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Open Access Publications from the University of California

Scholarly Works (8 results)

  • Article
UC Irvine Law Review , Volume 13, Issue 4 (2023)

Incarcerated people create, lead, and participate in a variety of associations in prison. These associations educate and advocate for members, serve the broader prison population, cultivate social bonds, and promote the individual growth that happens in relationship with others. The associations do so in the face of byzantine regulations that burden their formation, membership, and operations. These rules go unchecked because the constitutional right of association is under protected in prisons. The deferential Turner v. Safley test for rights violations in prison prizes ease of prison administration over rights protection. Thus, though the right of association is a fundamental constitutional right, in prison it does not enjoy the level of protection of a fundamental right.

This Article builds a conceptual framework of associations in prison. It provides a typology of the organizations that exist in prisons today. Most of these operate as they would on the outside, as part of civil society, which fills gaps in government provision. The Article also explores the kinds of effects the associations have on members, which are democracyenhancing in nature as well as communitarian and liberal. The Article then maps the types of limitations imposed on the groups by regulations and rules. By examining the unique challenges produced by and faced by these associations, the Article shows that broader associational jurisprudence can better protect fundamental aspects of associations by grappling with issues that arise in the unique context of incarceration.

    Cover page: Associations in Prison
    • Thesis
    • Peer Reviewed
    UCLA Electronic Theses and Dissertations (2024)

    Bounded-confidence models (BCMs) are a type of model of opinion dynamics with continuous-valued opinions. The two most popular BCMs are the Deffuant--Weisbuch (DW) model [DNA00] and the Hegselmann--Krause (HK) model [HK02]. In a BCM, interacting pairs of agents only influence each other if their opinions differ by less than some “confidence bound” between them.One major challenge in the study of opinion dynamics is making models more realistic and applicable to real-world data and situations. In this dissertation, we develop and study three generalizations of BCMs. They each incorporate some mechanism to make them more realistic, while maintaining tractability.

    We first develop and study a generalization of the DW model that uses node weights to model heterogeneous agent-activity levels. The node weights in this BCM allow us to consider individuals in a social network that share their ideas and opinions more frequently than others. Using numerical simulations, we systematically investigate the effects of node weights, which we assign uniformly at random to the nodes. We demonstrate that introducing heterogeneous node weights results in longer convergence times and more opinion fragmentation than in an associated baseline DW model.

    We then investigate BCMs in which each pair of agents has a distinct confidence bound that changes when the pair interacts. The confidence bounds in these BCMs encode the mutual willingness of agents to consider each other's opinions. We demonstrate numerically that our adaptive BCMs tend to promote consensus and yield longer convergence times than the associated baseline BCMs. We also show that these adaptive BCMs can have neighboring agents that converge to the same opinion but are not receptive to each other. This qualitative behavior does not occur in the associated baseline BCMs.

    Finally, we study BCMs that have multi-dimensional opinions that consist of multiple interdependent topics. When a pair of agents interact on a topic, whether or not they compromise their opinions depends on the differences in their opinions on all topics. Using numerical simulations, we demonstrate for these BCMs that the choice of initial opinion distribution has a large effect on the amount of opinion fragmentation.

      Cover page: Some Generalizations of Bounded-Confidence Models of Opinion Dynamics
      • Article
      • Peer Reviewed
      UC Berkeley Previously Published Works (2012)

      Background

      Eukaryotic cell proliferation involves DNA replication, a tightly regulated process mediated by a multitude of protein factors. In budding yeast, the initiation of replication is facilitated by the heterohexameric origin recognition complex (ORC). ORC binds to specific origins of replication and then serves as a scaffold for the recruitment of other factors such as Cdt1, Cdc6, the Mcm2-7 complex, Cdc45 and the Dbf4-Cdc7 kinase complex. While many of the mechanisms controlling these associations are well documented, mathematical models are needed to explore the network's dynamic behaviour. We have developed an ordinary differential equation-based model of the protein-protein interaction network describing replication initiation.

