Skip to main content
eScholarship
Open Access Publications from the University of California

Scholarly Works (77 results)

  • Thesis
  • Peer Reviewed
UC San Diego Electronic Theses and Dissertations (2021)

Cardiac ablation is a common procedure performed by cardiac electrophysiologists. The clinician will use a device, such as a radiofrequency ablation catheter, to thermally ablate or burn off defective heart tissue (myocardium). During the procedure, the esophagus can be in close proximity to the heart tissue. As heat transfers through the myocardium, it can also transfer to the esophagus, potentially damaging the esophagus tissue. The damage results in thermal lesions and, in worst-case scenarios, atrioesophageal fistulae. The work reported in this thesis was performed to devise a tool and method to protect the esophagus during the ablation procedure. The Esophageal Deflection Device (EDD) was designed and manufactured to move the esophagus away from the ablation location. The device comprises of a straight rod and a precurved overtube. If the rod is inserted into the overtube, the overtube is straightened out by the rod. If the assembled device is inserted into the esophagus, and the rod is retracted, the elastic memory effect will cause the tube to reassume its original curved shape, thereby moving the esophagus safely away from its close position to the heart. In this dissertation, the medical problem along with the design tools needed to address the above problem of moving the esophagus are investigated. The materials used for the Esophageal Deflection Device are reviewed, and the testing of 3D printed hyperelastic photopolymers used during preliminary designs is performed. Theoretical, experimental, and numerical methods were used to characterize the bending behavior of the Esophageal Deflection Device, and the Mooney-Rivlin materials properties for the hyperelastic tube material are determined. Thereafter, a temperature sensing Esophageal Deflection Device is described and tested. The temperature distribution during ablation is simulated using finite element analysis. Experimental and numerical results are discussed and compared. Finally, a summary and future direction of this work and our research is provided.

    Cover page: Design of an Esophageal Deflection and Thermal Monitoring Device for use during Cardiac Ablation Procedures
    • Article
    • Peer Reviewed
    Berkeley Research Impact Initiative (BRII) (2020)
    In the absence of spin-orbit coupling, the conventional dogma of Anderson localization asserts that all states localize in two dimensions, with a glaring exception: the quantum Hall plateau transition (QHPT). In that case, the localization length diverges and interference-induced quantum-critical spatial fluctuations appear at all length scales. Normally, QHPT states occur only at isolated energies; accessing them therefore requires fine-tuning of the electron density or magnetic field. In this paper we show that QHPT states can be realized throughout an energy continuum, i.e., as an “energy stack” of critical states wherein each state in the stack exhibits QHPT phenomenology. The stacking occurs without fine-tuning at the surface of a class AIII topological phase, where it is protected by U(1) and (anomalous) chiral or time-reversal symmetries. Spectrum-wide criticality is diagnosed by comparing numerics to universal results for the longitudinal Landauer conductance and wave function multifractality at the QHPT. Results are obtained from an effective 2D surface field theory and from a bulk 3D lattice model. We demonstrate that the stacking of quantum-critical QHPT states is a robust phenomenon that occurs for AIII topological phases with both odd and even winding numbers. The latter conclusion may have important implications for the still poorly understood logarithmic conformal field theory believed to describe the QHPT.
      • Article
      • Peer Reviewed
      LBL Publications (2017)
      We have developed a charge-coupled device (CCD) with 5 μm × 45 μm pixels on high-resistivity silicon. The fully depleted 200 μm-thick silicon detector is back-illuminated through a 10 nm-thick in situ doped polysilicon window and is thus highly efficient for soft through >8 keV hard X-rays. The device described here is a 1.5 megapixel CCD with 2496 × 620 pixels. The pixel and camera geometry was optimized for Resonant Inelastic X-ray Scattering (RIXS) and is particularly advantageous for spectrometers with limited arm lengths. In this article, we describe the device architecture, construction and operation, and its performance during tests at the Advance Light Source (ALS) 8.0.1 RIXS beamline. The improved spectroscopic performance, when compared with a current standard commercial camera, is demonstrated with a ∼280 eV (CK) X-ray beam on a graphite sample. Readout noise is typically 3-6 electrons and the point spread function for soft CK X-rays in the 5 μm direction is 4.0 μm ± 0.2 μm. The measured quantum efficiency of the CCD is greater than 75% in the range from 200 eV to 1 keV.
