Search

Your search keyword '"Palmer BE"' showing total 367,157 results
Start Over Author "Palmer BE"
367,157 results on '"Palmer BE"'

1. The Unrealized Promise of College-in-Prison: Financial Hurdles to Reenrollment and Completion in the Era of Pell Reinstatement

Author

Julia Bowling, Pavithra Nagarajan, Kristen Parsons, and Neal A. Palmer

Abstract

College-in-prison programs are positioned to expand substantially under the reinstatement of Pell Grant eligibility for people in prison. While this change will enable more students who have been systemically excluded from higher education to attend college, degree completion is rare during incarceration and post-release. Student perspectives can shed light on both the value of college-in-prison and the financial barriers to realizing its value. This study analyzes data from 12 focus groups with 105 total college-in-prison student participants, 114 student survey responses, and 45 stakeholder interviews. The data were collected between 2018-2022 during a process evaluation of the College-in-Prison Reentry Initiative, which provided funding to college-in-prison programs in New York State as part of the Manhattan District Attorney's Office Criminal Justice Investment Initiative. The findings demonstrate that students value college-in-prison, describing how it fostered self-reflection and personal growth and provided them with a skillset that may help them gain employment upon release. However, students also raised concerns about reenrolling and completing their degrees following release. Intentional, holistic reentry support could address the largely financial barriers to reenrollment. In so doing, students will be more likely to earn their college degrees after incarceration and experience the full value of a college education.

Published
2024

2. Enhanced Federated Anomaly Detection Through Autoencoders Using Summary Statistics-Based Thresholding

Author

Laridi, Sofiane, Palmer, Gregory, and Tam, Kam-Ming Mark

Subjects
Computer Science - Machine Learning
Abstract

In Federated Learning (FL), anomaly detection (AD) is a challenging task due to the decentralized nature of data and the presence of non-IID data distributions. This study introduces a novel federated threshold calculation method that leverages summary statistics from both normal and anomalous data to improve the accuracy and robustness of anomaly detection using autoencoders (AE) in a federated setting. Our approach aggregates local summary statistics across clients to compute a global threshold that optimally separates anomalies from normal data while ensuring privacy preservation. We conducted extensive experiments using publicly available datasets, including Credit Card Fraud Detection, Shuttle, and Covertype, under various data distribution scenarios. The results demonstrate that our method consistently outperforms existing federated and local threshold calculation techniques, particularly in handling non-IID data distributions. This study also explores the impact of different data distribution scenarios and the number of clients on the performance of federated anomaly detection. Our findings highlight the potential of using summary statistics for threshold calculation in improving the scalability and accuracy of federated anomaly detection systems.

Published
2024

3. Optimization of LYSO crystals and SiPM parameters for the CMS MIP timing detector

Author

Addesa, F., Anderson, T., Barria, P., Basile, C., Benaglia, A., Bertoni, R., Bethani, A., Bianco, R., Bornheim, A., Boldrini, G., Boletti, A., Bulla, A., Campana, M., Cardwell, B., Carniti, P., Cetorelli, F., De Guio, F., De Leo, K., De Riggi, F., Dervan, J., Fernandez, E., Gaile, A., Gallinaro, M., Ghezzi, A., Gotti, C., Goldouzian, R., Guglielmi, V., Heering, A., Hu, Z., Jose, M., Karneyeu, A., Krishna, A., Kronheim, B., Kuo, C., La Torre, A., Li, A., Lombardi, F., Lucchini, M. T., Malberti, M., Mao, Y., Marzocchi, B., Meridiani, P., Musienko, Y., Neu, C., Organtini, G., Orimoto, T., Palmer, C., Paganoni, M., Palluotto, S., Paramatti, R., Pessina, G., Perelman, R. T., Quaranta, C., Redaelli, N., Redaelli, S., Gutiérrez, G. Reales, Ronchi, S., Santanastasio, F., Schmidt, I., Silva, J. C., Sorrentino, G., Sun, X., de Fatis, T. Tabarelli, Tosi, M., Ujvari, B., Varela, J., Wang, J., Wayne, M., White, S., Zhang, L., and Zhang, M.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

For the High-Luminosity (HL-LHC) phase, the upgrade of the Compact Muon Solenoid (CMS) experiment at CERN will include a novel MIP Timing Detector (MTD). The central part of MTD, the barrel timing layer (BTL), is designed to provide a measurement of the time of arrival of charged particles with a precision of 30 ps at the beginning of HL-LHC, progressively degrading to 60 ps while operating in an extremely harsh radiation environment for over a decade. In this paper we present a comparative analysis of the time resolution of BTL module prototypes made of LYSO:Ce crystal bars read out by silicon photo-multipliers (SiPMs). The timing performance measured in beam test campaigns is presented for prototypes with different construction and operation parameters, such as different SiPM cell sizes (15, 20, 25 and 30 $\rm \mu m$), SiPM manufacturers and crystal bar thicknesses. The evolution of time resolution as a function of the irradiation level has been studied using non-irradiated SiPMs as well as SiPMs exposed up to $2\times 10^{14}~n_{eq}/cm^2$ fluence. The key parameters defining the module time resolution such as SiPM characteristics (gain, photon detection efficiency, radiation induced dark count rate) and crystal properties (light output and dimensions) are discussed. These results have informed the final choice of the MTD barrel sensor configuration and offer a unique starting point for the design of future large-area scintillator-based timing detectors in either low or high radiation environments.

Published
2024

4. Boosting the Capabilities of Compact Models in Low-Data Contexts with Large Language Models and Retrieval-Augmented Generation

Author

Shandilya, Bhargav and Palmer, Alexis

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

The data and compute requirements of current language modeling technology pose challenges for the processing and analysis of low-resource languages. Declarative linguistic knowledge has the potential to partially bridge this data scarcity gap by providing models with useful inductive bias in the form of language-specific rules. In this paper, we propose a retrieval augmented generation (RAG) framework backed by a large language model (LLM) to correct the output of a smaller model for the linguistic task of morphological glossing. We leverage linguistic information to make up for the lack of data and trainable parameters, while allowing for inputs from written descriptive grammars interpreted and distilled through an LLM. The results demonstrate that significant leaps in performance and efficiency are possible with the right combination of: a) linguistic inputs in the form of grammars, b) the interpretive power of LLMs, and c) the trainability of smaller token classification networks. We show that a compact, RAG-supported model is highly effective in data-scarce settings, achieving a new state-of-the-art for this task and our target languages. Our work also offers documentary linguists a more reliable and more usable tool for morphological glossing by providing well-reasoned explanations and confidence scores for each output., Comment: 13 pages, 1 figure, 5 tables, submitted to COLING 2025

Published
2024

5. Infector characteristics exposed by spatial analysis of SARS-CoV-2 sequence and demographic data analysed at fine geographical scales

Author

Gamża, Anna, Lycett, Samantha, Harvey, Will, Hughes, Joseph, Nickbakhsh, Sema, Robertson, David L, Palmer, Alison Smith, Wood, Anthony, and Kao, Rowland

Subjects
Quantitative Biology - Populations and Evolution, Quantitative Biology - Quantitative Methods
Abstract

Characterising drivers of SARS-CoV-2 circulation is crucial for understanding COVID-19 because of the severity of control measures adopted during the pandemic. Whole genome sequence data augmented with demographic metadata provides the best opportunity to do this. We use Random Forest Decision Tree models to analyse a combination of over 4000 SARS-CoV2 sequences from a densely sampled, mixed urban and rural population (Tayside) in Scotland in the period from August 2020 to July 2021, with fine scale geographical and socio-demographic metadata. Comparing periods in versus out of "lockdown" restrictions, we show using genetic distance relationships that individuals from more deprived areas are more likely to get infected during lockdown but less likely to spread the infection further. As disadvantaged communities were the most affected by both COVID-19 and its restrictions, our finding has important implications for informing future approaches to control future pandemics driven by similar respiratory infections., Comment: 186 pages, approx. 48 figures (including Methods ans Supplementary Information)

Published
2024

6. LEROjD: Lidar Extended Radar-Only Object Detection

Author

Palmer, Patrick, Krüger, Martin, Schütte, Stefan, Altendorfer, Richard, Adam, Ganesh, and Bertram, Torsten

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Robotics
Abstract

Accurate 3D object detection is vital for automated driving. While lidar sensors are well suited for this task, they are expensive and have limitations in adverse weather conditions. 3+1D imaging radar sensors offer a cost-effective, robust alternative but face challenges due to their low resolution and high measurement noise. Existing 3+1D imaging radar datasets include radar and lidar data, enabling cross-modal model improvements. Although lidar should not be used during inference, it can aid the training of radar-only object detectors. We explore two strategies to transfer knowledge from the lidar to the radar domain and radar-only object detectors: 1. multi-stage training with sequential lidar point cloud thin-out, and 2. cross-modal knowledge distillation. In the multi-stage process, three thin-out methods are examined. Our results show significant performance gains of up to 4.2 percentage points in mean Average Precision with multi-stage training and up to 3.9 percentage points with knowledge distillation by initializing the student with the teacher's weights. The main benefit of these approaches is their applicability to other 3D object detection networks without altering their architecture, as we show by analyzing it on two different object detectors. Our code is available at https://github.com/rst-tu-dortmund/lerojd, Comment: Accepted for publication as ECCV 2024

Published
2024

7. Performance Portable Monte Carlo Neutron Transport in MCDC via Numba

Author

Morgan, Joanna Piper, Variansyah, Ilham, Cuneo, Braxton, Palmer, Todd S., and Niemeyer, Kyle E.

