http://www.rssboard.org/rss-specification 720 https://escholarship.org/uc/ucla_etd/rss Recent eScholarship items from UCLA Electronic Theses and Dissertations Tue, 9 Jun 2026 01:50:28 +0000 https://escholarship.org/uc/item/8sc4388b The evolution of computing has transitioned from specialized analog mechanisms to general-purpose digital systems, culminating in the current dominance of data-driven deep learning. While effective, these models often suffer from prohibitive computational costs, lack of interpretability, and heavy reliance on massive training datasets. This dissertation presents a paradigm shift toward physics-inspired computing, where established physical laws serve as structural priors for algorithmic design. Rooted in the principles of Photonic Time Stretch (PTS), this research develops PhyCV (Physics-inspired Computer Vision), a library of algorithms that translate optical phenomena into digital image processing tasks. The core contribution of this work is the development and optimization of VEViD (Vision Enhancement via Virtual Diffraction and Coherent Detection), a physics-inspired algorithm for low-light enhancement. VEViD reimagines digital images as spatially varying light fields subject... https://escholarship.org/uc/item/8sc4388b Mon, 8 Jun 2026 00:00:00 +0000 Gunawan, Wesley https://escholarship.org/uc/item/7zr7p2b6 The Jovian moons Europa and Ganymede host subsurface oceans beneath their water-ice shells, and are therefore prime targets in the search for habitability beyond Earth. These oceans were discovered by meticulous analysis of the magnetometer data returned from the Galileo spacecraft. The interpretation of the magnetometer observations require a near-surface electrically conductive layer to react to Jupiter’s time varying magnetic field and produce the moons' induced secondary magnetic field. The recently launched European Space Agency’s (ESA) JUICE and NASA’s Europa Clipper missions will reach the Jovian system in the early 2030s with upgraded magnetometers. The aim of this dissertation is to prepare for the arrival of this finer-scale geophysical data, so it is ready to be interpreted in terms of the properties of the moons' interior, especially their ice-ocean hydrospheres. Here we present a series of studies addressing the properties of the moons’ interiors, in preparation... https://escholarship.org/uc/item/7zr7p2b6 Mon, 8 Jun 2026 00:00:00 +0000 Psarakis, Catherine Anne https://escholarship.org/uc/item/7x2930hj Blueprints: 11918 is a collection of miniatures inspired by family and home – a sincere labor of love. As my parents designed and built our home, I had the opportunity to experience this ambitious undertaking firsthand! The title originates from the architectural concept of a blueprint: a technical drawing, illustrating DNA of a designed space. Having an architect as a father means space is always a relevant conversation. It's about how we occupy space – those who live, breathe, and create in the space – and continually questioning what turns a house into home. Each movement offers glimpses into the unique personalities within my home, and each person’s motif was composed by applying his/her name to an “alphabet-to-musical-pitch” cypher I created. Further, there are seven letters in KAITLIN, and seven total possible combinations of the ensemble of this work: two violins and two pianos, solo violin, violin and piano, etc. This piece uses all combinations of this ensemble... https://escholarship.org/uc/item/7x2930hj Mon, 8 Jun 2026 00:00:00 +0000 Webster-Zuber, Kaitlin Rose https://escholarship.org/uc/item/9vb6g1d2 Coccidioidomycosis, also known as valley fever, is a fungal pathogen endemic to the Americas that kills thousands annually, yet the host factors that lead to increased risk of life-threatening dissemination of coccidioidomycosis, remain poorly understood. We assembled the largest, comprehensively sequenced coccidioidomycosis cohort to date, comprising 795 individuals with laboratory confirmed coccidioidomycosis and clinical disease severity phenotyping, many with paired whole blood genomic and transcriptomic data. Individuals with greater than 50% African genetic ancestry are significantly enriched in disseminated coccidioidomycosis (DCM) cases (OR=13.37, p=1.08×10⁻¹⁸), reflecting ancestry-associated differences in allele frequencies at immune loci. Transcriptomic profiling (n=267) revealed upregulation of interferon inducible genes IFI44 and IFI44L, the fungal recognition receptor CLEC4D, and pro-inflammatory protein S100A12, with sex specific expression differences in immune... https://escholarship.org/uc/item/9vb6g1d2 Fri, 5 Jun 2026 00:00:00 +0000 Jensen, Samantha Lee https://escholarship.org/uc/item/9bz0m4nm What do I know when I know someone and how do I know it? This dissertation is an answer to this question. Whereas I do not need to talk to someone in order to know about them, knowing someone essentially involves talking to them. If having a conversation with someone is how I get to know them, then my knowledge of someone is not the knowledge I have about them but rather is my knowledge of what I can do with them. Following G.E.M. Anscombe, we know that practical knowledge is the knowledge I have of what I am doing. In this dissertation, I show how my practical knowledge of the conversation I am having with someone is my knowledge of that person insofar as this is how I am getting to know them. https://escholarship.org/uc/item/9bz0m4nm Fri, 5 Jun 2026 00:00:00 +0000 Sindhu, Sahiba Kaur https://escholarship.org/uc/item/8176j13r “Amour de soi – the Stanchion of Sixties Soul Sovereigns Sam Cooke, Aretha Franklin, and Tina Turner” argues that the career accomplishments of these musical artists exemplified Rousseau’s concept, amour de soi as they took a leap of faith and led the soul music genre. The mid-twentieth century music business was fraught with pitfalls, risks, as well as powerful, unscrupulous, and even some very dangerous participants. Attributes of courage, discipline, and faith were indispensable qualities for those artists who struggled to survive the exigencies of an industry with historical affiliations with sex work and organized crime. Female artists faced sexism, misogyny, and the danger of sexual assault in this field dominated by men. African American artists encountered additional obstacles presented by racist music moguls. This project examines the history of the music industry and the racism present in locations relevant to the lives and careers of Cooke, Franklin, and Turner. In... https://escholarship.org/uc/item/8176j13r Fri, 5 Jun 2026 00:00:00 +0000 Kilman, Sandra https://escholarship.org/uc/item/74k2b86h The Metaverse is widely understood as a persistent, shared, immersive virtual space that integrates physical and digital realities. As the Internet evolves toward this paradigm, the convergence of spatial computing and machine learning is reshaping human-computer interaction. The resulting ecosystem rests on two complementary capabilities: a spatial interaction layer that captures continuous, embodied user kinematics, and a cognitive intelligence layer that synthesizes this data through predictive and generative models. Together they enable immersive experiences but also introduce system-level risks. Without careful design, the Metaverse may evolve into a pervasive sensing and inference infrastructure with expanded attack surfaces, opaque data practices, and entrenched centralization across both the spatial and cognitive layers. This dissertation reexamines the security and privacy foundations of Metaverse applications around this dual-pillar architecture. Rather than relying... https://escholarship.org/uc/item/74k2b86h Fri, 5 Jun 2026 00:00:00 +0000 Cai, Kunlin https://escholarship.org/uc/item/5wk30237 There is considerable heterogeneity in the expressive language development of autistic individuals across the lifespan. Some children score in the average (or even above average) range on language or vocabulary tests but exhibit more nuanced or subtle semantic and pragmatic language difficulties. At the other end of the continuum, a significant subset of the autistic population – estimated at around 30% – do not acquire functional expressive language, even after intensive interventions. Another approximately 40% of autistic individuals fall somewhere in between these endpoints. The heterogeneity in rate of language development and linguistic outcomes is not well understood. Furthermore, variable methods of expressive language measurement have complicated comparisons across autistic samples. The current study characterized trajectories of expressive language from ages 2 to 25 years and analyzed the influence of receptive language (as opposed to aspects of nonverbal cognition, such... https://escholarship.org/uc/item/5wk30237 Fri, 5 Jun 2026 00:00:00 +0000 Byrne, Katherine https://escholarship.org/uc/item/4c61q3cx Exposure to toxic metals during childhood can adversely affect neurodevelopment and long-term health. Food insecurity may serve as an indicator of broader structural and environmental inequities that influence patterns of metal exposure. This study examined associations between household food security and blood concentrations of lead (Pb), cadmium(Cd), total mercury (THg), and methyl mercury (MeHg) among U.S. children and adolescents ages 1 to 19 using National Health and Nutrition Examination Survey (NHANES) 2017 to 2023 data. Survey weighted regression models estimated adjusted associations, and dietary factors were explored as potential co-factors or exposure pathways. Blood lead concentrations were modestly higher among children from households with lower food security, although associations were not statistically significant. Cadmium concentrations were similar across food security categories. In contrast, THg and MeHg concentrations were 10-15% lower among children experiencing... https://escholarship.org/uc/item/4c61q3cx Fri, 5 Jun 2026 00:00:00 +0000 Campa, Isabella https://escholarship.org/uc/item/3qq1117g Background: Oversedation in mechanically ventilated patients in the Intensive Care Unit (ICU) is associated with adverse outcomes, including delirium, prolonged mechanical ventilation, and longer length of stay. Despite guidelines recommending light, goal-directed sedation, typically defined as a Richmond Agitation-Sedation Scale (RASS) target of −2 to 0, sedation practices and documentation remain variable at the bedside. Objectives: To evaluate the impact of the Oversedation Zero tool, a structured, consensus-based bundle, on nurses’ sedation knowledge, attitudes, and documentation practices in a mixed medical-surgical ICU. Methods: A pre–post quality improvement (QI) project was conducted over an eight-week period in a mixed medical-surgical ICU. The intervention included brief huddle-based education, visual reinforcement tools, and ongoing support from the project lead. Outcomes were measured using a sedation knowledge questionnaire, the Nurse Sedation Practices Scale (NSPS),... https://escholarship.org/uc/item/3qq1117g Fri, 5 Jun 2026 00:00:00 +0000 Orosco, Cinthia https://escholarship.org/uc/item/1vk4130r This thesis proposes a hybrid spatiotemporal modeling framework to address the limitations of traditional machine learning methods in capturing localized "neighbor effects" during the process of Electric Vehicle (EV) diffusion. Although the rate of EV adoption in the United States has accelerated significantly, passing 10% in 2023, growth remains highly heterogeneous across states. Utilizing a national dataset spanning all 50 U.S. states from 2018 to 2023, this study comparatively evaluates the predictive performance of the XGBoost model against a hybrid model incorporating Sequential Gaussian Simulation (SGS) techniques. The standalone XGBoost model achieved an R2 value of 0.70 on the 2023 test set and identified infrastructure density, socioeconomic fundamentals, policy and political environments, and environmental psychological characteristics as the primary drivers of EV adoption. Furthermore, a Global Moran’s I analysis revealed that, beginning in 2021, spatial autocorrelation... https://escholarship.org/uc/item/1vk4130r Fri, 5 Jun 2026 00:00:00 +0000 Xia, Ningze https://escholarship.org/uc/item/1ns8r6fv This study evaluates the effectiveness of pretrained transformer-based language models, DistilBERT and XLNet, for predicting categorical Yelp review ratings from text. Using datasets derived from the Yelp Open Dataset, the study examines model performance under varying class imbalance conditions and experimental configurations, including raw baseline, class weighting, and binary classification. The results show that pretrained language models significantly outperform the Random Forest baseline across all tasks. XLNet consistently achieves higher performance than DistilBERT, particularly in multi-class classification. However, both models exhibit reduced effectiveness in imbalanced multi-class settings, especially for intermediate classes. Performance improves substantially when the task is simplified to binary classification, while class weighting provides limited benefit. Additionally, the models demonstrate stable performance across state-level datasets, indicating strong geographic... https://escholarship.org/uc/item/1ns8r6fv Fri, 5 Jun 2026 00:00:00 +0000 Halabi, Ayah https://escholarship.org/uc/item/9p4160zz Link Floer homology is an invariant of knots and links by Ozsv´ath-Szab´o with many powerful applications. Recently, Manolescu-Sarkar constructed a stable homotopy type for the “hat version” of link Floer homology, which is equipped with stable homotopy invariants which are conjectured to contain additional information compared to link Floer homology.In this dissertation, we give an algorithm to compute second the Steenrod square Sq2 for link Floer homology. In order to do so, we use the grid homology formulation of link Floer homology due to