        Cover page: A 5-μm pitch charge-coupled device optimized for resonant inelastic soft X-ray scattering
        • Article
        • Peer Reviewed
        UC Irvine Previously Published Works (2017)
        We introduce phylodyn, an r package for phylodynamic analysis based on gene genealogies. The package's main functionality is Bayesian nonparametric estimation of effective population size fluctuations over time. Our implementation includes several Markov chain Monte Carlo-based methods and an integrated nested Laplace approximation-based approach for phylodynamic inference that have been developed in recent years. Genealogical data describe the timed ancestral relationships of individuals sampled from a population of interest. Here, individuals are assumed to be sampled at the same point in time (isochronous sampling) or at different points in time (heterochronous sampling); in addition, sampling events can be modelled with preferential sampling, which means that the intensity of sampling events is allowed to depend on the effective population size trajectory. We assume the coalescent and the sequentially Markov coalescent processes as generative models of genealogies. We include several coalescent simulation functions that are useful for testing our phylodynamics methods via simulation studies. We compare the performance and outputs of various methods implemented in phylodyn and outline their strengths and weaknesses. r package phylodyn is available at https://github.com/mdkarcher/phylodyn.
          Cover page: phylodyn: an R package for phylodynamic simulation and inferenceCreative Commons 'BY' version 4.0 license
          • Article
          • Peer Reviewed
          UC Irvine Previously Published Works (2015)
          MOTIVATION: The field of phylodynamics focuses on the problem of reconstructing population size dynamics over time using current genetic samples taken from the population of interest. This technique has been extensively used in many areas of biology but is particularly useful for studying the spread of quickly evolving infectious diseases agents, e.g. influenza virus. Phylodynamic inference uses a coalescent model that defines a probability density for the genealogy of randomly sampled individuals from the population. When we assume that such a genealogy is known, the coalescent model, equipped with a Gaussian process prior on population size trajectory, allows for nonparametric Bayesian estimation of population size dynamics. Although this approach is quite powerful, large datasets collected during infectious disease surveillance challenge the state-of-the-art of Bayesian phylodynamics and demand inferential methods with relatively low computational cost. RESULTS: To satisfy this demand, we provide a computationally efficient Bayesian inference framework based on Hamiltonian Monte Carlo for coalescent process models. Moreover, we show that by splitting the Hamiltonian function, we can further improve the efficiency of this approach. Using several simulated and real datasets, we show that our method provides accurate estimates of population size dynamics and is substantially faster than alternative methods based on elliptical slice sampler and Metropolis-adjusted Langevin algorithm. AVAILABILITY AND IMPLEMENTATION: The R code for all simulation studies and real data analysis conducted in this article are publicly available at http://www.ics.uci.edu/∼slan/lanzi/CODES.html and in the R package phylodyn available at https://github.com/mdkarcher/phylodyn. CONTACT: S.Lan@warwick.ac.uk or babaks@uci.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
            Cover page: An efficient Bayesian inference framework for coalescent-based nonparametric phylodynamics.
            • Article
            • Peer Reviewed
            UC Irvine Previously Published Works (2015)
            Both psychosis and anhedonia have been associated to some extent with striatal functioning. The current study examined whether either psychosis risk or social anhedonia was associated with performance on 3 tasks related to striatal functioning. Psychosis risk participants had extremely elevated Perceptual Aberration/Magical Ideation (PerMag) scores (n = 69), with 43% of psychosis risk participants also having semistructured interview-assessed psychotic-like experiences which further heightens their risk of psychotic disorder (Chapman, Chapman, Kwapil, Eckblad, & Zinser, 1994). Compared with both extremely elevated social anhedonia (n = 60) and control (n = 68) groups, the PerMag group exhibited poorer performance on 2 of the striatum-related tasks, the Weather Prediction Task (WPT) and the Learned Irrelevance Paradigm, but not on Finger Tapping. In addition, PerMag participants with psychotic-like experiences were especially impaired on the WPT. Overall, this study arguably provides the first evidence that psychosis risk but not social anhedonia is associated with performance on the WPT, a task thought to be strongly associated with activation in the associative striatum, and also suggests that the WPT might be especially useful as a behavioral measure of psychosis risk.