Subjects
Physics - Computational Physics
Abstract

Finding a software engineering approach that allows for portability, rapid development, open collaboration, and performance for high performance computing on GPUs and CPUs is a challenge. We implement a portability scheme using the Numba compiler for Python in Monte Carlo / Dynamic Code (MC/DC), a new neutron transport application for rapid Monte Carlo methods development. Using this scheme, we have built MC/DC as a single source, single language, single compiler application that can run as a pure Python, compiled CPU, or compiled GPU solver. In GPU mode, we use Numba paired with an asynchronous GPU scheduler called Harmonize to increase GPU performance. We present performance results for a time-dependent problem on both the CPU and GPU and compare them to a production code., Comment: 11 pages, 5 figures

Published
2024

8. Generalized geometric speed limits for quantum observables

Author

Bringewatt, Jacob, Steffen, Zach, Ritter, Martin A., Ehrenberg, Adam, Wang, Haozhi, Palmer, B. S., Kollár, Alicia J., Gorshkov, Alexey V., and García-Pintos, Luis Pedro

Subjects
Quantum Physics
Abstract

Leveraging quantum information geometry, we derive generalized quantum speed limits on the rate of change of the expectation values of observables. These bounds subsume and, for Hilbert space dimension $\geq 3$, tighten existing bounds -- in some cases by an arbitrarily large multiplicative constant. The generalized bounds can be used to design "fast" Hamiltonians that enable the rapid driving of the expectation values of observables with potential applications e.g.~to quantum annealing, optimal control, variational quantum algorithms, and quantum sensing. Our theoretical results are supported by illustrative examples and an experimental demonstration using a superconducting qutrit. Possibly of independent interest, along the way to one of our bounds we derive a novel upper bound on the generalized quantum Fisher information with respect to time (including the standard symmetric logarithmic derivative quantum Fisher information) for unitary dynamics in terms of the variance of the associated Hamiltonian and the condition number of the density matrix., Comment: 19 pages, 5 figures

Published
2024

9. Two-neutrino double electron capture of $^{124}$Xe in the first LUX-ZEPLIN exposure

Author

Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Balashov, S., Bang, J., Bargemann, J. W., Barillier, E. E., Beattie, K., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Bishop, E., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Burdin, S., Buuck, M., Carmona-Benitez, M. C., Carter, M., Chawla, A., Chen, H., Chin, Y. T., Chott, N. I., Converse, M. V., Coronel, R., Cottle, A., Cox, G., Curran, D., Dahl, C. E., David, A., Delgaudio, J., Dey, S., de Viveiros, L., Di Felice, L., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Dubey, S., Eriksen, S. R., Fan, A., Fearon, N. M., Fieldhouse, N., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T. M. A., Gaitskell, R. J., Geffre, A., Genovesi, J., Ghag, C., Gibbons, R., Gokhale, S., Green, J., van der Grinten, M. G. D., Haiston, J. J., Hall, C. R., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Hernandez, M. A., Hertel, S. A., Heuermann, G., Homenides, G. J., Horn, M., Huang, D. Q., Hunt, D., Jacquet, E., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., Kannichankandy, M., Khaitan, D., Khazov, A., Khurana, I., Kim, J., Kim, Y. D., Kingston, J., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., Kudryavtsev, V. A., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Lippincott, W. H., Lopes, M. I., Lorenzon, W., Lu, C., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Maupin, C., McCarthy, M. E., McDowell, G., McKinsey, D. N., McLaughlin, J., McLaughlin, J. B., McMonigle, R., Mizrachi, E., Monte, A., Monzani, M. E., Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naylor, A., Nelson, H. N., Neves, F., Nguyen, A., O'Brien, C. L., Olcina, I., Oliver-Mallory, K. C., Orpwood, J., Oyulmaz, K. Y, Palladino, K. J., Palmer, J., Pannifer, N. J., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Qie, Y., Reichenbacher, J., Rhyne, C. A., Riffard, Q., Rischbieter, G. R. C., Ritchey, E., Riyat, H. S., Rosero, R., Rushton, T., Rynders, D., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Sehr, G., Shafer, B., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Siniscalco, J., Smith, R., Solovov, V. N., Sorensen, P., Soria, J., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Szydagis, M., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Vacheret, A., Vaitkus, A. C., Valentino, O., Velan, V., Wang, A., Wang, J. J., Wang, Y., Watson, J. R., Weeldreyer, L., Whitis, T. J., Wild, K., Williams, M., Wisniewski, W. J., Wolf, L., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xu, J., Xu, Y., Yeh, M., Yeum, D., Zha, W., and Zweig, E. A.

Subjects
Nuclear Experiment, Physics - Instrumentation and Detectors
Abstract

The broad physics reach of the LUX-ZEPLIN (LZ) experiment covers rare phenomena beyond the direct detection of dark matter. We report precise measurements of the extremely rare decay of $^{124}$Xe through the process of two-neutrino double electron capture (2$\nu$2EC), utilizing a $1.39\,\mathrm{kg} \times \mathrm{yr}$ isotopic exposure from the first LZ science run. A half-life of $T_{1/2}^{2\nu2\mathrm{EC}} = (1.09 \pm 0.14_{\text{stat}} \pm 0.05_{\text{sys}}) \times 10^{22}\,\mathrm{yr}$ is observed with a statistical significance of $8.3\,\sigma$, in agreement with literature. First empirical measurements of the KK capture fraction relative to other K-shell modes were conducted, and demonstrate consistency with respect to recent signal models at the $1.4\,\sigma$ level., Comment: 15 pages, 3 figures

Published
2024

10. Validation Requirements for AI-based Intervention-Evaluation in Aging and Longevity Research and Practice

Author

Fuellen, Georg, Kulaga, Anton, Lobentanzer, Sebastian, Unfried, Maximilian, Avelar, Roberto, Palmer, Daniel, and Kennedy, Brian K.

Subjects
Computer Science - Human-Computer Interaction, 68T01 General topics in artificial intelligence
Abstract

The field of aging and longevity research is overwhelmed by vast amounts of data, calling for the use of Artificial Intelligence (AI), including Large Language Models (LLMs), for the evaluation of geroprotective interventions. Such evaluations should be correct, useful, comprehensive, explainable, and they should consider causality, interdisciplinarity, adherence to standards, longitudinal data and known aging biology. In particular, comprehensive analyses should go beyond comparing data based on canonical biomedical databases, suggesting the use of AI to interpret changes in biomarkers and outcomes. Our requirements motivate the use of LLMs with Knowledge Graphs and dedicated workflows employing, e.g., Retrieval-Augmented Generation. While naive trust in the responses of AI tools can cause harm, adding our requirements to LLM queries can improve response quality, calling for benchmarking efforts and justifying the informed use of LLMs for advice on longevity interventions., Comment: 11 pages, 1 Figure, 1 Table

Published
2024

11. Exploring the Use and Impact of Online Digital Resources in a Mathematics Module

Author

Violeta Morari, Catherine Palmer, Clodagh Carroll, Declan Manning, and Shane O’Rourke

Abstract

This study examines the relationship between student engagement with digital resources and final module grade in a particular mathematics module delivered online in an Irish technological university. Measures of student engagement with the module are defined and calculated using data from virtual learning environment. These measures are analyzed to provide a description of students' online study habits. We make an initial distinction between resources provided by the lecturer that are "lecture-based" or "exam-focused." We further categorize student engagement with these resources as "active" or "passive" and consider these measures of student engagement in an online context. With these categories and measures in mind, we then examine the correlation between student engagement and final module grade using a multivariable linear regression model.

Published
2024

12. The Effectiveness of Song and Music as Pedagogical Tools in Elementary School Science Lessons: A Systematic Review of Literature

Author

Tracey-Ann Palmer and Emily Booth

Abstract

This literature review offers compelling evidence for the significant role music and song can play in cultivating student engagement in elementary school science lessons. With students disengaging from science education, there is concern about the lack of necessary scientific literacy skills required in today's world. To explore whether music and song could be used engage students in science we conducted a thorough search of composite education databases for relevant scholarly articles published 1993-2021. Synthesis of the resulting 26 articles revealed four themes: the common goal of engagement, evidence of learning improvement, broad utility of music and songs as pedagogical tools, and limited long-term studies. While acknowledging the limited evidence presented in these articles, we emphasize that incorporating music and song into science lessons not only enriches the educational environment but also contributes to an arts-infused education known to enhance student performance across a wide range of curriculum domains. We recommend further research with a particular focus on investigating the impact of music and song on science engagement and learning over the long-term in elementary school science classrooms.

Published
2024

13. Testing a Novel Extended Educational Technology Acceptance Model Using Student Attitudes towards Virtual Classrooms

Author

Andrew Kemp, Edward Palmer, Peter Strelan, and Helen Thompson

Abstract

Many technology acceptance models used in education were originally designed for general technologies and later adopted by education researchers. This study extends Davis' technology acceptance model to specifically evaluate educational technologies in higher education, focusing on virtual classrooms. Prior research informed the construction of the model, which contains perceived usefulness, perceived ease of use, behavioural intent, access and convenience, system attributes and self-efficacy. Education-specific constructs include cognitive engagement, feedback, instructor practice and class interaction and communication. Additionally, a new construct called comfort and well-being is introduced. A total of 427 valid responses on a 5-point Likert scale were received from university students. Exploratory factor analysis, confirmatory factor analysis and structural equation modelling were used to analyse the data. The model accounted for 78% of variance of behavioural intent, with comfort and well-being demonstrating the strongest influence. Cognitive engagement, access and convenience influenced perceived usefulness, and system attributes and self-efficacy influenced perceived ease of use. Feedback, instructor practice and class interaction and communication were not significant as educational constructs for this cohort. Based on this analysis, a final extended educational technology acceptance model (EETAM) is proposed for further use and testing.