Manolescu-Ozsv´ath-Sarkar to explicitly compute the framings of the lowdimensional moduli spaces used in the Manolescu-Sarkar construction.In the meantime, we also extend the Manolescu-Sarkar construction to the more full link Floer complex CFK + , though for this “plus version” the stable homotopy type is not known. In the plus version, we obtain a framed 1-flow category, which is a construction by LobbOrson-Sch¨utz which contains enough... https://escholarship.org/uc/item/9p4160zz Thu, 4 Jun 2026 00:00:00 +0000 Tao, Yan https://escholarship.org/uc/item/9hq8c8qh The rise of antibiotic resistance necessitates developing alternative treatments with minimal potential for bacterial adaptation. Two promising solutions include membrane-disruptive polymers and phage therapy, which utilizes viruses specific to bacteria, but they face opposite shortcomings; many polymers lack specificity for bacterial cells, resulting in poor biocompatibility, while phages are restricted to a very narrow host range. In this dissertation, we aim to circumvent each agent’s individual shortcomings through the synergistic approach of engineering the non-lytic M13 bacteriophage into a polymer delivery platform. Our first goal was to modify M13 bacteriophage, which normally infects Escherichia coli, to target the pathogenic bacteria Staphylococcus aureus. We expressed an antibody fragment specific to a conserved surface polysaccharide, poly-N-acetylglucosamine, on the receptor-binding protein. Successful binding of the anti-PNAG phage was quantified through enzyme-linked... https://escholarship.org/uc/item/9hq8c8qh Thu, 4 Jun 2026 00:00:00 +0000 Vexler, Shelby https://escholarship.org/uc/item/9ch8s24n The Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) lander is a stationary lander located on Elysium Planitia that returned the first magnetometer data from the Martian surface. Arriving in November 2018, InSight observed the repeated occurrence of ultra-low frequency (ULF) electromagnetic waves during the nighttime. While ULF waves had been observed extensively in planetary magnetospheres throughout the solar system, including Mars, their common existence on the surface of Mars was not expected. In this dissertation, we embark on a journey to connect the observations of ULF waves on the surface with their origins throughout the Martian space environment.We catalog 444 nighttime ULF wave events throughout the InSight mission duration. The characteristic frequencies range from 1 mHz to 16 mHz, with a median frequency of about 7 mHz. ULF wave activity is found across all nighttime hours, but the activity is more commonly observed after midnight... https://escholarship.org/uc/item/9ch8s24n Thu, 4 Jun 2026 00:00:00 +0000 Webster, Kyle https://escholarship.org/uc/item/96d0f2r6 This dissertation examines how Caribbean popular music (CPM) facilitates pluralistic identity construction in New York City's West Indian diaspora. Utilizing narrative ethnography, census data, and a multidisciplinary literature review, I argue that Afro-West Indian communities use CPM styles—specifically Jamaican dancehall and Trinibagonian soca—as musical contact zones for transcultural identity construction. Despite substantial scholarship on Caribbean American migration, musical taste formation, and music’s role in identity construction, no critical analysis addresses music-making as a site for transcultural engagement in U.S.-based Afro-West Indian communities. Drawing on diaspora, postcolonial, and transcultural studies, my work addresses this gap by situating Afro-West Indian musico-cultural practices within transcultural identity construction discourse.My work employs the Pluralized Identity model, an anti-essentialist framework I developed to conceptualize the imaginary... https://escholarship.org/uc/item/96d0f2r6 Thu, 4 Jun 2026 00:00:00 +0000 Rhodd-Lee, Holland https://escholarship.org/uc/item/9405r7n6 Proving statements about small subsets of a large database, and in particular proving the correct execution of RAM programs on committed databases when the running time is sublinear in the size of the database, is a problem of substantial practical interest. Indeed, most real-world computations are naturally expressed as RAM algorithms in high-level programming languages such as C/C++, Python, and Rust. Efficient solutions to this problem have applications in searching data structures, sequence matching, such as for genomic data or blockchains, statistical analysis, secure inference, and proofs of training. Motivated by this goal, we introduce and study the notion of projection codes. A standard error-correcting code allows one to encode a message x into a codeword X, such that even if a constant fraction of X is corrupted, the message x can still be recovered. A projection code extends this guarantee to any subset of the bits of x. Concretely, for every projection of x... https://escholarship.org/uc/item/9405r7n6 Thu, 4 Jun 2026 00:00:00 +0000 Shah, Akash Amritlal https://escholarship.org/uc/item/8t59q83r This qualitative study examined the preparedness of K-12 public charter school principal leaders in Georgia and how they understood their role in ensuring schools’ academic, fiscal, and operational success while navigating challenges that can contribute to school closure. Grounded in Maslow’s hierarchy of needs and systems theory, the study explored how principals’ lived experiences shaped their ability to fulfill required responsibilities and the supports available to sustain their work. The study examined leaders’ educational backgrounds, experiences in charter and traditional public schools, student populations, facilities, and whether schools operated as standalone or network charter schools. It further investigated principals’ preparedness across key operational domains, including financial management, human resources, curriculum, community engagement, special education, staff support, enrollment, and teacher professional development. Drawing on survey data from 20 participants... https://escholarship.org/uc/item/8t59q83r Thu, 4 Jun 2026 00:00:00 +0000 Smith, Virginia Frine https://escholarship.org/uc/item/8q04g03w A traumatic brain injury (TBI) is a condition in which normal brain function is disrupted because of an external force which impacts the head. There are three main types of TBI: mild, moderate, and severe, with sports-related concussions (SRC) being a subcategory of mild cases. Mild TBI and sports-related concussions often involve slowed processing speed, attention deficits, difficulty recalling memories, trouble sleeping, and mood swings. On the other hand, moderate-to-severe cases involve more pronounced brain damage leading to challenges with language, executive function, memory loss, and in many cases, death. In the United States alone, TBI is the cause of over 5.3 million individuals living with a disability and each year an additional 1.7 million Americans also suffer across their lifespan, especially vulnerable groups, such as youth and older adults. Moderate-to-severe TBI leads to about 52,000 deaths each year in the United States alone, making it the main result of injury-induced... https://escholarship.org/uc/item/8q04g03w Thu, 4 Jun 2026 00:00:00 +0000 Ashikyan, Sonya https://escholarship.org/uc/item/88m0p4tg High-power electric propulsion systems are increasingly used for spacecraft station-keeping, orbital transfer, and deep-space missions, yet their ground-based qualification relies on measurements performed inside vacuum facilities. In these facilities, energetic plume species interact with chamber walls and diagnostic surfaces, producing electron emission that can modify plasma sheaths, alter local charge balance, and contribute to facility effects. While electron-induced secondary electron emission has been widely studied for relevant materials and energy ranges, ion-induced electron emission from low-energy propellant ions incident on facility-relevant surfaces remains comparatively under-characterized, particularly in the energy regime relevant to electric propulsion ground testing. This dissertation investigates ion-induced electron emission from facility wall materials during electric thruster testing. A physics-based computational framework is developed to describe... https://escholarship.org/uc/item/88m0p4tg Thu, 4 Jun 2026 00:00:00 +0000 FERNANDEZ-COPPEL VELASCO, JORGE https://escholarship.org/uc/item/7t74j65q Like many vernacular kana texts of the Heian period (794–1185), the writing of Kagerō nikki (ca. 972-974) is predicated on correspondence as the essential mode of informal writing for men and women. The records of poetry composition and exchange throughout Michitsuna’s Mother’s (935–995) diary emphasize how correspondence between figures in the aristocratic social world of the Imperial capital and across geographies in the material world of the Heian realm utilized epistolary and poetic conventions to negotiate for real-world benefits, play with literary convention, and experiment with vernacular forms of individual expression. Moreover, Kagerō’s autobiographical narrative of these exchanges reveals how the abstract, discursive spaces in which the social, political, and literary intersect: Letters, poems, and the messengers who carry them traverse the geographic, social, gendered, and ritual spaces of the Heian capital and beyond, and the poetic content of these missives takes... https://escholarship.org/uc/item/7t74j65q Thu, 4 Jun 2026 00:00:00 +0000 Price, Deborah Alexis https://escholarship.org/uc/item/7qc4j8ch Needle-based ophthalmic procedures require precise interaction with soft, deformable tissues under limited visualization, depth perception, and tactile feedback. In applications such as vascular cannulation and subretinal injection, success depends not only on accurate positioning, but also on reliable tissue penetration, confirmation of access, and safe response to failure. These challenges motivate robotic systems that can combine precise motion with intraoperative sensing and feedback at the tool--tissue interface. This dissertation presents robotic methods for safe, reliable, and repeatable needle access in ophthalmic procedures. First, a multimodal robotic framework is developed for vascular cannulation using microscope imaging, optical coherence tomography (OCT), and pressure sensing. The system localizes the vessel, aligns the needle, confirms successful access, detects failure modes, and enables reset-and-retry behavior. Bidirectional axial needle rotation is introduced... https://escholarship.org/uc/item/7qc4j8ch Thu, 4 Jun 2026 00:00:00 +0000 Foroutani, Yasamin https://escholarship.org/uc/item/7kk4x9n0 his thesis presents a Raman spectroscopy study of Bi4I4, a quasi-one-dimensional van der Waals material that exhibits two crystallographically similar polymorphs with distinct topological insulating phases. These α and β phases are separated by a first-order structural transition near room temperature, which occurs without a change in space group and is associated with a subtle rearrangement of chain stacking registry. The Raman-active phonon modes were investigated using polarization- and angle-resolved micro-Raman spectroscopy with 633 nm and 488 nm excitation sources. Rotation of the crystal relative to the incident polarization enabled the identification of the dominant ?? and ?? vibrational symmetries through their characteristic angular intensity modulation arising from Raman tensor selection rules. A complex Raman tensor formalism was used to describe deviations from the ideal angular response, accounting for absorption-induced phase effects in this anisotropic material.... https://escholarship.org/uc/item/7kk4x9n0 Thu, 4 Jun 2026 00:00:00 +0000 Thiruthukkal Puthenveettil, Nidhish https://escholarship.org/uc/item/7158c793 Plant-derived virus-like particles (VLPs) can self-assemble and package non-native, therapeutic RNAs, making them promising platforms for RNA delivery. However, the rational design of VLPs for therapeutic use depends on understanding the physical and chemical principles that govern self- assembly across different viral platforms. This thesis investigates the limits of viral self-assembly across three plant virus platforms: Cowpea Chlorotic Mottle Virus (CCMV), Brome Mosaic Virus (BMV), and Tobacco Mosaic Virus (TMV). Chapter 2 investigates the effect of a single surface mutation of alanine to cysteine on CCMV capsid assembly. While the mutation is useful for site-specific conjugation of targeting ligands, it impairs assembly efficiency, with most of the mutant capsid protein forming incomplete, aggregated structures. A gel electrophoresis framework is developed to quantify mutant subunit incorporation into mixed wild type/mutant VLPs, demonstrating that the number of incorporated... https://escholarship.org/uc/item/7158c793 Thu, 4 Jun 2026 00:00:00 +0000 Harpell, Nina Miranda https://escholarship.org/uc/item/6wx946c7 Deep learning has seen remarkable advancements in machine learning, yet it often demands extensive annotated data. In healthcare, vast clinical datasets are available, yet several barriers limit their use for training medical deep learning models, including privacy constraints, noisy or missing clinical annotations, and imperfect label extraction methods. These challenges slow both research progress and real-world deployment. In my PhD, I explore active learning and various forms of weak supervision to reduce annotation cost while preserving model performance. I then apply what we learned to emerging problems in medical AI, demonstrating strong performance relative to clinicians and highlighting the feasibility of developing low-cost, clinically useful medical foundation models. https://escholarship.org/uc/item/6wx946c7 Thu, 4 Jun 2026 00:00:00 +0000 Vepa, Arvind Murari https://escholarship.org/uc/item/6sp2d3ds Transitioning from high school to adulthood presents unique challenges for students with disabilities, particularly