      Results

      The model was validated against quantified levels of protein factors over a range of cell cycle timepoints. Using chromatin extracts from synchronized Saccharomyces cerevisiae cell cultures, we were able to monitor the in vivo fluctuations of several of the aforementioned proteins, with additional data obtained from the literature. The model behaviour conforms to perturbation trials previously reported in the literature, and accurately predicts the results of our own knockdown experiments. Furthermore, we successfully incorporated our replication initiation model into an established model of the entire yeast cell cycle, thus providing a comprehensive description of these processes.

      Conclusions

      This study establishes a robust model of the processes driving DNA replication initiation. The model was validated against observed cell concentrations of the driving factors, and characterizes the interactions between factors implicated in eukaryotic DNA replication. Finally, this model can serve as a guide in efforts to generate a comprehensive model of the mammalian cell cycle in order to explore cancer-related phenotypes.
        Cover page: A quantitative model of the initiation of DNA replication in Saccharomyces cerevisiae predicts the effects of system perturbations
        • Article
        • Peer Reviewed
        UC Berkeley Previously Published Works (2018)
        Dynamic nuclear polarization via contact with electronic spins has emerged as an attractive route to enhance the sensitivity of nuclear magnetic resonance beyond the traditional limits imposed by magnetic field strength and temperature. Among the various alternative implementations, the use of nitrogen vacancy (NV) centers in diamond-a paramagnetic point defect whose spin can be optically polarized at room temperature-has attracted widespread attention, but applications have been hampered by the need to align the NV axis with the external magnetic field. We overcome this hurdle through the combined use of continuous optical illumination and a microwave sweep over a broad frequency range. As a proof of principle, we demonstrate our approach using powdered diamond with which we attain bulk 13C spin polarization in excess of 0.25% under ambient conditions. Remarkably, our technique acts efficiently on diamond crystals of all orientations and polarizes nuclear spins with a sign that depends exclusively on the direction of the microwave sweep. Our work paves the way toward the use of hyperpolarized diamond particles as imaging contrast agents for biosensing and, ultimately, for the hyperpolarization of nuclear spins in arbitrary liquids brought in contact with their surface.
          Cover page: Orientation-independent room temperature optical 13C hyperpolarization in powdered diamond
          • Article
          • Peer Reviewed
          UCLA Previously Published Works (2021)
          We conducted a search for technosignatures in 2018 and 2019 April with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. These observations focused on regions surrounding 31 Sun-like stars near the plane of the Galaxy. We present the results of our search for narrowband signals in this data set, as well as improvements to our data processing pipeline. Specifically, we applied an improved candidate signal detection procedure that relies on the topographic prominence of the signal power, which nearly doubles the signal detection count of some previously analyzed data sets. We also improved the direction-of-origin filters that remove most radio frequency interference (RFI) to ensure that they uniquely link signals observed in separate scans. We performed a preliminary signal injection and recovery analysis to test the performance of our pipeline. We found that our pipeline recovers 93% of the injected signals over the usable frequency range of the receiver and 98% if we exclude regions with dense RFI. In this analysis, 99.73% of the recovered signals were correctly classified as technosignature candidates. Our improved data processing pipeline classified over 99.84% of the ∼26 million signals detected in our data as RFI. Of the remaining candidates, 4539 were detected outside of known RFI frequency regions. The remaining candidates were visually inspected and verified to be of anthropogenic nature. Our search compares favorably to other recent searches in terms of end-to-end sensitivity, frequency drift rate coverage, and signal detection count per unit bandwidth per unit integration time.
            Cover page: A Search for Technosignatures around 31 Sun-like Stars with the Green Bank Telescope at 1.15–1.73 GHz
            • Article
            • Peer Reviewed
            UCLA Previously Published Works (2022)