Published
2024
Full Text
View/download PDF

14. Music Education and Neurophysiological Regulation in Early Childhood: Should Teachers Guide or Get out of the Way?

Author

Eleanor D. Brown, Steven J. Holochwost, Dennie Palmer Wolf, Alyssa A. Allen, Mallory L. Garnett, Blanca Velazquez-Martin, Suzanne Varnell, and Jessa L. Malatesta

Abstract

Access to high-quality early music education programs may mitigate the effects of poverty on the hypothalamic-pituitary-adrenal (HPA) axis, but fundamental questions remain about the role of early educators in conveying these benefits. In the current study, we measured the basal or resting cortisol levels of 76 children (M[subscript age] = 4.17 years; 42% female) over the course of the school day while they attended a Head Start preschool that included early music education classes. The results of a series of hierarchical linear models (HLMs) indicated that child-directed music and movement activities during these classes were associated with lower levels of cortisol (relative to teacher-directed activities; B = -0.019, p = 0.013), as were higher quality teacher-child interactions (B = -0.018, p = 0.013); both associations were moderated by child age. We discuss the implications of these results for future educational neuroscience research that seeks to inform early education programs for young children placed at risk by poverty.

Published
2024
Full Text
View/download PDF

15. Using Design Experiment Processes to Adjust Money Habits of Adults with Disabilities

Author

Anthony M. Rodriguez, Susan B. Palmer, and Frances R. Duff

Abstract

As more adults with intellectual and developmental disabilities move into inclusive settings in the community, it is essential to address budgeting and finance issues to avoid real concerns of financial exploitation. Adults with intellectual and developmental disability often comprise the "working poor", even if they are among the 20% who are fortunate enough to have access to community-based, paid employment at above minimum wage. Those fortunate enough to be placed on government assistance (1 in 4 are still waiting for funded services) soon realize that this benefit comes with restrictions on their income and savings. These restrictions impact work options, pay range, and benefits. Each person's budget leaves little for saving and discretionary spending. Our present situation of rising inflation compounds these already significant concerns.

Published
2024
Full Text
View/download PDF

16. 'We Shouldn't Have to Choose between Maintaining and Bettering Our Lives': An Analysis of Older and Parenting College Students

Author

New America, Center on Education and Labor, Love, Ivy, Conroy, Edward, Palmer, Iris, and Sattelmeyer, Sarah

Abstract

The resources that federal financial aid, state financial aid, and federal public benefits programs provide, when they operate effectively, are critical to older students and students with children. This report seeks to shed light on how these programs are functioning by analyzing data and policies across four states--Colorado, Missouri, North Carolina, and Texas. We analyzed the designs of student financial aid programs to see how many state financial aid resources older students and student parents receive. We chose these states as test cases because they had state representative data in the 2018 National Postsecondary Student Aid Study, a survey administered by the U.S. Department of Education, and they were geographically, politically, and demographically diverse. In addition to examining financial aid programs, we also looked at states' public benefit program designs and policies and we conducted focus groups with older students and student parents in each state. This additional analysis provides a view of what it is like to rely on the system meant to support students to and through college, where it is falling short, and why. We found that Colorado, while far from perfect, designed its financial aid and safety net programs to provide the most robust support for adult and parenting students to enroll in and attend its institutions of higher education. Missouri and Texas provided the weakest support. North Carolina fell somewhere in the middle. We end this report by suggesting several recommendations for policymakers and stakeholders looking to design or reform state financial aid and safety net programs. Within budget constraints, they should adjust eligibility criteria for state aid programs so older students and student parents have the same access to grant programs as students leaving high school. Where states have flexibility in administering federal public benefit programs, they should use that flexibility to ease eligibility criteria and expand access. And they should communicate opportunities and fund supports to help older students and student parents to go to college and access public benefits.

Published
2023

17. Community Colleges and Apprenticeship: The Promise, the Challenge

Author

New America, Center on Education and Labor, Palmer, Iris, Prebil, Michael, and Rush-Marlowe, Rachel

Abstract

To better understand the challenges and opportunities facing community colleges that want to expand apprenticeship opportunities to their students, New America conducted a year-long study. We created an advisory committee to guide this work and spoke to apprenticeship, workforce development, and community college leaders about the community colleges role in expanding apprenticeship. Based on these conversations, we chose case studies and conducted in-depth interviews with leaders from the Community College System of New Hampshire's ApprenticeshipNH, Arapahoe in Colorado, San Jacinto in Texas, and Howard Community College in Maryland's programs in IT and cybersecurity, and Coastal Alabama Community College's nursing apprenticeship. Each of these colleges found a different way to fill the role of intermediary, taking on funding from different sources, using a mix of strategies for sponsorship, and finding place-based approaches to strengthening workforce partnerships. In a variety of sectors, these five colleges found ways to fill the intermediary role that worked for their context, and in doing so provided excellent programming that filled their community's needs. This mosaic of case studies demonstrates that there are some common challenges and successful strategies that colleges looking to serve as apprenticeship intermediaries can learn from.

Published
2023

18. Hard X-ray inverse Compton scattering at photon energy of 87.5 keV.

Author

Sakai, Yusuke, Babzien, Marcus, Fedurin, Mikhail, Kusche, Karl, Williams, Oliver, Fukasawa, Atsushi, Naranjo, Brian, Murokh, Alex, Agustsson, Ronald, Simmonds, Andrew, Jacob, Paul, Stenby, George, Malone, Robert, Polyanskiy, Mikhail, Pogorelsky, Igor, Palmer, Mark, and Rosenzweig, James

Abstract

Production of hard X-ray via inverse Compton scattering at photon energies below 100 keV range aimed at potential applications in medicine and material research is reported. Experiments have been performed at the Brookhaven National Laboratory, Accelerator Test Facility, employing the counter collision of a 70 MeV, 0.3 nC electron beam with a near infra-red Nd: YAG laser (1064 nm wavelength) pulse containing ~ 100 mJ in a single shot basis. The radiation distribution of the scattered photon beam is assessed to be sufficiently quasi monochromatic to produce clear contrast from the Au K- edge at 80.7 keV.

Published
2024

19. Genome‐wide association study of delay discounting in Heterogeneous Stock rats

Author

Lara, Montana Kay, Chitre, Apurva S, Chen, Denghui, Johnson, Benjamin B, Nguyen, Khai‐Minh, Cohen, Katarina A, Muckadam, Sakina A, Lin, Bonnie, Ziegler, Shae, Beeson, Angela, Sanches, Thiago M, Woods, Leah C Solberg, Polesskaya, Oksana, Palmer, Abraham A, and Mitchell, Suzanne H

Subjects
Pharmacology and Pharmaceutical Sciences, Biological Sciences, Biomedical and Clinical Sciences, Genetics, Brain Disorders, Behavioral and Social Science, Human Genome, Basic Behavioral and Social Science, Drug Abuse (NIDA only), Substance Misuse, 2.1 Biological and endogenous factors, Animals, Delay Discounting, Rats, Male, Female, Genome-Wide Association Study, Reward, Quantitative Trait Loci, adjusting amount, delay discounting, GWAS, Heterogeneous Stock rats, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Neurosciences
Abstract

Delay discounting refers to the behavioral tendency to devalue rewards as a function of their delay in receipt. Heightened delay discounting has been associated with substance use disorders and multiple co-occurring psychopathologies. Human and animal genetic studies have established that delay discounting is heritable, but only a few associated genes have been identified. We aimed to identify novel genetic loci associated with delay discounting through a genome-wide association study (GWAS) using Heterogeneous Stock (HS) rats, a genetically diverse outbred population derived from eight inbred founder strains. We assessed delay discounting in 650 male and female HS rats using an adjusting amount procedure in which rats chose between smaller immediate sucrose rewards or a larger reward at various delays. Preference switch points were calculated and both exponential and hyperbolic functions were fitted to these indifference points. Area under the curve (AUC) and the discounting parameter k of both functions were used as delay discounting measures. GWAS for AUC, exponential k, and one indifference point identified significant loci on chromosomes 20 and 14. The gene Slc35f1, which encodes a member of the solute carrier family, was the sole gene within the chromosome 20 locus. That locus also contained an eQTL for Slc35f1, suggesting that heritable differences in the expression might be responsible for the association with behavior. Adgrl3, which encodes a latrophilin subfamily G-protein coupled receptor, was the sole gene within the chromosome 14 locus. These findings implicate novel genes in delay discounting and highlight the need for further exploration.

Published
2024

20. Enhanced Carbon Flux Response to Atmospheric Aridity and Water Storage Deficit During the 2015–2016 El Niño Compromised Carbon Balance Recovery in Tropical South America

Author

Liu, Junjie, Bowman, Kevin, Palmer, Paul I, Joiner, Joanna, Levine, Paul, Bloom, A Anthony, Feng, Liang, Saatchi, Sassan, Keller, Michael, Longo, Marcos, Schimel, David, and Wennberg, Paul O

Subjects
Earth Sciences, Atmospheric Sciences, Climate Action, aridity, water storage deficit, tropical South America, recovery, Climate change science, Geology, Physical geography and environmental geoscience
Abstract

During the 2015–2016 El Niño, the Amazon basin released almost one gigaton of carbon (GtC) into the atmosphere due to extreme temperatures and drought. The link between the drought impact and recovery of the total carbon pools and its biogeochemical drivers is still unknown. With satellite-constrained net carbon exchange and its component fluxes including gross primary production and fire emissions, we show that the total carbon loss caused by the 2015–2016 El Niño had not recovered by the end of 2018. Forest ecosystems over the Northeastern (NE) Amazon suffered a cumulative total carbon loss of ∼0.6 GtC through December 2018, driven primarily by a suppression of photosynthesis whereas southeastern savannah carbon loss was driven in part by fire. We attribute the slow recovery to the unexpected large carbon loss caused by the severe atmospheric aridity coupled with a water storage deficit during drought. We show the attenuation of carbon uptake is three times higher than expected from the pre-drought sensitivity to atmospheric aridity and ground water supply. Our study fills an important knowledge gap in our understanding of the unexpectedly enhanced response of carbon fluxes to atmospheric aridity and water storage deficit and its impact on regional post-drought recovery as a function of the vegetation types and climate perturbations. Our results suggest that the disproportionate impact of water supply and demand could compromise resiliency of the Amazonian carbon balance to future increases in extreme events.