given the abrupt end of school-based services upon graduation or aging out. Despite federal mandates under the Individuals with Disabilities Education Act (IDEA, 2004) to support postsecondary transition, students with disabilities continue to lag behind their peers without disabilities in postsecondary engagement, college enrollment, and employment. This study examined demographic characteristics and in-school experiences as predictors of three postsecondary outcomes: postsecondary engagement, college enrollment, and competitive employment among high school leavers with disabilities in a large, diverse urban school district in Southern California. Using special education administrative records spanning 2008 to 2019, this cross-sectional study analyzed data from 13,823 students with documented postsecondary outcomes within one year of exiting high school. Multilevel... https://escholarship.org/uc/item/6sp2d3ds Thu, 4 Jun 2026 00:00:00 +0000 Kim, Eunice Kunyoung https://escholarship.org/uc/item/6s57d0fk Why do Latinos who face no personal risk of deportation mobilize politically in response to anti-Latino rhetoric and immigration enforcement? This dissertation argues the answer lies in a distinction existing frameworks have overlooked: the difference between anxiety experienced as an individual and anxiety experienced as a member of a group. Group-based anxiety, appraised as a collective threat to one's racial and ethnic community rather than a personal vulnerability, generates fundamentally different behavioral consequences than individually experienced anxiety, producing action tendencies oriented toward collective engagement rather than individual avoidance.Drawing on appraisal theory and intergroup emotions theory, I develop the Racialized Group Anxiety framework, which specifies a causal pathway through which racialized political threat produces collective political mobilization among racially marginalized groups, tested here among Latino adults in the United States. The... https://escholarship.org/uc/item/6s57d0fk Thu, 4 Jun 2026 00:00:00 +0000 Alegre, Claudia https://escholarship.org/uc/item/6hv4n9b4 The imperial and late antique periods saw a proliferation of commentary-writing in various communities, including among the early Christians and the Neoplatonists. While these commentaries have been studied independently of each other, the present investigation identifies and explores methodological similarities between the two traditions. In particular, it analyzes Origen’s Commentary on John and Proclus’ Commentary on Plato’s Timaeus as representative and innovative exegetical works with the aim of identifying common interpretative methodologies. Both authors use a multi-layered allegorical approach to their texts, in which the literal or historical meaning of the text is generally set aside in favor of a deeper theological meaning. The use of allegory and the claim to divine inspiration allow both commentators to exercise control over the meaning of the text (Chapter 1). Furthermore, both authors conceive of similar goals for their work, including preserving the supposed original... https://escholarship.org/uc/item/6hv4n9b4 Thu, 4 Jun 2026 00:00:00 +0000 Gram, Zakarias Dimitri https://escholarship.org/uc/item/6b82r5b3 Electroencephalography (EEG) recordings arise as a noninvasive and low-cost clinical imaging technology for monitoring brain development, facilitating earlier and more effective interventions. Their analysis, however, presents a rich set of statistical challenges due to the complex structure of the data, requiring methodological tools that preserve the underlying geometry of the observations. Motivated by the study of autism, this dissertation develops novel Bayesian methodology to address shape and phase heterogeneity in EEG power spectral densities. The proposed models focus on functional and distributional data analysis techniques aimed at identifying and quantifying biomarkers associated with autism. Chapter 2 introduces warped functional mixed membership models. Existing approaches for handling misalignment in functional observations typically assume that the data is governed either by a single common shape or by a finite mixture of population-level shapes. We instead propose... https://escholarship.org/uc/item/6b82r5b3 Thu, 4 Jun 2026 00:00:00 +0000 Landry, Emma Valentine Marie https://escholarship.org/uc/item/6b0538wt This thesis investigates the dynamics of area-preserving anisotropic mean curvature flow in the plane, with a particular emphasis on long-time behavior. The evolution is a gradient flow of the anisotropic surface energy and is thus expected to converge to a critical point. We study the flat flow solution in two regimes: smooth elliptic and crystalline anisotropies. In both regimes, we establish the unconditional exponential convergence of bounded initial data to a disjoint union of Wulff shapes. In the smooth elliptic setting, we also prove that certain reflection comparison symmetries are preserved under the flow, allowing us to specify further constraints on the convergent profile depending on the initial data. In the crystalline setting, we show that the flat flow solution coincides with a classical ODE evolution for regular initial data, which further implies the eventual regularity of the flat flow for arbitrary initial data. Our analysis mainly adopts variational perspectives,... https://escholarship.org/uc/item/6b0538wt Thu, 4 Jun 2026 00:00:00 +0000 Kim, Eric https://escholarship.org/uc/item/65m1j2wd The successful development of future space-based infrared mirrors requires agile manufacture of high-quality mirrors. Aluminum has been identified as an ideal mirror material for these applications due to the speed of manufacturing and resulting mirror quality. However, traditionally manufactured aluminum mirrors suffer from low mirror efficiency and thermal distortion. Laser-powder bed fusion (L-PBF) of aluminum mirrors can improve performance through stiffness-optimized structures, integrated iso-thermalization, and novel alloys. This dissertation investigates the mechanisms controlling the diamond turning performance of L-PBF modified aluminum alloys and identifies critical factors affecting the capillary performance to produce the next generation of highly reflective, isothermal aluminum mirrors.The first part of this work focuses on understanding the critical factors controlling mirror performance in nucleation-modified, additively manufactured (AM) 7xxx-series aluminum alloys.... https://escholarship.org/uc/item/65m1j2wd Thu, 4 Jun 2026 00:00:00 +0000 Lohser, Julian Rydale https://escholarship.org/uc/item/63t1d6b6 Forensic investigations increasingly rely on genomic and epigenomic analyses to extract identifying information from complex biological evidence. Advances in forensic DNA technologies have enabled the interpretation of mixed DNA profiles from multiple contributors and the estimation of chronological age from trace biological samples. However, these approaches depend on statistical frameworks that must account for substantial biological and technical variability. A central challenge is that forensic models may exhibit systematic inaccuracies or biases when underlying assumptions fail to capture the complexity of human genetic and epigenetic variation. Understanding these limitations is critical for improving the reliability and equity of forensic methodologies. In chapter 2, we investigate the accuracy of forensic DNA mixture interpretation across human genetic variation. Using simulated DNA mixtures generated from allele frequency distributions representing 83 human groups, we... https://escholarship.org/uc/item/63t1d6b6 Thu, 4 Jun 2026 00:00:00 +0000 Flores, Maria https://escholarship.org/uc/item/5s40333s This dissertation consists of two essays on dynamic game theory and mechanism design.The first chapter studies the credibility of optimal deadlines when a principal and an agent jointly contribute to a project of uncertain duration. The agent is privately informed about how quickly the project is likely to succeed and is more eager than the principal to start and continue. Deadlines can screen out projects unlikely to pay of soon, which the principal would rather not undertake. But deadlines may fail to be credible: once one expires without success, the principal may prefer to extend it, and the agent may anticipate this when deciding whether to start, harming the principal. I study when optimal deadlines are credible and when the ability to commit makes a difference. If the project’s hazard rate is always decreasing, as in a Poisson good-news environment, commitment has no value. With more general unimodal hazard rates, optimal deadlines may fail to be credible; lack of commitment... https://escholarship.org/uc/item/5s40333s Thu, 4 Jun 2026 00:00:00 +0000 Magganas, Aristotle https://escholarship.org/uc/item/53w7q39v Lithium-ion batteries have become the dominant energy storage technology for portable electronics and electric vehicles, thanks to their high energy density and long cycle life, but growing global demand for sustainable, large-scale storage has revealed their limitations. Key challenges include lithium scarcity, rising costs, safety risks from flammable organic electrolytes, and environmental concerns. Aqueous zinc-based batteries have emerged as promising candidates for safe and cost-effective energy storage, benefiting from the intrinsic nonflammability of water-based electrolytes, the natural abundance of zinc, and the high theoretical capacity of Zn metal. Despite their great potential, this technology remains underdeveloped for practical use. To address the limitations, the development and improvement of all facets of a Zn-based energy storage systems is discussed in this dissertation.First, a 3D-printed flooded electrochemical test cell is presented as an alternative to... https://escholarship.org/uc/item/53w7q39v Thu, 4 Jun 2026 00:00:00 +0000 Uemura, Sophia Kanani https://escholarship.org/uc/item/4rb0g9jn Atomistic simulations like molecular dynamics are essential tools for studying materials at the scale of individual atoms. Their usefulness depends on two things: the quality of the interatomic potential used to compute properties, and the efficiency with which simulations can be run. As machine-learned interatomic potentials become more common, simulation workflows increasingly need to connect model development with downstream material properties, many of which are not used as training labels and require running simulations. A second challenge is computational throughput: existing simulation workflows often run these systems one at a time, leaving modern accelerator hardware underused.This dissertation addresses these needs through differentiable and batched atomistic simulation. The first part develops methods for differentiating simulation outputs with respect to interatomic-potential parameters. This makes it possible to train potentials using material properties beyond energies... https://escholarship.org/uc/item/4rb0g9jn Thu, 4 Jun 2026 00:00:00 +0000 Gangan, Abhijeet https://escholarship.org/uc/item/4fn6w88f Adolescence is a critical period of development during which the brain undergoes massive reorganization. Excess synapses are pruned away, and key synapses are refined resulting in improved cognitive control, increased reward seeking behavior, and changes in decision making circuitry. Activation in the ventral striatum (VS) is known to peak during adolescence while the ventromedial prefrontal cortex (vmPFC) displays a delay in maturation in relation to subcortical regions. However, little is known about the functional connectivity (FC) among these key brain regions and how their coupling with other brain regions changes across time. Additionally, adolescence is also a time during which the emergence of anxiety disorders becomes increasingly prevalent and can have a negative impact on the development of regions such as the VS and vmPFC and their connectivity. Thus, this dissertation aimed to understand VS and vmPFC whole brain FC during cautious and risky decision making longitudinally... https://escholarship.org/uc/item/4fn6w88f Thu, 4 Jun 2026 00:00:00 +0000 Smith, Charles https://escholarship.org/uc/item/3s41v0pm This doctoral thesis links three different authors writing about motherhood in Argentina, Brazil, and Colombia to analyze how women writers throughout Latin America are representing the institution of motherhood. By focusing on the dissonance between institutional motherhood and individual mothering, this dissertation explores how women produce and reproduce knowledge about motherhood, an institution that interpellates them as gendered subjects. Specifically, this dissertation explores how women strategically appropriate, reject, and subvert patriarchal motherhood, paying close attention to their unexamined expectations and the moments of negotiation that unsettle them.The principal objects of analysis include Clarice Lispector’s Laços de Família, Pilar Quintana’s La perra, and Camila Sosa Villada’s Las malas. These texts use motherhood as a site of discursive identification wherein larger institutions are navigated, subverted, or reinforced. To ground the texts in their... https://escholarship.org/uc/item/3s41v0pm Thu, 4 Jun 2026 00:00:00 +0000 Jaramillo, Brenda Saraí https://escholarship.org/uc/item/3mg258g7 Background: New-graduate psychiatric-mental health nurse practitioners (PMHNPs) often begin practice without structured mentorship, contributing to role stress, reduced clinical confidence, and early turnover.Objectives: To evaluate a structured, virtual group mentorship program for new-graduate PMHNPs and examine feasibility, acceptability, and preliminary changes in self-rated competence, job stress, job satisfaction, and intent to stay.Methods: This single-group, pretest-posttest professional development program enrolled 10 PMHNPs with fewer than 12 