels in small geographic areas in Los Angeles County.</dc:description><dc:subject>4202 Epidemiology (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>44 Human Society (for-2020)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Climate-Related Exposures and Conditions (rcdc)</dc:subject><dc:subject>1 No Poverty (sdg)</dc:subject><dc:subject>Air Pollutants (mesh)</dc:subject><dc:subject>Bayes Theorem (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Theoretical (mesh)</dc:subject><dc:subject>Nitrogen Dioxide (mesh)</dc:subject><dc:subject>Particulate Matter (mesh)</dc:subject><dc:subject>Poverty (mesh)</dc:subject><dc:subject>Vehicle Emissions (mesh)</dc:subject><dc:subject>Vulnerable Populations (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Nitrogen Dioxide (mesh)</dc:subject><dc:subject>Air Pollutants (mesh)</dc:subject><dc:subject>Bayes Theorem (mesh)</dc:subject><dc:subject>Vehicle Emissions (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Theoretical (mesh)</dc:subject><dc:subject>Poverty (mesh)</dc:subject><dc:subject>Vulnerable Populations (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Particulate Matter (mesh)</dc:subject><dc:subject>Air Pollutants (mesh)</dc:subject><dc:subject>Bayes Theorem (mesh)</dc:subject><dc:subject>California (mesh)</dc:subject><dc:subject>Environmental Exposure (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Theoretical (mesh)</dc:subject><dc:subject>Nitrogen Dioxide (mesh)</dc:subject><dc:subject>Particulate Matter (mesh)</dc:subject><dc:subject>Poverty (mesh)</dc:subject><dc:subject>Vehicle Emissions (mesh)</dc:subject><dc:subject>Vulnerable Populations (mesh)</dc:subject><dc:subject>Environmental Sciences (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/49f6f7v9</dc:identifier><dc:identifier>https://escholarship.org/content/qt49f6f7v9/qt49f6f7v9.pdf</dc:identifier><dc:identifier>info:doi/10.1021/es104017x</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Science and Technology, vol 45, iss 18</dc:source><dc:coverage>7754 - 7760</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5cx7z609</identifier><datestamp>2026-09-15T19:22:27Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5cx7z609</dc:identifier><dc:title>Equivariant Perturbation in Gomory and Johnson’s Infinite Group Problem. VII. Inverse Semigroup Theory, Closures, Decomposition of Perturbations</dc:title><dc:creator>Hildebrand, Robert</dc:creator><dc:creator>Köppe, Matthias</dc:creator><dc:creator>Zhou, Yuan</dc:creator><dc:date>2022-01-01</dc:date><dc:description>In this self-contained paper, we present a theory of the piecewise linear minimal valid functions for the 1-row Gomory–Johnson infinite group problem. The non-extreme minimal valid functions are those that admit effective perturbations. We give a precise description of the space of these perturbations as a direct sum of certain finite- and infinite-dimensional subspaces. The infinite-dimensional subspaces have partial symmetries; to describe them, we develop a theory of inverse semigroups of partial bijections, interacting with the functional equations satisfied by the perturbations. Our paper provides the foundation for grid-free algorithms for the Gomory–Johnson model, in particular for testing extremality of piecewise linear functions whose breakpoints are rational numbers with huge denominators.</dc:description><dc:subject>4901 Applied Mathematics (for-2020)</dc:subject><dc:subject>4904 Pure Mathematics (for-2020)</dc:subject><dc:subject>49 Mathematical Sciences (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5cx7z609</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.5802/ojmo.16</dc:identifier><dc:type>article</dc:type><dc:source>Open Journal of Mathematical Optimization, vol 3</dc:source><dc:coverage>1 - 44</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt68p1908r</identifier><datestamp>2026-09-15T19:18:16Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt68p1908r</dc:identifier><dc:title>CUPID: The Next-Generation Neutrinoless Double Beta Decay Experiment</dc:title><dc:creator>Alfonso, K</dc:creator><dc:creator>Armatol, A</dc:creator><dc:creator>Augier, C</dc:creator><dc:creator>Avignone, FT</dc:creator><dc:creator>Azzolini, O</dc:creator><dc:creator>Balata, M</dc:creator><dc:creator>Barabash, AS</dc:creator><dc:creator>Bari, G</dc:creator><dc:creator>Barresi, A</dc:creator><dc:creator>Baudin, D</dc:creator><dc:creator>Bellini, F</dc:creator><dc:creator>Benato, G</dc:creator><dc:creator>Beretta, M</dc:creator><dc:creator>Bettelli, M</dc:creator><dc:creator>Biassoni, M</dc:creator><dc:creator>Billard, J</dc:creator><dc:creator>Boldrini, V</dc:creator><dc:creator>Branca, A</dc:creator><dc:creator>Brofferio, C</dc:creator><dc:creator>Bucci, C</dc:creator><dc:creator>Camilleri, J</dc:creator><dc:creator>Campani, A</dc:creator><dc:creator>Capelli, C</dc:creator><dc:creator>Capelli, S</dc:creator><dc:creator>Cappelli, L</dc:creator><dc:creator>Cardani, L</dc:creator><dc:creator>Carniti, P</dc:creator><dc:creator>Casali, N</dc:creator><dc:creator>Celi, E</dc:creator><dc:creator>Chang, C</dc:creator><dc:creator>Chiesa, D</dc:creator><dc:creator>Clemenza, M</dc:creator><dc:creator>Colantoni, I</dc:creator><dc:creator>Copello, S</dc:creator><dc:creator>Craft, E</dc:creator><dc:creator>Cremonesi, O</dc:creator><dc:creator>Creswick, RJ</dc:creator><dc:creator>Cruciani, A</dc:creator><dc:creator>D’Addabbo, A</dc:creator><dc:creator>D’Imperio, G</dc:creator><dc:creator>Dabagov, S</dc:creator><dc:creator>Dafinei, I</dc:creator><dc:creator>Danevich, FA</dc:creator><dc:creator>De Jesus, M</dc:creator><dc:creator>De Marcillac, P</dc:creator><dc:creator>Dell’Oro, S</dc:creator><dc:creator>Domizio, S Di</dc:creator><dc:creator>Lorenzo, S Di</dc:creator><dc:creator>Dixon, T</dc:creator><dc:creator>Dompè, V</dc:creator><dc:creator>Drobizhev, A</dc:creator><dc:creator>Dumoulin, L</dc:creator><dc:creator>Fantini, G</dc:creator><dc:creator>Faverzani, M</dc:creator><dc:creator>Ferri, E</dc:creator><dc:creator>Ferri, F</dc:creator><dc:creator>Ferroni, F</dc:creator><dc:creator>Figueroa-Feliciano, E</dc:creator><dc:creator>Foggetta, L</dc:creator><dc:creator>Formaggio, J</dc:creator><dc:creator>Franceschi, A</dc:creator><dc:creator>Fu, C</dc:creator><dc:creator>Fu, S</dc:creator><dc:creator>Fujikawa, BK</dc:creator><dc:creator>Gallas, A</dc:creator><dc:creator>Gascon, J</dc:creator><dc:creator>Ghislandi, S</dc:creator><dc:creator>Giachero, A</dc:creator><dc:creator>Gianvecchio, A</dc:creator><dc:creator>Gironi, L</dc:creator><dc:creator>Giuliani, A</dc:creator><dc:creator>Gorla, P</dc:creator><dc:creator>Gotti, C</dc:creator><dc:creator>Grant, C</dc:creator><dc:creator>Gras, P</dc:creator><dc:creator>Guillaumon, PV</dc:creator><dc:creator>Gutierrez, TD</dc:creator><dc:creator>Han, K</dc:creator><dc:creator>Hansen, EV</dc:creator><dc:creator>Heeger, KM</dc:creator><dc:creator>Helis, DL</dc:creator><dc:creator>Huang, HZ</dc:creator><dc:creator>Imbert, L</dc:creator><dc:creator>Johnston, J</dc:creator><dc:creator>Juillard, A</dc:creator><dc:creator>Karapetrov, G</dc:creator><dc:creator>Keppel, G</dc:creator><dc:creator>Khalife, H</dc:creator><dc:creator>Kobychev, VV</dc:creator><dc:creator>Kolomensky, Yu G</dc:creator><dc:creator>Konovalov, SI</dc:creator><dc:creator>Kowalski, R</dc:creator><dc:creator>Langford, T</dc:creator><dc:creator>Lefevre, M</dc:creator><dc:creator>Liu, R</dc:creator><dc:creator>Liu, Y</dc:creator><dc:creator>Loaiza, P</dc:creator><dc:creator>Ma, L</dc:creator><dc:creator>Madhukuttan, M</dc:creator><dc:creator>Mancarella, F</dc:creator><dc:date>2023-06-01</dc:date><dc:description>CUPID is a next-generation tonne-scale bolometric neutrinoless double beta decay experiment that will probe the Majorana nature of neutrinos and discover lepton number violation in case of observation of this singular process. CUPID will be built on experience, expertise and lessons learned in CUORE and will be installed in the current CUORE infra-structure in the Gran Sasso underground laboratory. The CUPID detector technology, successfully tested in the CUPID-Mo experiment, is based on scintillating bolometers of Li2$$_2$$MoO4$$_4$$ enriched in the isotope of interest 100$$^{100}$$Mo. In order to achieve its ambitious science goals, the CUPID collaboration aims to reduce the backgrounds in the region of interest by a factor 100 with respect to CUORE. This performance will be achieved by introducing the high efficient α$$\alpha$$/β$$\beta$$ discrimination demonstrated by the CUPID-0 and CUPID-Mo experiments, and using a high transition energy double beta decay nucleus such as 100$$^{100}$$Mo to minimize the impact of the gamma background. CUPID will consist of about 1500 hybrid heat-light detectors for a total isotope mass of 250&amp;nbsp;kg. The CUPID scientific reach is supported by a detailed and safe background model based on CUORE, CUPID-Mo and CUPID-0 results. The required performances have already been demonstrated and will be presented.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Neutrinoless double beta decay</dc:subject><dc:subject>Bolometers</dc:subject><dc:subject>Low radioactivity</dc:subject><dc:subject>Cryostat</dc:subject><dc:subject>Next-generation bolometric experiment</dc:subject><dc:subject>NSD-Neutrinos (c-lbnl-label)</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0203 Classical Physics (for)</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>5103 Classical physics (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/68p1908r</dc:identifier><dc:identifier>https://escholarship.org/content/qt68p1908r/qt68p1908r.pdf</dc:identifier><dc:identifier>info:doi/10.1007/s10909-022-02909-3</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Low Temperature Physics, vol 211, iss 5-6</dc:source><dc:coverage>375 - 383</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt27s7m0kh</identifier><datestamp>2026-09-15T19:14:15Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt27s7m0kh</dc:identifier><dc:title>Design, fabrication, and characterization of a high-field high-temperature superconducting Bi-2212 accelerator dipole magnet</dc:title><dc:creator>Shen, Tengming</dc:creator><dc:creator>Fajardo, Laura Garcia</dc:creator><dc:creator>Myers, Cory</dc:creator><dc:creator>Hafalia, Aurelio</dc:creator><dc:creator>Fernández, Jose Luis Rudeiros</dc:creator><dc:creator>Arbelaez, Diego</dc:creator><dc:creator>Brouwer, Lucas</dc:creator><dc:creator>Caspi, Shlomo</dc:creator><dc:creator>Ferracin, Paolo</dc:creator><dc:creator>Gourlay, Stephen</dc:creator><dc:creator>Marchevsky, Maxim</dc:creator><dc:creator>Pong, Ian</dc:creator><dc:creator>Prestemon, Soren</dc:creator><dc:creator>Teyber, Reed</dc:creator><dc:creator>Turqueti, Marcos</dc:creator><dc:creator>Wang, Xiaorong</dc:creator><dc:creator>Jiang, Jianyi</dc:creator><dc:creator>Bosque, Ernesto</dc:creator><dc:creator>Lu, Jun</dc:creator><dc:creator>Davis, Daniel</dc:creator><dc:creator>Trociewitz, Ulf</dc:creator><dc:creator>Hellstrom, Eric</dc:creator><dc:creator>Larbalestier, David</dc:creator><dc:date>2022-12-01</dc:date><dc:description>The use of high-field superconducting magnets has furthered the development of medical diagnosis, fusion research, accelerators, and particle physics. High-temperature superconductors enable magnets more powerful than those possible with Nb-Ti (superconducting transition temperature Tc of 9.2 K) and Nb3Sn (Tc of 18.4 K) conductors due to their very high critical field Bc2 of greater than 100 T near 4.2 K. However, the development of high-field accelerator magnets using high-temperature superconductors is still at its early stage. We report the construction of the world’s first high-temperature superconducting Bi2Sr2CaCu2Ox (Bi-2212 with Tc of ∼82 K) accelerator dipole magnet. The magnet is based on a canted-cosine-theta design with Bi-2212 Rutherford cables. A high critical current was achieved by an overpressure processing heat treatment. The magnet was constructed from a nine-strand Rutherford cable made from industrial 0.8 mm wires. At 4.2 K, it reached a quench current of 3600 A and a dipole field of 1.64 T in a bore of 31 mm. The magnet did not exhibit the undesirable quench training common in Nb-Ti and Nb3Sn accelerator magnets. It quenched a dozen times without degradation. The magnet exhibited low magnetic field hysteresis (&amp;lt;0.1%) as measured by a cryogenic Hall sensor. It was fast cycled to 1.47 T at 0.54 T/s without quenches. This work validates the canted-cosine-theta Bi-2212 dipole magnet design, illustrates the fabrication scheme, and establishes an initial performance benchmark.</dc:description><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>5104 Condensed Matter Physics (for-2020)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/27s7m0kh</dc:identifier><dc:identifier>https://escholarship.org/content/qt27s7m0kh/qt27s7m0kh.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevaccelbeams.25.122401</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review Accelerators and Beams, vol 25, iss 12</dc:source><dc:coverage>122401</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3xk50079</identifier><datestamp>2026-09-15T19:14:01Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3xk50079</dc:identifier><dc:title>Get on the BAND Wagon: a Bayesian framework for quantifying model uncertainties in nuclear dynamics</dc:title><dc:creator>Phillips, DR</dc:creator><dc:creator>Furnstahl, RJ</dc:creator><dc:creator>Heinz, U</dc:creator><dc:creator>Maiti, T</dc:creator><dc:creator>Nazarewicz, W</dc:creator><dc:creator>Nunes, FM</dc:creator><dc:creator>Plumlee, M</dc:creator><dc:creator>Pratola, MT</dc:creator><dc:creator>Pratt, S</dc:creator><dc:creator>Viens, FG</dc:creator><dc:creator>Wild, SM</dc:creator><dc:date>2021-07-01</dc:date><dc:description>We describe the Bayesian analysis of nuclear dynamics (BAND) framework, a cyberinfrastructure that we are developing which will unify the treatment of nuclear models, experimental data, and associated uncertainties. We overview the statistical principles and nuclear-physics contexts underlying the BAND toolset, with an emphasis on Bayesian methodology’s ability to leverage insights from multiple models. In order to facilitate understanding of these tools, we provide a simple and accessible example of the BAND framework’s application. Four case studies are presented to highlight how elements of the framework will enable progress in complex, far-ranging problems in nuclear physics (NP). By collecting notation and terminology, providing illustrative examples, and giving an overview of the associated techniques, this paper aims to open paths through which the NP and statistics communities can contribute to and build upon the BAND framework.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>statistical methods</dc:subject><dc:subject>uncertainty quantification</dc:subject><dc:subject>experimental design</dc:subject><dc:subject>heavy-ion collisions</dc:subject><dc:subject>nuclear mass models</dc:subject><dc:subject>nuclear reactions</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3xk50079</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1088/1361-6471/abf1df</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Physics G Nuclear and Particle Physics, vol 48, iss 7</dc:source><dc:coverage>072001</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1n09z7cb</identifier><datestamp>2026-09-15T19:10:21Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1n09z7cb</dc:identifier><dc:title>Tracking Mechanical Stress and Cell Migration with Inexpensive Polymer Thin‐Film Sensors</dc:title><dc:creator>Finney, Tanner J</dc:creator><dc:creator>Frank, Skye L</dc:creator><dc:creator>Bull, Michael R</dc:creator><dc:creator>Guy, Robert D</dc:creator><dc:creator>Kuhl, Tonya L</dc:creator><dc:date>2023-01-01</dc:date><dc:description>Polydiacetylene (PDA) Langmuir films are well known for their blue to red chromatic transitions in response to a variety of stimuli, including UV light, heat, bio-molecule bindings and mechanical stress. In this work, we detail the ability to tune PDA Langmuir films to exhibit discrete chromatic transitions in response to applied mechanical stress. Normal and shear-induced transitions were quantified using the Surface Forces Apparatus and established to be binary and tunable as a function of film formation conditions. Both monomer alkyl tail length and metal cations were used to manipulate the chromatic transition force threshold to enable discrete force sensing from ~50 to ~500 nN μm-2 for normal loading and ~2 to ~40 nN μm-2 for shear-induced transitions, which are appropriate for biological cells. The utility of PDA thin-film sensors was demonstrated with the slime mold Physarum polycephalum. The fluorescence readout of the films enabled: the area explored by Physarum to be visualized, the forces involved in locomotion to be quantified, and revealed novel puncta formation potentially associated with Physarum sampling its environment.</dc:description><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>4016 Materials Engineering (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>cell migration</dc:subject><dc:subject>mechanochromism</dc:subject><dc:subject>polydiacetylenes</dc:subject><dc:subject>slime mold</dc:subject><dc:subject>surface forces apparatus</dc:subject><dc:subject>Cell migration</dc:subject><dc:subject>Mechanochromism</dc:subject><dc:subject>Polydiacetylenes</dc:subject><dc:subject>Slime Mold</dc:subject><dc:subject>Surface Forces Apparatus</dc:subject><dc:subject>0306 Physical Chemistry (incl. Structural) (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>3403 Macromolecular and materials chemistry (for-2020)</dc:subject><dc:subject>4016 Materials engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1n09z7cb</dc:identifier><dc:identifier>https://escholarship.org/content/qt1n09z7cb/qt1n09z7cb.pdf</dc:identifier><dc:identifier>info:doi/10.1002/admi.202201808</dc:identifier><dc:type>article</dc:type><dc:source>Advanced Materials Interfaces, vol 10, iss 2</dc:source><dc:coverage>2201808</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1c4340md</identifier><datestamp>2026-09-15T19:05:59Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1c4340md</dc:identifier><dc:title>Trusted CI Operational Technology Procurement Vendor Matrix</dc:title><dc:creator>Peisert, Sean</dc:creator><dc:creator>Adams, Andrew</dc:creator><dc:creator>Arnold, Daniel</dc:creator><dc:creator>Dopheide, Jeannette</dc:creator><dc:creator>Kiser, Ryan</dc:creator><dc:creator>Krenz, Mark</dc:creator><dc:creator>Jones, Mikeal</dc:creator><dc:creator>Paine, Drew</dc:creator><dc:creator>Simpson, Michael</dc:creator><dc:creator>Zage, John</dc:creator><dc:date>2023-12-14</dc:date><dc:description>Operational Technology (OT), when installed on an organization's network, becomes part of the overall cyber attack surface for an organization. When procuring this OT, it is important for the purchasing organization to understand how it will integrate with the existing network and security controls as well as understand what new risks it might introduce. This document provides a prioritized list of questions for organizations to send to manufacturers and suppliers to try to get as much of this information as possible. 

Audience: Organizational leadership, procurement department, IT, cybersecurity

How to use this document: On the "Matrix" sheet of this spreadsheet document there is a list of questions for equipment vendors related to operational technology (OT). Read through the questions and familiarize yourself with them. During the procurement phase of any operational technology, you can send these questions to the OT manufacturer. It is expected that the manufacturer may take some time to get back all the information to you, so it wouldn't be unusual to have to wait a month. Make sure you plan for that in your procurement schedule. Once you receive answers from the manufacturer, it is strongly recommended that you share that information with your Cybersecurity and/or IT operations staff for a technical review and input. If you find the manufacturer's answers to be inadequate for your security needs, it is helpful to the community if you can provide the manufacturer that feedback so that they have a better understanding of the security needs of their customers. 