              Cover page: Examining Associations Between Psychosis Risk, Social Anhedonia, and Performance of Striatum-Related Behavioral Tasks
              • Article
              • Peer Reviewed
              UC Irvine Previously Published Works (2024)
              Bayesian inference is a popular and widely-used approach to infer phylogenies (evolutionary trees). However, despite decades of widespread application, it remains difficult to judge how well a given Bayesian Markov chain Monte Carlo (MCMC) run explores the space of phylogenetic trees. In this paper, we investigate the Monte Carlo error of phylogenies, focusing on high-dimensional summaries of the posterior distribution, including variability in estimated edge/branch (known in phylogenetics as split) probabilities and tree probabilities, and variability in the estimated summary tree. Specifically, we ask if there is any measure of effective sample size (ESS) applicable to phylogenetic trees which is capable of capturing the Monte Carlo error of these three summary measures. We find that there are some ESS measures capable of capturing the error inherent in using MCMC samples to approximate the posterior distributions on phylogenies. We term these tree ESS measures, and identify a set of three which are useful in practice for assessing the Monte Carlo error. Lastly, we present visualization tools that can improve comparisons between multiple independent MCMC runs by accounting for the Monte Carlo error present in each chain. Our results indicate that common post-MCMC workflows are insufficient to capture the inherent Monte Carlo error of the tree, and highlight the need for both within-chain mixing and between-chain convergence assessments.
                Cover page: How Trustworthy Is Your Tree? Bayesian Phylogenetic Effective Sample Size Through the Lens of Monte Carlo Error.
                • Article
                • Peer Reviewed
                UC Davis Previously Published Works (2020)
                Adverse childhood experiences (ACEs) are associated with increased risk for psychotic-like experiences (PLEs). However, ACEs and PLEs are also both associated with several shared factors (e.g., internalizing symptoms, suicidality). Few studies have explicitly examined whether the association between ACEs and PLEs remains over and above shared correlates. To address this question, using 10,800 9-11-year-olds, we examined whether ACEs and school-aged PLEs were associated when accounting for shared correlates, and whether there was evidence of mediation in associations between PLEs, ACEs, and these shared factors. Greater number of ACEs were associated with greater PLEs, including several specific ACEs (e.g., bullying). Importantly, ACEs and PLEs were related even when accounting for shared correlates. Further, PLEs partially mediated the relationships between ACEs and both internalizing symptoms and suicidality, including suicidal behavior. The current study helps clarify the nature of the associations between PLEs and ACE and has important clinical implications for addressing PLEs.
                  Cover page: Adverse childhood experiences and psychotic-like experiences are associated above and beyond shared correlates: Findings from the adolescent brain cognitive development study
                  • Article
                  • Peer Reviewed
                  UC Riverside Previously Published Works (2022)
                    Cover page: Laying hen production and welfare in a cage-free setting is impacted by the northern fowl miteCreative Commons 'BY-ND' version 4.0 license
                    • Article
                    • Peer Reviewed
                    UC Irvine Previously Published Works (2016)
                    Phylodynamics seeks to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. One way to accomplish this task formulates an observed sequence data likelihood exploiting a coalescent model for the sampled individuals' genealogy and then integrating over all possible genealogies via Monte Carlo or, less efficiently, by conditioning on one genealogy estimated from the sequence data. However, when analyzing sequences sampled serially through time, current methods implicitly assume either that sampling times are fixed deterministically by the data collection protocol or that their distribution does not depend on the size of the population. Through simulation, we first show that, when sampling times do probabilistically depend on effective population size, estimation methods may be systematically biased. To correct for this deficiency, we propose a new model that explicitly accounts for preferential sampling by modeling the sampling times as an inhomogeneous Poisson process dependent on effective population size. We demonstrate that in the presence of preferential sampling our new model not only reduces bias, but also improves estimation precision. Finally, we compare the performance of the currently used phylodynamic methods with our proposed model through clinically-relevant, seasonal human influenza examples.
                      Cover page: Quantifying and Mitigating the Effect of Preferential Sampling on Phylodynamic Inference
                      Top