months of experience who practiced in Southern California. Participants completed an 8-week virtual mentorship program delivered via Kajabi. Weekly 60-minute sessions led by an experienced PMHNP integrated case-based clinical reasoning and facilitated peer support. Outcomes measured at baseline and week 8 included perceived role competence, job satisfaction, perceived stress, retention intent, and program feedback. Non-parametric... https://escholarship.org/uc/item/3mg258g7 Thu, 4 Jun 2026 00:00:00 +0000 Sanchez, Alexander https://escholarship.org/uc/item/3gj1d7jk Background: Immune-based combination therapies (IBCTs), which are combinations of immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs), have transformed the treatment of metastatic renal cell carcinoma (mRCC) and have substantially improved survival outcomes. As survival for patients with metastatic cancer continues to increase, there is growing recognition that treatment-related burdens extend beyond traditional physical toxicities. In particular, the financial burden and healthcare time demands associated with modern mRCC therapies remain poorly understood.Methods: This dissertation used a retrospective cohort design utilizing the Merative MarketScan Commercial Claims databases to evaluate adults initiating systemic therapy for newly diagnosed mRCC between 2014 and 2023. Three aims were addressed: (1) to characterize the uptake and dissemination of IBCT over time and identify factors associated with treatment receipt, (2) to evaluate the association between... https://escholarship.org/uc/item/3gj1d7jk Thu, 4 Jun 2026 00:00:00 +0000 Baclig, Nikita Vashi https://escholarship.org/uc/item/3cp0q1hj Artificial intelligence has the potential to dramatically reshape how we teach, learn, and generate knowledge, and indeed is already doing so. As teachers, designers of academic programs and standards, and educational administrators seek to grapple with the novel challenges and opportunities posed by this technology, a thorough understanding of the changing practices of teacher education program (TEP) faculty can provide a roadmap to intentional program design. This is a mixed-methods study with a convergent design, using UTAUT2 as a lens, wherein TEP faculty at a local 4-year university were surveyed and interviewed to investigate their perceptions, changing practices, and support needs.The data show this population being characterized by general belief that lessons on AI would be beneficial for their students, and high intent on doing so, but lagging follow-through into actual implementation, which is primarily an issue of establishing new pedagogical habits. Those faculty who... https://escholarship.org/uc/item/3cp0q1hj Thu, 4 Jun 2026 00:00:00 +0000 Carroll, Ian Michael https://escholarship.org/uc/item/3943b6r6 This dissertation develops majorization–minimization (MM) algorithms for structured optimization models arising in image registration and sequential image reconstruction, clustering, graph embedding, and matrix equations with applications in computational biology and biomedical data analysis. Neuroimage registration and histological reconstruction are essential for building three-dimensional brain volumes, aligning time-series images, and mapping biological data into common coordinate systems. However, these tasks are complicated by high dimensionality, nonconvexity, image artifacts, and the need for accurate and robust optimization. To address pairwise neuroimage registration, we propose a gradient-independent rigid-motion algorithm that avoids step-length selection and improves performance over gradient descent on simulated and mouse brain microscopy images. To address sequential neuroimage alignment and reconstruction, we extend the MM framework to estimate 3D reconstructed... https://escholarship.org/uc/item/3943b6r6 Thu, 4 Jun 2026 00:00:00 +0000 Zhou, Gaiting https://escholarship.org/uc/item/3099h15f This dissertation develops and applies advanced quantitative magnetic resonance imaging pipelines to investigate functional and structural tissue adaptations in two complex clinical applications; obstetrics and oncology. The overarching objective is to bridge the gap between raw, high-dimensional radiological data and reliable clinical diagnostic accuracy through investigating the feasibility of spatially and biomechanically constrained imaging markers.In the obstetric application (Aims 1 and 2), multiparametric MRI, morphometrics, and radiomic analysis were utilized to evaluate early-gestation placental function and predict infant growth trajectories. Results demonstrated that early deviations in placental volume and spatial perfusion heterogeneity independently shape birth percentiles. Furthermore, specific morphometric features, such as elongation and sphericity, and habitat-wise radiomic texture features significantly outperformed clinical and mean multiparametric MRI features... https://escholarship.org/uc/item/3099h15f Thu, 4 Jun 2026 00:00:00 +0000 Ramirez, Raymi Odalys https://escholarship.org/uc/item/1z07z8ht Language and perception operate over fundamentally different representational regimes: language (especially in its textual form used to train models) tends to promote more discrete, symbolic processing, whereas perception and action are more continuous, gradient, and grounded in embodied experience. This distinction shapes how both humans and machines learn, generate, and evaluate information. This dissertation advances a unified account of how these representational differences influence model behavior and human–AI interaction, integrating theoretical analysis, computational modeling, and human experiments. Chapter 1 synthesizes prior work in cognitive science, language models, and multimodal AI to argue that, while language encodes substantial information about embodied experience through statistical regularities and compositional structure, it remains constrained by its reliance on representations of prior experience. Incorporating multimodality provides access to continuous... https://escholarship.org/uc/item/1z07z8ht Thu, 4 Jun 2026 00:00:00 +0000 Jiang, Yanru https://escholarship.org/uc/item/1dn7v3xx Driven quantum systems are central to quantum computation and quantum control across every major hardware platform. In the simplest setting, a qubit driven near resonance is well described by the rotating-wave approximation, which eliminates rapidly oscillating counterrotating terms and retains the slowly-varying resonant interaction. This picture breaks down when drives span multiple frequencies at incommensurate values, when near-resonant beat notes arise from higher-order interactions, or when corrections beyond leading order cannot be neglected. The existing toolkit handles each of these regimes separately: Floquet–Magnus and Van Vleck high-frequency expansions preserve unitarity for periodic drives but fail at resonance, while adiabatic elimination and Schrieffer–Wolff transformations break down as the detuning approaches the coupling strength. No single method treats the general multi-timescale case within a systematic, unitarity-preserving framework.We present a quantum... https://escholarship.org/uc/item/1dn7v3xx Thu, 4 Jun 2026 00:00:00 +0000 Barajas, Kristian https://escholarship.org/uc/item/0qm0g0pj In politics, questions of “feasibility” often concern whether proposed political change, such as the expansion of justice, can be achieved. But there is a second dimension of feasibility: whether just institutions and practices can be sustained over time. An acceptable theory of justice must therefore be feasible in the sense of being sustainable—or, in Rawls’s terminology, stable. This dissertation examines whether liberal democratic theories of justice are stable in this way. Taking Justice as Fairness as a central test case, I reconstruct and assess Rawls’s powerful argument for its stability. While I argue that Rawls succeeds in showing that Justice as Fairness can stably regulate a liberal democratic society, his account also reveals the inadequacy of coercion-centered explanations of political stability. The enduring maintenance of liberal democratic justice must depend very little upon coercive enforcement and primarily on citizens’ shared sense of justice, expressed through... https://escholarship.org/uc/item/0qm0g0pj Thu, 4 Jun 2026 00:00:00 +0000 Pensler, Samuel Levin https://escholarship.org/uc/item/98c1t8w0 Chronological age is widely used as a standard measure of health status in clinical studies. However, individuals may age at different rates due to variations in genetics, lifestyle, and environmental exposures. Therefore, chronological age often fails to capture the underlying tissue-level biological aging process. This limitation motivates the development of biological age (BA) as a more informative measure of physiological aging. Prior studies have estimated biological age using a range of biomarkers, including proteomic, physiological, medical imaging measurements etc. Although these studies suggest that biological age may better reflect abnormal aging than chronological age alone, several important limitations remain. First, many existing models are trained on large cohorts that either span a limited age range or lack rigorously defined inclusion criteria, particularly with respect to restricting the training population to individuals who represent normative aging without... https://escholarship.org/uc/item/98c1t8w0 Wed, 3 Jun 2026 00:00:00 +0000 Deng, Zengtian https://escholarship.org/uc/item/90h9268p The general theme of this thesis is the exploration of topological hydrodynamics across different subfields of condensed matter physics, focusing on new proposals for topological charge manipulation and next-generation technologies.In materials with short-range order, the value of the order parameter (which characterizes phases of matter) can spatially vary, so the homotopic properties of the order parameter space dictate the topological excitations that the system can host. The excitations of the order parameter field generically exhibit topological hydrodynamics, meaning transport and flows of topological charges adhere to a conservation law. Different from conservation laws stemming from a symmetry of the Lagrangian, topological conservation laws are rooted in the homotopic properties of the order parameter space, and so they are immune to any structural imperfections or anisotropies. The robustness of the topological conservation law to disorder and thermal fluctuations have... https://escholarship.org/uc/item/90h9268p Wed, 3 Jun 2026 00:00:00 +0000 Dao, Chau Nguyen https://escholarship.org/uc/item/84t012vx In this dissertation, I focus on marginalized and intersecting identities—oft-perceived as monstrous by the dominant culture—and argue for alternative ways to understand identity formation through the lens of monstrosity by primarily analyzing the music and sound from four indie video games: Undertale (2015), Night in the Woods (2017), Celeste (2018), and Hades (2020). I turn to the monster as a site of possibility and a way of being for marginalized peoples, who, in response to being Othered, have created something more for themselves that humans and the human category cannot offer. I blend interpretive analysis and ethnography to propose alternative ways in which the player/listener can hear and listen to the queer, gendered, racialized, and/or disabled monster, all the while embracing the complexities of their monstrousness. I am in dialogue with queer theorist Eve Kosovsky Sedgwick’s theorization of reparative reading and argue that repair has its limitations. Instead, I inquire... https://escholarship.org/uc/item/84t012vx Wed, 3 Jun 2026 00:00:00 +0000 Park, Hyeonjin https://escholarship.org/uc/item/5z23k3xr Horn Concertino is the result of two intersecting academic pursuits: recent research into the works of Aaron Copland, Wolfgang Amadeus Mozart, Andrew Norman, and Esa-Pekka Salonen, as well as a growing interest in contemporary compositional procedures. In this work, a motif from Mozart’s Symphony No. 41 is distorted through time-stretching and timbral procedures into material that becomes nearly unrecognizable from its original form. The pitch material of the motif is then transformed through various expansion processes to generate the core material of the third movement. These ideas are structured within formal frameworks influenced by the works of Copland and Salonen. https://escholarship.org/uc/item/5z23k3xr Wed, 3 Jun 2026 00:00:00 +0000 Harrison, Jacob https://escholarship.org/uc/item/4jp9q4x3 This dissertation comprises three chapters that study how learning is shaped by attention constraints, peer pressure in social networks, and the information provider's strategic incentives.The first chapter studies how the incentive to prolong engagement affects the quality of information provided to a learning agent. In many advisory and digital environments, information providers benefit from keeping consumers engaged rather than from the actions consumers ultimately take. We develop a continuous-time principal-agent model in which the principal chooses the precision of a drift-diffusion signal process, and the agent decides when to stop learning and take an action. The main result is that optimal precision is U-shaped in the agent's prior belief, reaching its minimum when the agent is most uncertain. The principal provides the least precise information to the agent with the highest underlying demand for information, because that agent's willingness to remain engaged is greatest,... https://escholarship.org/uc/item/4jp9q4x3 Wed, 3 Jun 2026 00:00:00 +0000 Zhai, Jiayin https://escholarship.org/uc/item/45j0g8t5 Modern deep learning is powered by large-scale data and large pretrained models, yet deploying them efficiently remains a fundamental challenge. Training on massive datasets is prohibitively expensive, and powerful generative models are too slow and