Companion document to the Guide to Using the Trusted CI OT Procurement Matrix.</dc:description><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1c4340md</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.5281/zenodo.13743313</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0rw8w2xf</identifier><datestamp>2026-09-15T18:53:39Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0rw8w2xf</dc:identifier><dc:title>Strong-field QED experiments using the BELLA PW laser dual beamlines</dc:title><dc:creator>Turner, M</dc:creator><dc:creator>Bulanov, SS</dc:creator><dc:creator>Benedetti, C</dc:creator><dc:creator>Gonsalves, AJ</dc:creator><dc:creator>Leemans, WP</dc:creator><dc:creator>Nakamura, K</dc:creator><dc:creator>van Tilborg, J</dc:creator><dc:creator>Schroeder, CB</dc:creator><dc:creator>Geddes, CGR</dc:creator><dc:creator>Esarey, E</dc:creator><dc:date>2022-11-01</dc:date><dc:description>The petawatt (PW) laser facility of the Berkeley Lab Laser Accelerator (BELLA) Center has recently commissioned its second laser pulse transport line. This new beamline can be operated in parallel with the first beamline and enables strong-field quantum electrodynamics (SF-QED) experiments at BELLA. In this paper, we present an overview of the upgraded BELLA PW facility with a SF-QED experimental layout in which intense laser pulses collide with GeV-class laser-wakefield-accelerated electron beams. We present simulation results showing that experiments will allow the study of laser-particle interactions from the classical to the SF-QED regime with a nonlinear quantum parameter of up to χ∼$$\chi \sim $$2. In addition, we show that experiments will enable the study and production of GeV-class, mrad-divergence positron beams via the Breit–Wheeler process.Graphical abstract</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>ATAP-BELLA Center (c-lbnl-label)</dc:subject><dc:subject>ATAP-GENERAL (c-lbnl-label)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0rw8w2xf</dc:identifier><dc:identifier>https://escholarship.org/content/qt0rw8w2xf/qt0rw8w2xf.pdf</dc:identifier><dc:identifier>info:doi/10.1140/epjd/s10053-022-00535-y</dc:identifier><dc:type>article</dc:type><dc:source>The European Physical Journal D, vol 76, iss 11</dc:source><dc:coverage>205</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4mx247ng</identifier><datestamp>2026-09-15T18:53:28Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4mx247ng</dc:identifier><dc:title>Aerobic respiration controls on shale weathering</dc:title><dc:creator>Stolze, Lucien</dc:creator><dc:creator>Arora, Bhavna</dc:creator><dc:creator>Dwivedi, Dipankar</dc:creator><dc:creator>Steefel, Carl</dc:creator><dc:creator>Li, Zhi</dc:creator><dc:creator>Carrero, Sergio</dc:creator><dc:creator>Gilbert, Benjamin</dc:creator><dc:creator>Nico, Peter</dc:creator><dc:creator>Bill, Markus</dc:creator><dc:date>2023-01-01</dc:date><dc:description>The weathering of shale exerts an important control on the hydrochemical fluxes to river systems, thus influencing the global carbon, nutrient, and geochemical cycles. However, the quantitative understanding of shale weathering and its impact on global biogeochemical cycles remains inadequate due to the complex interplay between hydrological, biogeochemical, and physical processes. In this study, we develop a novel modeling approach to quantitatively interpret the long-term chemical weathering of shale occurring since the last glaciation period (15,000&amp;nbsp;years) leading to the present geochemical conditions. The model explicitly considers processes occurring across multiple phases and involved in the weathering, including: (i) the infiltration of meteoric water, (ii) the interactions between the water and the mineral assemblage via dissolution/precipitation reactions, (iii) the microbially-mediated oxidation of organic matter, (iv) the evolution of porosity induced by mineral reactions, and (v) the exchange of gases between the subsurface and the atmosphere. To implement and test our model, we conduct this study at a well-instrumented hillslope underlain by Mancos Shale and located at the East River study site, Western Colorado. Consistent with field observations, the model successfully reproduces the stratified weathering front, the complex spatial distribution of organic carbon, and the gaseous emissions of carbon dioxide from the subsurface. Model simulations show that aerobic respiration exerts a fundamental control on the weathering of shale. While previous studies have highlighted the diffusion of oxygen from the atmosphere as the primary mechanism for shale weathering, our model simulations demonstrate that aerobic respiration limits the propagation of oxygen in the shallow subsurface, and thereby inhibits the dissolution of pyrite at depth. Aerobic respiration is particularly favored in the top soil horizon due to the constant flux of oxygen from the atmosphere, the replenishment of fresh litter/plant-derived organic matter, and to a lesser extent the presence of fossil shale-associated organic matter. The acidic pore water generated through aerobic respiration within the shallow subsurface is transported to greater depths, where it sustains the dissolution of carbonate (dolomite in this example). Overall, our results demonstrate that the evolution of pyrite and carbonate depletion fronts are significantly different, and primarily depend on the ability of microorganisms to carry out microbial respiration and the various transport pathways of reactants controlling the mineral reactions under partially saturated conditions.</dc:description><dc:subject>3707 Hydrology (for-2020)</dc:subject><dc:subject>3703 Geochemistry (for-2020)</dc:subject><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>14 Life Below Water (sdg)</dc:subject><dc:subject>Shale weathering</dc:subject><dc:subject>Aerobic respiration</dc:subject><dc:subject>Multiphase transport</dc:subject><dc:subject>Carbon cycling</dc:subject><dc:subject>Reactive transport modeling</dc:subject><dc:subject>0402 Geochemistry (for)</dc:subject><dc:subject>0403 Geology (for)</dc:subject><dc:subject>0406 Physical Geography and Environmental Geoscience (for)</dc:subject><dc:subject>Geochemistry &amp; Geophysics (science-metrix)</dc:subject><dc:subject>3703 Geochemistry (for-2020)</dc:subject><dc:subject>3705 Geology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4mx247ng</dc:identifier><dc:identifier>https://escholarship.org/content/qt4mx247ng/qt4mx247ng.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.gca.2022.11.002</dc:identifier><dc:type>article</dc:type><dc:source>Geochimica et Cosmochimica Acta, vol 340</dc:source><dc:coverage>172 - 188</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4tz8f9q1</identifier><datestamp>2026-09-15T18:53:24Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4tz8f9q1</dc:identifier><dc:title>An initial magnet experiment using high-temperature superconducting STAR® wires</dc:title><dc:creator>Wang, Xiaorong</dc:creator><dc:creator>Bogdanof, Timothy J</dc:creator><dc:creator>Ferracin, Paolo</dc:creator><dc:creator>Ghiorso, William B</dc:creator><dc:creator>Gourlay, Stephen A</dc:creator><dc:creator>Higley, Hugh C</dc:creator><dc:creator>Kadiyala, Janakiram Kaushal</dc:creator><dc:creator>Kar, Soumen</dc:creator><dc:creator>Lee, Reginald</dc:creator><dc:creator>Luo, Linqing</dc:creator><dc:creator>Maruszewski, Maxwell A</dc:creator><dc:creator>Memmo, Robert</dc:creator><dc:creator>Myers, Cory S</dc:creator><dc:creator>Prestemon, Soren O</dc:creator><dc:creator>Sandra, Jithin Sai</dc:creator><dc:creator>Selvamanickam, Venkat</dc:creator><dc:creator>Teyber, Reed</dc:creator><dc:creator>Turqueti, Marcos</dc:creator><dc:creator>Wu, Yuxin</dc:creator><dc:date>2022-12-01</dc:date><dc:description>A dipole magnet generating 20 T and beyond will require high-temperature superconductors such as Bi2Sr2CaCu2O 8−x and REBa2Cu3O 7−x (RE = rare earth, rebco). Symmetric tape round (star®) wires based on rebco tapes are emerging as a potential conductor for such a magnet, demonstrating a whole-conductor current density of 580 A mm−2 at 20 T, 4.2 K, and at a bend radius of 15 mm. There are, however, few magnet developments using star® wires. Here we report a subscale canted cosθ dipole magnet as an initial experiment for two purposes: to evaluate the conductor performance in a magnet configuration and to start developing the magnet technology, leveraging the small bend radius afforded by star® wires. The magnet was wound with two star® wires, electrically in parallel and without transposition. We tested the magnet at 77 and 4.2 K. The magnet reached a peak current of 8.9 kA, 78% of the short-sample prediction at 4.2 K, and a whole-conductor current density of 1500 A mm−2. The experiment demonstrated a minimum viable concept for dipole magnet applications using star® wires. The results also allowed us to identify further development needs for star® conductors and associated magnet technology to enable high-field rebco magnets.</dc:description><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>4008 Electrical Engineering (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>REBCO</dc:subject><dc:subject>magnet</dc:subject><dc:subject>STAR (R)</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>4016 Materials engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4tz8f9q1</dc:identifier><dc:identifier>https://escholarship.org/content/qt4tz8f9q1/qt4tz8f9q1.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1361-6668/ac9f82</dc:identifier><dc:type>article</dc:type><dc:source>Superconductor Science and Technology, vol 35, iss 12</dc:source><dc:coverage>125011</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt50p9z63f</identifier><datestamp>2026-09-15T18:49:48Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt50p9z63f</dc:identifier><dc:title>Baryon Acoustic Oscillations in the Ly-α forest of BOSS quasars</dc:title><dc:creator>Busca, Nicolás G</dc:creator><dc:creator>Delubac, Timothée</dc:creator><dc:creator>Rich, James</dc:creator><dc:creator>Bailey, Stephen</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>Kirkby, David</dc:creator><dc:creator>Goff, J-M Le</dc:creator><dc:creator>Pieri, Matthew M</dc:creator><dc:creator>Slosar, Anze</dc:creator><dc:creator>Aubourg, Éric</dc:creator><dc:creator>Bautista, Julian E</dc:creator><dc:creator>Bizyaev, Dmitry</dc:creator><dc:creator>Blomqvist, Michael</dc:creator><dc:creator>Bolton, Adam S</dc:creator><dc:creator>Bovy, Jo</dc:creator><dc:creator>Brewington, Howard</dc:creator><dc:creator>Borde, Arnaud</dc:creator><dc:creator>Brinkmann, J</dc:creator><dc:creator>Carithers, Bill</dc:creator><dc:creator>Croft, Rupert AC</dc:creator><dc:creator>Dawson, Kyle S</dc:creator><dc:creator>Ebelke, Garrett</dc:creator><dc:creator>Eisenstein, Daniel J</dc:creator><dc:creator>Hamilton, Jean-Christophe</dc:creator><dc:creator>Ho, Shirley</dc:creator><dc:creator>Hogg, David W</dc:creator><dc:creator>Honscheid, Klaus</dc:creator><dc:creator>Lee, Khee-Gan</dc:creator><dc:creator>Lundgren, Britt</dc:creator><dc:creator>Malanushenko, Elena</dc:creator><dc:creator>Malanushenko, Viktor</dc:creator><dc:creator>Margala, Daniel</dc:creator><dc:creator>Maraston, Claudia</dc:creator><dc:creator>Mehta, Kushal</dc:creator><dc:creator>Miralda-Escudé, Jordi</dc:creator><dc:creator>Myers, Adam D</dc:creator><dc:creator>Nichol, Robert C</dc:creator><dc:creator>Noterdaeme, Pasquier</dc:creator><dc:creator>Olmstead, Matthew D</dc:creator><dc:creator>Oravetz, Daniel</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Pan, Kaike</dc:creator><dc:creator>Pâris, Isabelle</dc:creator><dc:creator>Percival, Will J</dc:creator><dc:creator>Petitjean, Patrick</dc:creator><dc:creator>Roe, NA</dc:creator><dc:creator>Rollinde, Emmanuel</dc:creator><dc:creator>Ross, Nicholas P</dc:creator><dc:creator>Rossi, Graziano</dc:creator><dc:creator>Schlegel, David J</dc:creator><dc:creator>Schneider, Donald P</dc:creator><dc:creator>Shelden, Alaina</dc:creator><dc:creator>Sheldon, Erin S</dc:creator><dc:creator>Simmons, Audrey</dc:creator><dc:creator>Snedden, Stephanie</dc:creator><dc:creator>Tinker, Jeremy L</dc:creator><dc:creator>Viel, Matteo</dc:creator><dc:creator>Weaver, Benjamin A</dc:creator><dc:creator>Weinberg, David H</dc:creator><dc:creator>White, Martin</dc:creator><dc:creator>Yèche, Christophe</dc:creator><dc:creator>York, Donald G</dc:creator><dc:date>2012-11-12</dc:date><dc:description>We report a detection of the baryon acoustic oscillation (BAO) feature in the
three-dimensional correlation function of the transmitted flux fraction in the
\Lya forest of high-redshift quasars. The study uses 48,640 quasars in the
redshift range $2.1\le z \le 3.5$ from the Baryon Oscillation Spectroscopic
Survey (BOSS) of the third generation of the Sloan Digital Sky Survey
(SDSS-III). At a mean redshift $z=2.3$, we measure the monopole and quadrupole
components of the correlation function for separations in the range
$20\hMpc</dc:description><dc:subject>astro-ph.CO</dc:subject><dc:subject>astro-ph.CO</dc:subject><dc:subject>astro-ph.CO</dc:subject><dc:subject>astro-ph.CO</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/50p9z63f</dc:identifier><dc:identifier>https://escholarship.org/content/qt50p9z63f/qt50p9z63f.pdf</dc:identifier><dc:identifier>info:doi/10.1051/0004-6361/201220724</dc:identifier><dc:type>article</dc:type><dc:source>Astronomy and Astrophysics, vol 552</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3m16q2tx</identifier><datestamp>2026-09-15T18:45:58Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3m16q2tx</dc:identifier><dc:title>Pleiotropic genes for metabolic syndrome and inflammation</dc:title><dc:creator>Kraja, Aldi T</dc:creator><dc:creator>Chasman, Daniel I</dc:creator><dc:creator>North, Kari E</dc:creator><dc:creator>Reiner, Alexander P</dc:creator><dc:creator>Yanek, Lisa R</dc:creator><dc:creator>Kilpeläinen, Tuomas O</dc:creator><dc:creator>Smith, Jennifer A</dc:creator><dc:creator>Dehghan, Abbas</dc:creator><dc:creator>Dupuis, Josée</dc:creator><dc:creator>Johnson, Andrew D</dc:creator><dc:creator>Feitosa, Mary F</dc:creator><dc:creator>Tekola-Ayele, Fasil</dc:creator><dc:creator>Chu, Audrey Y</dc:creator><dc:creator>Nolte, Ilja M</dc:creator><dc:creator>Dastani, Zari</dc:creator><dc:creator>Morris, Andrew</dc:creator><dc:creator>Pendergrass, Sarah A</dc:creator><dc:creator>Sun, Yan V</dc:creator><dc:creator>Ritchie, Marylyn D</dc:creator><dc:creator>Vaez, Ahmad</dc:creator><dc:creator>Lin, Honghuang</dc:creator><dc:creator>Ligthart, Symen</dc:creator><dc:creator>Marullo, Letizia</dc:creator><dc:creator>Rohde, Rebecca</dc:creator><dc:creator>Shao, Yaming</dc:creator><dc:creator>Ziegler, Mark A</dc:creator><dc:creator>Im, Hae Kyung</dc:creator><dc:creator>Group, Cross Consortia Pleiotropy</dc:creator><dc:creator>Heart and, the Cohorts for</dc:creator><dc:creator>Epidemiology, Aging Research in Genetic</dc:creator><dc:creator>Consortium, the Genetic Investigation of Anthropometric Traits</dc:creator><dc:creator>Consortium, the Global Lipids Genetics</dc:creator><dc:creator>the Meta-Analyses of Glucose</dc:creator><dc:creator>Consortium, Insulin-related traits</dc:creator><dc:creator>Consortium, the Global BPgen</dc:creator><dc:creator>Consortium, The ADIPOGen</dc:creator><dc:creator>Study, the Women's Genome Health</dc:creator><dc:creator>Study, the Howard University Family</dc:creator><dc:creator>Schnabel, Renate B</dc:creator><dc:creator>Jørgensen, Torben</dc:creator><dc:creator>Jørgensen, Marit E</dc:creator><dc:creator>Hansen, Torben</dc:creator><dc:creator>Pedersen, Oluf</dc:creator><dc:creator>Stolk, Ronald P</dc:creator><dc:creator>Snieder, Harold</dc:creator><dc:creator>Hofman, Albert</dc:creator><dc:creator>Uitterlinden, Andre G</dc:creator><dc:creator>Franco, Oscar H</dc:creator><dc:creator>Ikram, M Arfan</dc:creator><dc:creator>Richards, J Brent</dc:creator><dc:creator>Rotimi, Charles</dc:creator><dc:creator>Wilson, James G</dc:creator><dc:creator>Lange, Leslie</dc:creator><dc:creator>Ganesh, Santhi K</dc:creator><dc:creator>Nalls, Mike</dc:creator><dc:creator>Rasmussen-Torvik, Laura J</dc:creator><dc:creator>Pankow, James S</dc:creator><dc:creator>Coresh, Josef</dc:creator><dc:creator>Tang, Weihong</dc:creator><dc:creator>Kao, WH Linda</dc:creator><dc:creator>Boerwinkle, Eric</dc:creator><dc:creator>Morrison, Alanna C</dc:creator><dc:creator>Ridker, Paul M</dc:creator><dc:creator>Becker, Diane M</dc:creator><dc:creator>Rotter, Jerome I</dc:creator><dc:creator>Kardia, Sharon LR</dc:creator><dc:creator>Loos, Ruth JF</dc:creator><dc:creator>Larson, Martin G</dc:creator><dc:creator>Hsu, Yi-Hsiang</dc:creator><dc:creator>Province, Michael A</dc:creator><dc:creator>Tracy, Russell</dc:creator><dc:creator>Voight, Benjamin F</dc:creator><dc:creator>Vaidya, Dhananjay</dc:creator><dc:creator>O'Donnell, Christopher J</dc:creator><dc:creator>Benjamin, Emelia J</dc:creator><dc:creator>Alizadeh, Behrooz Z</dc:creator><dc:creator>Prokopenko, Inga</dc:creator><dc:creator>Meigs, James B</dc:creator><dc:creator>Borecki, Ingrid B</dc:creator><dc:date>2014-08-01</dc:date><dc:description>Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>Nutrition (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Brain Disorders (rcdc)</dc:subject><dc:subject>Diabetes (rcdc)</dc:subject><dc:subject>Obesity (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Cardiovascular (rcdc)</dc:subject><dc:subject>2.1 Biological and endogenous factors (hrcs-rac)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:subject>Computational Biology (mesh)</dc:subject><dc:subject>Gene Regulatory Networks (mesh)</dc:subject><dc:subject>Genetic Pleiotropy (mesh)</dc:subject><dc:subject>Genetic Predisposition to Disease (mesh)</dc:subject><dc:subject>Genome-Wide Association Study (mesh)</dc:subject><dc:subject>Inflammation (mesh)</dc:subject><dc:subject>Metabolic Syndrome (mesh)</dc:subject><dc:subject>Phenotype (mesh)</dc:subject><dc:subject>Quantitative Trait</dc:subject><dc:subject>Heritable (mesh)</dc:subject><dc:subject>Metabolic syndrome</dc:subject><dc:subject>Inflammatory markers</dc:subject><dc:subject>Pleiotropic associations</dc:subject><dc:subject>Meta-analysis</dc:subject><dc:subject>Regulome</dc:subject><dc:subject>Cross Consortia Pleiotropy Group</dc:subject><dc:subject>Cohorts for Heart and</dc:subject><dc:subject>Aging Research in Genetic Epidemiology</dc:subject><dc:subject>Genetic Investigation of Anthropometric Traits Consortium</dc:subject><dc:subject>Global Lipids Genetics Consortium</dc:subject><dc:subject>Meta-Analyses of Glucose</dc:subject><dc:subject>Insulin-related traits Consortium</dc:subject><dc:subject>Global BPgen Consortium</dc:subject><dc:subject>ADIPOGen Consortium</dc:subject><dc:subject>Women's Genome Health Study</dc:subject><dc:subject>Howard University Family Study</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Genetic Predisposition to Disease (mesh)</dc:subject><dc:subject>Inflammation (mesh)</dc:subject><dc:subject>Computational Biology (mesh)</dc:subject><dc:subject>Quantitative Trait</dc:subject><dc:subject>Heritable (mesh)</dc:subject><dc:subject>Phenotype (mesh)</dc:subject><dc:subject>Gene Regulatory Networks (mesh)</dc:subject><dc:subject>Genome-Wide Association Study (mesh)</dc:subject><dc:subject>Genetic Pleiotropy (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:subject>Metabolic Syndrome (mesh)</dc:subject><dc:subject>Inflammatory markers</dc:subject><dc:subject>Meta-analysis</dc:subject><dc:subject>Metabolic syndrome</dc:subject><dc:subject>Pleiotropic associations</dc:subject><dc:subject>Regulome</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:subject>Computational Biology (mesh)</dc:subject><dc:subject>Gene Regulatory Networks (mesh)</dc:subject><dc:subject>Genetic Pleiotropy (mesh)</dc:subject><dc:subject>Genetic Predisposition to Disease (mesh)</dc:subject><dc:subject>Genome-Wide Association Study (mesh)</dc:subject><dc:subject>Inflammation (mesh)</dc:subject><dc:subject>Metabolic Syndrome (mesh)</dc:subject><dc:subject>Phenotype (mesh)</dc:subject><dc:subject>Quantitative Trait</dc:subject><dc:subject>Heritable (mesh)</dc:subject><dc:subject>1103 Clinical Sciences (for)</dc:subject><dc:subject>Genetics &amp; Heredity (science-metrix)</dc:subject><dc:subject>3105 Genetics (for-2020)</dc:subject><dc:subject>3202 Clinical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3m16q2tx</dc:identifier><dc:identifier>https://escholarship.org/content/qt3m16q2tx/qt3m16q2tx.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.ymgme.2014.04.007</dc:identifier><dc:type>article</dc:type><dc:source>Molecular Genetics and Metabolism, vol 112, iss 4</dc:source><dc:coverage>317 - 338</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt660639fj</identifier><datestamp>2026-09-15T18:45:53Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt660639fj</dc:identifier><dc:title>Overview of the Instrumentation for the Dark Energy Spectroscopic Instrument</dc:title><dc:creator>Collaboration, DESI</dc:creator><dc:creator>Abareshi, B</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Alam, Shadab</dc:creator><dc:creator>Alexander, David M</dc:creator><dc:creator>Alfarsy, R</dc:creator><dc:creator>Allen, L</dc:creator><dc:creator>Prieto, C Allende</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Ameel, J</dc:creator><dc:creator>Armengaud, E</dc:creator><dc:creator>Asorey, J</dc:creator><dc:creator>Aviles, Alejandro</dc:creator><dc:creator>Bailey, S</dc:creator><dc:creator>Balaguera-Antolínez, A</dc:creator><dc:creator>Ballester, O</dc:creator><dc:creator>Baltay, C</dc:creator><dc:creator>Bault, A</dc:creator><dc:creator>Beltran, SF</dc:creator><dc:creator>Benavides, B</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Berti, A</dc:creator><dc:creator>Besuner, R</dc:creator><dc:creator>Beutler, Florian</dc:creator><dc:creator>Bianchi, D</dc:creator><dc:creator>Blake, C</dc:creator><dc:creator>Blanc, P</dc:creator><dc:creator>Blum, R</dc:creator><dc:creator>Bolton, A</dc:creator><dc:creator>Bose, S</dc:creator><dc:creator>Bramall, D</dc:creator><dc:creator>Brieden, S</dc:creator><dc:creator>Brodzeller, A</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Brownewell, C</dc:creator><dc:creator>Buckley-Geer, E</dc:creator><dc:creator>Cahn, RN</dc:creator><dc:creator>Cai, Z</dc:creator><dc:creator>Canning, R</dc:creator><dc:creator>Capasso, R</dc:creator><dc:creator>Rosell, A Carnero</dc:creator><dc:creator>Carton, P</dc:creator><dc:creator>Casas, R</dc:creator><dc:creator>Castander, FJ</dc:creator><dc:creator>Cervantes-Cota, JL</dc:creator><dc:creator>Chabanier, S</dc:creator><dc:creator>Chaussidon, E</dc:creator><dc:creator>Chuang, C</dc:creator><dc:creator>Circosta, C</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>Cooper, AP</dc:creator><dc:creator>da Costa, L</dc:creator><dc:creator>Cousinou, M-C</dc:creator><dc:creator>Cuceu, A</dc:creator><dc:creator>Davis, TM</dc:creator><dc:creator>Dawson, K</dc:creator><dc:creator>de la Cruz-Noriega, R</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Della Costa, J</dc:creator><dc:creator>Demmer, P</dc:creator><dc:creator>Derwent, M</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Dhungana, G</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Dobson, C</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Donald-McCann, J</dc:creator><dc:creator>Donaldson, J</dc:creator><dc:creator>Douglass, K</dc:creator><dc:creator>Duan, Y</dc:creator><dc:creator>Dunlop, P</dc:creator><dc:creator>Edelstein, J</dc:creator><dc:creator>Eftekharzadeh, S</dc:creator><dc:creator>Eisenstein, DJ</dc:creator><dc:creator>Enriquez-Vargas, M</dc:creator><dc:creator>Escoffier, S</dc:creator><dc:creator>Evatt, M</dc:creator><dc:creator>Fagrelius, P</dc:creator><dc:creator>Fan, X</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Fawcett, VA</dc:creator><dc:creator>Ferraro, S</dc:creator><dc:creator>Ereza, J</dc:creator><dc:creator>Flaugher, B</dc:creator><dc:creator>Font-Ribera, A</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Frenk, CS</dc:creator><dc:creator>Fromenteau, S</dc:creator><dc:creator>Gänsicke, BT</dc:creator><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Garrison, L</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gerardi, F</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gonzalez-Morales, Alma X</dc:creator><dc:creator>Gonzalez-de-Rivera, G</dc:creator><dc:date>2022-11-01</dc:date><dc:description>The Dark Energy Spectroscopic Instrument (DESI) embarked on an ambitious 5 yr survey in 2021 May to explore the nature of dark energy with spectroscopic measurements of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the baryon acoustic oscillation method to measure distances from the nearby universe to beyond redshift z &amp;gt; 3.5, and employ redshift space distortions to measure the growth of structure and probe potential modifications to general relativity. We describe the significant instrumentation we developed to conduct the DESI survey. This includes: a wide-field, 3.°2 diameter prime-focus corrector; a focal plane system with 5020 fiber positioners on the 0.812 m diameter, aspheric focal surface; 10 continuous, high-efficiency fiber cable bundles that connect the focal plane to the spectrographs; and 10 identical spectrographs. Each spectrograph employs a pair of dichroics to split the light into three channels that together record the light from 360–980 nm with a spectral resolution that ranges from 2000–5000. We describe the science requirements, their connection to the technical requirements, the management of the project, and interfaces between subsystems. DESI was installed at the 4 m Mayall Telescope at Kitt Peak National Observatory and has achieved all of its performance goals. Some performance highlights include an rms positioner accuracy of better than 0.″1 and a median signal-to-noise ratio of 7 of the [O ii] doublet at 8 × 10−17 erg s−1 cm−2 in 1000 s for galaxies at z = 1.4–1.6. We conclude with additional highlights from the on-sky validation and commissioning, key successes, and lessons learned.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/660639fj</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.3847/1538-3881/ac882b</dc:identifier><dc:type>article</dc:type><dc:source>The Astronomical Journal, vol 164, iss 5</dc:source><dc:coverage>207</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8t74756x</identifier><datestamp>2026-09-15T18:34:20Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8t74756x</dc:identifier><dc:title>Search for Soft Unclustered Energy Patterns in Proton-Proton Collisions at 13 TeV</dc:title><dc:creator>Hayrapetyan, A</dc:creator><dc:creator>Tumasyan, A</dc:creator><dc:creator>Adam, W</dc:creator><dc:creator>Andrejkovic, JW</dc:creator><dc:creator>Bergauer, T</dc:creator><dc:creator>Chatterjee, S</dc:creator><dc:creator>Damanakis, K</dc:creator><dc:creator>Dragicevic, M</dc:creator><dc:creator>Hussain, PS</dc:creator><dc:creator>Jeitler, M</dc:creator><dc:creator>Krammer, N</dc:creator><dc:creator>Li, A</dc:creator><dc:creator>Liko, D</dc:creator><dc:creator>Mikulec, I</dc:creator><dc:creator>Schieck, J</dc:creator><dc:creator>Schöfbeck, R</dc:creator><dc:creator>Schwarz, D</dc:creator><dc:creator>Sonawane, M</dc:creator><dc:creator>Templ, S</dc:creator><dc:creator>Waltenberger, W</dc:creator><dc:creator>Wulz, C-E</dc:creator><dc:creator>Darwish, MR</dc:creator><dc:creator>Janssen, T</dc:creator><dc:creator>Van Mechelen, P</dc:creator><dc:creator>Breugelmans, N</dc:creator><dc:creator>D’Hondt, J</dc:creator><dc:creator>Dansana, S</dc:creator><dc:creator>De Moor, A</dc:creator><dc:creator>Delcourt, M</dc:creator><dc:creator>Heyen, F</dc:creator><dc:creator>Lowette, S</dc:creator><dc:creator>Makarenko, I</dc:creator><dc:creator>Müller, D</dc:creator><dc:creator>Tavernier, S</dc:creator><dc:creator>Tytgat, M</dc:creator><dc:creator>Van Onsem, GP</dc:creator><dc:creator>Van Putte, S</dc:creator><dc:creator>Vannerom, D</dc:creator><dc:creator>Clerbaux, B</dc:creator><dc:creator>Das, AK</dc:creator><dc:creator>De Lentdecker, G</dc:creator><dc:creator>Evard, H</dc:creator><dc:creator>Favart, L</dc:creator><dc:creator>Gianneios, P</dc:creator><dc:creator>Hohov, D</dc:creator><dc:creator>Jaramillo, J</dc:creator><dc:creator>Khalilzadeh, A</dc:creator><dc:creator>Khan, FA</dc:creator><dc:creator>Lee, K</dc:creator><dc:creator>Mahdavikhorrami, M</dc:creator><dc:creator>Malara, A</dc:creator><dc:creator>Paredes, S</dc:creator><dc:creator>Shahzad, MA</dc:creator><dc:creator>Thomas, L</dc:creator><dc:creator>Bemden, M Vanden</dc:creator><dc:creator>Vander Velde, C</dc:creator><dc:creator>Vanlaer, P</dc:creator><dc:creator>De Coen, M</dc:creator><dc:creator>Dobur, D</dc:creator><dc:creator>Gokbulut, G</dc:creator><dc:creator>Hong, Y</dc:creator><dc:creator>Knolle, J</dc:creator><dc:creator>Lambrecht, L</dc:creator><dc:creator>Marckx, D</dc:creator><dc:creator>Mestdach, G</dc:creator><dc:creator>Amarilo, K Mota</dc:creator><dc:creator>Samalan, A</dc:creator><dc:creator>Skovpen, K</dc:creator><dc:creator>Van Den Bossche, N</dc:creator><dc:creator>van der Linden, J</dc:creator><dc:creator>Wezenbeek, L</dc:creator><dc:creator>Benecke, A</dc:creator><dc:creator>Bethani, A</dc:creator><dc:creator>Bruno, G</dc:creator><dc:creator>Caputo, C</dc:creator><dc:creator>De Jeneret, J De Favereau</dc:creator><dc:creator>Delaere, C</dc:creator><dc:creator>Donertas, IS</dc:creator><dc:creator>Giammanco, A</dc:creator><dc:creator>Guzel, AO</dc:creator><dc:creator>Jain</dc:creator><dc:creator>Lemaitre, V</dc:creator><dc:creator>Lidrych, J</dc:creator><dc:creator>Mastrapasqua, P</dc:creator><dc:creator>Tran, TT</dc:creator><dc:creator>Wertz, S</dc:creator><dc:creator>Alves, GA</dc:creator><dc:creator>Pereira, M Alves Gallo</dc:creator><dc:creator>Coelho, E</dc:creator><dc:creator>Silva, G Correia</dc:creator><dc:creator>Hensel, C</dc:creator><dc:creator>De Oliveira, T Menezes</dc:creator><dc:creator>Moraes, A</dc:creator><dc:creator>Teles, P Rebello</dc:creator><dc:creator>Soeiro, M</dc:creator><dc:creator>Pereira, A Vilela</dc:creator><dc:creator>Júnior, WL Aldá</dc:creator><dc:creator>Filho, M Barroso Ferreira</dc:creator><dc:creator>Malbouisson, H Brandao</dc:creator><dc:creator>Carvalho, W</dc:creator><dc:date>2024-11-08</dc:date><dc:description>The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV, collected in 2016-2018 by the CMS detector at the LHC. Such SUEPs are predicted by hidden valley models with a new, confining force with a large 't Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics. With no observed excess of events over the standard model expectation, limits are set on the cross section for production via gluon fusion of a scalar mediator with SUEP-like decays.