UC Berkeley Previously Published Works

Deep Generative Models for Fast Photon Shower Simulation in ATLAS

(2024)

Abstract: The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques.

Software Performance of the ATLAS Track Reconstruction for LHC Run 3

(2024)

Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pile-up) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two.

Cover page of Gender, racial-ethnic, and socioeconomic disparities in the development of social-emotional competence among elementary school students

Gender, racial-ethnic, and socioeconomic disparities in the development of social-emotional competence among elementary school students

(2024)

Social-emotional competence (SEC) has been demonstrated to be a crucial factor for student mental health and is malleable through the high-quality implementation of effective school-based social and emotional learning (SEL) programs. SEL is now widely practiced in the United States as a Tier 1 strategy for the entire student body, yet it remains unclear whether disparities exist in the development of SEC across socioculturally classified subgroups of students. Also, despite the field’s widespread concern about teacher bias in assessing SEC within diverse student bodies, little evidence is available on the measurement invariance of the SEC assessment tools used to explore and facilitate SEC development. Based on a sociocultural view of student SEC development, this study aimed to measure and examine the extent to which gender, racial-ethnic, and socioeconomic disparities exist in SEC developmental trajectories during elementary school years. Specifically, using 3 years of SEC assessment data collected from a districtwide SEL initiative (N = 5452; Grades K–2 at baseline; nine measurement occasions), this study (a) tested the measurement invariance of a widely-used, teacher-rated SEC assessment tool (DESSA-Mini) across student gender, race and ethnicity, and socioeconomic status (SES); and (b) examined the extent to which multiyear SEC growth trajectories differed across these subgroups under a routine SEL practice condition. The invariance testing results supported strict factorial invariance of the DESSA-Mini across all the examined subgroups, thereby providing a foundation for valid cross-group comparisons of student SEC growth. The piecewise latent growth modeling results indicated that boys (vs. girls), Black students (vs. White students), Hispanic students (vs. White students), and low-income students (vs. middle-to-high-income students) started with a lower level of SEC, with these gaps being sustained or slightly widened throughout 3 elementary school years. Based on these findings, this study calls for future research that can inform practice efforts to ensure equitable SEC assessments and produce more equitable SEL outcomes, thereby promoting equity in school mental health.

Estimating geographic variation of infection fatality ratios during epidemics.

(2024)

OBJECTIVES: We aim to estimate geographic variability in total numbers of infections and infection fatality ratios (IFR; the number of deaths caused by an infection per 1,000 infected people) when the availability and quality of data on disease burden are limited during an epidemic. METHODS: We develop a noncentral hypergeometric framework that accounts for differential probabilities of positive tests and reflects the fact that symptomatic people are more likely to seek testing. We demonstrate the robustness, accuracy, and precision of this framework, and apply it to the United States (U.S.) COVID-19 pandemic to estimate county-level SARS-CoV-2 IFRs. RESULTS: The estimators for the numbers of infections and IFRs showed high accuracy and precision; for instance, when applied to simulated validation data sets, across counties, Pearson correlation coefficients between estimator means and true values were 0.996 and 0.928, respectively, and they showed strong robustness to model misspecification. Applying the county-level estimators to the real, unsimulated COVID-19 data spanning April 1, 2020 to September 30, 2020 from across the U.S., we found that IFRs varied from 0 to 44.69, with a standard deviation of 3.55 and a median of 2.14. CONCLUSIONS: The proposed estimation framework can be used to identify geographic variation in IFRs across settings.

Understanding Multiprogram Take-Up of Safety Net Programs Among California Families.

(2024)

INTRODUCTION: The U.S. safety net, which provides critical aid to households with low income, is composed of a patchwork of separate programs, and many people with low income benefit from accessing <1 program. However, little is known about multiprogram take-up, that is, participation conditioned on eligibility. This study examined individual and multiprogram take-up patterns and sociodemographic factors associated with multiprogram take-up of U.S. safety net programs. METHODS: The Assessing California Communities Experiences with Safety Net Supports study interviewed Californians and reviewed their 2019 tax forms between August 2020 and May 2021. Take-up of safety net programs was calculated among eligible participants (n=365), including the Earned Income Tax Credit; Supplemental Nutrition Assistance Program; the Special Supplemental Nutrition Program for Women, Infants, and Children; and Medicaid. Multivariable regressions identified sociodemographic factors associated with take-up of multiple programs. RESULTS: Take-up was highest for Medicaid (90.6%) and lowest for Supplemental Nutrition Assistance Program (57.5%). Among people who received benefits from at least 1 other program, take-up ranged from 81.7% to 84.8% for the Earned Income Tax Credit; 54.4%-62.0% for Supplemental Nutrition Assistance Program; 74.3%-80.1% for Special Supplemental Nutrition Program for Women, Infants, and Children; and 89.7%-98.1% for Medicaid. Having a lower income and being younger were associated with concurrent take-up of Supplemental Nutrition Assistance Program and Special Supplemental Nutrition Program for Women, Infants, and Children. Among Supplemental Nutrition Assistance Program and Special Supplemental Nutrition Program for Women, Infants, and Children recipients, having higher income, being older, and being primarily English speaking were associated with Earned Income Tax Credit take-up. CONCLUSIONS: Individual and multiprogram take-up vary between programs and by sociodemographic factors. Findings suggest opportunities to increase take-up of potentially synergistic programs by improving cross-program coordination, data sharing, and targeted recruitment of underenrolled subgroups (Supplemental Nutrition Assistance Program and Special Supplemental Nutrition Program for Women, Infants, and Children).