too limited in duration for real-time interactive applications. This thesis addresses both challenges under a unified theme of efficient learning at scale. I first study dataset distillation, where the goal is to compress a large dataset into a compact synthetic substitute. I show that progress in this area has been hampered by inconsistent evaluation, memory bottlenecks that prevent scaling, and a previously unrecognized tendency for compression to amplify data biases, and I propose solutions to each. I then turn to the problem of transferring knowledge from large pretrained video models into lightweight models capable of real-time, long-form streaming. I show that the key obstacles preventing real-time long-form generation can be... https://escholarship.org/uc/item/45j0g8t5 Wed, 3 Jun 2026 00:00:00 +0000 Cui, Jiaxing https://escholarship.org/uc/item/2058j6hm Background: Despite ongoing public health efforts, racial/ethnic disparities in breastfeeding remain a major barrier to maternal and child health equity. Minority women (e.g., Black and Hispanic) continue to experience lower breastfeeding rates than White women. Place-based SDOH, such as neighborhood conditions, are well-established determinants of health and may also be relevant to breastfeeding. Although research on their role in breastfeeding remains limited, existing studies have indicated an association that warrants further investigation. This dissertation attempts to address this gap by examining the association between structural and social determinants of health and breastfeeding (initiation, duration, and exclusivity) among low-income women, specifically participants in the Supplemental Nutrition Assistance Program for Woman, Infant, and Children (WIC) living in Los Angeles County. Three interconnected studies were conducted, each focusing on a distinct and understudied... https://escholarship.org/uc/item/2058j6hm Wed, 3 Jun 2026 00:00:00 +0000 Shodahl, Skye https://escholarship.org/uc/item/1ds7c5rr This dissertation examines Jacques Ferrandez’s ten-volume graphic novel series Carnets d’Orient (1994–2009) as a contested site of postcolonial memory for French Algeria, arguing that its cultural power cannot be captured by a simple opposition between nostalgic apology and critical denunciation. Chapter 1 maps the series’ fragmented reception among scholars, prize committees, the press, Algerian media, and state institutions. It shows how Carnets d’Orient is alternately canonized as neutral historical fresco and condemned as pied-noir nostalgia. Chapters 2 and 3 then offer a sustained ecocritical and food-centered rereading of the decalogy. Chapter 2 foregrounds land, agriculture, and non-human actors, tracing the Barthélemy family farms as lieux de mémoire that both expose and reproduce settler-colonial logics of dispossession, labor exploitation, and environmental “improvement.” Chapter 3 analyzes scenes of food, drink, and commensality in dialogue with pied-noir cookbooks... https://escholarship.org/uc/item/1ds7c5rr Wed, 3 Jun 2026 00:00:00 +0000 Sackett-Hassan, Amber https://escholarship.org/uc/item/1606x9g1 Background: Moderate to severe traumatic brain injury (msTBI) is a risk factor for ongoing cognitive decline, and cognitive impairment may progressively worsen into advanced dementia. Objectives: The Doctor of Nursing Practice (DNP) Scholarly Project aims to assess whether an 8-week moderate-intensity cycling exercise program can enhance neuropsychological and cognitive quality of life (QOL) scores in patients with TBI. Methods: A quasi-experimental pre- and post-intervention design was used. Seven msTBI participants with cognitive impairment, aged 22-65 and at least 6 months post-injury, completed eight weeks of supervised cycling exercise, twice weekly for 40 minutes per session, at a hospital wellness center. Three cognitive function tests [Modified Mini-Mental Status Exam (3MS), Trail Making Test Part A (TMT-A), Trail Making Test Part B (TMT-B)] and two Quality of Life measures [Traumatic Brain Injury Quality of Life (TBI-QOL) Cognition-General Concerns, and Executive Function]... https://escholarship.org/uc/item/1606x9g1 Wed, 3 Jun 2026 00:00:00 +0000 PAN, SUWEN https://escholarship.org/uc/item/14b2b9xk Writing with the Fly examines the housefly as a central figure of science communication in the 20th century that contributed to the transfer of racist ideologies from hygiene into digital network cultures. Situated at the intersection of media studies, medical humanities, and visual culture studies, this project demonstrates that racism relies on medial forms that contradict their own ideologies of exclusion. Questioning the contradicting paradigms of cleanliness, balance and efficiency, my goal is to understand how and why “black bodies” of houseflies and their unruly behaviors were racialized throughout the 20th century. In what contexts were houseflies staged in science and popular science communication? What prejudices were associated with their bodies in their function as disease carriers? How did racist undercurrents in medical knowledge integrate into popular conceptions of computer systems through the image of the fly? To answer these questions, this project explores the... https://escholarship.org/uc/item/14b2b9xk Wed, 3 Jun 2026 00:00:00 +0000 Trüper, Lena Sophie https://escholarship.org/uc/item/0926j27p This dissertation studies Heterogeneous Agent New Keynesian (HANK) models and their application to studying the effects of fiscal and monetary policy, with an emphasis on the former. In particular, I show the implications of HANK models under scenarios where the central bank does not raise interest rates in response to inflation and where the government does not (or cannot) commit to paying off its debt with new taxation for every path of the price level, but also does not explicitly default. I additionally show how this setting can be used in conjunction with information frictions to better understand the dynamics of macroeconomic variables.In Chapter 1, I show that when fiscal policy is active and monetary policy is passive in a HANK model, deficit-financed transfers to low-asset households lead to similar cumulative inflation but greater increases in real output than transfers to wealthier households. I use the inverse of the ``Phillips multiplier,'' the price level sacrifice... https://escholarship.org/uc/item/0926j27p Wed, 3 Jun 2026 00:00:00 +0000 Kwicklis, Noah Duncan https://escholarship.org/uc/item/9xb8j0n8 Performing statistical analyses with climate data requires accounting for many types of variability. This variability is complex and spatiotemporal in nature, and the variability often integrates overlapping processes at multiple spatial and temporal scales. While this makes climate a challenging setting for applying statistical methods, we can use scientific expertise to properly account for and leverage these spatiotemporal structures in our analyses. This dissertation develops statistical methods for performing large scale multiple hypothesis testing and uncertainty quantification in the climate setting. Chapter 1 introduces the climate setting and some of the particular challenges that methods face in this setting. Chapter 2 focuses on multiple hypothesis testing in a common regression setting in climate, where a univariate response variable is regressed against a spatial grid of covariates. The false discovery rate (FDR) control framework provides a practical method for... https://escholarship.org/uc/item/9xb8j0n8 Tue, 2 Jun 2026 00:00:00 +0000 McEvoy, Kyle Roberts https://escholarship.org/uc/item/9kr3t9j6 Observational studies seek to utilize the large wealth of patient-level observational data captured during the routine course of clinical care to produce real-world evidence that then guides clinical practices.In this dissertation, I seek to improve the generation process for real-world evidence by developing novel methods and evaluating existing processes for two core tasks in observational health research: patient-level prediction and population-level effect estimation. I first propose a transfer-learning Bayesian sparse logistic regression framework that leverages coefficient information from large-scale models fit to millions of patients and up to hundreds of thousands of features to inform model fitting in small-scale settings that struggle with small sample sizes and rare outcomes. The transfer-learning approach consistently outperforms traditional L1-regularized logistic regression in discrimination, bias, and sparsity, under both real-world studies and simulations. ... https://escholarship.org/uc/item/9kr3t9j6 Tue, 2 Jun 2026 00:00:00 +0000 Li, Kelly https://escholarship.org/uc/item/9gc451zc Research on the intersection of autism and gender diversity remains limited, particularly in how identity development is understood and described by this population. This mixed-methods study with a qualitative focus explored identity development in 20 gender-diverse, predominantly late-diagnosed autistic adults ages 19 to 47 years old (M = 30.1, SD = 8.01). Interviewees were asked to narrate their identity development journeys and identify factors that shaped their development. Questionnaire measures were also collected; this sample completed the Hospital Anxiety and Depression Scale (HADS), the Social Responsiveness Scale Second Edition (SRS-2), and an abbreviated version of the Gender Diversity and Autism Questionnaire (GDAQ). Three-quarters of the sample met the clinical threshold for anxiety and nearly half met the threshold for depression. Participants reported greater engagement in queer communities compared to autism-related communities, with all participants endorsing... https://escholarship.org/uc/item/9gc451zc Tue, 2 Jun 2026 00:00:00 +0000 Gohari, Dena https://escholarship.org/uc/item/997383jg Alzheimer's classification is essential to diagnosis and monitor a disease which severely impacts cognitive function. This thesis compares three representations of functional magnetic resonance imaging data, including correlation networks, causal relationships, and transformer derived patterns, and their efficacy for binary classification. Correlation networks are derived using sparse inverse covariance matrices; causal networks are derived using the Granger causality method. Standard preprocessing is run on a dataset of thirty images. The study evaluates the use of support vector machines with correlation and causal features versus two transformer architectures. The support vector machine with filtered causal features performed best with an area under the curve score of 0.8, with connections in the default mode network, hippocampus, and orbitofrontal lobes having the most predictive power. Transformers performed well given the limited data, but further study is needed on a larger... https://escholarship.org/uc/item/997383jg Tue, 2 Jun 2026 00:00:00 +0000 Lennemann, Lucy https://escholarship.org/uc/item/9698k583 This thesis is an inquiry into turquoise, a mineral primarily used as a gemstone in jewelry, and one of many different significant materials used in Southwestern Native American cultures and traditions. Despite the diversity of Native jewelry form and materials, jewelry set with turquoise generally overshadows other types of Native-made jewelry as a coveted and collected object for non-Native consumers. This thesis examines settler desires for turquoise mined from Native homelands through time, starting with the territorial New Mexico colonial political economy of turquoise mining in the 19th century in which settler men attempted to construct a narrative that Native turquoise mines had been abandoned. The mineral is also collected for Victorian curio cabinets and displayed on the bodies of white settler women for whom the gem becomes their connection to dead Native sisters of the female settler imaginary. The mineral discussed in this thesis has saturated the Southwest Native... https://escholarship.org/uc/item/9698k583 Tue, 2 Jun 2026 00:00:00 +0000 Dorsey, Kristen Barbara https://escholarship.org/uc/item/93q2p5ts As modern biobanks and large-scale cohorts gather extensive genotype data alongside rich clinical information, there is a pressing need for statistical methods that can perform genetic analysis of survival traits such as disease onset or progression at scale while accommodating diverse genetic architectures, and leverage summary-level data. We propose three frameworks to meet these challenges. First, we introduce the censored multiple variance component model (CVC), an extension of linear mixed models designed for right-censored data. CVC estimates the narrow-sense heritability of survival traits using synthetic variables for unbiased variance component estimation, achieving computational scalability with up to one million subjects. Second, we propose AFT-SV, a semi-parametric accelerated failure time model leveraging synthetic variables that directly models time-to-event outcomes. By employing Wald-type test with a saddle-point approximation, this method is computationally efficient,... https://escholarship.org/uc/item/93q2p5ts Tue, 2 Jun 2026 00:00:00 +0000 Kim, Do Hyun https://escholarship.org/uc/item/8tp0b22q This dissertation research deals with collective electronic transport and external control of charge-density-wave condensates in low-dimensional van der Waals materials. The charge-density-wave materials provide a unique platform for studying collective transport phenomena arising from strong electron–phonon coupling and offer potential pathways toward beyond-CMOS electronic functionalities. First, the dissertation describes the electrostatic modulation of the electron-lattice condensates in quasi-one-dimensional systems. In orthorhombic TaS3, a giant gate-induced modulation of the condensate charge density is demonstrated, exceeding predictions based on conventional geometrical capacitance by one to two orders of magnitude. The enhanced response