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>CMS Collaboration</dc:subject><dc:subject>01 Mathematical Sciences (for)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8t74756x</dc:identifier><dc:identifier>https://escholarship.org/content/qt8t74756x/qt8t74756x.pdf</dc:identifier><dc:identifier>info:doi/10.1103/physrevlett.133.191902</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review Letters, vol 133, iss 19</dc:source><dc:coverage>191902</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8rj4p6wz</identifier><datestamp>2026-09-15T18:33:47Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8rj4p6wz</dc:identifier><dc:title>ATHENA detector proposal — a totally hermetic electron nucleus apparatus proposed for IP6 at the Electron-Ion Collider</dc:title><dc:creator>Adam, J</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Agrawal, N</dc:creator><dc:creator>Aidala, C</dc:creator><dc:creator>Akers, W</dc:creator><dc:creator>Alekseev, M</dc:creator><dc:creator>Allen, MM</dc:creator><dc:creator>Ameli, F</dc:creator><dc:creator>Angerami, A</dc:creator><dc:creator>Antonioli, P</dc:creator><dc:creator>Apadula, NJ</dc:creator><dc:creator>Aprahamian, A</dc:creator><dc:creator>Armstrong, W</dc:creator><dc:creator>Arratia, M</dc:creator><dc:creator>Arrington, JR</dc:creator><dc:creator>Asaturyan, A</dc:creator><dc:creator>Aschenauer, EC</dc:creator><dc:creator>Augsten, K</dc:creator><dc:creator>Aune, S</dc:creator><dc:creator>Bailey, K</dc:creator><dc:creator>Baldanza, C</dc:creator><dc:creator>Bansal, M</dc:creator><dc:creator>Barbosa, F</dc:creator><dc:creator>Barion, L</dc:creator><dc:creator>Barish, K</dc:creator><dc:creator>Battaglieri, M</dc:creator><dc:creator>Bazilevsky, A</dc:creator><dc:creator>Behera, NK</dc:creator><dc:creator>Berdnikov, V</dc:creator><dc:creator>Bernauer, J</dc:creator><dc:creator>Berriaud, C</dc:creator><dc:creator>Bhasin, A</dc:creator><dc:creator>Bhattacharya, DS</dc:creator><dc:creator>Bielcik, J</dc:creator><dc:creator>Bielcikova, J</dc:creator><dc:creator>Bissolotti, C</dc:creator><dc:creator>Boeglin, W</dc:creator><dc:creator>Bondì, M</dc:creator><dc:creator>Borri, M</dc:creator><dc:creator>Bossù, F</dc:creator><dc:creator>Bouyjou, F</dc:creator><dc:creator>Brandenburg, JD</dc:creator><dc:creator>Bressan, A</dc:creator><dc:creator>Brooks, M</dc:creator><dc:creator>Bültmann, SL</dc:creator><dc:creator>Byer, D</dc:creator><dc:creator>Caines, H</dc:creator><dc:creator>de la Barca Sanchez, M Calderon</dc:creator><dc:creator>Calvelli, V</dc:creator><dc:creator>Camsonne, A</dc:creator><dc:creator>Cappelli, L</dc:creator><dc:creator>Capua, M</dc:creator><dc:creator>Castro, M</dc:creator><dc:creator>Cavazza, D</dc:creator><dc:creator>Cebra, D</dc:creator><dc:creator>Celentano, A</dc:creator><dc:creator>Chakaberia, I</dc:creator><dc:creator>Chan, B</dc:creator><dc:creator>Chang, W</dc:creator><dc:creator>Chartier, M</dc:creator><dc:creator>Chatterjee, C</dc:creator><dc:creator>Chen, D</dc:creator><dc:creator>Chen, J</dc:creator><dc:creator>Chen, K</dc:creator><dc:creator>Chen, Z</dc:creator><dc:creator>Chetri, H</dc:creator><dc:creator>Chiarusi, T</dc:creator><dc:creator>Chiosso, M</dc:creator><dc:creator>Chu, X</dc:creator><dc:creator>Chwastowski, JJ</dc:creator><dc:creator>Cicala, G</dc:creator><dc:creator>Cisbani, E</dc:creator><dc:creator>Cline, E</dc:creator><dc:creator>Cloët, I</dc:creator><dc:creator>Colella, D</dc:creator><dc:creator>Contalbrigo, M</dc:creator><dc:creator>Contin, G</dc:creator><dc:creator>Corliss, R</dc:creator><dc:creator>Corrales-Morales, Y</dc:creator><dc:creator>Crafts, J</dc:creator><dc:creator>Crawford, C</dc:creator><dc:creator>Cruz-Torres, R</dc:creator><dc:creator>D'Ago, D</dc:creator><dc:creator>D'Angelo, A</dc:creator><dc:creator>D'Hose, N</dc:creator><dc:creator>Dainton, J</dc:creator><dc:creator>Torre, S Dalla</dc:creator><dc:creator>Dasgupta, SS</dc:creator><dc:creator>Dash, S</dc:creator><dc:creator>Dashyan, N</dc:creator><dc:creator>Datta, J</dc:creator><dc:creator>Daugherity, M</dc:creator><dc:creator>De Vita, R</dc:creator><dc:creator>Deconinck, W</dc:creator><dc:creator>Defurne, M</dc:creator><dc:creator>Dehmelt, K</dc:creator><dc:creator>Del Dotto, A</dc:creator><dc:creator>Delcarro, F</dc:creator><dc:creator>Dellacasa, G</dc:creator><dc:creator>Demiroglu, ZS</dc:creator><dc:date>2022-10-01</dc:date><dc:description>ATHENA has been designed as a general purpose detector capable of delivering the full scientific scope of the Electron-Ion Collider. Careful technology choices provide fine tracking and momentum resolution, high performance electromagnetic and hadronic calorimetry, hadron identification over a wide kinematic range, and near-complete hermeticity. This article describes the detector design and its expected performance in the most relevant physics channels. It includes an evaluation of detector technology choices, the technical challenges to realizing the detector and the R&amp;amp;D required to meet those challenges.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Large detector systems for particle and astroparticle physics</dc:subject><dc:subject>Calorimeters</dc:subject><dc:subject>Cherenkov detectors</dc:subject><dc:subject>Particle tracking detectors</dc:subject><dc:subject>NSD-Relativistic Nuclear Collisions (c-lbnl-label)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8rj4p6wz</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1088/1748-0221/17/10/p10019</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Instrumentation, vol 17, iss 10</dc:source><dc:coverage>p10019</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0xh894cz</identifier><datestamp>2026-09-15T18:33:30Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0xh894cz</dc:identifier><dc:title>Online charge measurement for petawatt laser-driven ion acceleration</dc:title><dc:creator>Geulig, Laura D</dc:creator><dc:creator>Obst-Huebl, Lieselotte</dc:creator><dc:creator>Nakamura, Kei</dc:creator><dc:creator>Bin, Jianhui</dc:creator><dc:creator>Ji, Qing</dc:creator><dc:creator>Steinke, Sven</dc:creator><dc:creator>Snijders, Antoine M</dc:creator><dc:creator>Mao, Jian-Hua</dc:creator><dc:creator>Blakely, Eleanor A</dc:creator><dc:creator>Gonsalves, Anthony J</dc:creator><dc:creator>Bulanov, Stepan</dc:creator><dc:creator>van Tilborg, Jeroen</dc:creator><dc:creator>Schroeder, Carl B</dc:creator><dc:creator>Geddes, Cameron GR</dc:creator><dc:creator>Esarey, Eric</dc:creator><dc:creator>Roth, Markus</dc:creator><dc:creator>Schenkel, Thomas</dc:creator><dc:date>2022-10-01</dc:date><dc:description>Laser-driven ion beams have gained considerable attention for their potential use in multidisciplinary research and technology. Preclinical studies into their radiobiological effectiveness have established the prospect of using laser-driven ion beams for radiotherapy. In particular, research into the beneficial effects of ultrahigh instantaneous dose rates is enabled by the high ion bunch charge and uniquely short bunch lengths present for laser-driven ion beams. Such studies require reliable, online dosimetry methods to monitor the bunch charge for every laser shot to ensure that the prescribed dose is accurately applied to the biological sample. In this paper, we present the first successful use of an Integrating Current Transformer (ICT) for laser-driven ion accelerators. This is a noninvasive diagnostic to measure the charge of the accelerated ion bunch. It enables online estimates of the applied dose in radiobiological experiments and facilitates ion beam tuning, in particular, optimization of the laser ion source, and alignment of the proton transport beamline. We present the ICT implementation and the correlation with other diagnostics, such as radiochromic films, a Thomson parabola spectrometer, and a scintillator.</dc:description><dc:subject>5105 Medical and Biological Physics (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>Particle Accelerators (mesh)</dc:subject><dc:subject>Lasers (mesh)</dc:subject><dc:subject>Radiometry (mesh)</dc:subject><dc:subject>Radiobiology (mesh)</dc:subject><dc:subject>Acceleration (mesh)</dc:subject><dc:subject>Radiometry (mesh)</dc:subject><dc:subject>Lasers (mesh)</dc:subject><dc:subject>Radiobiology (mesh)</dc:subject><dc:subject>Acceleration (mesh)</dc:subject><dc:subject>Particle Accelerators (mesh)</dc:subject><dc:subject>Particle Accelerators (mesh)</dc:subject><dc:subject>Lasers (mesh)</dc:subject><dc:subject>Radiometry (mesh)</dc:subject><dc:subject>Radiobiology (mesh)</dc:subject><dc:subject>Acceleration (mesh)</dc:subject><dc:subject>ATAP-BELLA Center (c-lbnl-label)</dc:subject><dc:subject>ATAP-FS&amp;IBT (c-lbnl-label)</dc:subject><dc:subject>ATAP-FS-IBT (c-lbnl-label)</dc:subject><dc:subject>ATAP-2022 (c-lbnl-label)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>03 Chemical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Applied Physics (science-metrix)</dc:subject><dc:subject>34 Chemical sciences (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0xh894cz</dc:identifier><dc:identifier>https://escholarship.org/content/qt0xh894cz/qt0xh894cz.pdf</dc:identifier><dc:identifier>info:doi/10.1063/5.0096423</dc:identifier><dc:type>article</dc:type><dc:source>Review of Scientific Instruments, vol 93, iss 10</dc:source><dc:coverage>103301</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2x94t2sz</identifier><datestamp>2026-09-15T18:25:58Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2x94t2sz</dc:identifier><dc:title>Optimization of the first CUPID detector module</dc:title><dc:creator>Alfonso, K</dc:creator><dc:creator>Armatol, A</dc:creator><dc:creator>Augier, C</dc:creator><dc:creator>Avignone, FT</dc:creator><dc:creator>Azzolini, O</dc:creator><dc:creator>Balata, M</dc:creator><dc:creator>Barabash, AS</dc:creator><dc:creator>Bari, G</dc:creator><dc:creator>Barresi, A</dc:creator><dc:creator>Baudin, D</dc:creator><dc:creator>Bellini, F</dc:creator><dc:creator>Benato, G</dc:creator><dc:creator>Beretta, M</dc:creator><dc:creator>Bettelli, M</dc:creator><dc:creator>Biassoni, M</dc:creator><dc:creator>Billard, J</dc:creator><dc:creator>Boldrini, V</dc:creator><dc:creator>Branca, A</dc:creator><dc:creator>Brofferio, C</dc:creator><dc:creator>Bucci, C</dc:creator><dc:creator>Camilleri, J</dc:creator><dc:creator>Campani, A</dc:creator><dc:creator>Capelli, C</dc:creator><dc:creator>Capelli, S</dc:creator><dc:creator>Cappelli, L</dc:creator><dc:creator>Cardani, L</dc:creator><dc:creator>Carniti, P</dc:creator><dc:creator>Casali, N</dc:creator><dc:creator>Celi, E</dc:creator><dc:creator>Chang, C</dc:creator><dc:creator>Chiesa, D</dc:creator><dc:creator>Clemenza, M</dc:creator><dc:creator>Colantoni, I</dc:creator><dc:creator>Copello, S</dc:creator><dc:creator>Craft, E</dc:creator><dc:creator>Cremonesi, O</dc:creator><dc:creator>Creswick, RJ</dc:creator><dc:creator>Cruciani, A</dc:creator><dc:creator>D’Addabbo, A</dc:creator><dc:creator>D’Imperio, G</dc:creator><dc:creator>Dabagov, S</dc:creator><dc:creator>Dafinei, I</dc:creator><dc:creator>Danevich, FA</dc:creator><dc:creator>De Jesus, M</dc:creator><dc:creator>de Marcillac, P</dc:creator><dc:creator>Dell’Oro, S</dc:creator><dc:creator>Di Domizio, S</dc:creator><dc:creator>Di Lorenzo, S</dc:creator><dc:creator>Dixon, T</dc:creator><dc:creator>Dompè, V</dc:creator><dc:creator>Drobizhev, A</dc:creator><dc:creator>Dumoulin, L</dc:creator><dc:creator>Fantini, G</dc:creator><dc:creator>Faverzani, M</dc:creator><dc:creator>Ferri, E</dc:creator><dc:creator>Ferri, F</dc:creator><dc:creator>Ferroni, F</dc:creator><dc:creator>Figueroa-Feliciano, E</dc:creator><dc:creator>Foggetta, L</dc:creator><dc:creator>Formaggio, J</dc:creator><dc:creator>Franceschi, A</dc:creator><dc:creator>Fu, C</dc:creator><dc:creator>Fu, S</dc:creator><dc:creator>Fujikawa, BK</dc:creator><dc:creator>Gallas, A</dc:creator><dc:creator>Gascon, J</dc:creator><dc:creator>Ghislandi, S</dc:creator><dc:creator>Giachero, A</dc:creator><dc:creator>Gianvecchio, A</dc:creator><dc:creator>Gironi, L</dc:creator><dc:creator>Giuliani, A</dc:creator><dc:creator>Gorla, P</dc:creator><dc:creator>Gotti, C</dc:creator><dc:creator>Grant, C</dc:creator><dc:creator>Gras, P</dc:creator><dc:creator>Guillaumon, PV</dc:creator><dc:creator>Gutierrez, TD</dc:creator><dc:creator>Han, K</dc:creator><dc:creator>Hansen, EV</dc:creator><dc:creator>Heeger, KM</dc:creator><dc:creator>Helis, DL</dc:creator><dc:creator>Huang, HZ</dc:creator><dc:creator>Imbert, L</dc:creator><dc:creator>Johnston, J</dc:creator><dc:creator>Juillard, A</dc:creator><dc:creator>Karapetrov, G</dc:creator><dc:creator>Keppel, G</dc:creator><dc:creator>Khalife, H</dc:creator><dc:creator>Kobychev, VV</dc:creator><dc:creator>Kolomensky, Yu G</dc:creator><dc:creator>Konovalov, SI</dc:creator><dc:creator>Kowalski, R</dc:creator><dc:creator>Langford, T</dc:creator><dc:creator>Lefevre, M</dc:creator><dc:creator>Liu, R</dc:creator><dc:creator>Liu, Y</dc:creator><dc:creator>Loaiza, P</dc:creator><dc:creator>Ma, L</dc:creator><dc:creator>Madhukuttan, M</dc:creator><dc:creator>Mancarella, F</dc:creator><dc:date>2022-09-12</dc:date><dc:description>CUPID will be a next generation experiment searching for the neutrinoless double β$$\beta $$ decay, whose discovery would establish the Majorana nature of the neutrino. Based on the experience achieved with the CUORE experiment, presently taking data at LNGS, CUPID aims to reach a background free environment by means of scintillating Li2$$_{2}$$100$$^{100}$$MoO4$$_4$$ crystals coupled to light detectors. Indeed, the simultaneous heat and light detection allows us to reject the dominant background of α$$\alpha $$ particles, as proven by the CUPID-0 and CUPID-Mo demonstrators. In this work we present the results of the first test of the CUPID baseline module. In particular, we propose a new optimized detector structure and light sensors design to enhance the engineering and the light collection, respectively. We characterized the heat detectors, achieving an energy resolution of (5.9 ± 0.2)&amp;nbsp;keV FWHM at the Q-value of 100$$^{100}$$Mo (about 3034&amp;nbsp;keV). We studied the light collection of the baseline CUPID design with respect to an alternative configuration which features gravity-assisted light detectors’ mounting. In both cases we obtained an improvement in the light collection with respect to past measures and we validated the particle identification capability of the detector, which ensures an α$$\alpha $$ particle rejection higher than 99.9%, fully satisfying the requirements for CUPID.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>NSD-Neutrinos (c-lbnl-label)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0206 Quantum Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5102 Atomic</dc:subject><dc:subject>molecular and optical physics (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2x94t2sz</dc:identifier><dc:identifier>https://escholarship.org/content/qt2x94t2sz/qt2x94t2sz.pdf</dc:identifier><dc:identifier>info:doi/10.1140/epjc/s10052-022-10720-3</dc:identifier><dc:type>article</dc:type><dc:source>European Physical Journal C, vol 82, iss 9</dc:source><dc:coverage>810</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6d60q36g</identifier><datestamp>2026-09-15T18:25:53Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6d60q36g</dc:identifier><dc:title>Expansion of the global RNA virome reveals diverse clades of bacteriophages</dc:title><dc:creator>Neri, Uri</dc:creator><dc:creator>Wolf, Yuri I</dc:creator><dc:creator>Roux, Simon</dc:creator><dc:creator>Camargo, Antonio Pedro</dc:creator><dc:creator>Lee, Benjamin</dc:creator><dc:creator>Kazlauskas, Darius</dc:creator><dc:creator>Chen, I Min</dc:creator><dc:creator>Ivanova, Natalia</dc:creator><dc:creator>Allen, Lisa Zeigler</dc:creator><dc:creator>Paez-Espino, David</dc:creator><dc:creator>Bryant, Donald A</dc:creator><dc:creator>Bhaya, Devaki</dc:creator><dc:creator>Consortium, RNA Virus Discovery</dc:creator><dc:creator>Narrowe, Adrienne B</dc:creator><dc:creator>Probst, Alexander J</dc:creator><dc:creator>Sczyrba, Alexander</dc:creator><dc:creator>Kohler, Annegret</dc:creator><dc:creator>Séguin, Armand</dc:creator><dc:creator>Shade, Ashley</dc:creator><dc:creator>Campbell, Barbara J</dc:creator><dc:creator>Lindahl, Björn D</dc:creator><dc:creator>Reese, Brandi Kiel</dc:creator><dc:creator>Roque, Breanna M</dc:creator><dc:creator>DeRito, Chris</dc:creator><dc:creator>Averill, Colin</dc:creator><dc:creator>Cullen, Daniel</dc:creator><dc:creator>Beck, David AC</dc:creator><dc:creator>Walsh, David A</dc:creator><dc:creator>Ward, David M</dc:creator><dc:creator>Wu, Dongying</dc:creator><dc:creator>Eloe-Fadrosh, Emiley</dc:creator><dc:creator>Brodie, Eoin L</dc:creator><dc:creator>Young, Erica B</dc:creator><dc:creator>Lilleskov, Erik A</dc:creator><dc:creator>Castillo, Federico J</dc:creator><dc:creator>Martin, Francis M</dc:creator><dc:creator>LeCleir, Gary R</dc:creator><dc:creator>Attwood, Graeme T</dc:creator><dc:creator>Cadillo-Quiroz, Hinsby</dc:creator><dc:creator>Simon, Holly M</dc:creator><dc:creator>Hewson, Ian</dc:creator><dc:creator>Grigoriev, Igor V</dc:creator><dc:creator>Tiedje, James M</dc:creator><dc:creator>Jansson, Janet K</dc:creator><dc:creator>Lee, Janey</dc:creator><dc:creator>VanderGheynst, Jean S</dc:creator><dc:creator>Dangl, Jeff</dc:creator><dc:creator>Bowman, Jeff S</dc:creator><dc:creator>Blanchard, Jeffrey L</dc:creator><dc:creator>Bowen, Jennifer L</dc:creator><dc:creator>Xu, Jiangbing</dc:creator><dc:creator>Banfield, Jillian F</dc:creator><dc:creator>Deming, Jody W</dc:creator><dc:creator>Kostka, Joel E</dc:creator><dc:creator>Gladden, John M</dc:creator><dc:creator>Rapp, Josephine Z</dc:creator><dc:creator>Sharpe, Joshua</dc:creator><dc:creator>McMahon, Katherine D</dc:creator><dc:creator>Treseder, Kathleen K</dc:creator><dc:creator>Bidle, Kay D</dc:creator><dc:creator>Wrighton, Kelly C</dc:creator><dc:creator>Thamatrakoln, Kimberlee</dc:creator><dc:creator>Nusslein, Klaus</dc:creator><dc:creator>Meredith, Laura K</dc:creator><dc:creator>Ramirez, Lucia</dc:creator><dc:creator>Buee, Marc</dc:creator><dc:creator>Huntemann, Marcel</dc:creator><dc:creator>Kalyuzhnaya, Marina G</dc:creator><dc:creator>Waldrop, Mark P</dc:creator><dc:creator>Sullivan, Matthew B</dc:creator><dc:creator>Schrenk, Matthew O</dc:creator><dc:creator>Hess, Matthias</dc:creator><dc:creator>Vega, Michael A</dc:creator><dc:creator>O’Malley, Michelle A</dc:creator><dc:creator>Medina, Monica</dc:creator><dc:creator>Gilbert, Naomi E</dc:creator><dc:creator>Delherbe, Nathalie</dc:creator><dc:creator>Mason, Olivia U</dc:creator><dc:creator>Dijkstra, Paul</dc:creator><dc:creator>Chuckran, Peter F</dc:creator><dc:creator>Baldrian, Petr</dc:creator><dc:creator>Constant, Philippe</dc:creator><dc:creator>Stepanauskas, Ramunas</dc:creator><dc:creator>Daly, Rebecca A</dc:creator><dc:creator>Lamendella, Regina</dc:creator><dc:creator>Gruninger, Robert J</dc:creator><dc:creator>McKay, Robert M</dc:creator><dc:creator>Hylander, Samuel</dc:creator><dc:creator>Lebeis, Sarah L</dc:creator><dc:creator>Esser, Sarah P</dc:creator><dc:creator>Acinas, Silvia G</dc:creator><dc:creator>Wilhelm, Steven S</dc:creator><dc:creator>Singer, Steven W</dc:creator><dc:creator>Tringe, Susannah S</dc:creator><dc:creator>Woyke, Tanja</dc:creator><dc:creator>Reddy, TBK</dc:creator><dc:creator>Bell, Terrence H</dc:creator><dc:creator>Mock, Thomas</dc:creator><dc:creator>McAllister, Tim</dc:creator><dc:creator>Thiel, Vera</dc:creator><dc:date>2022-10-01</dc:date><dc:description>High-throughput RNA sequencing offers broad opportunities to explore the Earth RNA virome. Mining 5,150 diverse metatranscriptomes uncovered &amp;gt;2.5 million RNA virus contigs. Analysis of &amp;gt;330,000 RNA-dependent RNA polymerases (RdRPs) shows that this expansion corresponds to a 5-fold increase of the known RNA virus diversity. Gene content analysis revealed multiple protein domains previously not found in RNA viruses and implicated in virus-host interactions. Extended RdRP phylogeny supports the monophyly of the five established phyla and reveals two putative additional bacteriophage phyla and numerous putative additional classes and orders. The dramatically expanded phylum Lenarviricota, consisting of bacterial and related eukaryotic viruses, now accounts for a third of the RNA virome. Identification of CRISPR spacer matches and bacteriolytic proteins suggests that subsets of picobirnaviruses and partitiviruses, previously associated with eukaryotes, infect prokaryotic hosts.</dc:description><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3102 Bioinformatics and Computational Biology (for-2020)</dc:subject><dc:subject>Infectious Diseases (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Emerging Infectious Diseases (rcdc)</dc:subject><dc:subject>Microbiome (rcdc)</dc:subject><dc:subject>Infection (hrcs-hc)</dc:subject><dc:subject>Bacteriophages (mesh)</dc:subject><dc:subject>DNA-Directed RNA Polymerases (mesh)</dc:subject><dc:subject>Genome</dc:subject><dc:subject>Viral (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>RNA (mesh)</dc:subject><dc:subject>RNA Viruses (mesh)</dc:subject><dc:subject>RNA-Dependent RNA Polymerase (mesh)</dc:subject><dc:subject>Virome (mesh)</dc:subject><dc:subject>RNA Virus Discovery Consortium</dc:subject><dc:subject>Bacteriophages (mesh)</dc:subject><dc:subject>RNA Viruses (mesh)</dc:subject><dc:subject>DNA-Directed RNA Polymerases (mesh)</dc:subject><dc:subject>RNA (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Genome</dc:subject><dc:subject>Viral (mesh)</dc:subject><dc:subject>RNA-Dependent RNA Polymerase (mesh)</dc:subject><dc:subject>Virome (mesh)</dc:subject><dc:subject>Bactriophage</dc:subject><dc:subject>Functional protein annotation</dc:subject><dc:subject>Metatranscriptomics</dc:subject><dc:subject>RNA Virus</dc:subject><dc:subject>RNA dependent RNA polymerase</dc:subject><dc:subject>Viral Ecology</dc:subject><dc:subject>Virus</dc:subject><dc:subject>Virus - Host prediction</dc:subject><dc:subject>viral phylogeny</dc:subject><dc:subject>Bacteriophages (mesh)</dc:subject><dc:subject>DNA-Directed RNA Polymerases (mesh)</dc:subject><dc:subject>Genome</dc:subject><dc:subject>Viral (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>RNA (mesh)</dc:subject><dc:subject>RNA Viruses (mesh)</dc:subject><dc:subject>RNA-Dependent RNA Polymerase (mesh)</dc:subject><dc:subject>Virome (mesh)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>Developmental Biology (science-metrix)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6d60q36g</dc:identifier><dc:identifier>https://escholarship.org/content/qt6d60q36g/qt6d60q36g.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.cell.2022.08.023</dc:identifier><dc:type>article</dc:type><dc:source>Cell, vol 185, iss 21</dc:source><dc:coverage>4023 - 4037.e18</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt17x0v1g1</identifier><datestamp>2026-09-15T18:22:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt17x0v1g1</dc:identifier><dc:title>Binary pseudo-random array standards for calibration of 3D optical surface profilers used for metrology with aspheric x-ray optics</dc:title><dc:creator>Munechika, Keiko</dc:creator><dc:creator>Chao, Weilun</dc:creator><dc:creator>Dhuey, Scott</dc:creator><dc:creator>Lacey, Ian</dc:creator><dc:creator>Pina-Hernandez, Carlos</dc:creator><dc:creator>Rochester, Simon</dc:creator><dc:creator>Yashchuk, Valeriy V</dc:creator><dc:contributor>North-Morris, Michael B</dc:contributor><dc:contributor>Creath, Katherine</dc:contributor><dc:contributor>Porras-Aguilar, Rosario</dc:contributor><dc:date>2022-10-03</dc:date><dc:description>High-accuracy surface metrology is vitally important in manufacturing ultra-high-quality free-form mirrors designed to manipulate x-ray light with nanometer-scale wavelengths. The current and potential capabilities of x˗ray mirror manufacturing are limited by inherent imperfections of the integrated metrology tools. Metrology tools are currently calibrated with super-polished flat test-standard/reference mirrors. This is acceptable for fabrication of slightly curved x-ray optics. However, for even moderately curved aspherical x-ray mirrors the flat-reference calibration is not sufficiently accurate. For micro-stitching interferometry developed for surface measurements with curved x-ray mirrors, the tool aberration errors are known to be transferred into the optical surface topography of x-ray mirrors. Our approach to improving metrology is to thoroughly calibrate the measuring tool and apply the results of the calibration to deconvolution of the measured data. Here we explore the application of a recently developed technique for calibrating the instrument transfer function (ITF) of 3D optical surface profilers to metrology with significantly curved x-ray optics. The technique, based on test standards patterned with two-dimensional (2D) binary pseudo-random arrays (BPRAs), employs the unique properties of the BPRA patterns in the spatial frequency domain. The inherent 2D power spectral density of the pattern has a deterministic white-noise-like character that allows direct determination of the ITF with uniform sensitivity over the entire spatial frequency range and field of view of an instrument. The high efficacy of the technique has been previously demonstrated in application to metrology with flat and slightly curved optics. Here, we concentrate on development of an efficient fabrication process for production of highly randomized (HR) BPRA test standards on flat and 500-mm spherical optical substrates. We also compare and discuss the results of the ITF calibration of an interferometric microscope when using the HR BPRA standards on flat and curved substrates.