Published
2024

21. De novo variants in the RNU4-2 snRNA cause a frequent neurodevelopmental syndrome.

Author

Chen, Yuyang, Dawes, Ruebena, Kim, Hyung, Ljungdahl, Alicia, Stenton, Sarah, Walker, Susan, Lord, Jenny, Lemire, Gabrielle, Martin-Geary, Alexandra, Ganesh, Vijay, Ma, Jialan, Ellingford, Jamie, Delage, Erwan, DSouza, Elston, Dong, Shan, Adams, David, Allan, Kirsten, Bakshi, Madhura, Baldwin, Erin, Berger, Seth, Bernstein, Jonathan, Bhatnagar, Ishita, Blair, Ed, Brown, Natasha, Burrage, Lindsay, Chapman, Kimberly, Coman, David, Compton, Alison, Cunningham, Chloe, DSouza, Precilla, Danecek, Petr, Délot, Emmanuèle, Dias, Kerith-Rae, Elias, Ellen, Elmslie, Frances, Evans, Care-Anne, Ewans, Lisa, Ezell, Kimberly, Fraser, Jamie, Gallacher, Lyndon, Genetti, Casie, Goriely, Anne, Grant, Christina, Haack, Tobias, Higgs, Jenny, Hinch, Anjali, Hurles, Matthew, Kuechler, Alma, Lachlan, Katherine, Lalani, Seema, Lecoquierre, François, Leitão, Elsa, Fevre, Anna, Leventer, Richard, Liebelt, Jan, Lindsay, Sarah, Lockhart, Paul, Ma, Alan, Macnamara, Ellen, Mansour, Sahar, Maurer, Taylor, Mendez, Hector, Metcalfe, Kay, Montgomery, Stephen, Moosajee, Mariya, Nassogne, Marie-Cécile, Neumann, Serena, ODonoghue, Michael, OLeary, Melanie, Palmer, Elizabeth, Pattani, Nikhil, Phillips, John, Pitsava, Georgia, Pysar, Ryan, Rehm, Heidi, Reuter, Chloe, Revencu, Nicole, Riess, Angelika, Rius, Rocio, Rodan, Lance, Roscioli, Tony, Rosenfeld, Jill, Sachdev, Rani, Shaw-Smith, Charles, Simons, Cas, Sisodiya, Sanjay, Snell, Penny, St Clair, Laura, Stark, Zornitza, Stewart, Helen, Tan, Tiong, Tan, Natalie, Temple, Suzanna, Thorburn, David, Tifft, Cynthia, Uebergang, Eloise, VanNoy, Grace, Vasudevan, Pradeep, Vilain, Eric, and Viskochil, David

Subjects
Humans, RNA, Small Nuclear, Neurodevelopmental Disorders, Female, Male, Brain, Heterozygote, Alleles, Syndrome, Spliceosomes, Animals
Abstract

Around 60% of individuals with neurodevelopmental disorders (NDD) remain undiagnosed after comprehensive genetic testing, primarily of protein-coding genes1. Large genome-sequenced cohorts are improving our ability to discover new diagnoses in the non-coding genome. Here we identify the non-coding RNA RNU4-2 as a syndromic NDD gene. RNU4-2 encodes the U4 small nuclear RNA (snRNA), which is a critical component of the U4/U6.U5 tri-snRNP complex of the major spliceosome2. We identify an 18 base pair region of RNU4-2 mapping to two structural elements in the U4/U6 snRNA duplex (the T-loop and stem III) that is severely depleted of variation in the general population, but in which we identify heterozygous variants in 115 individuals with NDD. Most individuals (77.4%) have the same highly recurrent single base insertion (n.64_65insT). In 54 individuals in whom it could be determined, the de novo variants were all on the maternal allele. We demonstrate that RNU4-2 is highly expressed in the developing human brain, in contrast to RNU4-1 and other U4 homologues. Using RNA sequencing, we show how 5 splice-site use is systematically disrupted in individuals with RNU4-2 variants, consistent with the known role of this region during spliceosome activation. Finally, we estimate that variants in this 18 base pair region explain 0.4% of individuals with NDD. This work underscores the importance of non-coding genes in rare disorders and will provide a diagnosis to thousands of individuals with NDD worldwide.

Published
2024

22. Long-term investment and energy procurement risk management under uncertainty for an electrolytic green hydrogen producer

Author

Palmer, Owen, Radet, Hugo, Camal, Simon, and Girard, Robin

Subjects
Mathematics - Optimization and Control
Abstract

Green hydrogen production by electrolysis is considered essential for global climate ambitions, however development of the industry is lagging behind expectations due to the perceived financial risk for individual projects. For new bilateral Hydrogen Purchase Agreements (HPA's), green hydrogen project proponents will seek to manage operating cost risks using investment in flexible assets, and energy hedging - two sets of decisions that are usually considered separately, but are co-optimised in this study to form a comprehensive asset sizing and procurement strategy. A 2-stage market-focused stochastic program is developed to model a hydrogen producer supplying an industrial customer, including hydrogen storage, and energy hedging using Power Purchase Agreements (PPA's) and power futures. The effects of uncertainty in renewable production, market prices, and hydrogen demand are studied. Several planning methods are tested on the model, benchmarking stochastic methods against simpler methods that are common in literature and in industry. Finally, the model is applied to several regulatory contexts discernible in the European green hydrogen classification rules (Renewable Fuel of Non-Biological Origin, RFNBO). The results show that in less complex cases, simple rule-based hedging methods can be effective, while in cases with demand uncertainty stochastic models are advantageous. The results also suggest that new green hydrogen subsidies are likely to stimulate demand for technologically and geographically diverse PPA portfolios.

Published
2024

23. Exploring the Quantum Universe: Pathways to Innovation and Discovery in Particle Physics

Author

Asai, Shoji, Ballarino, Amalia, Bose, Tulika, Cranmer, Kyle, Cyr-Racine, Francis-Yan, Demers, Sarah, Geddes, Cameron, Gershtein, Yuri, Heeger, Karsten, Heinemann, Beate, Hewett, JoAnne, Huber, Patrick, Mahn, Kendall, Mandelbaum, Rachel, Maricic, Jelena, Merkel, Petra, Monahan, Christopher, Murayama, Hitoshi, Onyisi, Peter, Palmer, Mark, Raubenheimer, Tor, Sanchez, Mayly, Schnee, Richard, Seidel, Sally, Seo, Seon-Hee, Thaler, Jesse, Touramanis, Christos, Vieregg, Abigail, Weinstein, Amanda, Winslow, Lindley, Yu, Tien-Tien, and Zwaska, Robert

Subjects
High Energy Physics - Experiment, Astrophysics - Cosmology and Nongalactic Astrophysics, High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract

This is the report from the 2023 Particle Physics Project Prioritization Panel (P5) approved by High Energy Physics Advisory Panel (HEPAP) on December 8, 2023. The final version was made public on May 8, 2024 and submitted to DOE SC and NSF MPS., Comment: 2-page spread version. The online version is available at https://www.usparticlephysics.org/2023-p5-report/ and the graphics at https://usparticlephysics.org/media-assets-library

Published
2024
Full Text
View/download PDF

24. Inherent structural descriptors via machine learning

Author

Telari, Emanuele, Tinti, Antonio, Settem, Manoj, Rees, Morgan, Hoddinott, Henry, Dearg, Malcom, von Issendorff, Bernd, Held, Georg, Slater, Thomas J. A., Palmer, Richard E., Maragliano, Luca, Ferrando, Riccardo, and Giacomello, Alberto

Subjects
Physics - Computational Physics
Abstract

Finding proper collective variables for complex systems and processes is one of the most challenging tasks in simulations, which limits the interpretation of experimental and simulated data and the application of enhanced sampling techniques. Here, we propose a machine learning approach able to distill few, physically relevant variables by associating instantaneous configurations of the system to their corresponding inherent structures as defined in liquids theory. We apply this approach to the challenging case of structural transitions in nanoclusters, managing to characterize and explore the structural complexity of an experimentally relevant system constituted by 147 gold atoms. Our inherent-structure variables are shown to be effective at computing complex free-energy landscapes, transition rates, and at describing non-equilibrium melting and freezing processes. The effectiveness of this machine learning strategy guided by the generally-applicable concept of inherent structures shows promise to devise collective variables for a vast range of systems, including liquids, glasses, and proteins.

Published
2024

25. Dots and Boxes on Certain Families of Graphs

Author

Aryan, Vedant, Palmer, Alana, Skula, Alexander, Woolbert, Matthew, and Zelinsky, Joshua

Subjects
Mathematics - Combinatorics, 05C85, 91A46
Abstract

We investigate the Dots and Boxes game, also known as ``Strings and Coins,'' for certain specific families of graphs. These include complete graphs, wheel graphs, and friendship graphs.