originates from coupling between the applied electric field and the collective electron–lattice condensate, revealing an unusually large effective quantum capacitance. Complementary studies in top-gated h-BN/NbS3 heterostructures further... https://escholarship.org/uc/item/8tp0b22q Tue, 2 Jun 2026 00:00:00 +0000 Taheri, Maedeh https://escholarship.org/uc/item/7z86q182 Aging is characterized by chronic low-grade inflammation, termed inflammaging, which contributes to the development of metabolic and degenerative diseases. Cellular senescence is a key driver of this process; however, the identity and molecular features of senescent immune cells remain poorly defined. This dissertation investigates macrophage senescence as a central mechanism underlying immune aging. First, we establish that macrophages can undergo bona fide cellular senescence in response to DNA damage and metabolic stress, acquiring stable cell-cycle arrest and a senescence-associated secretory phenotype (SASP). Through multi-omic profiling, we identify a distinct transcriptional and metabolic signature of senescent macrophages characterized by p21 expression, type-I interferon signaling, and mitochondrial DNA–driven inflammation We further demonstrate that excess cholesterol loading via acetylated low-density lipoprotein is sufficient to induce a stable, lipid-laden senescent... https://escholarship.org/uc/item/7z86q182 Tue, 2 Jun 2026 00:00:00 +0000 Salladay-Perez, Ivan Alexander https://escholarship.org/uc/item/7j7558tn Imitation, the ability to copy another person’s gestures, acoustic features, or speech style, is a cognitive skill present throughout life and plays an important role in language learning and acquisition. Evidence from first language research shows that infants begin imitating speech patterns early in development. This capacity continues into adulthood, particularly during conversational interaction or when individuals are explicitly instructed to imitate a model. The present study investigates a method for teaching second language (L2) phonology to adult English-speaking learners of Spanish through explicit focused-attention imitation training. The method builds on a pilot study (Meléndez-Ballesteros, 2012) with students enrolled in a second-semester elementary Spanish course. Participants were divided into four groups and performed specific listening and speaking exercises. The current study focuses on the audio-visual exercise of that study. Students were randomly assigned... https://escholarship.org/uc/item/7j7558tn Tue, 2 Jun 2026 00:00:00 +0000 Melendez-Ballesteros, Nancy https://escholarship.org/uc/item/7cp5b5gg Throughout U.S. history, some white individuals have acted in solidarity with People of Color to fight racism. Often these individuals began developing critical race consciousness—capacities necessary for disrupting racism—during adolescence. Examining the development of critical race consciousness during adolescence is critical because this developmental period is marked by key increases in relevant cognitive capacities (e.g., abstract thinking) and opportunities to engage with social issues. Drawing on the integrative model of critical race consciousness (Bañales et al., 2023), this dissertation includes two studies that examined the development and socialization of the sociocognitive, reflective, and behavioral capacities necessary for disrupting racism. Study samples are comprised of monoracial white adolescents who participated in a large nationwide study of youth civic engagement. Study 1 utilized survey data from 265 white participants (Mage = 17.3 years), and Study 2 utilized... https://escholarship.org/uc/item/7cp5b5gg Tue, 2 Jun 2026 00:00:00 +0000 Kinnard, Lauren Ann https://escholarship.org/uc/item/6jb614j7 Amid renewed great-power competition, eroding arms control regimes, and emerging military technologies, what bounds what states can credibly communicate to allies and adversaries? Existing scholarship treats credibility as the central problem, studying how officials signal resolve and capability through costly signals, audience costs, and treaty design. I show that credibility depends on more than what officials say or commit to. Two undertheorized structural features of the communicative environment bound strategic communication: audience interdependence in alliance management, where one audience’s response becomes information for another, and strategic substitutability in arms control, where alternative capabilities determine which treaties form and which credibly hold. In multi-audience settings, communication across audiences produces downstream consequences that can convey what states did not intend. In alliance management, patrons routinely combine public commitments... https://escholarship.org/uc/item/6jb614j7 Tue, 2 Jun 2026 00:00:00 +0000 Luca, Laura Margareta https://escholarship.org/uc/item/6bh172nd The rapid advancement of modern technology is driven largely by improvements in semiconductor devices, which require manufacturing techniques capable of producing increasingly complex nanoscale three-dimensional structures with high precision, high throughput, and reasonable cost. Atomic layer deposition (ALD) and atomic layer etching (ALE) have emerged as critical techniques in advanced semiconductor manufacturing because their self-limiting surface reactions enable atomic-scale control of material deposition and removal, resulting in highly uniform thin films and precise surface modification. To better understand and optimize these processes, this dissertation develops multiscale modeling frameworks that integrate reactor-scale transport phenomena with surface reaction mechanisms to analyze atomic layer processes and identify optimal operating conditions, reactor geometries, and control strategies that improve precursor utilization and overall manufacturing efficiency. First,... https://escholarship.org/uc/item/6bh172nd Tue, 2 Jun 2026 00:00:00 +0000 Ou, Feiyang https://escholarship.org/uc/item/63p677mt This dissertation consists of three essays on industry dynamics and resource allocation. The first essay studies long-run common-pool resource management. Inefficiencies in open-access resources arise not only from resource use by existing participants but also from their capacity investment and the entry of new firms. This essay develops a model of firm dynamics in which firms interact through stock depletion and congestion, and estimates it using firm-level panel data from the American whaling industry (1804–1909). A tractable framework for optimal policy design is introduced by quantifying the shadow prices of externalities. Standard per-unit Pigouvian taxes substantially improve welfare but fall short of the first best: they correct stock externalities but leave congestion unpriced, leading to persistent overcapacity. Optimal regulation combines per-unit taxes with lump-sum fees to discipline entry, exit, and investment.The second essay, written jointly with Will Rafey, examines... https://escholarship.org/uc/item/63p677mt Tue, 2 Jun 2026 00:00:00 +0000 Yun, Yangkeun https://escholarship.org/uc/item/5w5539pc Recent advances in causal learning have established the identifiability of a directed acyclic graph (DAG) under additive noise models (ANMs), spurring the development of various causal discovery methods. However, most existing methods make restrictive model assumptions, rely heavily on general independence tests, or require substantial computation. To address these limitations, we propose a sequential procedure to orient undirected edges in a completed partial DAG (CPDAG), representing an equivalence class of DAGs, by leveraging a pairwise additive noise model (PANM) to identify their causal directions. We prove that this procedure can recover the true causal DAG assuming a restricted ANM. Building on this result, we develop a novel constraint-based algorithm for learning causal DAGs under nonlinear ANMs. Given an estimated CPDAG, we develop a ranking procedure that sorts undirected edges by their adherence to the PANM, which defines an evaluation order of the edges. To... https://escholarship.org/uc/item/5w5539pc Tue, 2 Jun 2026 00:00:00 +0000 Huang, Stella https://escholarship.org/uc/item/5pq786n8 Neuropsychiatric disorders frequently involve dysfunction in frontolimbic circuits that regulate emotion, motivation, and threat response, but the synaptic, cellular, and circuit mechanisms governing these behaviors remain incompletely understood. In this dissertation, I investigate how defined cell types and synapses within prefrontal and limbic networks shape emotional behavior in the context of therapeutic neuromodulation and development. First, I developed a preclinical mouse model of repetitive transcranial magnetic stimulation (rTMS) with strong clinical face validity and used it to identify circuit mechanisms underlying the rapid antidepressant effects of accelerated intermittent theta burst stimulation (aiTBS). I found that aiTBS induces cell type-specific plasticity in dorsomedial prefrontal cortex (dmPFC), selectively enhancing activity and dendritic spine density in intratelencephalic projection neurons, while parallel studies of inhibitory microcircuits revealed a... https://escholarship.org/uc/item/5pq786n8 Tue, 2 Jun 2026 00:00:00 +0000 Gongwer, Michael https://escholarship.org/uc/item/5gc1w4kw Biological regulation relies on the complex integration of biochemical and physical cues. While single-cell analysis has emerged to interrogate the cellular heterogeneity for underlying regulation, mapping the network requires overcoming bottlenecks in both mechanobiology and computational biology. First, how physical mechanical signals are regulated within intracellular space remains a knowledge gap. Second, while high-dimensional multimodal omics demand sophisticated machine learning models, their "black box" opacity prevents researchers from translating mathematical outputs into biological mechanisms. Therefore, this dissertation advances single-cell quantitative analysis across two critical fronts. To resolve the mechanobiology bottleneck, this work establishes an image-based framework utilizing a uniaxial cell stretcher and high-resolution microscopy. This approach uncovers an anti-correlated relationship between nuclear and cytoplasmic deformations in live epithelial monolayers,... https://escholarship.org/uc/item/5gc1w4kw Tue, 2 Jun 2026 00:00:00 +0000 Chen, Chichia https://escholarship.org/uc/item/5735s3xr Recent work in the structural approach to consciousness has shown promise as a research paradigm for the formal and empirical study of phenomenal qualities of experience, or qualia. Existing empirical work in this paradigm has primarily focused on characterizing qualia associated with narrower, local contents of consciousness through relational or similarity structures derived from behavioral judgments. A major next step for the structural approach is to extend these methods toward broader, phenomenally unified experiences, and to formalize the relationship between the phenomenal qualities of local and global aspects of consciousness. This dissertation presents both empirical and mathematical approaches to the structural characterization of broad qualia. First, linguistic feature-based representations generated by large language models are examined as approximations of human judgments of similarity between complex subjective experiences. The relationship between the relational... https://escholarship.org/uc/item/5735s3xr Tue, 2 Jun 2026 00:00:00 +0000 Lee, Youngzie Youngzie https://escholarship.org/uc/item/51z1p6zb Within the recent scholarly reappraisal of Chile’s Generation of 1938, this dissertation examines the work of Fernando Alegría (1918–2005) as an integrated intellectual, political, and narrative system organized around the problem of Chilean collective experience. Although Alegría has been recognized as a novelist, poet, intellectual, and cultural figure, his work has often been approached through fragmented readings that isolate genres, periods, or dimensions of his trajectory. The disparity between his historical significance and his critical reception stems in part from this fragmentation. I argue that Alegría’s writing develops a sustained reflection on forms of collective rootedness marked by classism, exclusion, violence, marginality, and social fracture, and that his oeuvre achieves coherence through three articulating principles: freedom, chilenidad as a collective sense of belonging, and the bicultural relation between Chile and the United States.Drawing on Roberto Hozven’s... https://escholarship.org/uc/item/51z1p6zb Tue, 2 Jun 2026 00:00:00 +0000 Cuevas-Collante, Pedro https://escholarship.org/uc/item/42591937 During the second postnatal week of development in rodents, cortical activity evolves from highly synchronized, low-dimensional dynamics to less synchronous activity spanning a greater number of dimensions, a process thought to underlie the emergence of sparse, flexible cortical representations. Previous studies have focused on the phenomenological characterization of this transition and on the role of sensory experience. However, how the geometric structure of population activity changes across this transition, what circuit mechanisms drive this reorganization, and the implications for information encoding have not been established. Using in vivo calcium imaging in early postnatal mice, we show that cortical desynchronization reflects a redistribution of population variance from dominant, low-dimensional modes into many weaker dimensions, fundamentally reorganizing the geometric structure of spontaneous cortical activity. All-optical circuit interrogation revealed that optogenetic... https://escholarship.org/uc/item/42591937 Tue, 2 Jun 2026 00:00:00 +0000 Wu, Michelle https://escholarship.org/uc/item/39b037tg The complexity of a Calabi–Yau pair pX, Bq is an invariant that relates the dimension of X, the