</dc:description><dc:subject>surface metrology</dc:subject><dc:subject>calibration</dc:subject><dc:subject>instrument transfer function</dc:subject><dc:subject>binary pseudo-random</dc:subject><dc:subject>test standard</dc:subject><dc:subject>power spectral density</dc:subject><dc:subject>aspheric optics</dc:subject><dc:subject>x-ray optics</dc:subject><dc:subject>4014 Manufacturing Engineering (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>4006 Communications engineering (for-2020)</dc:subject><dc:subject>4009 Electronics</dc:subject><dc:subject>sensors and digital hardware (for-2020)</dc:subject><dc:subject>5102 Atomic</dc:subject><dc:subject>molecular and optical physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/17x0v1g1</dc:identifier><dc:identifier>https://escholarship.org/content/qt17x0v1g1/qt17x0v1g1.pdf</dc:identifier><dc:identifier>info:doi/10.1117/12.2633163</dc:identifier><dc:type>article</dc:type><dc:source>Proceedings of SPIE--the International Society for Optical Engineering, vol 12223</dc:source><dc:coverage>1222307-1222307-19 - 1222307-1222307-19</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5qq7x2w0</identifier><datestamp>2026-09-15T18:18:37Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5qq7x2w0</dc:identifier><dc:title>Treatment-induced arteriolar revascularization and miR-126 enhancement in bone marrow niche protect leukemic stem cells in AML</dc:title><dc:creator>Zhang, Bin</dc:creator><dc:creator>Nguyen, Le Xuan Truong</dc:creator><dc:creator>Zhao, Dandan</dc:creator><dc:creator>Frankhouser, David E</dc:creator><dc:creator>Wang, Huafeng</dc:creator><dc:creator>Hoang, Dinh Hoa</dc:creator><dc:creator>Qiao, Junjing</dc:creator><dc:creator>Abundis, Christina</dc:creator><dc:creator>Brehove, Matthew</dc:creator><dc:creator>Su, Yu-Lin</dc:creator><dc:creator>Feng, Yuxin</dc:creator><dc:creator>Stein, Anthony</dc:creator><dc:creator>Ghoda, Lucy</dc:creator><dc:creator>Dorrance, Adrianne</dc:creator><dc:creator>Perrotti, Danilo</dc:creator><dc:creator>Chen, Zhen</dc:creator><dc:creator>Han, Anjia</dc:creator><dc:creator>Pichiorri, Flavia</dc:creator><dc:creator>Jin, Jie</dc:creator><dc:creator>Jovanovic-Talisman, Tijana</dc:creator><dc:creator>Caligiuri, Michael A</dc:creator><dc:creator>Kuo, Calvin J</dc:creator><dc:creator>Yoshimura, Akihiko</dc:creator><dc:creator>Li, Ling</dc:creator><dc:creator>Rockne, Russell C</dc:creator><dc:creator>Kortylewski, Marcin</dc:creator><dc:creator>Zheng, Yi</dc:creator><dc:creator>Carlesso, Nadia</dc:creator><dc:creator>Kuo, Ya-Huei</dc:creator><dc:creator>Marcucci, Guido</dc:creator><dc:date>2021-12-01</dc:date><dc:description>BackgroundDuring acute myeloid leukemia (AML) growth, the bone marrow (BM) niche acquires significant vascular changes that can be offset by therapeutic blast cytoreduction. The molecular mechanisms of this vascular plasticity remain to be fully elucidated. Herein, we report on the changes that occur in the vascular compartment of the FLT3-ITD+ AML BM niche pre and post treatment and their impact on leukemic stem cells (LSCs).MethodsBM vasculature was evaluated in FLT3-ITD+ AML models (MllPTD/WT/Flt3ITD/ITD mouse and patient-derived xenograft) by 3D confocal imaging of long bones, calvarium vascular permeability assays, and flow cytometry analysis. Cytokine levels were measured by Luminex assay and miR-126 levels evaluated by Q-RT-PCR and miRNA staining. Wild-type (wt) and&amp;nbsp;MllPTD/WT/Flt3ITD/ITD mice with endothelial cell (EC) miR-126 knockout or overexpression served as controls. The impact of treatment-induced BM vascular changes on LSC activity was evaluated by secondary transplantation of BM cells after administration of tyrosine kinase inhibitors (TKIs) to MllPTD/WT/Flt3ITD/ITD mice with/without either EC miR-126 KO or co-treatment with tumor necrosis factor alpha (TNFα) or anti-miR-126 miRisten.ResultsIn the normal BM niche, CD31+Sca-1high ECs lining arterioles have miR-126 levels higher than CD31+Sca-1low ECs lining sinusoids. We noted that during FLT3-ITD+ AML growth, the BM niche lost arterioles and gained sinusoids. These changes were mediated by TNFα, a cytokine produced by AML blasts, which induced EC miR-126 downregulation and caused depletion of CD31+Sca-1high ECs and gain in CD31+Sca-1low ECs. Loss of miR-126high ECs led to a decreased EC miR-126 supply to LSCs, which then entered the cell cycle and promoted leukemia growth. Accordingly, antileukemic treatment with TKI decreased the BM blast-produced TNFα and increased miR-126high ECs and the EC miR-126 supply to LSCs. High miR-126 levels safeguarded LSCs, as shown by more severe disease in secondary transplanted mice. Conversely, EC miR-126 deprivation via genetic or pharmacological EC miR-126 knock-down prevented treatment-induced BM miR-126high EC expansion and in turn LSC protection.ConclusionsTreatment-induced CD31+Sca-1high EC re-vascularization of the leukemic BM niche may represent a LSC extrinsic mechanism of treatment resistance that can be overcome with therapeutic EC miR-126 deprivation.Graphic abstract</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3201 Cardiovascular Medicine and Haematology (for-2020)</dc:subject><dc:subject>3211 Oncology and Carcinogenesis (for-2020)</dc:subject><dc:subject>Hematology (rcdc)</dc:subject><dc:subject>Pediatric Cancer (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Stem Cell Research - Nonembryonic - Non-Human (rcdc)</dc:subject><dc:subject>Rare Diseases (rcdc)</dc:subject><dc:subject>Cancer (rcdc)</dc:subject><dc:subject>Orphan Drug (rcdc)</dc:subject><dc:subject>Biotechnology (rcdc)</dc:subject><dc:subject>Childhood Leukemia (rcdc)</dc:subject><dc:subject>Stem Cell Research (rcdc)</dc:subject><dc:subject>2.1 Biological and endogenous factors (hrcs-rac)</dc:subject><dc:subject>Cancer (hrcs-hc)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Bone Marrow (mesh)</dc:subject><dc:subject>Gene Expression Regulation</dc:subject><dc:subject>Leukemic (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Leukemia</dc:subject><dc:subject>Myeloid</dc:subject><dc:subject>Acute (mesh)</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>Mice</dc:subject><dc:subject>Inbred C57BL (mesh)</dc:subject><dc:subject>MicroRNAs (mesh)</dc:subject><dc:subject>Neoplastic Stem Cells (mesh)</dc:subject><dc:subject>Up-Regulation (mesh)</dc:subject><dc:subject>fms-Like Tyrosine Kinase 3 (mesh)</dc:subject><dc:subject>Acute myeloid leukemia</dc:subject><dc:subject>BM vascular niche</dc:subject><dc:subject>TNF alpha</dc:subject><dc:subject>miR-126</dc:subject><dc:subject>Leukemic stem cell</dc:subject><dc:subject>Treatment resistance</dc:subject><dc:subject>Bone Marrow (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Mice</dc:subject><dc:subject>Inbred C57BL (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>MicroRNAs (mesh)</dc:subject><dc:subject>Gene Expression Regulation</dc:subject><dc:subject>Leukemic (mesh)</dc:subject><dc:subject>Up-Regulation (mesh)</dc:subject><dc:subject>fms-Like Tyrosine Kinase 3 (mesh)</dc:subject><dc:subject>Neoplastic Stem Cells (mesh)</dc:subject><dc:subject>Leukemia</dc:subject><dc:subject>Myeloid</dc:subject><dc:subject>Acute (mesh)</dc:subject><dc:subject>Acute myeloid leukemia</dc:subject><dc:subject>BM vascular niche</dc:subject><dc:subject>Leukemic stem cell</dc:subject><dc:subject>TNFα</dc:subject><dc:subject>Treatment resistance</dc:subject><dc:subject>miR-126</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Bone Marrow (mesh)</dc:subject><dc:subject>Gene Expression Regulation</dc:subject><dc:subject>Leukemic (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Leukemia</dc:subject><dc:subject>Myeloid</dc:subject><dc:subject>Acute (mesh)</dc:subject><dc:subject>Mice (mesh)</dc:subject><dc:subject>Mice</dc:subject><dc:subject>Inbred C57BL (mesh)</dc:subject><dc:subject>MicroRNAs (mesh)</dc:subject><dc:subject>Neoplastic Stem Cells (mesh)</dc:subject><dc:subject>Up-Regulation (mesh)</dc:subject><dc:subject>fms-Like Tyrosine Kinase 3 (mesh)</dc:subject><dc:subject>1102 Cardiorespiratory Medicine and Haematology (for)</dc:subject><dc:subject>1112 Oncology and Carcinogenesis (for)</dc:subject><dc:subject>3201 Cardiovascular medicine and haematology (for-2020)</dc:subject><dc:subject>3211 Oncology and carcinogenesis (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5qq7x2w0</dc:identifier><dc:identifier>https://escholarship.org/content/qt5qq7x2w0/qt5qq7x2w0.pdf</dc:identifier><dc:identifier>info:doi/10.1186/s13045-021-01133-y</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Hematology &amp; Oncology, vol 14, iss 1</dc:source><dc:coverage>122</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4qs2f8gg</identifier><datestamp>2026-09-15T18:17:32Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4qs2f8gg</dc:identifier><dc:title>Lithium diffusion-controlled Li-Al alloy negative electrode for all-solid-state battery</dc:title><dc:creator>Jeon, Yuju</dc:creator><dc:creator>Lee, Dong Ju</dc:creator><dc:creator>Zheng, Hongkui</dc:creator><dc:creator>Behara, Sesha Sai</dc:creator><dc:creator>Lee, Jung-Pil</dc:creator><dc:creator>Wu, Junlin</dc:creator><dc:creator>Li, Feng</dc:creator><dc:creator>Tang, Wei</dc:creator><dc:creator>Zhang, Lanshuang</dc:creator><dc:creator>Chen, Yu-Ting</dc:creator><dc:creator>Xu, Dapeng</dc:creator><dc:creator>Kim, Jiyoung</dc:creator><dc:creator>Song, Min-Sang</dc:creator><dc:creator>Van der Ven, Anton</dc:creator><dc:creator>He, Kai</dc:creator><dc:creator>Chen, Zheng</dc:creator><dc:date>2025-10-31</dc:date><dc:description>Metal alloy negative electrodes are promising candidates for lithium all-solid-state batteries due to their high specific capacity and low cost. However, chemo-mechanical degradation and atomic transport limitations in the solid state remain unresolved challenges. Herein, we demonstrate a&amp;nbsp;lithium-aluminum alloy negative electrode design (LixAl1, x = molar ratio of lithium to aluminum) based on a comprehensive understanding of the&amp;nbsp;underlying diffusion mechanisms within the lithium-poor α (0 ≤ x ≤ 0.05) and lithium-rich β phases (0.95 ≤ x ≤ 1). The lithium-aluminum alloy negative electrodes with a higher lithium to aluminum&amp;nbsp;ratio facilitate lithium migration through the β-LiAl phases, which serve as highly lithium-conductive channels with a lithium diffusion coefficient that is&amp;nbsp;ten orders of magnitude higher than that of the α phase. In addition, a bulk dense negative electrode and an intimate negative electrode-electrolyte interface is demonstrated in the cross-sections of the lithium-aluminum alloy negative electrodes. Consequently, a high-rate capability of 7 mA cm−2 is attained in LiNi0.8Co0.1Mn0.1O2-based full-cell operation. The optimal cell configuration of Li0.5Al1 | |LiNi0.8Co0.1Mn0.1O2 shows stable lithium reversibility during 2000 cycles with a capacity retention of 83% at 4 mA cm−2 with a LiNi0.8Co0.1Mn0.1O2 loading of 5 mAh cm−2.</dc:description><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>4016 Materials Engineering (for-2020)</dc:subject><dc:subject>34 Chemical Sciences (for-2020)</dc:subject><dc:subject>3406 Physical Chemistry (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4qs2f8gg</dc:identifier><dc:identifier>https://escholarship.org/content/qt4qs2f8gg/qt4qs2f8gg.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41467-025-64386-y</dc:identifier><dc:type>article</dc:type><dc:source>Nature Communications, vol 16, iss 1</dc:source><dc:coverage>9629</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2g668163</identifier><datestamp>2026-09-15T18:14:27Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2g668163</dc:identifier><dc:title>Measurement of H Λ 4 and He Λ 4 binding energy in Au+Au collisions at s NN = 3 GeV</dc:title><dc:creator>Collaboration, STAR</dc:creator><dc:creator>Abdallah, MS</dc:creator><dc:creator>Aboona, BE</dc:creator><dc:creator>Adam, J</dc:creator><dc:creator>Adamczyk, L</dc:creator><dc:creator>Adams, JR</dc:creator><dc:creator>Adkins, JK</dc:creator><dc:creator>Aggarwal, I</dc:creator><dc:creator>Aggarwal, MM</dc:creator><dc:creator>Ahammed, Z</dc:creator><dc:creator>Anderson, DM</dc:creator><dc:creator>Aschenauer, EC</dc:creator><dc:creator>Ashraf, MU</dc:creator><dc:creator>Atchison, J</dc:creator><dc:creator>Bairathi, V</dc:creator><dc:creator>Baker, W</dc:creator><dc:creator>Ball, JG</dc:creator><dc:creator>Barish, K</dc:creator><dc:creator>Behera, A</dc:creator><dc:creator>Bellwied, R</dc:creator><dc:creator>Bhagat, P</dc:creator><dc:creator>Bhasin, A</dc:creator><dc:creator>Bielcik, J</dc:creator><dc:creator>Bielcikova, J</dc:creator><dc:creator>Brandenburg, JD</dc:creator><dc:creator>Cai, XZ</dc:creator><dc:creator>Caines, H</dc:creator><dc:creator>de la Barca Sánchez, M Calderón</dc:creator><dc:creator>Cebra, D</dc:creator><dc:creator>Chakaberia, I</dc:creator><dc:creator>Chaloupka, P</dc:creator><dc:creator>Chan, BK</dc:creator><dc:creator>Chang, Z</dc:creator><dc:creator>Chatterjee, A</dc:creator><dc:creator>Chattopadhyay, S</dc:creator><dc:creator>Chen, D</dc:creator><dc:creator>Chen, J</dc:creator><dc:creator>Chen, JH</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Chen, Z</dc:creator><dc:creator>Cheng, J</dc:creator><dc:creator>Choudhury, S</dc:creator><dc:creator>Christie, W</dc:creator><dc:creator>Chu, X</dc:creator><dc:creator>Crawford, HJ</dc:creator><dc:creator>Csanád, M</dc:creator><dc:creator>Daugherity, M</dc:creator><dc:creator>Deppner, IM</dc:creator><dc:creator>Dhamija, A</dc:creator><dc:creator>Di Carlo, L</dc:creator><dc:creator>Didenko, L</dc:creator><dc:creator>Dixit, P</dc:creator><dc:creator>Dong, X</dc:creator><dc:creator>Drachenberg, JL</dc:creator><dc:creator>Duckworth, E</dc:creator><dc:creator>Dunlop, JC</dc:creator><dc:creator>Engelage, J</dc:creator><dc:creator>Eppley, G</dc:creator><dc:creator>Esumi, S</dc:creator><dc:creator>Evdokimov, O</dc:creator><dc:creator>Ewigleben, A</dc:creator><dc:creator>Eyser, O</dc:creator><dc:creator>Fatemi, R</dc:creator><dc:creator>Fawzi, FM</dc:creator><dc:creator>Fazio, S</dc:creator><dc:creator>Feng, CJ</dc:creator><dc:creator>Feng, Y</dc:creator><dc:creator>Finch, E</dc:creator><dc:creator>Fisyak, Y</dc:creator><dc:creator>Francisco, A</dc:creator><dc:creator>Fu, C</dc:creator><dc:creator>Gagliardi, CA</dc:creator><dc:creator>Galatyuk, T</dc:creator><dc:creator>Geurts, F</dc:creator><dc:creator>Ghimire, N</dc:creator><dc:creator>Gibson, A</dc:creator><dc:creator>Gopal, K</dc:creator><dc:creator>Gou, X</dc:creator><dc:creator>Grosnick, D</dc:creator><dc:creator>Gupta, A</dc:creator><dc:creator>Guryn, W</dc:creator><dc:creator>Hamed, A</dc:creator><dc:creator>Han, Y</dc:creator><dc:creator>Harabasz, S</dc:creator><dc:creator>Harasty, MD</dc:creator><dc:creator>Harris, JW</dc:creator><dc:creator>Harrison, H</dc:creator><dc:creator>He, S</dc:creator><dc:creator>He, W</dc:creator><dc:creator>He, XH</dc:creator><dc:creator>He, Y</dc:creator><dc:creator>Heppelmann, S</dc:creator><dc:creator>Herrmann, N</dc:creator><dc:creator>Hoffman, E</dc:creator><dc:creator>Holub, L</dc:creator><dc:creator>Hu, C</dc:creator><dc:creator>Hu, Q</dc:creator><dc:creator>Hu, Y</dc:creator><dc:creator>Huang, H</dc:creator><dc:creator>Huang, HZ</dc:creator><dc:date>2022-11-01</dc:date><dc:description>Measurements of mass and Λ binding energy of Λ 4 H and Λ 4 He in Au+Au collisions at s NN = 3 GeV are presented, with an aim to address the charge symmetry breaking (CSB) problem in hypernuclei systems with atomic number A = 4. The Λ binding energies are measured to be 2.22 ± 0.06 (stat.)±0.14(syst.) MeV and 2.38 ± 0.13 (stat.)±0.12(syst.) MeV for Λ 4 H and Λ 4 He, respectively. The measured Λ binding-energy difference is 0.16 ± 0.14 ( stat . ) ± 0.10 ( syst . ) MeV for ground states. Combined with the γ-ray transition energies, the binding-energy difference for excited states is − 0.16 ± 0.14 ( stat . ) ± 0.10 ( syst . ) MeV, which is negative and comparable to the value of the ground states within uncertainties. These new measurements on the Λ binding-energy difference in A = 4 hypernuclei systems are consistent with the theoretical calculations that result in Δ B Λ 4 ( 1 exc + ) ≈ − Δ B Λ 4 ( 0 g.s. + ) &amp;lt; 0 and present a new method for the study of CSB effect using relativistic heavy-ion collisions.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>NSD-Relativistic Nuclear Collisions (c-lbnl-label)</dc:subject><dc:subject>0105 Mathematical Physics (for)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>49 Mathematical sciences (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2g668163</dc:identifier><dc:identifier>https://escholarship.org/content/qt2g668163/qt2g668163.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.physletb.2022.137449</dc:identifier><dc:type>article</dc:type><dc:source>Physics Letters B, vol 834</dc:source><dc:coverage>137449</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt55941411</identifier><datestamp>2026-09-15T18:13:49Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt55941411</dc:identifier><dc:title>UPC++ v1.0 Specification, Revision 2022.9.0</dc:title><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Kamil, Amir</dc:creator><dc:date>2022-09-30</dc:date><dc:description>UPC++ is a C++ library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). All communication operations are syntactically explicit and default to non-blocking; asynchrony is managed through the use of futures, promises and continuation callbacks, enabling the programmer to construct a graph of operations to execute asynchronously as high-latency dependencies are satisfied. A global pointer abstraction provides system-wide addressability of shared memory, including host and accelerator memories. The parallelism model is primarily process-based, but the interface is thread-safe and designed to allow efficient and expressive use in multi-threaded applications. The interface is designed for extreme scalability throughout, and deliberately avoids design features that could inhibit scalability.</dc:description><dc:subject>Exascale Computing</dc:subject><dc:subject>Library specification</dc:subject><dc:subject>parallel distributed programming</dc:subject><dc:subject>PGAS</dc:subject><dc:subject>scientific computing</dc:subject><dc:subject>UPC++</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/55941411</dc:identifier><dc:identifier>https://escholarship.org/content/qt55941411/qt55941411.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S4M59P</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt872004w9</identifier><datestamp>2026-09-15T18:13:45Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt872004w9</dc:identifier><dc:title>UPC++ v1.0 Programmer’s Guide, Revision 2022.9.0</dc:title><dc:creator>Bachan, John</dc:creator><dc:creator>Baden, Scott</dc:creator><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Corbino, Johnny</dc:creator><dc:creator>Grossman, Johnathan</dc:creator><dc:creator>Hargrove, Paul H</dc:creator><dc:creator>Hofmeyr, Steven</dc:creator><dc:creator>Jacquelin, Mathias</dc:creator><dc:creator>Kamil, Amir</dc:creator><dc:creator>Van Straalen, Brian</dc:creator><dc:creator>Waters, Daniel</dc:creator><dc:date>2022-09-29</dc:date><dc:description>UPC++ is a C++ library that supports Partitioned Global Address Space (PGAS) programming. It is designed for writing efficient, scalable parallel programs on distributed-memory parallel computers. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). The UPC++ control model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. The PGAS memory model additionally provides one-sided RMA communication to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ also features Remote Procedure Call (RPC) communication, making it easy to move computation to operate on data that resides on remote processes.

UPC++ was designed to support exascale high-performance computing, and the library interfaces and implementation are focused on maximizing scalability. In UPC++, all communication operations are syntactically explicit, which encourages programmers to consider the costs associated with communication and data movement. Moreover, all communication operations are asynchronous by default, encouraging programmers to seek opportunities for overlapping communication latencies with other useful work. UPC++ provides expressive and composable abstractions designed for efficiently managing aggressive use of asynchrony in programs. Together, these design principles are intended to enable programmers to write applications using UPC++ that perform well even on hundreds of thousands of cores.</dc:description><dc:subject>Exascale Computing</dc:subject><dc:subject>GASNet</dc:subject><dc:subject>Library Programmer's Guide</dc:subject><dc:subject>parallel distributed programming</dc:subject><dc:subject>PGAS</dc:subject><dc:subject>scientific computing</dc:subject><dc:subject>UPC++</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/872004w9</dc:identifier><dc:identifier>https://escholarship.org/content/qt872004w9/qt872004w9.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S4QW26</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6dn8z4sg</identifier><datestamp>2026-09-15T18:06:29Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6dn8z4sg</dc:identifier><dc:title>Cosmological constraints from the cross-correlation of DESI Luminous Red Galaxies with CMB lensing from Planck PR4 and ACT DR6</dc:title><dc:creator>Sailer, Noah</dc:creator><dc:creator>Kim, Joshua</dc:creator><dc:creator>Ferraro, Simone</dc:creator><dc:creator>Madhavacheril, Mathew S</dc:creator><dc:creator>White, Martin</dc:creator><dc:creator>Abril-Cabezas, Irene</dc:creator><dc:creator>Aguilar, Jessica Nicole</dc:creator><dc:creator>Ahlen, Steven</dc:creator><dc:creator>Bond, J Richard</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>Burtin, Etienne</dc:creator><dc:creator>Calabrese, Erminia</dc:creator><dc:creator>Chen, Shi-Fan</dc:creator><dc:creator>Choi, Steve K</dc:creator><dc:creator>Claybaugh, Todd</dc:creator><dc:creator>Dawson, Kyle</dc:creator><dc:creator>de la Macorra, Axel</dc:creator><dc:creator>DeRose, Joseph</dc:creator><dc:creator>Dey, Arjun</dc:creator><dc:creator>Dey, Biprateep</dc:creator><dc:creator>Doel, Peter</dc:creator><dc:creator>Dunkley, Jo</dc:creator><dc:creator>Embil-Villagra, Carmen</dc:creator><dc:creator>Farren, Gerrit S</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>Forero-Romero, Jaime E</dc:creator><dc:creator>Gaztañaga, Enrique</dc:creator><dc:creator>Gluscevic, Vera</dc:creator><dc:creator>Gontcho, Satya Gontcho A</dc:creator><dc:creator>Honscheid, Klaus</dc:creator><dc:creator>Howlett, Cullan</dc:creator><dc:creator>Juneau, Stephanie</dc:creator><dc:creator>Kirkby, David</dc:creator><dc:creator>Kisner, Theodore</dc:creator><dc:creator>Kremin, Anthony</dc:creator><dc:creator>Landriau, Martin</dc:creator><dc:creator>Le Guillou, Laurent</dc:creator><dc:creator>Levi, Michael</dc:creator><dc:creator>Manera, Marc</dc:creator><dc:creator>Meisner, Aaron</dc:creator><dc:creator>Miquel, Ramon</dc:creator><dc:creator>Moodley, Kavilan</dc:creator><dc:creator>Moustakas, John</dc:creator><dc:creator>Niemack, Michael D</dc:creator><dc:creator>Niz, Gustavo</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Percival, Will</dc:creator><dc:creator>Prada, Francisco</dc:creator><dc:creator>Qu, Frank J</dc:creator><dc:creator>Rossi, Graziano</dc:creator><dc:creator>Sanchez, Eusebio</dc:creator><dc:creator>Schaan, Emmanuel</dc:creator><dc:creator>Schlafly, Edward</dc:creator><dc:creator>Schlegel, David</dc:creator><dc:creator>Schubnell, Michael</dc:creator><dc:creator>Sehgal, Neelima</dc:creator><dc:creator>Seo, Hee-Jong</dc:creator><dc:creator>Sherwin, Blake</dc:creator><dc:creator>Sifón, Cristóbal</dc:creator><dc:creator>Sprayberry, David</dc:creator><dc:creator>Staggs, Suzanne T</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Weaver, Benjamin Alan</dc:creator><dc:creator>Yèche, Christophe</dc:creator><dc:creator>Zhou, Rongpu</dc:creator><dc:creator>Zou, Hu</dc:creator><dc:date>2025-06-01</dc:date><dc:description>We infer the growth of large scale structure over the redshift range 0.4 ≲ z ≲ 1 from the cross-correlation of spectroscopically calibrated Luminous Red Galaxies (LRGs) selected from the Dark Energy Spectroscopic Instrument (DESI) legacy imaging survey with CMB lensing maps reconstructed from the latest Planck and ACT data. We adopt a hybrid effective field theory (HEFT) model that robustly regulates the cosmological information obtainable from smaller scales, such that our cosmological constraints are reliably derived from the (predominantly) linear regime. We perform an extensive set of bandpower- and parameter-level systematics checks to ensure the robustness of our results and to characterize the uniformity of the LRG sample. We demonstrate that our results are stable to a wide range of modeling assumptions, finding excellent agreement with a linear theory analysis performed on a restricted range of scales. From a tomographic analysis of the four LRG photometric redshift bins we find that the rate of structure growth is consistent with ΛCDM with an overall amplitude that is ≃ 5-7% lower than predicted by primary CMB measurements with modest (∼ 2σ) statistical significance. From the combined analysis of all four bins and their cross-correlations with Planck we obtain S 8 = 0.765 ± 0.023, which is less discrepant with primary CMB measurements than previous DESI LRG cross Planck CMB lensing results. From the cross-correlation with ACT we obtain S 8 = 0.790+0.024 -0.027, while when jointly analyzing Planck and ACT we find S 8 = 0.775+0.019 -0.022 from our data alone and σ 8 = 0.772+0.020 -0.023 with the addition of BAO data. These constraints are consistent with the latest Planck primary CMB analyses at the ≃ 1.6-2.2σ level, and are in excellent agreement with galaxy lensing surveys.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>cosmological parameters from LSS</dc:subject><dc:subject>galaxy clustering</dc:subject><dc:subject>gravitational lensing</dc:subject><dc:subject>redshift surveys</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6dn8z4sg</dc:identifier><dc:identifier>https://escholarship.org/content/qt6dn8z4sg/qt6dn8z4sg.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/06/008</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 06</dc:source><dc:coverage>008</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1jf3t79n</identifier><datestamp>2026-09-15T18:06:12Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1jf3t79n</dc:identifier><dc:title>The effect of quasar redshift errors on Lyman-α forest correlation functions</dc:title><dc:creator>Youles, Samantha</dc:creator><dc:creator>Bautista, Julian E</dc:creator><dc:creator>Font-Ribera, Andreu</dc:creator><dc:creator>Bacon, David</dc:creator><dc:creator>Rich, James</dc:creator><dc:creator>Brooks, David</dc:creator><dc:creator>Davis, Tamara M</dc:creator><dc:creator>Dawson, Kyle</dc:creator><dc:creator>de la Macorra, Axel</dc:creator><dc:creator>Dhungana, Govinda</dc:creator><dc:creator>Doel, Peter</dc:creator><dc:creator>Fanning, Kevin</dc:creator><dc:creator>Gaztañaga, Enrique</dc:creator><dc:creator>Gontcho, Satya Gontcho A</dc:creator><dc:creator>Gonzalez-Morales, Alma X</dc:creator><dc:creator>Guy, Julien</dc:creator><dc:creator>Honscheid, Klaus</dc:creator><dc:creator>Iršič, Vid</dc:creator><dc:creator>Kehoe, Robert</dc:creator><dc:creator>Kirkby, David</dc:creator><dc:creator>Kisner, Theodore</dc:creator><dc:creator>Landriau, Martin</dc:creator><dc:creator>Le Guillou, Laurent</dc:creator><dc:creator>Levi, Michael E</dc:creator><dc:creator>Martini, Paul</dc:creator><dc:creator>Muñoz-Gutiérrez, Andrea</dc:creator><dc:creator>Palanque-Delabrouille, Nathalie</dc:creator><dc:creator>Pérez-Ràfols, Ignasi</dc:creator><dc:creator>Poppett, Claire</dc:creator><dc:creator>Ramírez-Pérez, César</dc:creator><dc:creator>Schubnell, Michael</dc:creator><dc:creator>Tarlé, Gregory</dc:creator><dc:creator>Walther, Michael</dc:creator><dc:date>2022-08-25</dc:date><dc:description>ABSTRACT