Published
2024

26. Conformity to continuous and discrete ordinal traits

Author

Mora, Elisa Heinrich, Denton, Kaleda K., Palmer, Michael E., and Feldman, Marcus W.

Subjects
Quantitative Biology - Populations and Evolution
Abstract

Models of conformity and anti-conformity have typically focused on cultural traits with nominal (unordered) variants, such as baby names, strategies (cooperate/defect), or the presence/absence of an innovation. There have been fewer studies of conformity to "ordinal" cultural traits with ordered variants, such as level of cooperation (low to high) or fraction of time spent on a task (0 to 1). In these latter studies, conformity is conceptualized as a preference for the mean trait value in a population even if no members of the population have variants near this mean; e.g., 50% of the population has variant 0 and 50% has variant 1, producing a mean of 0.5. Here, we introduce models of conformity to ordinal traits, which can be either discrete or continuous and linear (with minimum and maximum values) or circular (without boundaries). In these models, conformists prefer to adopt more popular cultural variants, even if these variants are far from the population mean. To measure a variant's "popularity" in cases where no two individuals share precisely the same variant on a continuum, we introduce a metric called $k$-dispersal; this takes into account a variant's distance to its $k$ closest neighbors, with more "popular" variants having lower distances to their neighbors. We demonstrate through simulations that conformity to ordinal traits need not produce a homogeneous population, as has previously been claimed. Under some combinations of parameter values, conformity sustains substantial trait variation over many generations. Anti-conformist transmission may produce high levels of polarization., Comment: 13 pages, 9 figures, 1 table

Published
2024

27. Interim report for the International Muon Collider Collaboration (IMCC)

Author

Accettura, C., Adrian, S., Agarwal, R., Ahdida, C., Aimé, C., Aksoy, A., Alberghi, G. L., Alden, S., Amapane, N., Amorim, D., Andreetto, P., Anulli, F., Appleby, R., Apresyan, A., Asadi, P., Mahmoud, M. Attia, Auchmann, B., Back, J., Badea, A., Bae, K. J., Bahng, E. J., Balconi, L., Balli, F., Bandiera, L., Barbagallo, C., Barlow, R., Bartoli, C., Bartosik, N., Barzi, E., Batsch, F., Bauce, M., Begel, M., Berg, J. S., Bersani, A., Bertarelli, A., Bertinelli, F., Bertolin, A., Bhat, P., Bianchi, C., Bianco, M., Bishop, W., Black, K., Boattini, F., Bogacz, A., Bonesini, M., Bordini, B., de Sousa, P. Borges, Bottaro, S., Bottura, L., Boyd, S., Breschi, M., Broggi, F., Brunoldi, M., Buffat, X., Buonincontri, L., Burrows, P. N., Burt, G. C., Buttazzo, D., Caiffi, B., Calatroni, S., Calviani, M., Calzaferri, S., Calzolari, D., Cantone, C., Capdevilla, R., Carli, C., Carrelli, C., Casaburo, F., Casarsa, M., Castelli, L., Catanesi, M. G., Cavallucci, L., Cavoto, G., Celiberto, F. G., Celona, L., Cemmi, A., Ceravolo, S., Cerri, A., Cerutti, F., Cesarini, G., Cesarotti, C., Chancé, A., Charitonidis, N., Chiesa, M., Chiggiato, P., Ciccarella, V. L., Puviani, P. Cioli, Colaleo, A., Colao, F., Collamati, F., Costa, M., Craig, N., Curtin, D., D'Angelo, L., Da Molin, G., Damerau, H., Dasu, S., de Blas, J., De Curtis, S., De Gersem, H., Del Moro, T., Delahaye, J. -P., Denisov, D., Denizli, H., Dermisek, R., Valdor, P. Desiré, Desponds, C., Di Luzio, L., Di Meco, E., Di Petrillo, K. F., Di Sarcina, I., Diociaiuti, E., Dorigo, T., Dreimanis, K., Pree, T. du, Edgecock, T., Fabbri, S., Fabbrichesi, M., Farinon, S., Ferrand, G., Somoza, J. A. Ferreira, Fieg, M., Filthaut, F., Fox, P., Franceschini, R., Ximenes, R. Franqueira, Gallinaro, M., Garcia-Sciveres, M., Garcia-Tabares, L., Gargiulo, R., Garion, C., Garzelli, M. V., Gast, M., Gerber, C. E., Giambastiani, L., Gianelle, A., Gianfelice-Wendt, E., Gibson, S., Gilardoni, S., Giove, D. A., Giovinco, V., Giraldin, C., Glioti, A., Gorzawski, A., Greco, M., Grojean, C., Grudiev, A., Gschwendtner, E., Gueli, E., Guilhaudin, N., Han, C., Han, T., Hauptman, J. M., Herndon, M., Hillier, A. D., Hillman, M., Holmes, T. R., Homiller, S., Jana, S., Jindariani, S., Johannesson, S., Johnson, B., Jones, O. R., Jurj, P. -B., Kahn, Y., Kamath, R., Kario, A., Karpov, I., Kelliher, D., Kilian, W., Kitano, R., Kling, F., Kolehmainen, A., Kong, K. C., Kosse, J., Krintiras, G., Krizka, K., Kumar, N., Kvikne, E., Kyle, R., Laface, E., Lane, K., Latina, A., Lechner, A., Lee, J., Lee, L., Lee, S. W., Lefevre, T., Leonardi, E., Lerner, G., Li, P., Li, Q., Li, T., Li, W., Voti, R. Li, Lindroos, M., Lipton, R., Liu, D., Liu, M., Liu, Z., Lombardi, A., Lomte, S., Long, K., Longo, L., Lorenzo, J., Losito, R., Low, I., Lu, X., Lucchesi, D., Luo, T., Lupato, A., Métral, E., Mękała, K., Ma, Y., Mańczak, J. M., Machida, S., Madlener, T., Magaletti, L., Maggi, M., Durand, H. Mainaud, Maltoni, F., Mandurrino, M., Marchand, C., Mariani, F., Marin, S., Mariotto, S., Martin-Haugh, S., Masullo, M. R., Mauro, G. S., Mazzolari, A., Mele, B., Meloni, F., Meng, X., Mentink, M., Miceli, R., Milas, N., Mohammadi, A., Moll, D., Montella, A., Morandin, M., Morrone, M., Mulder, T., Musenich, R., Nardecchia, M., Nardi, F., Neuffer, D., Newbold, D., Novelli, D., Olvegård, M., Onel, Y., Orestano, D., Osborne, J., Otten, S., Torres, Y. M. Oviedo, Paesani, D., Griso, S. Pagan, Pagani, D., Pal, K., Palmer, M., Pampaloni, A., Panci, P., Pani, P., Papaphilippou, Y., Paparella, R., Paradisi, P., Passeri, A., Pastrone, N., Pellecchia, A., Piccinini, F., Piekarz, H., Pieloni, T., Plouin, J., Portone, A., Potamianos, K., Potdevin, J., Prestemon, S., Puig, T., Qiang, J., Quettier, L., Rabemananjara, T. R., Radicioni, E., Radogna, R., Rago, I. C., Ratkus, A., Resseguie, E., Reuter, J., Ribani, P. L., Riccardi, C., Ricciardi, S., Robens, T., Robert, Y., Roger, C., Rojo, J., Romagnoni, M., Ronald, K., Rosser, B., Rossi, C., Rossi, L., Rozanov, L., Ruhdorfer, M., Ruiz, R., Queiroz, F. S., Saini, S., Sala, F., Salierno, C., Salmi, T., Salvini, P., Salvioni, E., Sammut, N., Santini, C., Saputi, A., Sarra, I., Scarantino, G., Schneider-Muntau, H., Schulte, D., Scifo, J., Sen, T., Senatore, C., Senol, A., Sertore, D., Sestini, L., Rêgo, R. C. Silva, Simone, F. M., Skoufaris, K., Sorbello, G., Sorbi, M., Sorti, S., Soubirou, L., Spataro, D., Stamerra, A., Stapnes, S., Stark, G., Statera, M., Stechauner, B. M., Su, S., Su, W., Sun, X., Sytov, A., Tang, J., Taylor, R., Kate, H. Ten, Testoni, P., Thiele, L. S., Garcia, R. Tomas, Mugglestone, M. Topp, Torims, T., Torre, R., Tortora, L. T., Trifinopoulos, S., Udongwo, S. -A., Vai, I., Valente, R. U., van Rienen, U., van Weelderen, R., Vanwelde, M., Velev, G., Venditti, R., Vendrasco, A., Verna, A., Verweij, A., Verwilligen, P., Villamzar, Y., Vittorio, L., Vitulo, P., Vojskovic, I., Wang, D., Wang, L. -T., Wang, X., Wendt, M., Widorski, M., Wozniak, M., Wu, Y., Wulzer, A., Xie, K., Yang, Y., Yap, Y. C., Yonehara, K., Yoo, H. D., You, Z., Zanetti, M., Zaza, A., Zhang, L., Zhu, R., Zlobin, A., Zuliani, D., and Zurita, J. F.