            BACKGROUND AND OBJECTIVE: Cerebral venous thrombosis (CVT) is a rare cause of stroke carrying a nearly 4% risk of recurrence after 1 year. There are limited data on predictors of recurrent venous thrombosis in patients with CVT. In this study, we aim to identify those predictors. METHODS: This is a secondary analysis of the ACTION-CVT study which is a multicenter international study of consecutive patients hospitalized with a diagnosis of CVT over a 6-year period. Patients with cancer-associated CVT, CVT during pregnancy, or CVT in the setting of known antiphospholipid antibody syndrome were excluded per the ACTION-CVT protocol. The study outcome was recurrent venous thrombosis defined as recurrent venous thromboembolism (VTE) or de novo CVT. We compared characteristics between patients with vs without recurrent venous thrombosis during follow-up and performed adjusted Cox regression analyses to determine important predictors of recurrent venous thrombosis. RESULTS: Nine hundred forty-seven patients were included with a mean age of 45.2 years, 63.9% were women, and 83.6% had at least 3 months of follow-up. During a median follow-up of 308 (interquartile range 120-700) days, there were 5.05 recurrent venous thromboses (37 VTE and 24 de novo CVT) per 100 patient-years. Predictors of recurrent venous thrombosis were Black race (adjusted hazard ratio [aHR] 2.13, 95% CI 1.14-3.98, p = 0.018), history of VTE (aHR 3.40, 95% CI 1.80-6.42, p < 0.001), and the presence of one or more positive antiphospholipid antibodies (aHR 3.85, 95% CI 1.97-7.50, p < 0.001). Sensitivity analyses including events only occurring on oral anticoagulation yielded similar findings. DISCUSSION: Black race, history of VTE, and the presence of one or more antiphospholipid antibodies are associated with recurrent venous thrombosis among patients with CVT. Future studies are needed to validate our findings to better understand mechanisms and treatment strategies in patients with CVT.
              Cover page: Predictors of Recurrent Venous Thrombosis After Cerebral Venous Thrombosis: Analysis of the ACTION-CVT Study.
              • Article
              • Peer Reviewed
              UC San Francisco Previously Published Works (2019)
              This letter addresses the controversial issue of the use of oral corticosteroids during wheezing exacerbations in preschool-aged children by demonstrating findings of a prematurely terminated multi-center clinical trial, discussing lessons learned, and suggesting future directions.
                Cover page: Challenges in assessing the efficacy of systemic corticosteroids for severe wheezing episodes in preschool children
                • Article
                • Peer Reviewed
                UC San Francisco Previously Published Works (2022)
                Asthma is a heterogeneous disease, with multiple underlying inflammatory pathways and structural airway abnormalities that impact disease persistence and severity. Recent progress has been made in developing targeted asthma therapeutics, especially for subjects with eosinophilic asthma. However, there is an unmet need for new approaches to treat patients with severe and exacerbation-prone asthma, who contribute disproportionately to disease burden. Extensive deep phenotyping has revealed the heterogeneous nature of severe asthma and identified distinct disease subtypes. A current challenge in the field is to translate new and emerging knowledge about different pathobiologic mechanisms in asthma into patient-specific therapies, with the ultimate goal of modifying the natural history of disease. Here, we describe the Precision Interventions for Severe and/or Exacerbation-Prone Asthma (PrecISE) Network, a groundbreaking collaborative effort of asthma researchers and biostatisticians from around the United States. The PrecISE Network was designed to conduct phase II/proof-of-concept clinical trials of precision interventions in the population with severe asthma, and is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health. Using an innovative adaptive platform trial design, the PrecISE Network will evaluate up to 6 interventions simultaneously in biomarker-defined subgroups of subjects. We review the development and organizational structure of the PrecISE Network, and choice of interventions being studied. We hope that the PrecISE Network will enhance our understanding of asthma subtypes and accelerate the development of therapeutics for severe asthma.
                  Cover page: The Precision Interventions for Severe and/or Exacerbation-Prone (PrecISE) Asthma Network: An overview of Network organization, procedures, and interventions
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