                  Using synthetic Lyman-α forests from the Dark Energy Spectroscopic Instrument (DESI) survey, we present a study of the impact of errors in the estimation of quasar redshift on the Lyman-α correlation functions. Estimates of quasar redshift have large uncertainties of a few hundred km s−1 due to the broadness of the emission lines and the intrinsic shifts from other emission lines. We inject Gaussian random redshift errors into the mock quasar catalogues, and measure the auto-correlation and the Lyman-α-quasar cross-correlation functions. We find a smearing of the BAO feature in the radial direction, but changes in the peak position are negligible. However, we see a significant unphysical correlation for small separations transverse to the line of sight which increases with the amplitude of the redshift errors. We interpret this contamination as a result of the broadening of emission lines in the measured mean continuum, caused by quasar redshift errors, combined with the unrealistically strong clustering of the simulated quasars on small scales.</dc:description><dc:subject>5101 Astronomical Sciences (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>large-scale structure of Universe</dc:subject><dc:subject>cosmology: theory</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>Astronomy &amp; Astrophysics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:subject>5109 Space sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1jf3t79n</dc:identifier><dc:identifier>https://escholarship.org/content/qt1jf3t79n/qt1jf3t79n.pdf</dc:identifier><dc:identifier>info:doi/10.1093/mnras/stac2102</dc:identifier><dc:type>article</dc:type><dc:source>Monthly Notices of the Royal Astronomical Society, vol 516, iss 1</dc:source><dc:coverage>421 - 433</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt63f2185k</identifier><datestamp>2026-09-15T17:57:57Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt63f2185k</dc:identifier><dc:title>Long-term missing value imputation for time series data using deep neural networks</dc:title><dc:creator>Park, Jangho</dc:creator><dc:creator>Müller, Juliane</dc:creator><dc:creator>Arora, Bhavna</dc:creator><dc:creator>Faybishenko, Boris</dc:creator><dc:creator>Pastorello, Gilberto</dc:creator><dc:creator>Varadharajan, Charuleka</dc:creator><dc:creator>Sahu, Reetik</dc:creator><dc:creator>Agarwal, Deborah</dc:creator><dc:date>2023-04-01</dc:date><dc:description>We present an approach that uses a deep learning model, in particular, a MultiLayer Perceptron, for estimating the missing values of a variable in multivariate time series data. We focus on filling a long continuous gap (e.g., multiple months of missing daily observations) rather than on individual randomly missing observations. Our proposed gap filling algorithm uses an automated method for determining the optimal MLP model architecture, thus allowing for optimal prediction performance for the given time series. We tested our approach by filling gaps of various lengths (three months to three years) in three environmental datasets with different time series characteristics, namely daily groundwater levels, daily soil moisture, and hourly Net Ecosystem Exchange. We compared the accuracy of the gap-filled values obtained with our approach to the widely used R-based time series gap filling methods ImputeTS and mtsdi. The results indicate that using an MLP for filling a large gap leads to better results, especially when the data behave nonlinearly. Thus, our approach enables the use of datasets that have a large gap in one variable, which is common in many long-term environmental monitoring observations.</dc:description><dc:subject>46 Information and Computing Sciences (for-2020)</dc:subject><dc:subject>4611 Machine Learning (for-2020)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>Bioengineering (rcdc)</dc:subject><dc:subject>Networking and Information Technology R&amp;D (NITRD) (rcdc)</dc:subject><dc:subject>Generic health relevance (hrcs-hc)</dc:subject><dc:subject>Missing value imputation</dc:subject><dc:subject>Environmental data</dc:subject><dc:subject>Machine learning</dc:subject><dc:subject>Hyperparameter optimization</dc:subject><dc:subject>Derivative-free optimization</dc:subject><dc:subject>Surrogate models</dc:subject><dc:subject>0801 Artificial Intelligence and Image Processing (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>1702 Cognitive Sciences (for)</dc:subject><dc:subject>Artificial Intelligence &amp; Image Processing (science-metrix)</dc:subject><dc:subject>4602 Artificial intelligence (for-2020)</dc:subject><dc:subject>4603 Computer vision and multimedia computation (for-2020)</dc:subject><dc:subject>4611 Machine learning (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/63f2185k</dc:identifier><dc:identifier>https://escholarship.org/content/qt63f2185k/qt63f2185k.pdf</dc:identifier><dc:identifier>info:doi/10.1007/s00521-022-08165-6</dc:identifier><dc:type>article</dc:type><dc:source>Neural Computing and Applications, vol 35, iss 12</dc:source><dc:coverage>9071 - 9091</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3rr6s00x</identifier><datestamp>2026-09-15T17:57:25Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3rr6s00x</dc:identifier><dc:title>Mixed TDP-43 proteinopathy and tauopathy in frontotemporal lobar degeneration: nine case series</dc:title><dc:creator>Kim, Eun-Joo</dc:creator><dc:creator>Brown, Jesse A</dc:creator><dc:creator>Deng, Jersey</dc:creator><dc:creator>Hwang, Ji-Hye L</dc:creator><dc:creator>Spina, Salvatore</dc:creator><dc:creator>Miller, Zachary A</dc:creator><dc:creator>DeMay, Mary G</dc:creator><dc:creator>Valcour, Victor</dc:creator><dc:creator>Karydas, Anna</dc:creator><dc:creator>Ramos, Eliana Marisa</dc:creator><dc:creator>Coppola, Giovanni</dc:creator><dc:creator>Miller, Bruce L</dc:creator><dc:creator>Rosen, Howard J</dc:creator><dc:creator>Seeley, William W</dc:creator><dc:creator>Grinberg, Lea T</dc:creator><dc:date>2018-12-01</dc:date><dc:description>ObjectivesTo determine the clinical, anatomical, genetic and pathological features of dual frontotemporal lobar degeneration (FTLD) pathology: FTLD-tau and FTLD-TDP-43 in a large clinicopathological cohort.MethodsWe selected subjects with mixed FTLD-TDP and FTLD-tau from 247 FTLD cases from the University of California, San Francisco, Neurodegenerative Disease Brain Bank collected between 2000 and 2016 and compared their clinical, anatomical, genetic, imaging and pathological signatures with those of subjects with pure FTLD.ResultsWe found nine cases (3.6%) with prominent FTLD-TDP and FTLD-tau. Six cases were sporadic, whereas one case had a C9ORF72 expansion, another had a TARDBP A90V variant, and the other had an MAPT p.A152T variant. The subtypes of FTLD-TDP and FTLD-tau varied. Mixed FTLD cases were older and tended to show a higher burden of Alzheimer disease pathology (3/9, 33%). The neuroimaging signature of mixed cases, in general, included more widespread atrophy than that of pure groups. Specifically, cases of mixed corticobasal degeneration (CBD) with FTLD-TDP showed more prominent asymmetric left-sided atrophy than did those of pure CBD. However, the clinical phenotype of mixed cases was similar to that seen in pure FTLD.ConclusionsAlthough patients with mixed FTLD-TDP and FTLD-tau are rare, in-depth clinical, pathological and genetic investigations may shed light on the genetic and biochemical pathways that cause the accumulation of multiple proteinaceous inclusions and inform therapeutic targets that may be beneficial to each one of these abnormal protein misfoldings.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>Frontotemporal Dementia (FTD) (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Neurodegenerative (rcdc)</dc:subject><dc:subject>Brain Disorders (rcdc)</dc:subject><dc:subject>Alzheimer's Disease Related Dementias (ADRD) (rcdc)</dc:subject><dc:subject>Alzheimer's Disease (rcdc)</dc:subject><dc:subject>Dementia (rcdc)</dc:subject><dc:subject>Rare Diseases (rcdc)</dc:subject><dc:subject>Acquired Cognitive Impairment (rcdc)</dc:subject><dc:subject>Aging (rcdc)</dc:subject><dc:subject>Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) (rcdc)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>2.1 Biological and endogenous factors (hrcs-rac)</dc:subject><dc:subject>Neurological (hrcs-hc)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Aged</dc:subject><dc:subject>80 and over (mesh)</dc:subject><dc:subject>Atrophy (mesh)</dc:subject><dc:subject>Brain (mesh)</dc:subject><dc:subject>C9orf72 Protein (mesh)</dc:subject><dc:subject>DNA-Binding Proteins (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Frontotemporal Lobar Degeneration (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Magnetic Resonance Imaging (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Tauopathies (mesh)</dc:subject><dc:subject>tau Proteins (mesh)</dc:subject><dc:subject>Frontotemporal lobar degeneration</dc:subject><dc:subject>TAR-DNA binding protein-43</dc:subject><dc:subject>Tau</dc:subject><dc:subject>Brain (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Tauopathies (mesh)</dc:subject><dc:subject>Atrophy (mesh)</dc:subject><dc:subject>tau Proteins (mesh)</dc:subject><dc:subject>DNA-Binding Proteins (mesh)</dc:subject><dc:subject>Magnetic Resonance Imaging (mesh)</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Aged</dc:subject><dc:subject>80 and over (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Frontotemporal Lobar Degeneration (mesh)</dc:subject><dc:subject>C9orf72 Protein (mesh)</dc:subject><dc:subject>Frontotemporal lobar degeneration</dc:subject><dc:subject>TAR-DNA binding protein-43</dc:subject><dc:subject>Tau</dc:subject><dc:subject>Aged (mesh)</dc:subject><dc:subject>Aged</dc:subject><dc:subject>80 and over (mesh)</dc:subject><dc:subject>Atrophy (mesh)</dc:subject><dc:subject>Brain (mesh)</dc:subject><dc:subject>C9orf72 Protein (mesh)</dc:subject><dc:subject>DNA-Binding Proteins (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Frontotemporal Lobar Degeneration (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Magnetic Resonance Imaging (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Middle Aged (mesh)</dc:subject><dc:subject>Tauopathies (mesh)</dc:subject><dc:subject>tau Proteins (mesh)</dc:subject><dc:subject>1103 Clinical Sciences (for)</dc:subject><dc:subject>1109 Neurosciences (for)</dc:subject><dc:subject>Neurology &amp; Neurosurgery (science-metrix)</dc:subject><dc:subject>3202 Clinical sciences (for-2020)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3rr6s00x</dc:identifier><dc:identifier>https://escholarship.org/content/qt3rr6s00x/qt3rr6s00x.pdf</dc:identifier><dc:identifier>info:doi/10.1007/s00415-018-9086-2</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Neurology, vol 265, iss 12</dc:source><dc:coverage>2960 - 2971</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt01h204x9</identifier><datestamp>2026-09-15T17:56:48Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt01h204x9</dc:identifier><dc:title>Agile Acceleration of LLVM Flang Support for Fortran 2018 Parallel Programming</dc:title><dc:creator>Rasmussen, Katherine</dc:creator><dc:creator>Rouson, Damian</dc:creator><dc:creator>George, Najé</dc:creator><dc:creator>Bonachea, Dan</dc:creator><dc:creator>Kadhem, Hussain</dc:creator><dc:creator>Friesen, Brian</dc:creator><dc:date>2022-11-15</dc:date><dc:description>The LLVM Flang compiler ("Flang") is currently Fortran 95 compliant, and the frontend can parse Fortran 2018. However, Flang does not have a comprehensive 2018 test suite and does not fully implement the static semantics of the 2018 standard. We are investigating whether agile software development techniques, such as pair programming and test-driven development (TDD), can help Flang to rapidly progress to Fortran 2018 compliance. Because of the paramount importance of parallelism in high-performance computing, we are focusing on Fortran’s parallel features, commonly denoted “Coarray Fortran.” We are developing what we believe are the first exhaustive, open-source tests for the static semantics of Fortran 2018 parallel features, and contributing them to the LLVM project. A related effort involves writing runtime tests for parallel 2018 features and supporting those tests by developing a new parallel runtime library: the CoArray Fortran Framework of Efficient Interfaces to Network Environments (Caffeine).</dc:description><dc:subject>Compiler Testing</dc:subject><dc:subject>Exascale Computing</dc:subject><dc:subject>HPC</dc:subject><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/01h204x9</dc:identifier><dc:identifier>https://escholarship.org/content/qt01h204x9/qt01h204x9.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S4CP4S</dc:identifier><dc:type>non_textual</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5vd903qw</identifier><datestamp>2026-09-15T17:56:45Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5vd903qw</dc:identifier><dc:title>Near‐Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub‐Arctic Watershed</dc:title><dc:creator>Shirley, Ian A</dc:creator><dc:creator>Mekonnen, Zelalem A</dc:creator><dc:creator>Wainwright, Haruko</dc:creator><dc:creator>Romanovsky, Vladimir E</dc:creator><dc:creator>Grant, Robert F</dc:creator><dc:creator>Hubbard, Susan S</dc:creator><dc:creator>Riley, William J</dc:creator><dc:creator>Dafflon, Baptiste</dc:creator><dc:date>2022-09-01</dc:date><dc:description>Abstract  Discontinuous permafrost environments exhibit strong spatial heterogeneity at scales too small to be driven by weather forcing or captured by Earth System Models. Here we analyze effects of observed spatial heterogeneity in soil and vegetation properties, hydrology, and thermal dynamics on ecosystem carbon dynamics in a watershed on the Seward Peninsula in Alaska. We apply a Morris global sensitivity analysis to a process‐rich, successfully tested terrestrial ecosystem model (TEM), ecosys , varying soil properties, boundary conditions, and weather forcing. We show that landscape heterogeneity strongly impacts soil temperatures and vegetation composition. Snow depth, O‐horizon thickness, and near‐surface water content, which vary at scales of O(m), control the soil thermal regime more than an air temperature gradient corresponding to a 140&amp;nbsp;km north–south distance. High shrub productivity is simulated only in talik (perennially unfrozen) soils with high nitrogen availability. Through these effects on plant and permafrost dynamics, landscape heterogeneity impacts ecosystem productivity. Simulations with near‐surface taliks have higher microbial respiration (by 78.0&amp;nbsp;gC&amp;nbsp;m −2 &amp;nbsp;yr −1 ) and higher net primary productivity (by 104.9&amp;nbsp;gC&amp;nbsp;m −2 &amp;nbsp;yr −1 ) compared to runs with near‐surface permafrost, and simulations with high shrub productivity have outlying values of net carbon uptake. We explored the prediction uncertainty associated with ignoring observed landscape heterogeneity, and found that watershed net carbon uptake is 60% larger when heterogeneity is accounted for. Our results highlight the complexity inherent in discontinuous permafrost environments and demonstrate that missing representation of subgrid heterogeneity in TEMs could bias predictions of high‐latitude carbon budget. 
Plain Language Summary At high‐latitudes, properties such as soil temperatures, soil wetness, snowpack, and vegetation cover vary considerably across a landscape. The scale of this variation can be as small as 1–10&amp;nbsp;m (e.g., a patch of tall shrubs with a deep snowpack and warm soil temperatures is surrounded by low‐lying tundra vegetation with shallow snowpack and cold soil temperatures). The resolution of terrestrial ecosystem models that are used to predict global responses to climate change, however, is much coarser (∼100–300&amp;nbsp;km). The mismatch between the scales of landscape variation and the scales of models may introduce bias into predictions of ecosystem processes. In order to better understand the causes and implications of landscape variability, we explore the response of an ecosystem model to variation in soil properties, boundary conditions, and weather forcing. We find that landscape variability in snowpack and soil properties strongly influences soil temperatures, vegetation cover, and ecosystem carbon cycling. In particular, we show that net carbon uptake of the studied area is 60% higher when we account for the observed variability in shrub distribution. These results demonstrate the need for higher resolution measurements and improved model representation of landscape variability.
Key Points    Discontinuous permafrost environments are characterized by strong spatial heterogeneity and complex feedback loops   Near‐surface hydrology and soil properties are strong drivers of spatial heterogeneity in these systems   Missing representation of subgrid heterogeneity in Terrestrial Ecosystem Models could bias predictions of high‐latitude carbon budget</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>3706 Geophysics (for-2020)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>0404 Geophysics (for)</dc:subject><dc:subject>3706 Geophysics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5vd903qw</dc:identifier><dc:identifier>https://escholarship.org/content/qt5vd903qw/qt5vd903qw.pdf</dc:identifier><dc:identifier>info:doi/10.1029/2022jg006864</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Geophysical Research Biogeosciences, vol 127, iss 9</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9k94x6h8</identifier><datestamp>2026-09-15T17:53:11Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9k94x6h8</dc:identifier><dc:title>Maternal Allergic Asthma Induces Prenatal Neuroinflammation</dc:title><dc:creator>Tamayo, Juan M</dc:creator><dc:creator>Rose, Destanie</dc:creator><dc:creator>Church, Jamie S</dc:creator><dc:creator>Schwartzer, Jared J</dc:creator><dc:creator>Ashwood, Paul</dc:creator><dc:date>2022-08-01</dc:date><dc:description>Autism spectrum disorder (ASD) is a class of neurodevelopmental disorders characterized by impaired social interactions and communication skills and repetitive or stereotyped behaviors. Rates of ASD diagnosis continue to rise, with current estimates at 1 in 44 children in the US (Maenner 2021). Epidemiological studies have suggested a link between maternal allergic asthma and an increased likelihood of having a child diagnosed with ASD. However, a lack of robust laboratory models prevents mechanistic research from being carried out. We developed a novel mouse model of maternal asthma-allergy (MAA) and previously reported that offspring from these mothers exhibit behavioral deficits compared to controls. In addition, it was shown that epigenetic regulation of gene expression in microglia was altered in these offspring, including several autism candidate genes. To further elucidate if there is neuroinflammation in the fetus following MAA, we investigated how allergic asthma impacts the maternal environment and inflammatory markers in the placenta and fetal brain during gestation. Female C57Bl/6 mice were primed with ovalbumin (OVA) prior to allergic asthma induction during pregnancy by administering aerosolized ovalbumin or PBS control to pregnant dams at gestational days (GD)9.5, 12.5, and 17.5. Four hours after the final induction, placenta and fetal brains were collected and measured for changes in cytokines using a Luminex bead-based multiplex assay. Placental MAA tissue showed a decrease in interleukin (IL)-17 in male and female offspring. There was a sex-dependent decrease in female monocyte chemoattractant protein 1 (MCP-1). In male placentas, IL-4, C-X-C motif chemokine 10 (CXCL10)-also known as interferon γ-induced protein 10 kDa (IP-10)-and chemokine (C-C motif) ligand 5 (RANTES) were decreased. In fetal brains, elevated inflammatory cytokines were found in MAA offspring when compared to controls. Specifically, interferon-gamma (IFN-γ), granulocyte-macrophage colony-stimulating factor (GM-CSF), interleukin 1α (IL-1α), IL-6, and tumor necrosis factor α (TNFα) were elevated in both males and females. In contrast, a decrease in the cytokine IL-9 was also observed. There were slight sex differences after OVA exposures. Male fetal brains showed elevated levels of macrophage inflammatory protein-2 (MIP-2), whereas female brains showed increased keratinocytes-derived chemokine (KC). In addition, IL-1? and IP-10 in male fetal brains were decreased. Together, these data indicate that repeated exposure to allergic asthma during pregnancy alters cytokine expression in the fetal environment in a sex-dependent way, resulting in homeostatic and neuroinflammatory alterations in the fetal brain.</dc:description><dc:subject>3215 Reproductive Medicine (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>Brain Disorders (rcdc)</dc:subject><dc:subject>Perinatal Period - Conditions Originating in Perinatal Period (rcdc)</dc:subject><dc:subject>Mental Health (rcdc)</dc:subject><dc:subject>Asthma (rcdc)</dc:subject><dc:subject>Intellectual and Developmental Disabilities (IDD) (rcdc)</dc:subject><dc:subject>Pregnancy (rcdc)</dc:subject><dc:subject>Autism (rcdc)</dc:subject><dc:subject>Lung (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Basic Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>2.1 Biological and endogenous factors (hrcs-rac)</dc:subject><dc:subject>Reproductive health and childbirth (hrcs-hc)</dc:subject><dc:subject>mouse model</dc:subject><dc:subject>neurodevelopment</dc:subject><dc:subject>cytokines</dc:subject><dc:subject>autism spectrum disorder</dc:subject><dc:subject>schizophrenia</dc:subject><dc:subject>ADHD</dc:subject><dc:subject>pregnancy</dc:subject><dc:subject>neuroinflammation</dc:subject><dc:subject>asthma</dc:subject><dc:subject>allergy</dc:subject><dc:subject>fetal brain</dc:subject><dc:subject>placenta</dc:subject><dc:subject>ADHD</dc:subject><dc:subject>allergy</dc:subject><dc:subject>asthma</dc:subject><dc:subject>autism spectrum disorder</dc:subject><dc:subject>cytokines</dc:subject><dc:subject>fetal brain</dc:subject><dc:subject>mouse model</dc:subject><dc:subject>neurodevelopment</dc:subject><dc:subject>neuroinflammation</dc:subject><dc:subject>placenta</dc:subject><dc:subject>pregnancy</dc:subject><dc:subject>schizophrenia</dc:subject><dc:subject>1109 Neurosciences (for)</dc:subject><dc:subject>1701 Psychology (for)</dc:subject><dc:subject>1702 Cognitive Sciences (for)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:subject>5201 Applied and developmental psychology (for-2020)</dc:subject><dc:subject>5202 Biological psychology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9k94x6h8</dc:identifier><dc:identifier>https://escholarship.org/content/qt9k94x6h8/qt9k94x6h8.pdf</dc:identifier><dc:identifier>info:doi/10.3390/brainsci12081041</dc:identifier><dc:type>article</dc:type><dc:source>Brain Sciences, vol 12, iss 8</dc:source><dc:coverage>1041</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt97t2j1n5</identifier><datestamp>2026-09-15T17:49:36Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt97t2j1n5</dc:identifier><dc:title>Metatranscriptomes of California grassland soil microbial communities in response to rewetting</dc:title><dc:creator>Chuckran, Peter F</dc:creator><dc:creator>Estera-Molina, Katerina</dc:creator><dc:creator>Huntemann, Marcel</dc:creator><dc:creator>Foster, Brian</dc:creator><dc:creator>Roux, Simon</dc:creator><dc:creator>Mukherjee, Supratim</dc:creator><dc:creator>Hajek, Patrick</dc:creator><dc:creator>Reddy, TBK</dc:creator><dc:creator>Daum, Chris</dc:creator><dc:creator>Chen, I-Min A</dc:creator><dc:creator>Pennacchio, Christa</dc:creator><dc:creator>Eloe-Fadrosh, Emiley A</dc:creator><dc:creator>Dijkstra, Paul</dc:creator><dc:creator>Firestone, Mary K</dc:creator><dc:creator>Blazewicz, Steven J</dc:creator><dc:creator>Pett-Ridge, Jennifer</dc:creator><dc:contributor>Thrash, J Cameron</dc:contributor><dc:date>2024-06-11</dc:date><dc:description>When very dry soil is rewet, rapid stimulation of microbial activity has important implications for ecosystem biogeochemistry, yet associated changes in microbial transcription are poorly known. Here, we present metatranscriptomes of California annual grassland soil microbial communities, collected over 1 week from soils rewet after a summer drought-providing a time series of short-term transcriptional response during rewetting.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>metatranscriptomics</dc:subject><dc:subject>biogeochemistry</dc:subject><dc:subject>biogeochemistry</dc:subject><dc:subject>metatranscriptomics</dc:subject><dc:subject>0601 Biochemistry and Cell Biology (for)</dc:subject><dc:subject>0604 Genetics (for)</dc:subject><dc:subject>0605 Microbiology (for)</dc:subject><dc:subject>3107 Microbiology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/97t2j1n5</dc:identifier><dc:identifier>https://escholarship.org/content/qt97t2j1n5/qt97t2j1n5.pdf</dc:identifier><dc:identifier>info:doi/10.1128/mra.00322-24</dc:identifier><dc:type>article</dc:type><dc:source>Microbiology Resource Announcements, vol 13, iss 6</dc:source><dc:coverage>e00322 - e00324</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt34g9528p</identifier><datestamp>2026-09-15T17:48:52Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt34g9528p</dc:identifier><dc:title>Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics</dc:title><dc:creator>Uhlemann, Sebastian</dc:creator><dc:creator>Dafflon, Baptiste</dc:creator><dc:creator>Wainwright, Haruko Murakami</dc:creator><dc:creator>Williams, Kenneth Hurst</dc:creator><dc:creator>Minsley, Burke</dc:creator><dc:creator>Zamudio, Katrina</dc:creator><dc:creator>Carr, Bradley</dc:creator><dc:creator>Falco, Nicola</dc:creator><dc:creator>Ulrich, Craig</dc:creator><dc:creator>Hubbard, Susan</dc:creator><dc:date>2022-03-25</dc:date><dc:description>Bedrock property quantification is critical for predicting the hydrological response of watersheds to climate disturbances. Estimating bedrock hydraulic properties over watershed scales is inherently difficult, particularly in fracture-dominated regions. Our analysis tests the covariability of above- and belowground features on a watershed scale, by linking borehole geophysical data, near-surface geophysics, and remote sensing data. We use machine learning to quantify the relationships between bedrock geophysical/hydrological properties and geomorphological/vegetation indices and show that machine learning relationships can estimate most of their covariability. Although we can predict the electrical resistivity variation across the watershed, regions of lower variability in the input parameters are shown to provide better estimates, indicating a limitation of commonly applied geomorphological models. Our results emphasize that such an integrated approach can be used to derive detailed bedrock characteristics, allowing for identification of small-scale variations across an entire watershed that may be critical to assess the impact of disturbances on hydrological systems.</dc:description><dc:subject>3707 Hydrology (for-2020)</dc:subject><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>Networking and Information Technology R&amp;D (NITRD) (rcdc)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/34g9528p</dc:identifier><dc:identifier>https://escholarship.org/content/qt34g9528p/qt34g9528p.pdf</dc:identifier><dc:identifier>info:doi/10.1126/sciadv.abj2479</dc:identifier><dc:type>article</dc:type><dc:source>Science Advances, vol 8, iss 12</dc:source><dc:coverage>eabj2479</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3237r2dh</identifier><datestamp>2026-09-15T17:48:46Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3237r2dh</dc:identifier><dc:title>Ecosystem Fabrication (EcoFAB) Protocols for The Construction of Laboratory Ecosystems Designed to Study Plant-microbe Interactions</dc:title><dc:creator>Gao, Jian</dc:creator><dc:creator>Sasse, Joelle</dc:creator><dc:creator>Lewald, Kyle M</dc:creator><dc:creator>Zhalnina, Kateryna</dc:creator><dc:creator>Cornmesser, Lloyd T</dc:creator><dc:creator>Duncombe, Todd A</dc:creator><dc:creator>Yoshikuni, Yasuo</dc:creator><dc:creator>Vogel, John P</dc:creator><dc:creator>Firestone, Mary K</dc:creator><dc:creator>Northen, Trent R</dc:creator><dc:date>2018-04-01</dc:date><dc:description>Beneficial plant-microbe interactions offer a sustainable biological solution with the potential to boost low-input food and bioenergy production. A better mechanistic understanding of these complex plant-microbe interactions will be crucial to improving plant production as well as performing basic ecological studies investigating plant-soil-microbe interactions. Here, a detailed description for ecosystem fabrication is presented, using widely available 3D printing technologies, to create controlled laboratory habitats (EcoFABs) for mechanistic studies of plant-microbe interactions within specific environmental conditions. Two sizes of EcoFABs are described that are suited for the investigation of microbial interactions with various plant species, including Arabidopsis thaliana, Brachypodium distachyon, and Panicum virgatum. These flow-through devices allow for controlled manipulation and sampling of root microbiomes, root chemistry as well as imaging of root morphology and microbial localization. This protocol includes the details for maintaining sterile conditions inside EcoFABs and mounting independent LED light systems onto EcoFABs. Detailed methods for addition of different forms of media, including soils, sand, and liquid growth media coupled to the characterization of these systems using imaging and metabolomics are described. Together, these systems enable dynamic and detailed investigation of plant and plant-microbial consortia including the manipulation of microbiome composition (including mutants), the monitoring of plant growth, root morphology, exudate composition, and microbial localization under controlled environmental conditions. We anticipate that these detailed protocols will serve as an important starting point for other researchers, ideally helping create standardized experimental systems for investigating plant-microbe interactions.</dc:description><dc:subject>3108 Plant Biology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>Microbiome (rcdc)</dc:subject><dc:subject>2 Zero Hunger (sdg)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Metabolomics (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Plant Roots (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Environmental Sciences</dc:subject><dc:subject>Issue 134</dc:subject><dc:subject>Laboratory ecosystems</dc:subject><dc:subject>EcoFAB</dc:subject><dc:subject>plant-microbe interactions</dc:subject><dc:subject>microbiome</dc:subject><dc:subject>root morphology</dc:subject><dc:subject>root exudates</dc:subject><dc:subject>LC-MS</dc:subject><dc:subject>NIMS</dc:subject><dc:subject>metabolomics</dc:subject><dc:subject>microscopic imaging</dc:subject><dc:subject>Plant Roots (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Metabolomics (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Ecosystem (mesh)</dc:subject><dc:subject>Metabolomics (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Plant Roots (mesh)</dc:subject><dc:subject>Soil Microbiology (mesh)</dc:subject><dc:subject>0601 Biochemistry and Cell Biology (for)</dc:subject><dc:subject>1701 Psychology (for)</dc:subject><dc:subject>1702 Cognitive Sciences (for)</dc:subject><dc:subject>3101 Biochemistry and cell biology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3237r2dh</dc:identifier><dc:identifier>https://escholarship.org/content/qt3237r2dh/qt3237r2dh.pdf</dc:identifier><dc:identifier>info:doi/10.3791/57170</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Visualized Experiments, vol 2018, iss 134</dc:source><dc:coverage>57170</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3ff0n1jc</identifier><datestamp>2026-09-15T17:36:41Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3ff0n1jc</dc:identifier><dc:title>Anatomy of an agricultural antagonist: Feeding complex structure and function of three xylem sap‐feeding insects illuminated with synchrotron‐based 3D imaging</dc:title><dc:creator>Clark, Elizabeth G</dc:creator><dc:creator>Cornara, Daniele</dc:creator><dc:creator>Brodersen, Craig R</dc:creator><dc:creator>McElrone, Andrew J</dc:creator><dc:creator>Parkinson, Dilworth Y</dc:creator><dc:creator>Almeida, Rodrigo PP</dc:creator><dc:date>2023-10-01</dc:date><dc:description>Many insects feed on xylem or phloem sap of vascular plants. Although physical damage to the plant is minimal, the process of insect feeding can transmit lethal viruses and bacterial pathogens. Disparities between insect-mediated pathogen transmission efficiency have been identified among xylem sap-feeding insects; however, the mechanistic drivers of these trends are unclear. Identifying and understanding the structural factors and associated integrated functional components that may ultimately determine these disparities are critical for managing plant diseases. Here, we applied synchrotron-based X-ray microcomputed tomography to digitally reconstruct the morphology of three xylem sap-feeding insect vectors of plant pathogens: Graphocephala atropunctata (blue-green sharpshooter; Hemiptera, Cicadellidae) and Homalodisca vitripennis (glassy-winged sharpshooter; Hemiptera, Cicadellidae), and the spittlebug Philaenus spumarius (meadow spittlebug; Hemiptera, Aphrophoridae). The application of this technique revealed previously undescribed anatomical features of these organisms, such as key components of the salivary complex. The visualization of the 3D structure of the precibarial valve led to new insights into the mechanism of how this structure functions. Morphological disparities with functional implications between taxa were highlighted as well, including the morphology and volume of the cibarial dilator musculature responsible for extracting xylem sap, which has implications for force application capabilities. These morphological insights will be used to target analyses illuminating functional differences in feeding behavior.