Subjects
Physics - Accelerator Physics, High Energy Physics - Experiment
Abstract

The International Muon Collider Collaboration (IMCC) [1] was established in 2020 following the recommendations of the European Strategy for Particle Physics (ESPP) and the implementation of the European Strategy for Particle Physics-Accelerator R&D Roadmap by the Laboratory Directors Group [2], hereinafter referred to as the the European LDG roadmap. The Muon Collider Study (MuC) covers the accelerator complex, detectors and physics for a future muon collider. In 2023, European Commission support was obtained for a design study of a muon collider (MuCol) [3]. This project started on 1st March 2023, with work-packages aligned with the overall muon collider studies. In preparation of and during the 2021-22 U.S. Snowmass process, the muon collider project parameters, technical studies and physics performance studies were performed and presented in great detail. Recently, the P5 panel [4] in the U.S. recommended a muon collider R&D, proposed to join the IMCC and envisages that the U.S. should prepare to host a muon collider, calling this their "muon shot". In the past, the U.S. Muon Accelerator Programme (MAP) [5] has been instrumental in studies of concepts and technologies for a muon collider., Comment: This document summarises the International Muon Collider Collaboration (IMCC) progress and status of the Muon Collider R&D programme

Published
2024

28. Swift-BAT GUANO follow-up of gravitational-wave triggers in the third LIGO-Virgo-KAGRA observing run

Author

Raman, Gayathri, Ronchini, Samuele, Delaunay, James, Tohuvavohu, Aaron, Kennea, Jamie A., Parsotan, Tyler, Ambrosi, Elena, Bernardini, Maria Grazia, Campana, Sergio, Cusumano, Giancarlo, D'Ai, Antonino, D'Avanzo, Paolo, D'Elia, Valerio, De Pasquale, Massimiliano, Dichiara, Simone, Evans, Phil, Hartmann, Dieter, Kuin, Paul, Melandri, Andrea, O'Brien, Paul, Osborne, Julian P., Page, Kim, Palmer, David M., Sbarufatti, Boris, Tagliaferri, Gianpiero, Troja, Eleonora, Abac, A. G., Abbott, R., Abe, H., Abouelfettouh, I., Acernese, F., Ackley, K., Adamcewicz, C., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Bai, Y., Baier, J. G., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Barthelmy, S. D., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Bazzan, M., Bécsy, B., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Beniwal, D., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Bogaert, G., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boumerdassi, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannavacciuolo, M., Cannon, K. C., Cao, H., Cao, Z., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castaldi, G., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, C., Chan, J. C. L., Chan, K. H. M., Chan, M., Chan, W. L., Chandra, K., Chang, R. -J., Chanial, P., Chao, S., Chapman-Bird, C., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, K. H., Chen, X., Chen, Yi-Ru, Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Chia, H. Y., Chiadini, F., Chiang, C., Chiarini, G., Chiba, A., Chiba, R., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chung, K. W., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Clara, F., Clark, J. A., Clarke, T. A., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Codazzo, E., Cohadon, P. -F., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Conti, L., Cooper, S. J., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Cousins, B., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Croquette, M., Crouch, R., Crowder, S. G., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Daw, E. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., Del Favero, V., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., De Simone, R., Dhani, A., Dhurandhar, S., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Donahue, L., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Drori, Y., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Emma, M., Engelby, E., Engl, A. J., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Fan, P. C., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Fenyvesi, E., Ferguson, D. L., Ferrante, I., Ferreira, T. A., Fidecaro, F., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fukunaga, I., Fulda, P., Fyffe, M., Gabella, W. E., Gadre, B., Gair, J. R., Galaudage, S., Gallardo, S., Gallego, B., Gamba, R., Gamboa, A., Ganapathy, D., Ganguly, A., Gaonkar, S. G., Garaventa, B., Garcia-Bellido, J., García-Núñez, C., García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garron, A., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., George, J., George, R., Gerberding, O., Gergely, L., Ghadiri, N., Ghosh, Archisman, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gibson, D. T., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Gleckl, A. E., Glotin, F., Godfrey, J., Godwin, P., Goebbels, N. L., Goetz, E., Golomb, J., Lopez, S. Gomez, Goncharov, B., González, G., Goodarzi, P., Goodwin-Jones, A. W., Gosselin, M., Göttel, A. S., Gouaty, R., Gould, D. W., Goyal, S., Grace, B., Grado, A., Graham, V., Granados, A. E., Granata, M., Granata, V., Argianas, L. Granda, Gras, S., Grassia, P., Gray, C., Gray, R., Greco, G., Green, A. C., Green, S. M., Green, S. R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimaud, C., Grote, H., Gruson, A. S., Guerra, D., Guetta, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H., Guo, W., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, Ish, Gupta, N. C., Gupta, P., Gupta, S. K., Gupta, T., Gupte, N., Gurav, R., Gurs, J., Gutierrez, N., Guzman, F., Haba, D., Haberland, M., Haegel, L., Hain, G., Haino, S., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hanselman, A. G., Hansen, H., Hanson, J., Harada, R., Harder, T., Haris, K., Harmark, T., Harms, J., Harry, G. M., Harry, I. W., Haskell, B., Haster, C. -J., Hathaway, J. S., Haughian, K., Hayakawa, H., Hayama, K., Healy, J., Heffernan, A., Heidmann, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Hendry, M., Heng, I. S., Hennes, E., Hennig, J. -S., Hennig, M., Henshaw, C., Hernandez, A., Hertog, T., Heurs, M., Hewitt, A. L., Higginbotham, S., Hild, S., Hill, P., Hill, S., Himemoto, Y., Hines, A. S., Hirata, N., Hirose, C., Ho, J., Hoang, S., Hochheim, S., Hofman, D., Holland, N. A., Holley-Bockelmann, K., Hollows, I. J., Holmes, Z. J., Holz, D. E., Hong, C., Hornung, J., Hoshino, S., Hough, J., Hourihane, S., Howell, E. J., Hoy, C. G., Hoyland, D., Hrishikesh, C. A., Hsieh, H. -F., Hsiung, C., Hsu, H. C., Hsu, S. -C., Hsu, W. -F., Hu, P., Hu, Q., Huang, H. Y., Huang, Y. -J., Huang, Y., Huang, Y. T., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V., Hur, R., Husa, S., Huxford, R., Huynh-Dinh, T., Iakovlev, A., Iandolo, G. A., Iess, A., Inayoshi, K., Inoue, Y., Iorio, G., Irwin, J., Isi, M., Ismail, M. A., Itoh, Y., Iwaya, M., Iyer, B. R., JaberianHamedan, V., Jacquet, P. -E., Jadhav, S. J., Jadhav, S. P., Jain, T., James, A. L., James, P. A., Jamshidi, R., Jan, A. Z., Jani, K., Janiurek, L., Janquart, J., Janssens, K., Janthalur, N. N., Jaraba, S., Jaranowski, P., Jasal, P., Jaume, R., Javed, W., Jennings, A., Jia, W., Jiang, J., Jin, H. -B., Johansmeyer, K., Johns, G. R., Johnson, N. A., Johnston, R., Johny, N., Jones, D. H., Jones, D. I., Jones, R., Jose, S., Joshi, P., Ju, L., Jung, K., Junker, J., Juste, V., Kajita, T., Kalaghatgi, C., Kalogera, V., Kamiizumi, M., Kanda, N., Kandhasamy, S., Kang, G., Kanner, J. B., Kapadia, S. J., Kapasi, D. P., Karat, S., Karathanasis, C., Karki, S., Kashyap, R., Kasprzack, M., Kastaun, W., Kato, J., Kato, T., Katsanevas, S., Katsavounidis, E., Katzman, W., Kaur, T., Kaushik, R., Kawabe, K., Keitel, D., Kelley-Derzon, J., Kennington, J., Kesharwani, R., Key, J. S., Khadka, S., Khalili, F. Y., Khan, F., Khan, I., Khanam, T., Khazanov, E. A., Khursheed, M., Kiendrebeogo, W., Kijbunchoo, N., Kim, C., Kim, J. C., Kim, K., Kim, M. H., Kim, S., Kim, W. S., Kim, Y. -M., Kimball, C., Kimura, N., Kinley-Hanlon, M., Kinnear, M., Kissel, J. S., Kiyota, T., Klimenko, S., Klinger, T., Knee, A. M., Knust, N., Koch, P., Koehlenbeck, S. M., Koekoek, G., Kohri, K., Kokeyama, K., Koley, S., Kolitsidou, P., Kolstein, M., Komori, K., Kong, A. K. H., Kontos, A., Korobko, M., Kossak, R. V., Kou, X., Koushik, A., Kouvatsos, N., Kovalam, M., Koyama, N., Kozak, D. B., Kranzhoff, S. L., Kringel, V., Krishnendu, N. V., Królak, A., Kuehn, G., Kuijer, P., Kulkarni, S., Ramamohan, A. Kulur, Kumar, A., Kumar, Praveen, Kumar, Prayush, Kumar, Rahul, Kumar, Rakesh, Kume, J., Kuns, K., Kuroyanagi, S., Kuwahara, S., Kwak, K., Kwan, K., Lacaille, G., Lagabbe, P., Laghi, D., Lai, S., Laity, A. H., Lakkis, M. H., Lalande, E., Lalleman, M., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., La Rana, A., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Lawrence, J., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., LeBohec, S., Lecoeuche, Y. K., Lee, H. M., Lee, H. W., Lee, K., Lee, R. -K., Lee, R., Lee, S., Lee, Y., Legred, I. N., Lehmann, J., Lehner, L., Lemaître, A., Lenti, M., Leonardi, M., Leonova, E., Lequime, M., Leroy, N., Lesovsky, M., Letendre, N., Lethuillier, M., Levesque, C., Levin, Y., Leyde, K., Li, A. K. Y., Li, K. L., Li, T. G. F., Li, X., Lin, Chien-Yu, Lin, Chun-Yu, Lin, E. T., Lin, F., Lin, H., Lin, L. C. -C., Linde, F., Linker, S. D., Littenberg, T. B., Liu, A., Liu, G. C., Liu, Jian, Llamas, F., Llobera-Querol, J., Lo, R. K. L., Locquet, J. -P., London, L., Longo, A., Lopez, D., Portilla, M. Lopez, Lorenzini, M., Loriette, V., Lormand, M., Losurdo, G., Lott