rank of the group of divisors, and the coefficients of B. If the complexity is less than one, then X is a toric variety. We study other geometric consequences of small complexity. We give a characterization of log Calabi–Yau pairs of complexity zero and arbitrary index. As an application, we show that a log Calabi–Yau pair of birational complexity zero admits a crepant birational model which is a generalized Bott tower. We prove that if the complexity is less than two, then X is a Fano type variety. Furthermore, if the complexity is less than 3/2, then X admits a Calabi–Yau structure of complexity one and index at most two, and it admits a finite cover Y Ñ X of degree at most 2, where Y is a cluster type variety. In particular, if the complexity is one and the index is one, pX, Bq is cluster type. Finally, we establish a connection with the theory of T-varieties. We prove that a variety... https://escholarship.org/uc/item/39b037tg Tue, 2 Jun 2026 00:00:00 +0000 Enwright, Joshua Lee https://escholarship.org/uc/item/37j9k1zp Public health departments play a critical role in identifying and investigating disease outbreaks. Traditional approaches to outbreak identification often rely on empirical observation, which can delay response and increase both disease burden and resources needed for control. Consequently, systematic methods that can be applied to routine surveillance data have gained interest as tools for earlier outbreak detection. Cluster detection methods such as the spatiotemporal scan statistic have demonstrated potential for improving outbreak detection, but the effects of case ascertainment, validation against related methods, and the cost-effectiveness of implementation remain underexplored. This dissertation is motivated by the California Department of Public Health’s (CDPH) use of the spatiotemporal scan statistic for COVID-19 cluster detection. Chapter 1 reviews the public health context for applying the spatiotemporal scan statistic and describes CDPH’s implementation. Chapter 2... https://escholarship.org/uc/item/37j9k1zp Tue, 2 Jun 2026 00:00:00 +0000 Lu, Phoebe https://escholarship.org/uc/item/29f9w8c4 The rapid growth of experimental data and increasing analytical complexity in calcium imaging demand a new generation of computational tools. Modern experiments extend traditional limits by enabling continuous recordings over days or weeks and incorporating closed-loop systems that respond to neural activity in real time. These advances require analysis pipelines capable of processing terabytes of data, supporting real-time computation, and integrating with adaptive experimental systems.However, most existing analysis pipelines are not designed to meet these demands or require substantial software engineering expertise to adapt. Additionally, there is a lack of tools that enable scientists to easily develop, share, and reuse novel analysis software. As a result, creating and maintaining pipelines remains perpetually labor-intensive, and few solutions achieve the reach and longevity required to become a part of shared infrastructure.This dissertation addresses these challenges... https://escholarship.org/uc/item/29f9w8c4 Tue, 2 Jun 2026 00:00:00 +0000 Chang, Raymond Woochan https://escholarship.org/uc/item/2993x58h This dissertation comprises three essays in labor and health economics that examine the role of social networks, firms, and public mental health infrastructure in shaping inequality in the United States. The first chapter studies how racial segregation in coworker networks affects the transmission of labor market opportunities and contributes to persistent Black-White earnings gaps. Using matched employer-employee data covering workers across three U.S. states from 2002-2019, I find that same-race former coworkers transmit outside job opportunities more effectively than cross-race contacts. Job-to-job transitions are approximately five times more responsive to shocks of the same-race network than the cross-race network. I develop a sequential-auction labor market model with homophilous network transmission in which minority workers receive fewer effective outside offers because opportunities diffuse primarily through same-race contacts. Together, the model and empirical... https://escholarship.org/uc/item/2993x58h Tue, 2 Jun 2026 00:00:00 +0000 Righi, Giovanni https://escholarship.org/uc/item/27n1f78n Polynucleotide phosphorylase (PNPase) is a critical regulator of mitochondrial double-stranded RNA (mtdsRNA) homeostasis. Loss of PNPase leads to the export of mtdsRNA to the cytosol, triggering a Type-I interferon response via the MDA5-MAVS signaling axis. Because PNPase is essential for cellular viability, we developed a "plug-and-play" murine embryonic fibroblast (MEF) cell line utilizing a tamoxifen-inducible Cre-ERT2 system for endogenous PNPT1 knockout, paired with a FLP-in recombinase locus for the stable expression of PNPase variants. Upon knockout of endogenous PNPase, mtdsRNA rapidly accumulates and is exported to the cytosol, leading to MAVS recruitment to the mitochondrial outer membrane and eventual cell death via apoptosis. Notably, mitochondrial DNA (mtDNA) copy number remains stable and is not exported, identifying mtdsRNA as the primary inflammatory ligand. Functional localization studies revealed that targeting PNPase to the mitochondrial intermembrane space,... https://escholarship.org/uc/item/27n1f78n Tue, 2 Jun 2026 00:00:00 +0000 Short, Connor W. https://escholarship.org/uc/item/26h93505 This study examines how labor is made visible and structured within the visual and architectural program of the Southwest Palace at Nineveh, constructed under King Sennacherib in the late seventh century BCE, and traces how this system shifts as the imagery moves from relief to drawing to print. Rather than treating these images as fixed representations, it approaches them as a sequence of transformations across media that reorganize how labor is structured and made legible. Focusing on the reliefs of Court VI, where the quarrying, transport, and installation of monumental lamassu unfold across a sequence of scenes encountered through movement along the palace walls, this thesis argues that these images do not present discrete actions but organize bodies through repetition, posture, spacing, and hierarchy into a coordinated visual system. Laboring figures appear in substantial numbers, yet their presence is structured in ways that subsume individuality within a larger compositional... https://escholarship.org/uc/item/26h93505 Tue, 2 Jun 2026 00:00:00 +0000 Harris, Wanda Y https://escholarship.org/uc/item/1zf327gt Transformer-based in-context learning (ICL) has demonstrated remarkable ability to perform regression tasks by conditioning on demonstration examples within a single forward pass, without parameter updates. While ICL predictions improve with more demonstrations, quantifying the uncertainty of these predictions with formal coverage guarantees remains an open challenge. In this work, we conduct a systematic empirical study of conditional conformal prediction methods— specifically CondConf and its computationally efficient variant SpeedCP—applied to ICL regression across multiple experimental axes. We investigate how model architecture (width, depth, and standard presets), task complexity (linear, quadratic, neural network, and decision tree regression), signal-to-noise ratio, and input dimensionality jointly influence both point prediction quality and the resulting conformal prediction intervals. Across 44 experimental configurations encompassing 12 architectures (S13–S24), 16 task–noise... https://escholarship.org/uc/item/1zf327gt Tue, 2 Jun 2026 00:00:00 +0000 Lin, Jinrui https://escholarship.org/uc/item/1tk2323p Social scientists often consider the state policy context when investigating shifts in reproductive and population health responses to policy change or exogenous shock. For example, after the Dobbs v. Jackson Women’s Health Organization Supreme Court decision, U.S. states passed increasingly strict abortion service restrictions and total bans on provision of abortion, inciting a wide swath of natural experiment studies in public health, economics, public policy, and demography. In studying the associated or causal impacts, access to abortion and other reproductive health and social and economic constraints at the population level offer important insight into how heterogeneity across state contexts moderate the relationship between the national shock and outcomes. Previous studies adjust for the policy environment using 1) proxies, such as partisanship in state government, 2) single domain indices, such as those on abortion or contraception policy restrictiveness, or 3) specific... https://escholarship.org/uc/item/1tk2323p Tue, 2 Jun 2026 00:00:00 +0000 Nayak, Monika https://escholarship.org/uc/item/1nh2q5z1 Bayesian multidimensional scaling (BMDS) is a probabilistic dimension reduction tool that models and visualizes dissimilarities between pairs of objects in a low-dimensional Euclidean space. Compared to classic MDS, BMDS is more robust to model misspecification and supports posterior uncertainty quantification and joint estimation within hierarchical models. However, standard BMDS inference becomes computationally prohibitive as the number of data points N grows, requiring O(N2 ) operations per Markov chain Monte Carlo (MCMC) iteration to evaluate the likelihood or gradient. To combat this computational bottleneck, we invent fast approximations for the BMDS likelihood and gradient, which we integrate into novel MCMC algorithms for scalable Bayesian inference.Chapter 1 establishes a unified framework for BMDS used throughout this work. In Chapter 2, we propose and compare two sparse versions of BMDS that apply log-likelihood and gradient calculations to subsets of the observed... https://escholarship.org/uc/item/1nh2q5z1 Tue, 2 Jun 2026 00:00:00 +0000 Sheth, Ami https://escholarship.org/uc/item/0xb6t9vb Mitral valve regurgitation (MR) is one of the most common valvular heart conditions in adults, and the choice between contemporary treatments—including surgical mitral repair, minimally invasive surgical approaches, and transcatheter edge-to-edge repair (TEER)—is increasingly preference-sensitive. As the therapeutic landscape has expanded, the decision facing patients and clinicians has become more complex, with meaningful tradeoffs in durability, recovery, time horizon to benefit, and patient-reported quality of life. Yet, shared decision-making (SDM) remains inconsistently operationalized in cardiac surgery practice, and the evidence inputs needed to support a well-informed encounter—mid-to-long-term patient-reported outcomes, age-appropriate comparative effectiveness data, and accessible patient-facing communication—are incomplete.This three-paper dissertation contributes empirical evidence to three domains of an adapted SDM framework for MR decision-making. Paper 1 develops... https://escholarship.org/uc/item/0xb6t9vb Tue, 2 Jun 2026 00:00:00 +0000 Sallam, Aminah https://escholarship.org/uc/item/0gb902qp In network data, such as those representing social and economic relationships, the connections between entities depend on one another. Exponential-family random graph models (ERGMs) are the standard tool for capturing this dependence. They are difficult to fit because their parameter space has a challenging geometry. Large regions of it produce networks that are either nearly empty or nearly complete, neither of which is wanted by practitioners. Common Bayesian methods either ignore this geometry or work around it inefficiently. This dissertation develops methodology that respects it. The first chapter shows that a recent variational method for ERGM estimation introduces a formulation that neglects tie dependence and works poorly in realistic settings. The second chapter proposes a new prior distribution for Bayesian ERGM inference. Unlike standard priors, it concentrates on parameter values that produce realistic networks. The third chapter shows that the new prior generalizes... https://escholarship.org/uc/item/0gb902qp Tue, 2 Jun 2026 00:00:00 +0000 Resch, Joseph https://escholarship.org/uc/item/85n604jw High-dimensional regression problems are common in biomedical research, where accurate inference and prediction may be challenging when target-study sample sizes are limited. Transfer learning offers a principled way to improve estimation and prediction by borrowing information from related source studies. However, naive borrowing from heterogeneous or biased sources can lead to negative transfer, thereby degrading model reliability and performance. This dissertation develops Bayesian transfer learning methodology for high-dimensional regression models designed to selectively borrow information from auxiliary sources and improve inference in a target study. The first part of the dissertation introduces BLAST, Bayesian Linear regression with Adaptive Shrinkage for Transfer, a Bayesian multi-source transfer learning framework for high-dimensional linear regression. BLAST combines global-local shrinkage priors with Bayesian source selection to identify informative auxiliary... https://escholarship.org/uc/item/85n604jw Mon, 1 Jun 2026 00:00:00 +0000 Jamshidian, Parsa Mehdi https://escholarship.org/uc/item/7vt623b9 Over recent years, single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics have transformed transcriptomic research by enabling high-resolution gene expression profiling and making it possible to generate atlas-scale datasets efficiently and cost-effectively. Yet rigorous scRNA-seq analysis remains challenging because key tasks, including cell-type annotation, data integration, and visualization, are often affected by substantial methodological and practical limitations. Cell-type annotation relies on a flexible multi-step pipeline whose functions and parameter choices are often shaped by analysts’ judgment and expertise, introducing subjectivity that can reduce reproducibility. Integration across batches is essential for large-scale and multi-condition studies, but it requires balancing the removal of between-batch variation with the preservation of true cell identity. Existing integration workflows still lack principled annotation-free strategies for feature selection... https://escholarship.org/uc/item/7vt623b9 Mon, 1 Jun 2026 00:00:00 +0000 Zhai, Zhiqian https://escholarship.org/uc/item/6k43938s The two leitmotifs of this dissertation are Fukaya categories of orbifolds and Hecke algebras. We develop methods and notions to study and compute wrapped Fukaya categories of global quotient Liouville domains. Of primary interest to us are cotangent bundles of smooth global quotient orbifolds, especially of symmetric products. Our methods allow us to show that A∞-algebras of cotangent fibers of such orbifolds are closely tied to their Hecke algebras. • Chapter 1 is based on the work in progress with Ko Honda, Yin Tian, and Tianyu Yuan. There, we study obstructions to smoothings of nodal orbicurves and wrapped Fukaya categories of T ∗ [X/G] for X a complex manifold equipped with an effective action of a finite group G.