</dc:description><dc:subject>3108 Plant Biology (for-2020)</dc:subject><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>Infectious Diseases (rcdc)</dc:subject><dc:subject>Vector-Borne Diseases (rcdc)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Imaging</dc:subject><dc:subject>Three-Dimensional (mesh)</dc:subject><dc:subject>Synchrotrons (mesh)</dc:subject><dc:subject>X-Ray Microtomography (mesh)</dc:subject><dc:subject>Insecta (mesh)</dc:subject><dc:subject>Feeding Behavior (mesh)</dc:subject><dc:subject>3D imaging</dc:subject><dc:subject>Auchenorryncha</dc:subject><dc:subject>functional morphology</dc:subject><dc:subject>vectors of plant pathogens</dc:subject><dc:subject>xylem sap-feeding insects</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Imaging</dc:subject><dc:subject>Three-Dimensional (mesh)</dc:subject><dc:subject>Feeding Behavior (mesh)</dc:subject><dc:subject>Synchrotrons (mesh)</dc:subject><dc:subject>X-Ray Microtomography (mesh)</dc:subject><dc:subject>Insecta (mesh)</dc:subject><dc:subject>3D imaging</dc:subject><dc:subject>Auchenorryncha</dc:subject><dc:subject>functional morphology</dc:subject><dc:subject>vectors of plant pathogens</dc:subject><dc:subject>xylem sap-feeding insects</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Imaging</dc:subject><dc:subject>Three-Dimensional (mesh)</dc:subject><dc:subject>Synchrotrons (mesh)</dc:subject><dc:subject>X-Ray Microtomography (mesh)</dc:subject><dc:subject>Insecta (mesh)</dc:subject><dc:subject>Feeding Behavior (mesh)</dc:subject><dc:subject>0606 Physiology (for)</dc:subject><dc:subject>0608 Zoology (for)</dc:subject><dc:subject>Anatomy &amp; Morphology (science-metrix)</dc:subject><dc:subject>3109 Zoology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3ff0n1jc</dc:identifier><dc:identifier>https://escholarship.org/content/qt3ff0n1jc/qt3ff0n1jc.pdf</dc:identifier><dc:identifier>info:doi/10.1002/jmor.21639</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Morphology, vol 284, iss 10</dc:source><dc:coverage>e21639</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt7qp9c8mk</identifier><datestamp>2026-09-15T17:36:36Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt7qp9c8mk</dc:identifier><dc:title>Study of dielectric breakdown in liquid xenon with XeBrA: The xenon breakdown apparatus</dc:title><dc:creator>Watson, J</dc:creator><dc:creator>Olcina, I</dc:creator><dc:creator>Soria, J</dc:creator><dc:creator>McKinsey, DN</dc:creator><dc:creator>Kravitz, S</dc:creator><dc:creator>Deck, EE</dc:creator><dc:creator>Bernard, EP</dc:creator><dc:creator>Tvrznikova, L</dc:creator><dc:creator>Waldron, WL</dc:creator><dc:creator>Riffard, Q</dc:creator><dc:creator>O’Sullivan, K</dc:creator><dc:date>2023-01-01</dc:date><dc:description>Maintaining the electric fields necessary for the current generation of noble liquid time projection chambers (TPCs), with drift lengths exceeding 1&amp;nbsp;m, requires a large negative voltage applied to their cathode. Delivering such high voltage is associated with an elevated risk of electrostatic discharge and electroluminescence, which would be detrimental to the performance of the experiment. The Xenon Breakdown Apparatus (XeBrA) is a 5-l, high voltage test chamber built to investigate the contributing factors to electrical breakdown in noble liquids. In this work, we present the main findings after conducting scans over stressed electrode areas, surface finish, pressure, and high voltage ramp speed in the medium of liquid xenon. Area scaling and surface finish were observed to be the dominant factors affecting breakdown, whereas no significant changes were observed with varying pressure or ramp speed. A general rise in both the anode current and photon rate was observed in the last 30&amp;nbsp;s, leading up to a breakdown, with a marked increase in the last couple of seconds. In addition, the position of breakdowns was reconstructed with a system of high-speed cameras and a moderate correlation with the Fowler-Nordheim field emission model was found. Tentative evidence for bubble nucleation being the originating mechanism of breakdown in the liquid was also observed. We deem the results presented in this work to be of particular interest for the design of future, large TPCs, and practical recommendations are provided.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>03 Chemical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Applied Physics (science-metrix)</dc:subject><dc:subject>34 Chemical sciences (for-2020)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/7qp9c8mk</dc:identifier><dc:identifier>https://escholarship.org/content/qt7qp9c8mk/qt7qp9c8mk.pdf</dc:identifier><dc:identifier>info:doi/10.1063/5.0107082</dc:identifier><dc:type>article</dc:type><dc:source>Review of Scientific Instruments, vol 94, iss 1</dc:source><dc:coverage>015112</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt2j30j157</identifier><datestamp>2026-09-15T17:33:18Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt2j30j157</dc:identifier><dc:title>A quantitative framework reveals ecological drivers of grassland microbial community assembly in response to warming</dc:title><dc:creator>Ning, Daliang</dc:creator><dc:creator>Yuan, Mengting</dc:creator><dc:creator>Wu, Linwei</dc:creator><dc:creator>Zhang, Ya</dc:creator><dc:creator>Guo, Xue</dc:creator><dc:creator>Zhou, Xishu</dc:creator><dc:creator>Yang, Yunfeng</dc:creator><dc:creator>Arkin, Adam P</dc:creator><dc:creator>Firestone, Mary K</dc:creator><dc:creator>Zhou, Jizhong</dc:creator><dc:date>2020-09-18</dc:date><dc:description>Unraveling the drivers controlling community assembly is a central issue in ecology. Although it is generally accepted that selection, dispersal, diversification and drift are major community assembly processes, defining their relative importance is very challenging. Here, we present a framework to quantitatively infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP). iCAMP shows high accuracy (0.93–0.99), precision (0.80–0.94), sensitivity (0.82–0.94), and specificity (0.95–0.98) on simulated communities, which are 10–160% higher than those from the entire community-based approach. Application of iCAMP to grassland microbial communities in response to experimental warming reveals dominant roles of homogeneous selection (38%) and ‘drift’ (59%). Interestingly, warming decreases ‘drift’ over time, and enhances homogeneous selection which is primarily imposed on Bacillales. In addition, homogeneous selection has higher correlations with drought and plant productivity under warming than control. iCAMP provides an effective and robust tool to quantify microbial assembly processes, and should also be useful for plant and animal ecology.</dc:description><dc:subject>31 Biological Sciences (for-2020)</dc:subject><dc:subject>3103 Ecology (for-2020)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:subject>Droughts (mesh)</dc:subject><dc:subject>Ecology (mesh)</dc:subject><dc:subject>Global Warming (mesh)</dc:subject><dc:subject>Grassland (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Biological (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Sensitivity and Specificity (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Sensitivity and Specificity (mesh)</dc:subject><dc:subject>Ecology (mesh)</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Biological (mesh)</dc:subject><dc:subject>Droughts (mesh)</dc:subject><dc:subject>Global Warming (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Grassland (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Bacteria (mesh)</dc:subject><dc:subject>Biodiversity (mesh)</dc:subject><dc:subject>Droughts (mesh)</dc:subject><dc:subject>Ecology (mesh)</dc:subject><dc:subject>Global Warming (mesh)</dc:subject><dc:subject>Grassland (mesh)</dc:subject><dc:subject>Microbiota (mesh)</dc:subject><dc:subject>Models</dc:subject><dc:subject>Biological (mesh)</dc:subject><dc:subject>Phylogeny (mesh)</dc:subject><dc:subject>Sensitivity and Specificity (mesh)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/2j30j157</dc:identifier><dc:identifier>https://escholarship.org/content/qt2j30j157/qt2j30j157.pdf</dc:identifier><dc:identifier>info:doi/10.1038/s41467-020-18560-z</dc:identifier><dc:type>article</dc:type><dc:source>Nature Communications, vol 11, iss 1</dc:source><dc:coverage>4717</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt08w8g9wb</identifier><datestamp>2026-09-15T17:29:40Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt08w8g9wb</dc:identifier><dc:title>Constraints on the polarization angle oscillations of the Crab Nebula with the Simons Array and its applications to the search for axionlike particles</dc:title><dc:creator>Adkins, Tylor</dc:creator><dc:creator>Arnold, Kam</dc:creator><dc:creator>Baccigalupi, Carlo</dc:creator><dc:creator>Barron, Darcy R</dc:creator><dc:creator>Bixler, Bryce</dc:creator><dc:creator>Chinone, Yuji</dc:creator><dc:creator>Chu, Matthew R</dc:creator><dc:creator>Crowley, Kevin T</dc:creator><dc:creator>Farias, Nicole</dc:creator><dc:creator>Fujino, Takuro</dc:creator><dc:creator>Hasegawa, Masaya</dc:creator><dc:creator>Hazumi, Masashi</dc:creator><dc:creator>Hirose, Haruaki</dc:creator><dc:creator>Ito, Jennifer</dc:creator><dc:creator>Jeong, Oliver</dc:creator><dc:creator>Kaneko, Daisuke</dc:creator><dc:creator>Keating, Brian</dc:creator><dc:creator>Kusaka, Akito</dc:creator><dc:creator>Lee, Adrian T</dc:creator><dc:creator>Murata, Masaaki</dc:creator><dc:creator>Piccirillo, Lucio</dc:creator><dc:creator>Reichardt, Christian L</dc:creator><dc:creator>Sakaguri, Kana</dc:creator><dc:creator>Arani, Shahed Shayan</dc:creator><dc:creator>Siritanasak, Praween</dc:creator><dc:creator>Takakura, Satoru</dc:creator><dc:creator>Takatori, Sayuri</dc:creator><dc:creator>Tajima, Osamu</dc:creator><dc:creator>Yamada, Kyohei</dc:creator><dc:creator>Zhou, Yuyang</dc:creator><dc:date>2026-02-15</dc:date><dc:description>We present a search for polarization oscillation of the Crab Nebula, also known as Tau A, at millimeter wavelengths using observations with the Simons Array, the successor experiment to POLARBEAR. We follow up on previous work by POLARBEAR using 90 GHz band data of the 2023 observing season of the Simons Array to evaluate the variability of Tau A’s polarization angle. Tau A is widely used as a polarization angle calibration source in millimeter-wave astronomy, and thus it is necessary to validate the stability. Additionally, an interesting application of the time-resolved polarimetry of Tau A is to search for axionlike particles (ALPs). We do not detect a global signal across the frequencies considered in this analysis and place a median 95% upper bound of polarization oscillation amplitude A&amp;lt;0.12° over oscillation frequencies from 3.39 yr-1 to 1.50 day-1. This constrains the ALP-photon coupling at a median 95% upper bound of gaγγ&amp;lt;3.84×10-12×(ma/10-21 eV) in the mass range from 4.4×10-22 to 7.2×10-20 eV, assuming the ALP constitutes all of dark matter, its field is a stochastic Gaussian field, and it is the sole source of Tau A’s polarization angle oscillation. Additionally, we do not detect signal at the frequencies where 2.5σ hints were previously reported by POLARBEAR, but we do not exclude these signals at the 95% confidence level.</dc:description><dc:subject>5107 Particle and High Energy Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/08w8g9wb</dc:identifier><dc:identifier>https://escholarship.org/content/qt08w8g9wb/qt08w8g9wb.pdf</dc:identifier><dc:identifier>info:doi/10.1103/9wqc-tgzq</dc:identifier><dc:type>article</dc:type><dc:source>Physical Review D, vol 113, iss 4</dc:source><dc:coverage>043044</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt14b2b9wx</identifier><datestamp>2026-09-15T17:29:36Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt14b2b9wx</dc:identifier><dc:title>Analysis of Screening Current Effects in a Hybrid Nb$_{3}$Sn/REBCO Superconducting Accelerator Magnet Using a T-A Formulation</dc:title><dc:creator>Yang, Ye</dc:creator><dc:creator>Yan, Yufan</dc:creator><dc:creator>Kurian, Febin</dc:creator><dc:creator>Dhakarwal, Mukesh</dc:creator><dc:creator>Iio, Masami</dc:creator><dc:creator>Suzuki, Kento</dc:creator><dc:creator>Wang, Xiaorong</dc:creator><dc:creator>Gupta, Ramesh</dc:creator><dc:creator>Ogitsu, Toru</dc:creator><dc:creator>Shen, Tengming</dc:creator><dc:date>2025-08-01</dc:date><dc:description>To explore the feasibility of using high-temperature superconducting (HTS) REBCO coated conductors in future accelerator magnets, two REBCO flat racetrack coils were fabricated using 4-mm wide EuBCO tapes at the High Energy Accelerator Research Organization (KEK). These coils were tested as an insert inside a Nb$_{3}$Sn common-coil dipole magnet, which provides a background field of up to $\sim$ 9.5T, at the Brookhaven National Laboratory (BNL). REBCO tapes offer exceptionally high critical current density under strong magnetic fields; however, they also exhibit significant magnetization due to screening currents, leading to magnetic field errors. This study presents a 2D finite element model of screening current-induced fields (SCIF) in REBCO coils using the T-A formulation, along with the results obtained. Simulations were then performed for two KEK test cases: one where the REBCO conductors were oriented with the HTS tapes parallel to the background field, and another where the tapes were perpendicular to it. Since screening currents also influence the stress distribution and increase the peak stress in the coils, the mechanical effects of these currents were analyzed. The implications of these simulation and test results for the design of Nb$_{3}$Sn/REBCO superconducting accelerator magnets are discussed.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>High-temperature superconductors</dc:subject><dc:subject>Superconducting magnets</dc:subject><dc:subject>Coils</dc:subject><dc:subject>Magnetomechanical effects</dc:subject><dc:subject>Magnetic resonance</dc:subject><dc:subject>Magnetic fields</dc:subject><dc:subject>Superconductivity</dc:subject><dc:subject>Stress</dc:subject><dc:subject>Accelerator magnets</dc:subject><dc:subject>Vectors</dc:subject><dc:subject>common-coil dipole</dc:subject><dc:subject>HTS insert coil</dc:subject><dc:subject>hybrid magnet</dc:subject><dc:subject>screening current</dc:subject><dc:subject>ATAP-GENERAL (c-lbnl-label)</dc:subject><dc:subject>ATAP-2025 (c-lbnl-label)</dc:subject><dc:subject>ATAP-SMP (c-lbnl-label)</dc:subject><dc:subject>0204 Condensed Matter Physics (for)</dc:subject><dc:subject>0906 Electrical and Electronic Engineering (for)</dc:subject><dc:subject>0912 Materials Engineering (for)</dc:subject><dc:subject>General Physics (science-metrix)</dc:subject><dc:subject>4008 Electrical engineering (for-2020)</dc:subject><dc:subject>5104 Condensed matter physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/14b2b9wx</dc:identifier><dc:identifier>https://escholarship.org/content/qt14b2b9wx/qt14b2b9wx.pdf</dc:identifier><dc:identifier>info:doi/10.1109/tasc.2025.3528378</dc:identifier><dc:type>article</dc:type><dc:source>IEEE Transactions on Applied Superconductivity, vol 35, iss 5</dc:source><dc:coverage>1 - 5</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0v03x58p</identifier><datestamp>2026-09-15T17:29:20Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0v03x58p</dc:identifier><dc:title>Variability in observed stable water isotopes in snowpack across a mountainous watershed in Colorado</dc:title><dc:creator>Carroll, Rosemary WH</dc:creator><dc:creator>Deems, Jeffery</dc:creator><dc:creator>Maxwell, Reed</dc:creator><dc:creator>Sprenger, Matthias</dc:creator><dc:creator>Brown, Wendy</dc:creator><dc:creator>Newman, Alexander</dc:creator><dc:creator>Beutler, Curtis</dc:creator><dc:creator>Bill, Markus</dc:creator><dc:creator>Hubbard, Susan S</dc:creator><dc:creator>Williams, Kenneth H</dc:creator><dc:date>2022-08-01</dc:date><dc:description>Abstract  Isotopic information from 81 snowpits was collected over a 5‐year period in a large, Colorado watershed. Data spans gradients in elevation, aspect, vegetation, and seasonal climate. They are combined with overlapping campaigns for water isotopes in precipitation and snowmelt, and a land‐surface model for detailed estimates of snowfall and climate at sample locations. Snowfall isotopic inputs, describe the majority of δ 18 O snowpack variability. Aspect is a secondary control, with slightly more enriched conditions on east and north facing slopes. This is attributed to preservation of seasonally enriched snowfall and vapour loss in the early winter. Sublimation, expressed by decreases in snowpack d‐excess in comparison to snowfall contributions, increases at low elevation and when seasonal temperature and solar radiation are high. At peak snow accumulation, post‐depositional fractionation appears to occur in the top 25 ± 14% of the snowpack due to melt‐freeze redistribution of lighter isotopes deeper into the snowpack and vapour loss to the atmosphere during intermittent periods of low relative humidity and high windspeed. Relative depth of fractionation increases when winter daytime temperatures are high and winter precipitation is low. Once isothermal, snowpack isotopic homogenization and enrichment was observed with initial snowmelt isotopically depleted in comparison to snowpack and enriching over time. The rate of δ 18 O increase (d‐excess decrease) in snowmelt was 0.02‰ per day per 100‐m elevation loss. Isotopic data suggests elevation dictates snowpack and snowmelt evolution by controlling early snow persistence (or absence), isotopic lapse rates in precipitation and the ratio of energy to snow availability. Hydrologic tracer studies using stable water isotopes in basins of large topographic relief will require adjustment for these elevational controls to properly constrain stream water sourcing from snowmelt.</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>3701 Atmospheric Sciences (for-2020)</dc:subject><dc:subject>3709 Physical Geography and Environmental Geoscience (for-2020)</dc:subject><dc:subject>3703 Geochemistry (for-2020)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>Colorado</dc:subject><dc:subject>d-excess</dc:subject><dc:subject>mountains</dc:subject><dc:subject>snowfall</dc:subject><dc:subject>snowmelt</dc:subject><dc:subject>snowpack</dc:subject><dc:subject>stable water isotopes</dc:subject><dc:subject>Colorado</dc:subject><dc:subject>d-excess</dc:subject><dc:subject>mountains</dc:subject><dc:subject>snowfall</dc:subject><dc:subject>snowmelt</dc:subject><dc:subject>snowpack</dc:subject><dc:subject>stable water isotopes</dc:subject><dc:subject>0406 Physical Geography and Environmental Geoscience (for)</dc:subject><dc:subject>0905 Civil Engineering (for)</dc:subject><dc:subject>0907 Environmental Engineering (for)</dc:subject><dc:subject>Environmental Engineering (science-metrix)</dc:subject><dc:subject>3707 Hydrology (for-2020)</dc:subject><dc:subject>3709 Physical geography and environmental geoscience (for-2020)</dc:subject><dc:subject>4005 Civil engineering (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0v03x58p</dc:identifier><dc:identifier>https://escholarship.org/content/qt0v03x58p/qt0v03x58p.pdf</dc:identifier><dc:identifier>info:doi/10.1002/hyp.14653</dc:identifier><dc:type>article</dc:type><dc:source>Hydrological Processes, vol 36, iss 8</dc:source></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8304q46r</identifier><datestamp>2026-09-15T17:29:08Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8304q46r</dc:identifier><dc:title>Race, Ethnicity, Income Concentration and 10-Year Change in Urban Greenness in the United States</dc:title><dc:creator>Casey, Joan A</dc:creator><dc:creator>James, Peter</dc:creator><dc:creator>Cushing, Lara</dc:creator><dc:creator>Jesdale, Bill M</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:date>2017-12-01</dc:date><dc:description>Background: Cross-sectional studies suggest urban greenness is unequally distributed by neighborhood demographics. However, the extent to which inequalities in greenness have changed over time remains unknown. Methods: We estimated 2001 and 2011 greenness using Moderate-resolution Imaging Spectroradiometer (MODIS) satellite-derived normalized difference vegetative index (NDVI) in 59,483 urban census tracts in the contiguous U.S. We fit spatial error models to estimate the association between baseline census tract demographic composition in 2000 and (1) 2001 greenness and (2) change in greenness between 2001 and 2011. Results: In models adjusted for population density, climatic factors, housing tenure, and Index of Concentration at the Extremes for income (ICE), an SD increase in percent White residents (a 30% increase) in 2000 was associated with 0.021 (95% CI: 0.018, 0.023) higher 2001 NDVI. We observed a stepwise reduction in 2001 NDVI with increased concentration of poverty. Tracts with a higher proportion of Hispanic residents in 2000 lost a small, statistically significant amount of greenness between 2001 and 2011 while tracts with higher proportions of Whites experienced a small, statistically significant increase in greenness over the same period. Conclusions: Census tracts with a higher proportion of racial/ethnic minorities, compared to a higher proportion of White residents, had less greenness in 2001 and lost more greenness between 2001 and 2011. Policies are needed to increase greenness, a health-promoting neighborhood asset, in disadvantaged communities.</dc:description><dc:subject>4406 Human Geography (for-2020)</dc:subject><dc:subject>4206 Public Health (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>44 Human Society (for-2020)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Minority Health (rcdc)</dc:subject><dc:subject>10 Reduced Inequalities (sdg)</dc:subject><dc:subject>Cities (mesh)</dc:subject><dc:subject>Environment (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Minority Groups (mesh)</dc:subject><dc:subject>Plants (mesh)</dc:subject><dc:subject>Population Density (mesh)</dc:subject><dc:subject>Population Groups (mesh)</dc:subject><dc:subject>Racial Groups (mesh)</dc:subject><dc:subject>Residence Characteristics (mesh)</dc:subject><dc:subject>Satellite Imagery (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>urban greenspace</dc:subject><dc:subject>neighborhood</dc:subject><dc:subject>ethnicity</dc:subject><dc:subject>socioeconomic factors</dc:subject><dc:subject>residence characteristics</dc:subject><dc:subject>environment</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Plants (mesh)</dc:subject><dc:subject>Environment (mesh)</dc:subject><dc:subject>Cities (mesh)</dc:subject><dc:subject>Population Density (mesh)</dc:subject><dc:subject>Residence Characteristics (mesh)</dc:subject><dc:subject>Minority Groups (mesh)</dc:subject><dc:subject>Population Groups (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Satellite Imagery (mesh)</dc:subject><dc:subject>Racial Groups (mesh)</dc:subject><dc:subject>environment</dc:subject><dc:subject>ethnicity</dc:subject><dc:subject>neighborhood</dc:subject><dc:subject>residence characteristics</dc:subject><dc:subject>socioeconomic factors</dc:subject><dc:subject>urban greenspace</dc:subject><dc:subject>Cities (mesh)</dc:subject><dc:subject>Environment (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Minority Groups (mesh)</dc:subject><dc:subject>Plants (mesh)</dc:subject><dc:subject>Population Density (mesh)</dc:subject><dc:subject>Population Groups (mesh)</dc:subject><dc:subject>Racial Groups (mesh)</dc:subject><dc:subject>Residence Characteristics (mesh)</dc:subject><dc:subject>Satellite Imagery (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Toxicology (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8304q46r</dc:identifier><dc:identifier>https://escholarship.org/content/qt8304q46r/qt8304q46r.pdf</dc:identifier><dc:identifier>info:doi/10.3390/ijerph14121546</dc:identifier><dc:type>article</dc:type><dc:source>International Journal of Environmental Research and Public Health, vol 14, iss 12</dc:source><dc:coverage>1546</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt9t38p564</identifier><datestamp>2026-09-15T17:29:03Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt9t38p564</dc:identifier><dc:title>Environmental Chemicals in an Urban Population of Pregnant Women and Their Newborns from San Francisco</dc:title><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Cushing, Lara J</dc:creator><dc:creator>Jesdale, Bill M</dc:creator><dc:creator>Schwartz, Jackie M</dc:creator><dc:creator>Guo, Weihong</dc:creator><dc:creator>Guo, Tan</dc:creator><dc:creator>Wang, Miaomiao</dc:creator><dc:creator>Harwani, Suhash</dc:creator><dc:creator>Petropoulou, Syrago-Styliani E</dc:creator><dc:creator>Duong, Wendy</dc:creator><dc:creator>Park, June-Soo</dc:creator><dc:creator>Petreas, Myrto</dc:creator><dc:creator>Gajek, Ryszard</dc:creator><dc:creator>Alvaran, Josephine</dc:creator><dc:creator>She, Jianwen</dc:creator><dc:creator>Dobraca, Dina</dc:creator><dc:creator>Das, Rupali</dc:creator><dc:creator>Woodruff, Tracey J</dc:creator><dc:date>2016-11-15</dc:date><dc:description>Exposures to environmental pollutants in utero may increase the risk of adverse health effects. We measured the concentrations of 59 potentially harmful chemicals in 77 maternal and 65 paired umbilical cord blood samples collected in San Francisco during 2010-2011, including polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), polybrominated diphenyl ethers (PBDEs), hydroxylated PBDEs (OH-PBDEs), and perfluorinated compounds (PFCs) in serum and metals in whole blood. Consistent with previous studies, we found evidence that concentrations of mercury (Hg) and lower-brominated PBDEs were often higher in umbilical cord blood or serum than in maternal samples (median cord:maternal ratio &amp;gt; 1), while for most PFCs and lead (Pb), concentrations in cord blood or serum were generally equal to or lower than their maternal pair (median cord:maternal ratio ≤ 1). In contrast to the conclusions of a recent review, we found evidence that several PCBs and OCPs were also often higher in cord than maternal serum (median cord:maternal ratio &amp;gt; 1) when concentrations are assessed on a lipid-adjusted basis. Our findings suggest that for many chemicals, fetuses may experience higher exposures than their mothers and highlight the need to characterize potential health risks and inform policies aimed at reducing sources of exposure.