Lets Connect: Impact Evaluation of an Intervention to Reduce Mental Health Disparities Among People Who are LGBTQ+ .

(2024)

Lesbian, gay, bisexual, transgender, queer, or similarly identified (LGBTQ+) people experience substantial mental health disparities compared to heterosexuals. The Lets Connect intervention was designed to improve mental health outcomes for LGBTQ+ people. This impact evaluation aimed to assess effectiveness of this intervention during its pilot phase, using a single arm pilot trial. Respondents completed baseline surveys at intervention start, a post survey on the last day of the intervention (at 6 weeks), then a follow-up survey 6 weeks after the intervention ended (at 12 weeks). Pre-post differences in outcomes were analyzed using paired t-tests, chi-square tests, and generalized estimating equations to evaluate impact on mental health outcomes at 6 and 12 weeks, and identify characteristics associated with loss to follow-up. The average value of all three outcome measures decreased substantially between the baseline and post surveys; all of these differences were highly statistically significant, and further decreased between the end of the intervention at 6 weeks and the 12 week follow-up survey. Lets Connect participants did experience substantial improvements in mental health outcomes, on average, between the start and end of this intervention. Further study of this intervention using a randomized design and control group is warranted.

Editorial: Festschrift Coda

Buckland, Michael Keeble

(2024)

Cover page of Hypoxia exposure blunts angiogenic signaling and upregulates the antioxidant system in endothelial cells derived from elephant seals.

Hypoxia exposure blunts angiogenic signaling and upregulates the antioxidant system in endothelial cells derived from elephant seals.

(2024)

BACKGROUND: Elephant seals exhibit extreme hypoxemic tolerance derived from repetitive hypoxia/reoxygenation episodes they experience during diving bouts. Real-time assessment of the molecular changes underlying protection against hypoxic injury in seals remains restricted by their at-sea inaccessibility. Hence, we developed a proliferative arterial endothelial cell culture model from elephant seals and used RNA-seq, functional assays, and confocal microscopy to assess the molecular response to prolonged hypoxia. RESULTS: Seal and human endothelial cells exposed to 1% O2 for up to 6 h respond differently to acute and prolonged hypoxia. Seal cells decouple stabilization of the hypoxia-sensitive transcriptional regulator HIF-1α from angiogenic signaling. Rapid upregulation of genes involved in glutathione (GSH) metabolism supports the maintenance of GSH pools, and intracellular succinate increases in seal but not human cells. High maximal and spare respiratory capacity in seal cells after hypoxia exposure occurs in concert with increasing mitochondrial branch length and independent from major changes in extracellular acidification rate, suggesting that seal cells recover oxidative metabolism without significant glycolytic dependency after hypoxia exposure. CONCLUSIONS: We found that the glutathione antioxidant system is upregulated in seal endothelial cells during hypoxia, while this system remains static in comparable human cells. Furthermore, we found that in contrast to human cells, hypoxia exposure rapidly activates HIF-1 in seal cells, but this response is decoupled from the canonical angiogenesis pathway. These results highlight the unique mechanisms that confer extraordinary tolerance to limited oxygen availability in a champion diving mammal.

Reinvented: An Attosecond Chemist

Leone, Stephen R

(2024)

Attosecond science requires a substantial rethinking of how to make measurements on very short timescales; how to acquire the necessary equipment, technology, and personnel; and how to build a set of laboratories for such experiments. This entails a rejuvenation of the author in many respects, in the laboratory itself, with regard to students and postdocs, and in generating funding for research. It also brings up questions of what it means to do attosecond science, and the discovery of the power of X-ray spectroscopy itself, which complements the short timescales addressed. The lessons learned, expressed in the meanderings of this autobiographical article, may be of benefit to others who try to reinvent themselves. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 75 is April 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.