• Chapter 2 is based on the work [HKT25] with Ko Honda, Yin Tian, and Tianyu Yuan. There, we develop a cylindrical model for the wrapped Fukaya category of the symmetric product Symκ (T ∗M), and its Morse-theoretic counterpart. We use it to give a full computation... https://escholarship.org/uc/item/6k43938s Mon, 1 Jun 2026 00:00:00 +0000 Krutovskiy, Roman https://escholarship.org/uc/item/5ds844k3 In this thesis, we discuss three topics related to stochastic optimization, numerical stability, and privacy. First, in Chapter 2, we study incomplete tensor linear systems under the tensor t-product. We develop a stochastic iterative method to solve these incomplete systems. We prove two theoretical convergence results under some general conditions on the correlation of the missingness pattern. To showcase the generality of these conditions, we provide three examples of missing data models that satisfy the necessary conditions. We then run experiments on synthetic data and video data to support the two theoretical results. In Chapter 3, we analyze the numerical stability of (accelerated) randomized Kaczmarz. We show that randomized Kaczmarz is not fully forward stable. Next, we prove a black-box result for iterative refinement stating that as long as the underlying solver satisfies some convergence condition, then the solver becomes forward stable when paired with iterative refinement.... https://escholarship.org/uc/item/5ds844k3 Mon, 1 Jun 2026 00:00:00 +0000 Xue, Alexander Jing https://escholarship.org/uc/item/4qh2z4jz Infancy is a critical period for brain and behavioral development. Disruptions in neural architecture or the presence of genetic risk factors may alter developmental trajectories to increase vulnerability for neurodevelopmental disorders, such as Autism Spectrum Disorder (ASD). Sleep problems are a common feature in ASD and have been reported in infants prior to a formal diagnosis. While sleep and ASD are both in-part under genetic control, it remains unknown how genetic factors predisposing for sleep problems and ASD may influence the functional connectome in infancy. This dissertation aims to advance our understanding of how early sleep disruption is associated with functional brain connectivity in early life, as well as uncover how genetic predisposition for ASD and atypical sleep impact these patterns. In Study 1, functional magnetic resonance imaging (fMRI) data from infants at varying familial likelihood for ASD was used to examine how functional connectivity of the Salience... https://escholarship.org/uc/item/4qh2z4jz Mon, 1 Jun 2026 00:00:00 +0000 Chiem, Emily https://escholarship.org/uc/item/3kp5q3hf The transport of solar energetic particles (SEPs) through the heliosphere is governed by their interaction with the highly variable interplanetary magnetic field. Yet standard quasi-linear models, which assume scattering by small-amplitude, randomly phased fluctuations, fail to account for current sheets, coherent, intermittent structures that pervade the solar wind. This dissertation develops a quantitative, observation-informed framework for understanding how kinetic-scale current sheets scatter energetic particles and shape their transport across the inner heliosphere. On the observational side, we analyze more than 175,000 current sheets identified by Parker Solar Probe (0.17 AU), Juno (1–5 AU), ARTEMIS, WIND, and STEREO using a robust, time-resolution-independent detection algorithm. We find that their normalized thicknesses (2–4 ion inertial lengths) and current densities (0.05–0.15 Alfvén current densities) remain broadly invariant across 0.17–5 AU and follow an inverse... https://escholarship.org/uc/item/3kp5q3hf Mon, 1 Jun 2026 00:00:00 +0000 Zhang, Zijin https://escholarship.org/uc/item/1v77q79b The 2015 to 2016 Aliso Canyon natural gas blowout, the largest recorded methane leak in US history, raised concern regarding potential adverse health effects among nearby communities exposed to hazardous air pollutants. Prior analyses using standard difference-in-differences (DiD) models reported elevated rates of low birthweight (LBW) and reduced birthweight among higher risk infants exposed during late pregnancy. However, traditional DiD approaches may fail to capture important features of the data, including spatial heterogeneity, nonstandard outcome distributions, and variation in exposure intensity. To address these limitations, this dissertation develops three extensions of the DiD framework. First, we introduce spatial DiD models that allow treatment effects to vary across geographic regions. Second, we develop an ordinal logistic DiD framework to model birthweight severity among higher risk infants, providing robustness to skewness and heteroskedasticity in continuous... https://escholarship.org/uc/item/1v77q79b Mon, 1 Jun 2026 00:00:00 +0000 Arputhasamy, Valentina https://escholarship.org/uc/item/0zq410dt This dissertation contains two essays in empirical industrial organization. Both essays study how firms respond to incentives, either from public procurement rules or from imperfect factor markets.Chapter 1 studies how delay days are classified after construction begins in California highway projects. A delay day can be recorded as a working day, a change-order day, or an excused weather non-working day. That classification determines whether the contractor pays liquidated damages, CalTrans pays for authorized additional time, or the contract is extended without a payment or penalty. I assemble a panel of CalTrans progress payments, match it to observed weather condition from the Global Historical Climatology stations, and study 1,916 paving projects auctioned between 2009 and 2017. The data show that the gap between CalTrans-recorded weather non-working days and externally measured adverse weather is large and grows over time, even though California weather does not follow the... https://escholarship.org/uc/item/0zq410dt Mon, 1 Jun 2026 00:00:00 +0000 Wu, Yingjie https://escholarship.org/uc/item/5wz0w7sq As mental health awareness increases, there has been growing interest in developing machine learning models to assist with early detection of depression. Building on prior studies that have explored this task, this study aims to replicate and extend previous findings using a different dataset and models. Approximately 10,000 comments were collected from each of the subreddits r/depression and r/AskReddit, resulting in a dataset of roughly 20,000 Reddit comments. The task is a binary classification problem to detect depressive language and to compare the performance of classical machine learning models with modern deep learning models. The classical models—Logistic Regression, k-Nearest Neighbors, and Multinomial Naive Bayes, were evaluated alongside a feedforward neural network and a fine-tuned BERT model. Results show that BERT achieved the highest performance at approximately 85.2% accuracy and 86.2% recall for the depressed class. However, Multinomial Naive Bayes had the second... https://escholarship.org/uc/item/5wz0w7sq Fri, 29 May 2026 00:00:00 +0000 Chan, Clayton https://escholarship.org/uc/item/4gr0k9sb This dissertation develops novel semi-supervised and self-supervised learning algorithms, motivated by settings where labeled training data is scarce or unavailable, respectively. We study two core problems in graph-based semi-supervised learning: how to construct a meaningful graph, and how to exploit its structure. To address the former, we derive backpropagation equations to precisely integrate graph construction and graph-based learning into a neural network, so end-to-end training directly learns data embeddings conducive to high-quality graphs. Our novel Graph Learning Layer (GLL) demonstrates improved generalization and adversarial robustness compared to the standard softmax classification head across vision datasets, architectures, and label rates. To tackle the latter, we leverage graph curvature to design coreset selection and active learning routines that dynamically target different regions of the graph according to its topology. We also present an algorithm that modifies... https://escholarship.org/uc/item/4gr0k9sb Fri, 29 May 2026 00:00:00 +0000 Hardiman-Mostow, Harris Howard https://escholarship.org/uc/item/3sr7v7km Stock price forecasting has long been an area of active research in both statistics and financial mathematics. A large portion of that work has relied on classical time series models, such as ARIMA, GARCH, and exponential smoothing, which are well understood and continue to serve as strong baselines. More recently, advances in natural language processing have introduced a new direction: using transformer-based models to extract sentiment from financial news and incorporate those signals into forecasting pipelines. This thesis sits at the intersection of both traditions.We build directly on the work of Berninger, who applied classical time series models to forecast Apple Inc.'s monthly opening stock price and found that a consensus average of all model forecasts produced the lowest root mean square error (RMSE) over a 12-month test window. We extend that framework by using Python instead of R, use different stocks, which are Tesla (TSLA), NVIDIA (NVDA), and Microsoft (MSFT), alongside... https://escholarship.org/uc/item/3sr7v7km Fri, 29 May 2026 00:00:00 +0000 Mo, Kathy https://escholarship.org/uc/item/30r0f6c2 Many environmental and epidemiological studies produce spatially referenced data with two linked layers: the locations at which observations occur, such as participant residences or cases, and the outcomes measured among the observed individuals, such as continuous health measurements recorded at those locations. Spatial clustering in the observed sample can reflect population density, recruitment, access to care, or other spatially patterned factors, while spatial variation in outcomes may reflect exposure gradients and other spatially structured determinants. This dissertation develops Bayesian marked log-Gaussian Cox process (LGCP) models that separate the observation-location process from the conditional outcome process while allowing layer-specific covariates and latent spatial structure.Chapter 1 introduces the environmental-exposure setting near the Inglewood Oil Field in Los Angeles and frames the central modeling goals: interpretable inference and calibrated uncertainty... https://escholarship.org/uc/item/30r0f6c2 Fri, 29 May 2026 00:00:00 +0000 Zhou, Linyu https://escholarship.org/uc/item/0fk9691k Problem: The COVID-19 pandemic has ushered in a new reliance on non-traditional voting methods, as over one third of voters utilized vote-by-mail (VBM) in the 2024 general election. While this sweeping transition has increased convenience for many voters, it has opened a door for another form of voter suppression: ballot rejection via signature discrepancy. In the 2024 general election, over 580,000 VBM ballots were rejected nationwide - with the most popular reason being a signature discrepancy. Importantly, these ballot rejections are not randomly distributed and are instead felt unequally by racial minorities. VBM ballot rejections are an important component to election outcomes, yet the processes leading to these types of rejections has yet to be empirically scrutinized.Methodology: My dissertation investigates disproportionate ballot rejection through two approaches. First, I conduct an observational analysis using detailed voter data from California and Washington to measure... https://escholarship.org/uc/item/0fk9691k Fri, 29 May 2026 00:00:00 +0000 HERNDON, MICHAEL https://escholarship.org/uc/item/7088h46p This dissertation studies the historical development of federal education policy in the United States, with particular emphasis on vocational education, the G.I. Bill, and the relationship between human capital policy and labor markets during the twentieth century. Across three essays, I examine how federal education programs expanded workforce training opportunities while also shaping patterns of inequality and educational access.The first chapter provides a historical analysis of the Smith–Hughes Federal Vocational Education Act of 1917, the first major federal commitment to vocational education below the collegiate level. Using archival reports from state boards of vocational education and federal agencies, I document the administrative structure, political origins, and long-run expansion of federally supported vocational training programs in agriculture, trades and industry, and home economics. The chapter also introduces a newly digitized dataset constructed from annual vocational... https://escholarship.org/uc/item/7088h46p Thu, 28 May 2026 00:00:00 +0000 Molligo, Patrick