</dc:description><dc:subject>3215 Reproductive Medicine (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>4105 Pollution and Contamination (for-2020)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Stem Cell Research (rcdc)</dc:subject><dc:subject>Endocrine Disruptors (rcdc)</dc:subject><dc:subject>Stem Cell Research - Umbilical Cord Blood/ Placenta (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Stem Cell Research - Nonembryonic - Human (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Conditions Affecting the Embryonic and Fetal Periods (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Stem Cell Research - Umbilical Cord Blood/ Placenta - Human (rcdc)</dc:subject><dc:subject>Perinatal Period - Conditions Originating in Perinatal Period (rcdc)</dc:subject><dc:subject>2.2 Factors relating to the physical environment (hrcs-rac)</dc:subject><dc:subject>Reproductive health and childbirth (hrcs-hc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Environmental Monitoring (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Halogenated Diphenyl Ethers (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Hydrocarbons</dc:subject><dc:subject>Chlorinated (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Maternal Exposure (mesh)</dc:subject><dc:subject>Maternal-Fetal Exchange (mesh)</dc:subject><dc:subject>Polychlorinated Biphenyls (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>San Francisco (mesh)</dc:subject><dc:subject>Urban Population (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Polychlorinated Biphenyls (mesh)</dc:subject><dc:subject>Hydrocarbons</dc:subject><dc:subject>Chlorinated (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Environmental Monitoring (mesh)</dc:subject><dc:subject>Maternal Exposure (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Maternal-Fetal Exchange (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Urban Population (mesh)</dc:subject><dc:subject>San Francisco (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Halogenated Diphenyl Ethers (mesh)</dc:subject><dc:subject>Environmental Monitoring (mesh)</dc:subject><dc:subject>Environmental Pollutants (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Halogenated Diphenyl Ethers (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Hydrocarbons</dc:subject><dc:subject>Chlorinated (mesh)</dc:subject><dc:subject>Infant</dc:subject><dc:subject>Newborn (mesh)</dc:subject><dc:subject>Maternal Exposure (mesh)</dc:subject><dc:subject>Maternal-Fetal Exchange (mesh)</dc:subject><dc:subject>Polychlorinated Biphenyls (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>San Francisco (mesh)</dc:subject><dc:subject>Urban Population (mesh)</dc:subject><dc:subject>Environmental Sciences (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/9t38p564</dc:identifier><dc:identifier>https://escholarship.org/content/qt9t38p564/qt9t38p564.pdf</dc:identifier><dc:identifier>info:doi/10.1021/acs.est.6b03492</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Science and Technology, vol 50, iss 22</dc:source><dc:coverage>12464 - 12472</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4p49372p</identifier><datestamp>2026-09-15T17:25:08Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4p49372p</dc:identifier><dc:title>Causality guided machine learning model on wetland CH4 emissions across global wetlands</dc:title><dc:creator>Yuan, Kunxiaojia</dc:creator><dc:creator>Zhu, Qing</dc:creator><dc:creator>Li, Fa</dc:creator><dc:creator>Riley, William J</dc:creator><dc:creator>Torn, Margaret</dc:creator><dc:creator>Chu, Housen</dc:creator><dc:creator>McNicol, Gavin</dc:creator><dc:creator>Chen, Min</dc:creator><dc:creator>Knox, Sara</dc:creator><dc:creator>Delwiche, Kyle</dc:creator><dc:creator>Wu, Huayi</dc:creator><dc:creator>Baldocchi, Dennis</dc:creator><dc:creator>Ma, Hongxu</dc:creator><dc:creator>Desai, Ankur R</dc:creator><dc:creator>Chen, Jiquan</dc:creator><dc:creator>Sachs, Torsten</dc:creator><dc:creator>Ueyama, Masahito</dc:creator><dc:creator>Sonnentag, Oliver</dc:creator><dc:creator>Helbig, Manuel</dc:creator><dc:creator>Tuittila, Eeva-Stiina</dc:creator><dc:creator>Jurasinski, Gerald</dc:creator><dc:creator>Koebsch, Franziska</dc:creator><dc:creator>Campbell, David</dc:creator><dc:creator>Schmid, Hans Peter</dc:creator><dc:creator>Lohila, Annalea</dc:creator><dc:creator>Goeckede, Mathias</dc:creator><dc:creator>Nilsson, Mats B</dc:creator><dc:creator>Friborg, Thomas</dc:creator><dc:creator>Jansen, Joachim</dc:creator><dc:creator>Zona, Donatella</dc:creator><dc:creator>Euskirchen, Eugenie</dc:creator><dc:creator>Ward, Eric J</dc:creator><dc:creator>Bohrer, Gil</dc:creator><dc:creator>Jin, Zhenong</dc:creator><dc:creator>Liu, Licheng</dc:creator><dc:creator>Iwata, Hiroki</dc:creator><dc:creator>Goodrich, Jordan</dc:creator><dc:creator>Jackson, Robert</dc:creator><dc:date>2022-09-01</dc:date><dc:description>Wetland CH4 emissions are among the most uncertain components of the global CH4 budget. The complex nature of wetland CH4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH4 emissions. In this study, we used the flux measurements of CH4 from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra) to construct a causality-constrained machine learning (ML) framework to explain the regulative factors and to capture CH4 emissions at sub-seasonal scale. We found that soil temperature is the dominant factor for CH4 emissions in all studied wetland types. Ecosystem respiration (CO2) and gross primary productivity exert controls at bog, fen, and marsh sites with lagged responses of days to weeks. Integrating these asynchronous environmental and biological causal relationships in predictive models significantly improved model performance. More importantly, modeled CH4 emissions differed by up to a factor of 4 under a +1°C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH4 emissions especially under future warming conditions, while traditional data-driven ML models may reproduce observations for the wrong reasons. Our proposed causality-guided model could benefit predictive modeling, large-scale upscaling, data gap-filling, and surrogate modeling of wetland CH4 emissions within earth system land models.</dc:description><dc:subject>37 Earth Sciences (for-2020)</dc:subject><dc:subject>Networking and Information Technology R&amp;D (NITRD) (rcdc)</dc:subject><dc:subject>Machine Learning and Artificial Intelligence (rcdc)</dc:subject><dc:subject>13 Climate Action (sdg)</dc:subject><dc:subject>Eddy covariance CH4 emission</dc:subject><dc:subject>Wetlands</dc:subject><dc:subject>Causal inference</dc:subject><dc:subject>Machine learning</dc:subject><dc:subject>eddy covariance CH4 emission</dc:subject><dc:subject>wetlands</dc:subject><dc:subject>causal inference</dc:subject><dc:subject>predictive model</dc:subject><dc:subject>04 Earth Sciences (for)</dc:subject><dc:subject>06 Biological Sciences (for)</dc:subject><dc:subject>07 Agricultural and Veterinary Sciences (for)</dc:subject><dc:subject>Meteorology &amp; Atmospheric Sciences (science-metrix)</dc:subject><dc:subject>30 Agricultural</dc:subject><dc:subject>veterinary and food sciences (for-2020)</dc:subject><dc:subject>31 Biological sciences (for-2020)</dc:subject><dc:subject>37 Earth sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4p49372p</dc:identifier><dc:identifier>https://escholarship.org/content/qt4p49372p/qt4p49372p.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.agrformet.2022.109115</dc:identifier><dc:type>article</dc:type><dc:source>Agricultural and Forest Meteorology, vol 324</dc:source><dc:coverage>109115</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0nm3n5fp</identifier><datestamp>2026-09-15T17:24:58Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0nm3n5fp</dc:identifier><dc:title>HOD-dependent systematics in Emission Line Galaxies for the DESI 2024 BAO analysis</dc:title><dc:creator>Garcia-Quintero, C</dc:creator><dc:creator>Mena-Fernández, J</dc:creator><dc:creator>Rocher, A</dc:creator><dc:creator>Yuan, S</dc:creator><dc:creator>Hadzhiyska, B</dc:creator><dc:creator>Alves, O</dc:creator><dc:creator>Rashkovetskyi, M</dc:creator><dc:creator>Seo, H</dc:creator><dc:creator>Padmanabhan, N</dc:creator><dc:creator>Nadathur, S</dc:creator><dc:creator>Howlett, C</dc:creator><dc:creator>Ishak, M</dc:creator><dc:creator>Medina-Varela, L</dc:creator><dc:creator>McDonald, P</dc:creator><dc:creator>Ross, AJ</dc:creator><dc:creator>Xie, Y</dc:creator><dc:creator>Chen, X</dc:creator><dc:creator>Bera, A</dc:creator><dc:creator>Aguilar, J</dc:creator><dc:creator>Ahlen, S</dc:creator><dc:creator>Andrade, U</dc:creator><dc:creator>BenZvi, S</dc:creator><dc:creator>Brooks, D</dc:creator><dc:creator>Burtin, E</dc:creator><dc:creator>Chen, S</dc:creator><dc:creator>Claybaugh, T</dc:creator><dc:creator>Cole, S</dc:creator><dc:creator>de la Macorra, A</dc:creator><dc:creator>de Mattia, A</dc:creator><dc:creator>Dey, A</dc:creator><dc:creator>Dey, B</dc:creator><dc:creator>Ding, Z</dc:creator><dc:creator>Doel, P</dc:creator><dc:creator>Fanning, K</dc:creator><dc:creator>Forero-Romero, JE</dc:creator><dc:creator>Gaztañaga, E</dc:creator><dc:creator>Gil-Marín, H</dc:creator><dc:creator>Gontcho, S Gontcho A</dc:creator><dc:creator>Gutierrez, G</dc:creator><dc:creator>Guy, J</dc:creator><dc:creator>Hahn, C</dc:creator><dc:creator>Honscheid, K</dc:creator><dc:creator>Kremin, A</dc:creator><dc:creator>Landriau, M</dc:creator><dc:creator>Le Guillou, L</dc:creator><dc:creator>Levi, ME</dc:creator><dc:creator>Manera, M</dc:creator><dc:creator>Martini, P</dc:creator><dc:creator>Meisner, A</dc:creator><dc:creator>Miquel, R</dc:creator><dc:creator>Moustakas, J</dc:creator><dc:creator>Mueller, E</dc:creator><dc:creator>Muñoz-Gutiérrez, A</dc:creator><dc:creator>Myers, AD</dc:creator><dc:creator>Newman, JA</dc:creator><dc:creator>Nie, J</dc:creator><dc:creator>Niz, G</dc:creator><dc:creator>Paillas, E</dc:creator><dc:creator>Palanque-Delabrouille, N</dc:creator><dc:creator>Percival, WJ</dc:creator><dc:creator>Poppett, C</dc:creator><dc:creator>Pérez-Fernández, A</dc:creator><dc:creator>Rosado-Marin, A</dc:creator><dc:creator>Rossi, G</dc:creator><dc:creator>Ruggeri, R</dc:creator><dc:creator>Sanchez, E</dc:creator><dc:creator>Schlegel, D</dc:creator><dc:creator>Schubnell, M</dc:creator><dc:creator>Sprayberry, D</dc:creator><dc:creator>Tarlé, G</dc:creator><dc:creator>Vargas-Magaña, M</dc:creator><dc:creator>Weaver, BA</dc:creator><dc:creator>Yu, J</dc:creator><dc:creator>Zhang, H</dc:creator><dc:creator>Zhou, R</dc:creator><dc:creator>Zou, H</dc:creator><dc:date>2025-01-01</dc:date><dc:description>The Dark Energy Spectroscopic Instrument (DESI) will provide precise measurements of Baryon Acoustic Oscillations (BAO) to constrain the expansion history of the Universe and set stringent constraints on dark energy. Therefore, precise control of the global error budget due to various systematic effects is required for the DESI 2024 BAO analysis. In this work, we estimate the level of systematics induced in the DESI BAO analysis due the assumed Halo Occupation Distribution (HOD) model for the Emission Line Galaxy (ELG) tracer. We make use of mock galaxy catalogs constructed by fitting various HOD models to early DESI data, namely the One-Percent survey data. Our analysis includes typical HOD models for the ELG tracer used in the literature as well as extensions to the baseline models. Among the extensions, we consider various recipes for galactic conformity and assembly bias. We use 25 AbacusSummit simulations under the ΛCDM cosmology for each HOD model and perform independent analyses in Fourier space and in configuration space. To recover the BAO signal from our mocks we perform BAO reconstruction and apply the control variates technique to reduce sample variance noise. Our BAO analyses can recover the isotropic BAO parameter α iso within 0.1% and the Alcock Paczynski parameter α AP within 0.3%. Overall, we find that the systematic error due to the HOD dependence is below 0.17%, with the Fourier space analysis being more robust against the HOD systematics. We conclude that our analysis pipeline is robust enough against the HOD systematics for the ELG tracer in the DESI 2024 BAO analysis, for the assumptions made.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>baryon acoustic oscillations</dc:subject><dc:subject>galaxy clustering</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5101 Astronomical sciences (for-2020)</dc:subject><dc:subject>5107 Particle and high energy physics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0nm3n5fp</dc:identifier><dc:identifier>https://escholarship.org/content/qt0nm3n5fp/qt0nm3n5fp.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1475-7516/2025/01/132</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Cosmology and Astroparticle Physics, vol 2025, iss 01</dc:source><dc:coverage>132</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt5pj2c0q8</identifier><datestamp>2026-09-15T17:24:38Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt5pj2c0q8</dc:identifier><dc:title>Nature-based adaptation in San Francisco Bay: Social and economic benefits of nature-based adaptation solutions to protect San Mateo County from storms and sea level rise</dc:title><dc:creator>Gonzalez Reguero, Borja</dc:creator><dc:creator>Taylor-Burns, Rae</dc:creator><dc:creator>Fogg, Sandra</dc:creator><dc:creator>Lowrie, Chris</dc:creator><dc:creator>Constantz, Brook</dc:creator><dc:creator>Heard, Sarah</dc:creator><dc:creator>Mann, A</dc:creator><dc:creator>Chamberlin, S</dc:creator><dc:creator>Beck, MW</dc:creator><dc:date>2025-05-01</dc:date><dc:subject>nature-based solutions</dc:subject><dc:subject>adaptation</dc:subject><dc:subject>flood risk</dc:subject><dc:subject>saltmarsh restoration</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/5pj2c0q8</dc:identifier><dc:identifier>https://escholarship.org/content/qt5pj2c0q8/qt5pj2c0q8.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4m0270sj</identifier><datestamp>2026-09-15T17:24:35Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4m0270sj</dc:identifier><dc:title>Julienne + Assert == Correctness-Checking for Functional Fortran</dc:title><dc:creator>Rasmussen, Katherine</dc:creator><dc:creator>Rouson, Damian</dc:creator><dc:creator>Bonachea, Dan</dc:creator><dc:date>2025-04-08</dc:date><dc:description>The agile software development practice of test-driven development (TDD) advocates unit testing as an essential driver of software design and construction. In TDD, tests of individual units of software (e.g., procedures) serve documentation and verification roles. As documentation, tests specify the behaviors required for code correctness. Executing a suite of tests verifies that the actual behaviors satisfy the documented requirements. As inspired by the Veggies and Garden unit testing frameworks for modern Fortran, the more lightweight Julienne framework uses the Template Method pattern to report serial or parallel test results in the form of a specification (https://go.lbl.gov/julienne). As such, Julienne’s test output names the test subject (e.g., a class or type-bound procedure), the expected behavior, the test outcome (pass or fail), and provides diagnostic information if a test fails.

The use of Julienne centers around users defining a test in the form of a non-abstract child type that extends Julienne’s abstract test_t derived type. The user’s child type thus inherits an obligation to define type-bound procedures that name the subject of the test and provide the test results. As a template method, test_t’s type-bound “report” procedure invokes the user’s procedures by referencing the aforementioned deferred bindings and reporting on the collective success or failure across multiple images (processes) in programs that use Fortran’s multi-image parallel programming features.

Working from the example test suite in the Julienne repository, attendees will learn how to write and run a simple test suite, including how to use Julienne’s string-handling for producing rich diagnostic information from a failing test. Attendees will also see examples of Julienne’s use in other Berkeley Lab software projects such as the Fiats deep learning library and Matcha T-cell motility simulator.

Attendees will also learn a functional programming pattern developed and used by the Berkeley Lab Fortran presenters. Functional programming centers around the definition of pure procedures that are free of side effects, including file input and output. To supplement the material on external verification via unit tests, this tutorial will also introduce our Assert utility library and Assert’s use for runtime correctness-checking inside procedures (https://go.lbl.gov/assert). Attendees will learn how Assert addresses a common reason developers cite for not writing pure procedures: a desire to produce diagnostic output when debugging code. We posit that most developers seek output to verify an expectation about data and that such expectations can be stated in assertions that take the form of logical expressions. Attendees will learn how Assert empowers developers to obtain rich, customized diagnostic information through character stop codes when an assertion fails, resulting in error termination. Attendees will also learn how to use Assert in such a way that guarantees zero runtime overhead by automatically eliminating assertions in production builds of user software.</dc:description><dc:subject>class-fortran (c-lbnl-label)</dc:subject><dc:subject>LBLCS-class-fortran (c-lbnl-label)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4m0270sj</dc:identifier><dc:identifier>https://escholarship.org/content/qt4m0270sj/qt4m0270sj.pdf</dc:identifier><dc:identifier>info:doi/10.25344/S4401K</dc:identifier><dc:type>non_textual</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8t59m2m3</identifier><datestamp>2026-09-15T17:17:42Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8t59m2m3</dc:identifier><dc:title>The Advisory Group on Risk Evidence Education for Dementia: Multidisciplinary and Open to All</dc:title><dc:creator>Rosen, Allyson C</dc:creator><dc:creator>Arias, Jalayne J</dc:creator><dc:creator>Ashford, J Wesson</dc:creator><dc:creator>Blacker, Deborah</dc:creator><dc:creator>Chhatwal, Jasmeer P</dc:creator><dc:creator>Chin, Nathan A</dc:creator><dc:creator>Clark, Lindsay</dc:creator><dc:creator>Denny, Sharon S</dc:creator><dc:creator>Goldman, Jill S</dc:creator><dc:creator>Gleason, Carey E</dc:creator><dc:creator>Grill, Joshua D</dc:creator><dc:creator>Heidebrink, Judith L</dc:creator><dc:creator>Henderson, Victor W</dc:creator><dc:creator>Lavacot, James A</dc:creator><dc:creator>Lingler, Jennifer H</dc:creator><dc:creator>Menon, Malavika</dc:creator><dc:creator>Nosheny, Rachel L</dc:creator><dc:creator>Oliveira, Fabricio F</dc:creator><dc:creator>Parker, Monica W</dc:creator><dc:creator>Rahman-Filipiak, Annalise</dc:creator><dc:creator>Revoori, Anwita</dc:creator><dc:creator>Rumbaugh, Malia C</dc:creator><dc:creator>Sanchez, Danurys L</dc:creator><dc:creator>Schindler, Suzanne E</dc:creator><dc:creator>Schwarz, Christopher G</dc:creator><dc:creator>Toy, Leslie</dc:creator><dc:creator>Tyrone, Jamie</dc:creator><dc:creator>Walter, Sarah</dc:creator><dc:creator>Wang, Li-san</dc:creator><dc:creator>Wijsman, Ellen M</dc:creator><dc:creator>Zallen, Doris T</dc:creator><dc:creator>Aggarwal, Neelum T</dc:creator><dc:creator>members of AGREEDementia</dc:creator><dc:date>2022-01-01</dc:date><dc:description>The brain changes of Alzheimer's disease and other degenerative dementias begin long before cognitive dysfunction develops, and in people with subtle cognitive complaints, clinicians often struggle to predict who will develop dementia. The public increasingly sees benefits to accessing dementia risk evidence (DRE) such as biomarkers, predictive algorithms, and genetic information, particularly as this information moves from research to demonstrated usefulness in guiding diagnosis and clinical management. For example, the knowledge that one has high levels of amyloid in the brain may lead one to seek amyloid reducing medications, plan for disability, or engage in health promoting behaviors to fight cognitive decline. Researchers often hesitate to share DRE data, either because they are insufficiently validated or reliable for use in individuals, or there are concerns about assuring responsible use and ensuring adequate understanding of potential problems when one's biomarker status is known. Concerns include warning people receiving DRE about situations in which they might be compelled to disclose their risk status potentially leading to discrimination or stigma. The Advisory Group on Risk Evidence Education for Dementia (AGREEDementia) welcomes all concerned with how best to share and use DRE. Supporting understanding in clinicians, stakeholders, and people with or at risk for dementia and clearly delineating risks, benefits, and gaps in knowledge is vital. This brief overview describes elements that made this group effective as a model for other health conditions where there is interest in unfettered collaboration to discuss diagnostic uncertainty and the appropriate use and communication of health-related risk information.</dc:description><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>5202 Biological Psychology (for-2020)</dc:subject><dc:subject>3202 Clinical Sciences (for-2020)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:subject>52 Psychology (for-2020)</dc:subject><dc:subject>Aging (rcdc)</dc:subject><dc:subject>Acquired Cognitive Impairment (rcdc)</dc:subject><dc:subject>Dementia (rcdc)</dc:subject><dc:subject>Neurodegenerative (rcdc)</dc:subject><dc:subject>Brain Disorders (rcdc)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Basic Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Alzheimer's Disease (rcdc)</dc:subject><dc:subject>Neurological (hrcs-hc)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Dementia (mesh)</dc:subject><dc:subject>Alzheimer Disease (mesh)</dc:subject><dc:subject>Cognitive Dysfunction (mesh)</dc:subject><dc:subject>Amyloid (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:subject>Alzheimer's disease</dc:subject><dc:subject>amyloid</dc:subject><dc:subject>biomarkers</dc:subject><dc:subject>dementia</dc:subject><dc:subject>genetics</dc:subject><dc:subject>members of AGREEDementia</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Dementia (mesh)</dc:subject><dc:subject>Alzheimer Disease (mesh)</dc:subject><dc:subject>Amyloid (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:subject>Cognitive Dysfunction (mesh)</dc:subject><dc:subject>Alzheimer’s disease</dc:subject><dc:subject>amyloid</dc:subject><dc:subject>biomarkers</dc:subject><dc:subject>dementia</dc:subject><dc:subject>genetics</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Dementia (mesh)</dc:subject><dc:subject>Alzheimer Disease (mesh)</dc:subject><dc:subject>Cognitive Dysfunction (mesh)</dc:subject><dc:subject>Amyloid (mesh)</dc:subject><dc:subject>Biomarkers (mesh)</dc:subject><dc:subject>1103 Clinical Sciences (for)</dc:subject><dc:subject>1109 Neurosciences (for)</dc:subject><dc:subject>1702 Cognitive Sciences (for)</dc:subject><dc:subject>Neurology &amp; Neurosurgery (science-metrix)</dc:subject><dc:subject>3202 Clinical sciences (for-2020)</dc:subject><dc:subject>3209 Neurosciences (for-2020)</dc:subject><dc:subject>5202 Biological psychology (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8t59m2m3</dc:identifier><dc:identifier>https://escholarship.org/content/qt8t59m2m3/qt8t59m2m3.pdf</dc:identifier><dc:identifier>info:doi/10.3233/jad-220458</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Alzheimer’s Disease, vol 90, iss 3</dc:source><dc:coverage>953 - 962</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt79m493wz</identifier><datestamp>2026-09-15T17:13:45Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt79m493wz</dc:identifier><dc:title>PFAS-Contaminated Pesticides Applied near Public Supply Wells Disproportionately Impact Communities of Color in California</dc:title><dc:creator>Libenson, Arianna</dc:creator><dc:creator>Karasaki, Seigi</dc:creator><dc:creator>Cushing, Lara J</dc:creator><dc:creator>Tran, Tien</dc:creator><dc:creator>Rempel, Jenny L</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>Pace, Clare E</dc:creator><dc:date>2024-06-14</dc:date><dc:description>Contaminated drinking water from widespread environmental pollutants such as perfluoroalkyl and polyfluoroalkyl substances (PFAS) poses a rising threat to public health. PFAS monitoring in groundwater is limited and fails to consider pesticides found to contain PFAS as a potential contamination source. Given previous findings on the disproportionate exposure of communities of Color to both pesticides and PFAS, we investigated disparities in PFAS-contaminated pesticide applications in California based on community-level sociodemographic characteristics. We utilized statewide pesticide application data from the California Department of Pesticide Regulation and recently reported concentrations of PFAS chemicals detected in eight pesticide products to calculate the areal density of PFAS applied within 1 km of individual community water systems' (CWSs) supply wells. Spatial regression analyses suggest that statewide, CWSs that serve a greater proportion of Latinx and non-Latinx People of Color residents experience a greater areal density of PFAS applied and greater likelihood of PFAS application near their public supply wells. These results highlight agroecosystems as potentially important sources of PFAS in drinking water and identify areas that may be at risk of PFAS contamination and warrant additional PFAS monitoring and remediation.</dc:description><dc:subject>41 Environmental Sciences (for-2020)</dc:subject><dc:subject>4105 Pollution and Contamination (for-2020)</dc:subject><dc:subject>Rural Health (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Minority Health (rcdc)</dc:subject><dc:subject>Foodborne Illness (rcdc)</dc:subject><dc:subject>Endocrine Disruptors (rcdc)</dc:subject><dc:subject>2.2 Factors relating to the physical environment (hrcs-rac)</dc:subject><dc:subject>Environmental Justice</dc:subject><dc:subject>Human Right to Water</dc:subject><dc:subject>Community Water Systems (CWSs)</dc:subject><dc:subject>Pollution</dc:subject><dc:subject>Disparities</dc:subject><dc:subject>PFAS</dc:subject><dc:subject>Pesticides</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/79m493wz</dc:identifier><dc:identifier>https://escholarship.org/content/qt79m493wz/qt79m493wz.pdf</dc:identifier><dc:identifier>info:doi/10.1021/acsestwater.3c00845</dc:identifier><dc:type>article</dc:type><dc:source>ACS ES&amp;T Water, vol 4, iss 6</dc:source><dc:coverage>2495 - 2503</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt3cg7176d</identifier><datestamp>2026-09-15T17:13:42Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt3cg7176d</dc:identifier><dc:title>The polarization sensitivity of GRETINA</dc:title><dc:creator>Morse, C</dc:creator><dc:creator>Crawford, HL</dc:creator><dc:creator>Macchiavelli, AO</dc:creator><dc:creator>Wiens, A</dc:creator><dc:creator>Albers, M</dc:creator><dc:creator>Ayangeakaa, AD</dc:creator><dc:creator>Bender, PC</dc:creator><dc:creator>Campbell, CM</dc:creator><dc:creator>Carpenter, MP</dc:creator><dc:creator>Chowdhury, P</dc:creator><dc:creator>Clark, RM</dc:creator><dc:creator>Cromaz, M</dc:creator><dc:creator>David, HM</dc:creator><dc:creator>Fallon, P</dc:creator><dc:creator>Janssens, RVF</dc:creator><dc:creator>Lauritsen, T</dc:creator><dc:creator>Lee, I-Y</dc:creator><dc:creator>Lister, CJ</dc:creator><dc:creator>Miller, D</dc:creator><dc:creator>Prasher, VS</dc:creator><dc:creator>Tabor, SL</dc:creator><dc:creator>Weisshaar, D</dc:creator><dc:creator>Zhu, S</dc:creator><dc:date>2022-02-01</dc:date><dc:description>Compton polarimeters have played an important role in the study of nuclear structure physics, but have often been limited in their applications because of relatively low γ -ray detection efficiency. With the advent of γ -ray tracking detector arrays, which feature nearly 4 π solid angle coverage and the ability to identify the location of Compton-scattering events to within a few millimeters, this limitation can be overcome. Here we present a characterization of the performance of the Gamma Ray Energy Tracking In-beam Nuclear Array (GRETINA) as a Compton polarimeter using the 24Mg( p , p ′ ) reaction at 2.45&amp;nbsp;MeV proton energy. We also discuss a new capability added to the simulation package UCGretina to simulate the emission of polarized photons, and compare it to the measured data. Finally, we use these simulations to predict the performance of the Gamma Ray Energy Tracking Array (GRETA).</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>5110 Synchrotrons and Accelerators (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>7 Affordable and Clean Energy (sdg)</dc:subject><dc:subject>Polarization</dc:subject><dc:subject>Tracking detectors</dc:subject><dc:subject>NSD-Low Energy Nuclear Physics (c-lbnl-label)</dc:subject><dc:subject>0201 Astronomical and Space Sciences (for)</dc:subject><dc:subject>0202 Atomic</dc:subject><dc:subject>Molecular</dc:subject><dc:subject>Nuclear</dc:subject><dc:subject>Particle and Plasma Physics (for)</dc:subject><dc:subject>0299 Other Physical Sciences (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>5106 Nuclear and plasma physics (for-2020)</dc:subject><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/3cg7176d</dc:identifier><dc:identifier/><dc:identifier>info:doi/10.1016/j.nima.2021.166155</dc:identifier><dc:type>article</dc:type><dc:source>Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, vol 1025</dc:source><dc:coverage>166155</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt0q17h3w0</identifier><datestamp>2026-09-15T17:13:08Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt0q17h3w0</dc:identifier><dc:title>Exposure to melamine and its derivatives and aromatic amines among pregnant women in the United States: The ECHO Program</dc:title><dc:creator>Choi, Giehae</dc:creator><dc:creator>Kuiper, Jordan R</dc:creator><dc:creator>Bennett, Deborah H</dc:creator><dc:creator>Barrett, Emily S</dc:creator><dc:creator>Bastain, Theresa M</dc:creator><dc:creator>Breton, Carrie V</dc:creator><dc:creator>Chinthakindi, Sridhar</dc:creator><dc:creator>Dunlop, Anne L</dc:creator><dc:creator>Farzan, Shohreh F</dc:creator><dc:creator>Herbstman, Julie B</dc:creator><dc:creator>Karagas, Margaret R</dc:creator><dc:creator>Marsit, Carmen J</dc:creator><dc:creator>Meeker, John D</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:creator>O'Connor, Thomas G</dc:creator><dc:creator>Pellizzari, Edo D</dc:creator><dc:creator>Romano, Megan E</dc:creator><dc:creator>Sathyanarayana, Sheela</dc:creator><dc:creator>Schantz, Susan</dc:creator><dc:creator>Schmidt, Rebecca J</dc:creator><dc:creator>Watkins, Deborah J</dc:creator><dc:creator>Zhu, Hongkai</dc:creator><dc:creator>Kannan, Kurunthachalam</dc:creator><dc:creator>Buckley, Jessie P</dc:creator><dc:creator>Woodruff, Tracey J</dc:creator><dc:creator>Outcomes, program collaborators for Environmental influences on Child Health</dc:creator><dc:date>2022-11-01</dc:date><dc:description>BACKGROUND: Melamine, melamine derivatives, and aromatic amines are nitrogen-containing compounds with known toxicity and widespread commercial uses. Nevertheless, biomonitoring of these chemicals is lacking, particularly during pregnancy, a period of increased susceptibility to adverse health effects.
OBJECTIVES: We aimed to measure melamine, melamine derivatives, and aromatic amine exposure in pregnant women across the United States (U.S.) and evaluate associations with participant and urine sample collection characteristics.
METHODS: We measured 43 analytes, representing 45 chemicals (i.e., melamine, three melamine derivatives, and 41 aromatic amines), in urine from pregnant women in nine diverse ECHO cohorts during 2008-2020 (N = 171). To assess relations with participant and urine sample collection characteristics, we used generalized estimating equations to estimate prevalence ratios (PRs) for analytes dichotomized at the detection limit, % differences (%Δ) for continuous analytes, and 95% confidence intervals. Multivariable models included age, race/ethnicity, marital status, urinary cotinine, and year of sample collection.
RESULTS: Twelve chemicals were detected in &amp;gt;60% of samples, with near ubiquitous detection of cyanuric acid, melamine, aniline, 4,4'-methylenedianiline, and a composite of o-toluidine and m-toluidine (99-100%). In multivariable adjusted models, most chemicals were associated with higher exposures among Hispanic and non-Hispanic Black participants. For example, concentrations of 3,4-dichloroaniline were higher among Hispanic (%Δ: +149, 95% CI: +17, +431) and non-Hispanic Black (%Δ: +136, 95% CI: +35, +311) women compared with non-Hispanic White women. We observed similar results for ammelide, o-/m-toluidine, 4,4'-methylenedianiline, and 4-chloroaniline. Most chemicals were positively associated with urinary cotinine, with strongest associations observed for o-/m-toluidine (%Δ: +23; 95% CI: +16, +31) and 3,4-dichloroaniline (%Δ: +25; 95% CI: +17, +33). Some chemicals exhibited annual trends (e.g., %Δ in melamine per year: -11; 95% CI: -19, -1) or time of day, seasonal, and geographic variability.
DISCUSSION: Exposure to melamine, cyanuric acid, and some aromatic amines was ubiquitous in this first investigation of these analytes in pregnant women. Future research should expand biomonitoring, identify sources of exposure disparities by race/ethnicity, and evaluate potential adverse health effects.</dc:description><dc:subject>3215 Reproductive Medicine (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>34 Chemical Sciences (for-2020)</dc:subject><dc:subject>Minority Health (rcdc)</dc:subject><dc:subject>Social Determinants of Health (rcdc)</dc:subject><dc:subject>Health Disparities and Racial or Ethnic Minority Health Research (rcdc)</dc:subject><dc:subject>Pregnancy (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Health Disparities (rcdc)</dc:subject><dc:subject>Amines (mesh)</dc:subject><dc:subject>Aniline Compounds (mesh)</dc:subject><dc:subject>Cotinine (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Nitrogen (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Pregnant People (mesh)</dc:subject><dc:subject>Toluidines (mesh)</dc:subject><dc:subject>Triazines (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Benzhydryl Compounds (mesh)</dc:subject><dc:subject>Biomonitoring</dc:subject><dc:subject>chemical exposure</dc:subject><dc:subject>pregnancy</dc:subject><dc:subject>aromatic amines</dc:subject><dc:subject>melamine</dc:subject><dc:subject>tobacco</dc:subject><dc:subject>program collaborators for Environmental influences on Child Health Outcomes</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Nitrogen (mesh)</dc:subject><dc:subject>Amines (mesh)</dc:subject><dc:subject>Aniline Compounds (mesh)</dc:subject><dc:subject>Toluidines (mesh)</dc:subject><dc:subject>Benzhydryl Compounds (mesh)</dc:subject><dc:subject>Cotinine (mesh)</dc:subject><dc:subject>Triazines (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Pregnant People (mesh)</dc:subject><dc:subject>Biomonitoring</dc:subject><dc:subject>aromatic amines</dc:subject><dc:subject>chemical exposure</dc:subject><dc:subject>melamine</dc:subject><dc:subject>pregnancy</dc:subject><dc:subject>tobacco</dc:subject><dc:subject>Amines (mesh)</dc:subject><dc:subject>Aniline Compounds (mesh)</dc:subject><dc:subject>Cotinine (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Nitrogen (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Pregnant People (mesh)</dc:subject><dc:subject>Toluidines (mesh)</dc:subject><dc:subject>Triazines (mesh)</dc:subject><dc:subject>United States (mesh)</dc:subject><dc:subject>Benzhydryl Compounds (mesh)</dc:subject><dc:subject>Biomonitoring</dc:subject><dc:subject>chemical exposure</dc:subject><dc:subject>pregnancy</dc:subject><dc:subject>Aromatic amines</dc:subject><dc:subject>Melamine</dc:subject><dc:subject>Tobacco</dc:subject><dc:subject>Environmental Sciences (science-metrix)</dc:subject><dc:subject>Meteorology &amp; Atmospheric Sciences (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/0q17h3w0</dc:identifier><dc:identifier>https://escholarship.org/content/qt0q17h3w0/qt0q17h3w0.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.chemosphere.2022.135599</dc:identifier><dc:type>article</dc:type><dc:source>Chemosphere, vol 307, iss Pt 2</dc:source><dc:coverage>135599</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt6140s280</identifier><datestamp>2026-09-15T17:09:49Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt6140s280</dc:identifier><dc:title>Full-Scale 10-Story Cold-Formed Steel Building Shake Table Test: Protocol Development and Shake Table Performance</dc:title><dc:creator>Zhang, Jiachen</dc:creator><dc:creator>Sorosh, Shokrullah</dc:creator><dc:creator>Ji, Ruipu</dc:creator><dc:creator>Lotfizadeh, Koorosh</dc:creator><dc:creator>Schafer, Benjamin</dc:creator><dc:creator>Hutchinson, Tara</dc:creator><dc:date>2026-07-13</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/6140s280</dc:identifier><dc:identifier>https://escholarship.org/content/qt6140s280/qt6140s280.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt1ct4b0ng</identifier><datestamp>2026-09-15T17:05:30Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt1ct4b0ng</dc:identifier><dc:title>Evolution of Modal Characteristics and Model Comparison for a 10-Story Cold-Formed Steel Framed Building under Seismic Excitation</dc:title><dc:creator>Zhang, Jiachen</dc:creator><dc:creator>Sorosh, Shokrullah</dc:creator><dc:creator>Singh, Amanpreet</dc:creator><dc:creator>Schafer, Benjamin</dc:creator><dc:creator>Hutchinson, Tara</dc:creator><dc:date>2026-01-19</dc:date><dc:format>application/pdf</dc:format><dc:rights>CC-BY</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/1ct4b0ng</dc:identifier><dc:identifier>https://escholarship.org/content/qt1ct4b0ng/qt1ct4b0ng.pdf</dc:identifier><dc:type>article</dc:type></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt4gp4d7m2</identifier><datestamp>2026-09-15T17:01:59Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt4gp4d7m2</dc:identifier><dc:title>Using the Key Characteristics of Carcinogens to Develop Research on Chemical Mixtures and Cancer</dc:title><dc:creator>Rider, Cynthia V</dc:creator><dc:creator>McHale, Cliona M</dc:creator><dc:creator>Webster, Thomas F</dc:creator><dc:creator>Lowe, Leroy</dc:creator><dc:creator>GoodsonIII, William H</dc:creator><dc:creator>La, Michele A</dc:creator><dc:creator>Merrill</dc:creator><dc:creator>Rice, Glenn</dc:creator><dc:creator>Zeise, Lauren</dc:creator><dc:creator>Zhang, Luoping</dc:creator><dc:creator>Smith, Martyn T</dc:creator><dc:date>2021-03-01</dc:date><dc:description>BACKGROUND: People are exposed to numerous chemicals throughout their lifetimes. Many of these chemicals display one or more of the key characteristics of carcinogens or interact with processes described in the hallmarks of cancer. Therefore, evaluating the effects of chemical mixtures on cancer development is an important pursuit. Challenges involved in designing research studies to evaluate the joint action of chemicals on cancer risk include the time taken to perform the experiments because of the long latency and choosing an appropriate experimental design.
OBJECTIVES: The objectives of this work are to present the case for developing a research program on mixtures of environmental chemicals and cancer risk and describe recommended approaches.
METHODS: A working group comprising the coauthors focused attention on the design of mixtures studies to inform cancer risk assessment as part of a larger effort to refine the key characteristics of carcinogens and explore their application. Working group members reviewed the key characteristics of carcinogens, hallmarks of cancer, and mixtures research for other disease end points. The group discussed options for developing tractable projects to evaluate the joint effects of environmental chemicals on cancer development.
RESULTS AND DISCUSSION: Three approaches for developing a research program to evaluate the effects of mixtures on cancer development were proposed: a chemical screening approach, a transgenic model-based approach, and a disease-centered approach. Advantages and disadvantages of each are discussed. https://doi.org/10.1289/EHP8525.</dc:description><dc:subject>4203 Health Services and Systems (for-2020)</dc:subject><dc:subject>42 Health Sciences (for-2020)</dc:subject><dc:subject>Cancer (rcdc)</dc:subject><dc:subject>Genetics (rcdc)</dc:subject><dc:subject>Human Genome (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Cancer Genomics (rcdc)</dc:subject><dc:subject>2.2 Factors relating to the physical environment (hrcs-rac)</dc:subject><dc:subject>Cancer (hrcs-hc)</dc:subject><dc:subject>Carcinogens (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Neoplasms (mesh)</dc:subject><dc:subject>Risk (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Neoplasms (mesh)</dc:subject><dc:subject>Carcinogens (mesh)</dc:subject><dc:subject>Risk (mesh)</dc:subject><dc:subject>Carcinogens (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Neoplasms (mesh)</dc:subject><dc:subject>Risk (mesh)</dc:subject><dc:subject>05 Environmental Sciences (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>Toxicology (science-metrix)</dc:subject><dc:subject>32 Biomedical and clinical sciences (for-2020)</dc:subject><dc:subject>41 Environmental sciences (for-2020)</dc:subject><dc:subject>42 Health sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/4gp4d7m2</dc:identifier><dc:identifier>https://escholarship.org/content/qt4gp4d7m2/qt4gp4d7m2.pdf</dc:identifier><dc:identifier>info:doi/10.1289/ehp8525</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Health Perspectives, vol 129, iss 3</dc:source><dc:coverage>035003</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8274g9tp</identifier><datestamp>2026-09-15T17:01:28Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8274g9tp</dc:identifier><dc:title>Association of maternal fish consumption and ω-3 supplement use during pregnancy with child autism-related outcomes: results from a cohort consortium analysis</dc:title><dc:creator>Lyall, Kristen</dc:creator><dc:creator>Westlake, Matt</dc:creator><dc:creator>Musci, Rashelle J</dc:creator><dc:creator>Gachigi, Kennedy</dc:creator><dc:creator>Barrett, Emily S</dc:creator><dc:creator>Bastain, Theresa M</dc:creator><dc:creator>Bush, Nicole R</dc:creator><dc:creator>Buss, Claudia</dc:creator><dc:creator>Camargo, Carlos A</dc:creator><dc:creator>Croen, Lisa A</dc:creator><dc:creator>Dabelea, Dana</dc:creator><dc:creator>Dunlop, Anne L</dc:creator><dc:creator>Elliott, Amy J</dc:creator><dc:creator>Ferrara, Assiamira</dc:creator><dc:creator>Ghassabian, Akhgar</dc:creator><dc:creator>Gern, James E</dc:creator><dc:creator>Hare, Marion E</dc:creator><dc:creator>Hertz-Picciotto, Irva</dc:creator><dc:creator>Hipwell, Alison E</dc:creator><dc:creator>Hockett, Christine W</dc:creator><dc:creator>Karagas, Margaret R</dc:creator><dc:creator>Lugo-Candelas, Claudia</dc:creator><dc:creator>O’Connor, Thomas G</dc:creator><dc:creator>Schmidt, Rebecca J</dc:creator><dc:creator>Stanford, Joseph B</dc:creator><dc:creator>Straughen, Jennifer K</dc:creator><dc:creator>Shuster, Coral L</dc:creator><dc:creator>Wright, Robert O</dc:creator><dc:creator>Wright, Rosalind J</dc:creator><dc:creator>Zhao, Qi</dc:creator><dc:creator>Oken, Emily</dc:creator><dc:creator>Outcomes, program collaborators for Environmental influences on Child Health</dc:creator><dc:creator>Components, ECHO</dc:creator><dc:creator>Center, Coordinating</dc:creator><dc:creator>Smith, PB</dc:creator><dc:creator>Newby, KL</dc:creator><dc:creator>Center, Data Analysis</dc:creator><dc:creator>Jacobson, LP</dc:creator><dc:creator>Catellier, DJ</dc:creator><dc:creator>Core, Person-Reported Outcomes</dc:creator><dc:creator>Gershon, R</dc:creator><dc:creator>Cella, D</dc:creator><dc:creator>Awardees and Cohorts, ECHO</dc:creator><dc:creator>Alshawabkeh, AN</dc:creator><dc:creator>Cordero, J</dc:creator><dc:creator>Meeker, J</dc:creator><dc:creator>Aschner, J</dc:creator><dc:creator>Teitelbaum, SL</dc:creator><dc:creator>Stroustrup, A</dc:creator><dc:creator>Mansbach, JM</dc:creator><dc:creator>Spergel, JM</dc:creator><dc:creator>Samuels-Kalow, ME</dc:creator><dc:creator>Stevenson</dc:creator><dc:creator>Bauer, CS</dc:creator><dc:creator>Mitchell, D Koinis</dc:creator><dc:creator>Deoni, S</dc:creator><dc:creator>D’Sa, V</dc:creator><dc:creator>Duarte, CS</dc:creator><dc:creator>Monk, C</dc:creator><dc:creator>Posner, J</dc:creator><dc:creator>Canino, G</dc:creator><dc:creator>Seroogy, C</dc:creator><dc:creator>Bendixsen, C</dc:creator><dc:creator>Hertz-Picciotto, I</dc:creator><dc:creator>Keenan, K</dc:creator><dc:creator>Karr, C</dc:creator><dc:creator>Tylavsky, F</dc:creator><dc:creator>Mason, A</dc:creator><dc:creator>Zhao, Q</dc:creator><dc:creator>Sathyanarayana, S</dc:creator><dc:creator>LeWinn, KZ</dc:creator><dc:creator>Lester, B</dc:creator><dc:creator>Carter, B</dc:creator><dc:creator>Pastyrnak, S</dc:creator><dc:creator>Neal, C</dc:creator><dc:creator>Smith, L</dc:creator><dc:creator>Helderman, J</dc:creator><dc:creator>Weiss</dc:creator><dc:creator>Litonjua, A</dc:creator><dc:creator>O’Connor, G</dc:creator><dc:creator>Zeiger, R</dc:creator><dc:creator>Bacharier, L</dc:creator><dc:creator>Volk, H</dc:creator><dc:creator>Ozonoff, S</dc:creator><dc:creator>Schmidt, R</dc:creator><dc:creator>Simhan, H</dc:creator><dc:creator>Kerver, JM</dc:creator><dc:creator>Barone, C</dc:creator><dc:creator>Fussman, C</dc:creator><dc:creator>Paneth, N</dc:creator><dc:creator>Elliott, M</dc:creator><dc:creator>Ruden, D</dc:creator><dc:creator>Porucznik, C</dc:creator><dc:creator>Giardino, A</dc:creator><dc:creator>Innocenti, M</dc:creator><dc:creator>Silver, R</dc:creator><dc:creator>Conradt, E</dc:creator><dc:creator>Bosquet-Enlow, M</dc:creator><dc:creator>Huddleston, K</dc:creator><dc:creator>Nguyen, R</dc:creator><dc:date>2024-09-01</dc:date><dc:description>BACKGROUND: Prenatal fish intake is a key source of omega-3 (ω-3) polyunsaturated fatty acids needed for brain development, yet intake is generally low, and studies addressing associations with autism spectrum disorder (ASD) and related traits are lacking.
OBJECTIVE: This study aimed to examine associations of prenatal fish intake and ω-3 supplement use with both autism diagnosis and broader autism-related traits.
METHODS: Participants were drawn from 32 cohorts in the Environmental influences on Child Health Outcomes Cohort Consortium. Children were born between 1999 and 2019 and part of ongoing follow-up with data available for analysis by August 2022. Exposures included self-reported maternal fish intake and ω-3/fish oil supplement use during pregnancy. Outcome measures included parent report of clinician-diagnosed ASD and parent-reported autism-related traits measured by the Social Responsiveness Scale (SRS)-second edition (n = 3939 and v3609 for fish intake analyses, respectively; n = 4537 and n = 3925 for supplement intake analyses, respectively).
RESULTS: In adjusted regression models, relative to no fish intake, fish intake during pregnancy was associated with reduced odds of autism diagnosis (odds ratio: 0.84; 95% confidence interval [CI]: 0.77, 0.92), and a modest reduction in raw total SRS scores (β: -1.69; 95% CI: -3.3, -0.08). Estimates were similar across categories of fish consumption from "any" or "less than once per week" to "more than twice per week." For ω-3 supplement use, relative to no use, no significant associations with autism diagnosis were identified, whereas a modest relation with SRS score was suggested (β: 1.98; 95% CI: 0.33, 3.64).
CONCLUSIONS: These results extend previous work by suggesting that prenatal fish intake, but not ω-3 supplement use, may be associated with lower likelihood of both autism diagnosis and related traits. Given the low-fish intake in the United States general population and the rising autism prevalence, these findings suggest the need for better public health messaging regarding guidelines on fish intake for pregnant individuals.</dc:description><dc:subject>3215 Reproductive Medicine (for-2020)</dc:subject><dc:subject>32 Biomedical and Clinical Sciences (for-2020)</dc:subject><dc:subject>Pregnancy (rcdc)</dc:subject><dc:subject>Neurosciences (rcdc)</dc:subject><dc:subject>Nutrition (rcdc)</dc:subject><dc:subject>Conditions Affecting the Embryonic and Fetal Periods (rcdc)</dc:subject><dc:subject>Clinical Research (rcdc)</dc:subject><dc:subject>Pediatric Research Initiative (rcdc)</dc:subject><dc:subject>Complementary and Integrative Health (rcdc)</dc:subject><dc:subject>Basic Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Behavioral and Social Science (rcdc)</dc:subject><dc:subject>Autism (rcdc)</dc:subject><dc:subject>Intellectual and Developmental Disabilities (IDD) (rcdc)</dc:subject><dc:subject>Prevention (rcdc)</dc:subject><dc:subject>Brain Disorders (rcdc)</dc:subject><dc:subject>Mental Health (rcdc)</dc:subject><dc:subject>Women's Health (rcdc)</dc:subject><dc:subject>Mental health (hrcs-hc)</dc:subject><dc:subject>Reproductive health and childbirth (hrcs-hc)</dc:subject><dc:subject>3 Good Health and Well Being (sdg)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Fatty Acids</dc:subject><dc:subject>Omega-3 (mesh)</dc:subject><dc:subject>Dietary Supplements (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Autism Spectrum Disorder (mesh)</dc:subject><dc:subject>Seafood (mesh)</dc:subject><dc:subject>Fishes (mesh)</dc:subject><dc:subject>Prenatal Exposure Delayed Effects (mesh)</dc:subject><dc:subject>Child</dc:subject><dc:subject>Preschool (mesh)</dc:subject><dc:subject>Autistic Disorder (mesh)</dc:subject><dc:subject>Diet (mesh)</dc:subject><dc:subject>Maternal Nutritional Physiological Phenomena (mesh)</dc:subject><dc:subject>pregnancy</dc:subject><dc:subject>autism</dc:subject><dc:subject>quantitative traits</dc:subject><dc:subject>fish</dc:subject><dc:subject>omega-3 supplement</dc:subject><dc:subject>pregnancy</dc:subject><dc:subject>autism</dc:subject><dc:subject>quantitative traits</dc:subject><dc:subject>program collaborators for Environmental influences on Child Health Outcomes</dc:subject><dc:subject>ECHO Components</dc:subject><dc:subject>Coordinating Center</dc:subject><dc:subject>Data Analysis Center</dc:subject><dc:subject>Person-Reported Outcomes Core</dc:subject><dc:subject>ECHO Awardees and Cohorts</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Fishes (mesh)</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Prenatal Exposure Delayed Effects (mesh)</dc:subject><dc:subject>Fatty Acids</dc:subject><dc:subject>Omega-3 (mesh)</dc:subject><dc:subject>Diet (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Autistic Disorder (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Dietary Supplements (mesh)</dc:subject><dc:subject>Seafood (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Child</dc:subject><dc:subject>Preschool (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Maternal Nutritional Physiological Phenomena (mesh)</dc:subject><dc:subject>Autism Spectrum Disorder (mesh)</dc:subject><dc:subject>autism</dc:subject><dc:subject>fish</dc:subject><dc:subject>pregnancy</dc:subject><dc:subject>quantitative traits</dc:subject><dc:subject>ω-3 supplement</dc:subject><dc:subject>Humans (mesh)</dc:subject><dc:subject>Female (mesh)</dc:subject><dc:subject>Pregnancy (mesh)</dc:subject><dc:subject>Fatty Acids</dc:subject><dc:subject>Omega-3 (mesh)</dc:subject><dc:subject>Dietary Supplements (mesh)</dc:subject><dc:subject>Cohort Studies (mesh)</dc:subject><dc:subject>Animals (mesh)</dc:subject><dc:subject>Male (mesh)</dc:subject><dc:subject>Child (mesh)</dc:subject><dc:subject>Adult (mesh)</dc:subject><dc:subject>Autism Spectrum Disorder (mesh)</dc:subject><dc:subject>Seafood (mesh)</dc:subject><dc:subject>Fishes (mesh)</dc:subject><dc:subject>Prenatal Exposure Delayed Effects (mesh)</dc:subject><dc:subject>Child</dc:subject><dc:subject>Preschool (mesh)</dc:subject><dc:subject>Autistic Disorder (mesh)</dc:subject><dc:subject>Diet (mesh)</dc:subject><dc:subject>Maternal Nutritional Physiological Phenomena (mesh)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>11 Medical and Health Sciences (for)</dc:subject><dc:subject>Nutrition &amp; Dietetics (science-metrix)</dc:subject><dc:subject>3202 Clinical sciences (for-2020)</dc:subject><dc:subject>3210 Nutrition and dietetics (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC-ND</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8274g9tp</dc:identifier><dc:identifier>https://escholarship.org/content/qt8274g9tp/qt8274g9tp.pdf</dc:identifier><dc:identifier>info:doi/10.1016/j.ajcnut.2024.06.013</dc:identifier><dc:type>article</dc:type><dc:source>American Journal of Clinical Nutrition, vol 120, iss 3</dc:source><dc:coverage>583 - 592</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt10w575j4</identifier><datestamp>2026-09-15T17:01:06Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt10w575j4</dc:identifier><dc:title>Beam dynamics challenges in linear colliders based on laser-plasma accelerators</dc:title><dc:creator>Schroeder, CB</dc:creator><dc:creator>Benedetti, C</dc:creator><dc:creator>Bulanov, SS</dc:creator><dc:creator>Terzani, D</dc:creator><dc:creator>Esarey, E</dc:creator><dc:creator>Geddes, CGR</dc:creator><dc:date>2022-05-01</dc:date><dc:description>In this paper we discuss design considerations and beam dynamics challenges associated with laser-driven plasma-based accelerators as applied to multi-TeV-scale linear colliders. Plasma accelerators provide ultra-high gradients and ultra-short bunches, offering the potential for compact linacs and reduced power requirements. We show that stable, efficient acceleration with beam quality preservation is possible in the nonlinear bubble regime of laser-plasma accelerators using beam shaping. Ion motion, naturally occuring for dense beams (i.e., low emittance and high energy) severely damps transverse beam instabilities. Coulomb scattering by the background ions is considered and it is shown that the strong focusing in the plasma strongly suppresses scattering-induced emittance growth. Betatron radiation emission from the transverse motion of the beam in the plasma will result in beam power loss and energy spread growth; however for sub-100 nm emittances, the beam power loss and energy spread growth will be sub-percent for multi-TeV-class plasma linacs.</dc:description><dc:subject>5106 Nuclear and Plasma Physics (for-2020)</dc:subject><dc:subject>51 Physical Sciences (for-2020)</dc:subject><dc:subject>Wake-field acceleration (laser-driven</dc:subject><dc:subject>electron-driven)</dc:subject><dc:subject>Beam dynamics</dc:subject><dc:subject>ATAP-BELLA Center (c-lbnl-label)</dc:subject><dc:subject>ATAP-GENERAL (c-lbnl-label)</dc:subject><dc:subject>02 Physical Sciences (for)</dc:subject><dc:subject>09 Engineering (for)</dc:subject><dc:subject>Nuclear &amp; Particles Physics (science-metrix)</dc:subject><dc:subject>40 Engineering (for-2020)</dc:subject><dc:subject>51 Physical sciences (for-2020)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>CC-BY-NC</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/10w575j4</dc:identifier><dc:identifier>https://escholarship.org/content/qt10w575j4/qt10w575j4.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1748-0221/17/05/p05011</dc:identifier><dc:type>article</dc:type><dc:source>Journal of Instrumentation, vol 17, iss 05</dc:source><dc:coverage>p05011</dc:coverage></oai_dc:dc></metadata></record><record><header><identifier>oai:escholarship.org:ark:/13030/qt8vd3s288</identifier><datestamp>2026-09-15T17:00:48Z</datestamp></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>qt8vd3s288</dc:identifier><dc:title>Applying the hierarchy of controls to oil and gas development</dc:title><dc:creator>Deziel, Nicole C</dc:creator><dc:creator>McKenzie, Lisa M</dc:creator><dc:creator>Casey, Joan A</dc:creator><dc:creator>McKone, Thomas E</dc:creator><dc:creator>Johnston, Jill E</dc:creator><dc:creator>Gonzalez, David JX</dc:creator><dc:creator>Shonkoff, Seth BC</dc:creator><dc:creator>Morello-Frosch, Rachel</dc:creator><dc:date>2022-07-01</dc:date><dc:subject>oil and gas development</dc:subject><dc:subject>public health</dc:subject><dc:subject>environmental hazards</dc:subject><dc:subject>risk management</dc:subject><dc:subject>energy extraction</dc:subject><dc:subject>energy extraction</dc:subject><dc:subject>environmental hazards</dc:subject><dc:subject>oil and gas development</dc:subject><dc:subject>public health</dc:subject><dc:subject>risk management</dc:subject><dc:subject>Meteorology &amp; Atmospheric Sciences (science-metrix)</dc:subject><dc:format>application/pdf</dc:format><dc:rights>public</dc:rights><dc:publisher>eScholarship, University of California</dc:publisher><dc:identifier>https://escholarship.org/uc/item/8vd3s288</dc:identifier><dc:identifier>https://escholarship.org/content/qt8vd3s288/qt8vd3s288.pdf</dc:identifier><dc:identifier>info:doi/10.1088/1748-9326/ac7967</dc:identifier><dc:type>article</dc:type><dc:source>Environmental Research Letters, vol 17, iss 7</dc:source><dc:coverage>071003</dc:coverage></oai_dc:dc></metadata></record><resumptionToken expirationDate="2026-09-17T21:27:43Z" cursor="0" completeListSize="564973">oai_dc::500:564973:eyJmaXJzdCI6NTAwLCJiZWZvcmUiOiIyMDI2LTA5LTE2VDE0OjI0OjEyKzAwOjAwIiwiYWZ0ZXIiOiIyMDExLTAzLTE4VDE0OjMyOjQyKzAwOjAwIiwiaW5jbHVkZSI6WyJQVUJMSVNIRUQiLCJFTUJBUkdPRUQiXSwib3JkZXIiOiJVUERBVEVEX0RFU0MiLCJsYXN0SUQiOiJxdDh2ZDNzMjg4IiwibGFzdERhdGUiOiIyMDI2LTA5LTE1VDE3OjAwOjQ4KzAwOjAwIn0</resumptionToken></ListRecords></OAI-PMH>