IV, T. P., Lough, J. D., Loughlin, H. A., Lousto, C. O., Lowry, M. J., Lück, H., Lumaca, D., Lundgren, A. P., Lussier, A. W., Ma, L. -T., Ma, S., Ma'arif, M., Macas, R., MacInnis, M., Maciy, R. R., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Macri, D., Maeda, K., Maenaut, S., Hernandez, I. Magaña, Magare, S. S., Magazzù, C., Magee, R. M., Maggio, E., Maggiore, R., Magnozzi, M., Mahesh, M., Mahesh, S., Maini, M., Majhi, S., Majorana, E., Makarem, C. N., Malaquias-Reis, J. A., Maliakal, S., Malik, A., Man, N., Mandic, V., Mangano, V., Mannix, B., Mansell, G. L., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Pina, D. Marín, Marion, F., Márka, S., Márka, Z., Markakis, C., Markosyan, A. S., Markowitz, A., Maros, E., Marquina, A., Marsat, S., Martelli, F., Martin, I. W., Martin, R. M., Martinez, B. B., Martinez, M., Martinez, V., Martini, A., Martinovic, K., Martins, J. C., Martynov, D. V., Marx, E. J., Massaro, L., Masserot, A., Masso-Reid, M., Mastrodicasa, M., Mastrogiovanni, S., Mateu-Lucena, M., Matiushechkina, M., Matsuyama, M., Mavalvala, N., Maxwell, N., McCarrol, G., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McGhee, G. I., McGowan, K. B. M., Mchedlidze, M., McIsaac, C., McIver, J., McKinney, K., McLeod, A., McRae, T., McWilliams, S. T., Meacher, D., Mehta, A. K., Meijer, Q., Melatos, A., Mellaerts, S., Menendez-Vazquez, A., Menoni, C. S., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Mérou, J. R., Merritt, J. D., Merzougui, M., Messenger, C., Messick, C., Meyer-Conde, M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Miller, A. L., Miller, S., Millhouse, M., Milotti, E., Minenkov, Y., Mio, N., Mir, Ll. M., Mirasola, L., Miravet-Tenés, M., Miritescu, C. -A., Mishra, A. K., Mishra, A., Mishra, C., Mishra, T., Mitchell, A. L., Mitchell, J. G., Mitra, S., Mitrofanov, V. P., Mitselmakher, G., Mittleman, R., Miyakawa, O., Miyamoto, S., Miyoki, S., Mo, G., Mobilia, L., Modafferi, L. M., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondal, C., Mondin, M., Montani, M., Moore, C. J., Morales, M., Moraru, D., Morawski, F., More, A., More, S., Moreno, C., Moreno, G., Morisaki, S., Moriwaki, Y., Morras, G., Moscatello, A., Mourier, P., Mours, B., Mow-Lowry, C. M., Mozzon, S., Muciaccia, F., Mukherjee, D., Mukherjee, Samanwaya, Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Mungioli, C. L., Munn, M., Oberg, W. R. Munn, Murakoshi, M., Murray, P. G., Muusse, S., Nadji, S. L., Nagar, A., Nagarajan, N., Nagler, K. N., Nakamura, K., Nakano, H., Nakano, M., Nandi, D., Napolano, V., Narayan, P., Nardecchia, I., Narola, H., Naticchioni, L., Nayak, R. K., Neil, B. F., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Neunzert, A., Ng, S., Nguyen, C., Nguyen, P., Quynh, L. Nguyen, Nichols, S. A., Nielsen, A. B., Nieradka, G., Niko, A., Nishino, Y., Nishizawa, A., Nissanke, S., Nitoglia, E., Niu, W., Nocera, F., Norman, M., North, C., Novak, J., Siles, J. F. Nuño, Nurbek, G., Nuttall, L. K., Obayashi, K., Oberling, J., O'Dell, J., Oertel, M., Offermans, A., Oganesyan, G., Oh, J. J., Oh, K., Oh, S. H., O'Hanlon, T., Ohashi, M., Ohkawa, M., Ohme, F., Ohta, H., Oliveira, A. S., Oliveri, R., Oloworaran, V., O'Neal, B., Oohara, K., O'Reilly, B., Ormsby, N. D., Orselli, M., O'Shaughnessy, R., Oshima, Y., Oshino, S., Ossokine, S., Osthelder, C., Ottaway, D. J., Ouzriat, A., Overmier, H., Owen, B. J., Pace, A. E., Pagano, R., Page, M. A., Pai, A., Pai, S. A., Pal, A., Pal, S., Palaia, M. A., Palashov, O., Pálfi, M., Palma, P. P., Palomba, C., Pan, K. C., Panda, P. K., Panebianco, L., Pang, P. T. H., Pannarale, F., Pant, B. C., Panther, F. H., Panzer, C. D., Paoletti, F., Paoli, A., Paolone, A., Papalexakis, E. E., Papalini, L., Papigkiotis, G., Parisi, A., Park, J., Parker, W., Pascale, G., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passuello, D., Patane, O., Patel, M., Pathak, D., Pathak, M., Patra, A., Patricelli, B., Patron, A. S., Paul, S., Payne, E., Pearce, T., Pedraza, M., Pegna, R., Pele, A., Arellano, F. E. Peña, Penn, S., Penuliar, M. D., Perego, A., Pereira, A., Perez, J. J., Périgois, C., Perkins, C. C., Perna, G., Perreca, A., Perret, J., Perriès, S., Perry, J. W., Pesios, D., Petrillo, C., Pfeiffer, H. P., Pham, H., Pham, K. A., Phukon, K. S., Phurailatpam, H., Piccinni, O. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierini, L., Pierra, G., Pierro, V., Pietrzak, M., Pillas, M., Pilo, F., Pinard, L., Pineda-Bosque, C., Pinto, I. M., Pinto, M., Piotrzkowski, B. J., Pirello, M., Pitkin, M. D., Placidi, A., Placidi, E., Planas, M. L., Plastino, W., Poggiani, R., Polini, E., Pompili, L., Poon, J., Porcelli, E., Portell, J., Porter, E. K., Posnansky, C., Poulton, R., Powell, J., Pracchia, M., Pradhan, B. K., Pradier, T., Prajapati, A. K., Prasai, K., Prasanna, R., Prasia, P., Pratten, G., Principe, M., Prodi, G. A., Prokhorov, L., Prosposito, P., Prudenzi, L., Puecher, A., Pullin, J., Punturo, M., Puosi, F., Puppo, P., Pürrer, M., Qi, H., Qin, J., Quéméner, G., Quetschke, V., Quigley, C., Quinonez, P. J., Quitzow-James, R., Raab, F. J., Raaijmakers, G., Radulesco, N., Raffai, P., Rail, S. X., Raja, S., Rajan, C., Rajbhandari, B., Ramirez, D. S., Ramirez, K. E., Vidal, F. A. Ramis, Ramos-Buades, A., Rana, D., Randel, E., Ranjan, S., Rapagnani, P., Ratto, B., Rawat, S., Ray, A., Raymond, V., Razzano, M., Read, J., Payo, M. Recaman, Regimbau, T., Rei, L., Reid, S., Reid, S. W., Reitze, D. H., Relton, P., Renzini, A., Rettegno, P., Revenu, B., Reza, A., Rezac, M., Rezaei, A. S., Ricci, F., Ricci, M., Richards, D., Richardson, C. J., Richardson, J. W., Rijal, A., Riles, K., Riley, H. K., Rinaldi, S., Rittmeyer, J., Robertson, C., Robinet, F., Robinson, M., Rocchi, A., Rolland, L., Rollins, J. G., Romanelli, M., Romano, A. E., Romano, R., Romero, A., Romero-Shaw, I. M., Romie, J. H., Roocke, T. J., Rosa, L., Rosauer, T. J., Rose, C. A., Rosińska, D., Ross, M. P., Rossello, M., Rowan, S., Roy, S. K., Roy, S., Rozza, D., Ruggi, P., Morales, E. Ruiz, Ruiz-Rocha, K., Sachdev, S., Sadecki, T., Sadiq, J., Saffarieh, P., Sah, M. R., Saha, S. S., Sainrat, T., Menon, S. Sajith, Sakai, K., Sakellariadou, M., Sako, T., Sakon, S., Salafia, O. S., Salces-Carcoba, F., Salconi, L., Saleem, M., Salemi, F., Sallé, M., Salvador, S., Sanchez, A., Sanchez, E. J., Sanchez, J. H., Sanchez, L. E., Sanchis-Gual, N., Sanders, J. R., Sänger, E. M., Saravanan, T. R., Sarin, N., Sasli, A., Sassi, P., Sassolas, B., Satari, H., Sato, R., Sato, S., Sato, Y., Sauter, O., Savage, R. L., Sawada, T., Sawant, H. L., Sayah, S., Schaetzl, D., Scheel, M., Scheuer, J., Schiworski, M. G., Schmidt, P., Schmidt, S., Schnabel, R., Schneewind, M., Schofield, R. M. S., Schouteden, K., Schuler, H., Schulte, B. W., Schutz, B. F., Schwartz, E., Scott, J., Scott, S. M., Seetharamu, T. C., Seglar-Arroyo, M., Sekiguchi, Y., Sellers, D., Sengupta, A. S., Sentenac, D., Seo, E. G., Seo, J. W., Sequino, V., Sergeev, A., Serra, M., Servignat, G., Setyawati, Y., Shaffer, T., Shah, U. S., Shahriar, M. S., Shaikh, M. A., Shams, B., Shao, L., Sharma, A. K., Sharma, P., Sharma-Chaudhary, S., Shawhan, P., Shcheblanov, N. S., Shen, B., Shikano, Y., Shikauchi, M., Shimode, K., Shinkai, H., Shiota, J., Shoemaker, D. H., Shoemaker, D. M., Short, R. W., ShyamSundar, S., Sider, A., Siegel, H., Sieniawska, M., Sigg, D., Silenzi, L., Simmonds, M., Singer, L. P., Singh, A., Singh, D., Singh, M. K., Singha, A., Sintes, A. M., Sipala, V., Skliris, V., Slagmolen, B. J. J., Slaven-Blair, T. J., Smetana, J., Smith, J. R., Smith, L., Smith, R. J. E., Smith, W. J., Soldateschi, J., Somala, S. N., Somiya, K., Soni, K., Soni, S., Sordini, V., Sorrentino, F., Sorrentino, N., Soulard, R., Souradeep, T., Southgate, A., Sowell, E., Spagnuolo, V., Spencer, A. P., Spera, M., Spinicelli, P., Srivastava, A. K., Stachurski, F., Steer, D. A., Steinlechner, J., Steinlechner, S., Stergioulas, N., Stevens, P., StPierre, M., Strang, L. C., Stratta, G., Strong, M. D., Strunk, A., Sturani, R., Stuver, A. L., Suchenek, M., Sudhagar, S., Sueltmann, N., Sullivan, A. G., Sullivan, K. D., Sun, L., Sunil, S., Sur, A., Suresh, J., Sutton, P. J., Suzuki, Takamasa, Suzuki, Takanori, Swinkels, B. L., Syx, A., Szczepańczyk, M. J., Szewczyk, P., Tacca, M., Tagoshi, H., Tait, S. C., Takahashi, H., Takahashi, R., Takamori, A., Takatani, K., Takeda, H., Takeda, M., Talbot, C. J., Talbot, C., Tamaki, M., Tamanini, N., Tanabe, D., Tanaka, K., Tanaka, S. J., Tanaka, T., Tanasijczuk, A. J., Tang, D., Tanioka, S., Tanner, D. B., Tao, L., Tapia, R. D., Martín, E. N. Tapia San, Tarafder, R., Taranto, C., Taruya, A., Tasson, J. D., Teloi, M., Tenorio, R., Themann, H., Theodoropoulos, A., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tissino, J., Tiwari, A., Tiwari, Shubhanshu, Tiwari, Srishti, Tiwari, V., Todd, M. R., Toivonen, A. M., Toland, K., Tolley, A. E., Tomaru, T., Tomita, K., Tomura, T., Tong-Yu, C., Toriyama, A., Toropov, N., Torres-Forné, A., Torrie, C. I., Toscani, M., Melo, I. Tosta e, Tournefier, E., Trani, A. A., Trapananti, A., Travasso, F., Traylor, G., Trenado, J., Trevor, M., Tringali, M. C., Tripathee, A., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. J., Tsang, T. T. L., Tso, R., Tsuchida, S., Tsukada, L., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Ubach, H., Ubhi, A. S., Uchikata, N., Uchiyama, T., Udall, R. P., Uehara, T., Ueno, K., Unnikrishnan, C. S., Ushiba, T., Utina, A., Vacatello, M., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valencia, J., Valentini, M., Vallejo-Peña, S. A., Vallero, S., Valsan, V., van Bakel, N., van Beuzekom, M., van Dael, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Sluys, M., Van de Walle, A., van Dongen, J., Vandra, K., van Haevermaet, H., van Heijningen, J. V., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venikoudis, S., Venneberg, J., Verdier, P., Verkindt, D., Verma, B., Verma, P., Verma, Y., Vermeulen, S. M., Veske, D., Vetrano, F., Veutro, A., Vibhute, A. M., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Vilkha, A., Villa-Ortega, V., Vincent, E. T., Vinet, J. -Y., Viret, S., Virtuoso, A., Vitale, S., Vocca, H., Voigt, D., von Reis, E. R. G., von Wrangel, J. S. A., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Walet, R. C., Walker, M., Wallace, G. S., Wallace, L., Wang, H., Wang, J. Z., Wang, W. H., Wang, Z., Waratkar, G., Ward, R. L., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watarai, D., Wayt, K. E., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Weller, C. M., Weller, R. A., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., White, D. D., Whiting, B. F., Whittle, C., Wildberger, J. B., Wilk, O. S., Wilken, D., Willetts, K., Williams, D., Williams, M. J., Williams, N. S., Willis, J. L., Willke, B., Wils, M., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wolfe, N. E., Wong, D., Wong, H. T., Wong, H. W. Y., Wong, I. C. F., Wright, J. L., Wright, M., Wu, C., Wu, D. S., Wu, H., Wysocki, D. M., Xiao, L., Xu, V. A., Xu, Y., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, M., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yan, T., Yang, F. W., Yang, F., Yang, K. Z., Yang, L. -C., Yang, Y., Yarbrough, Z., Yeh, S. -W., Yelikar, A. B., Yeung, S. M. C., Yin, X., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuzurihara, H., Zadrożny, A., Zannelli, A. J., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zeoli, M., Zerrad, M., Zevin, M., Zhang, A. C., Zhang, J., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhong, S., Zhou, R., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract

We present results from a search for X-ray/gamma-ray counterparts of gravitational-wave (GW) candidates from the third observing run (O3) of the LIGO-Virgo-KAGRA (LVK) network using the Swift Burst Alert Telescope (Swift-BAT). The search includes 636 GW candidates received in low latency, 86 of which have been confirmed by the offline analysis and included in the third cumulative Gravitational-Wave Transient Catalogs (GWTC-3). Targeted searches were carried out on the entire GW sample using the maximum--likelihood NITRATES pipeline on the BAT data made available via the GUANO infrastructure. We do not detect any significant electromagnetic emission that is temporally and spatially coincident with any of the GW candidates. We report flux upper limits in the 15-350 keV band as a function of sky position for all the catalog candidates. For GW candidates where the Swift-BAT false alarm rate is less than 10$^{-3}$ Hz, we compute the GW--BAT joint false alarm rate. Finally, the derived Swift-BAT upper limits are used to infer constraints on the putative electromagnetic emission associated with binary black hole mergers., Comment: 50 pages, 10 figures, 4 tables

Published
2024

29. Can we teach language models to gloss endangered languages?

Author

Ginn, Michael, Hulden, Mans, and Palmer, Alexis

Subjects
Computer Science - Computation and Language
Abstract

Interlinear glossed text (IGT) is a popular format in language documentation projects, where each morpheme is labeled with a descriptive annotation. Automating the creation of interlinear glossed text would be desirable to reduce annotator effort and maintain consistency across annotated corpora. Prior research has explored a number of statistical and neural methods for automatically producing IGT. As large language models (LLMs) have showed promising results across multilingual tasks, even for rare, endangered languages, it is natural to wonder whether they can be utilized for the task of generating IGT. We explore whether LLMs can be effective at the task of interlinear glossing with in-context learning, without any traditional training. We propose new approaches for selecting examples to provide in-context, observing that targeted selection can significantly improve performance. We find that LLM-based methods beat standard transformer baselines, despite requiring no training at all. These approaches still underperform state-of-the-art supervised systems for the task, but are highly practical for researchers outside of the NLP community, requiring minimal effort to use., Comment: Accepted to EMNLP 2024 Findings

Published
2024

30. First detection of coherent elastic neutrino-nucleus scattering on germanium

Author

Adamski, S., Ahn, M., Barbeau, P. S., Belov, V., Bernardi, I., Bock, C., Bolozdynya, A., Bouabid, R., Browning, J., Cabrera-Palmer, B., Cedarblade-Jones, N., Rivera, J. Colón, Conley, E., da Silva, V., Daughhetee, J., Detwiler, J., Ding, K., Durand, M. R., Efremenko, Y., Elliott, S. R., Erlandson, A., Fabris, L., Galindo-Uribarri, A., Green, M. P., Hakenmüller, J., Heath, M. R., Hedges, S., Jeong, H., Johnson, B. A., Johnson, T., Jones, H., Khromov, A., Konovalov, A., Kozlova, E., Kumpan, A., Kyzylova, O., Lee, Y., Li, G., Li, L., Link, J. M., Liu, J., Luxnat, M., Major, A., Mann, K., Markoff, D. M., Mattingly, J., Moye, J., Mueller, P. E., Newby, J., Ogoi, N., O'Reilly, J., Parno, D. S., Pérez-Loureiro, D., Pershey, D., Prior, C. G., Queen, J., Rapp, R., Ray, H., Razuvaeva, O., Reyna, D., Rich, G. C., Rudik, D., Runge, J., Salvat, D. J., Sander, J., Scholberg, K., Shakirov, A., Simakov, G., Snow, W. M., Sosnovtsev, V., Stringer, M., Subedi, T., Suh, B., Sur, B., Tayloe, R., Tellez-Giron-Flores, K., Tsai, Y. -T., van Nieuwenhuizen, E. E., Virtue, C. J., Visser, G., Walkup, K., Ward, E. M., Wongjirad, T., Yang, Y., Yoo, J., Yu, C. -H., and Zaalishvili, A.

Subjects
High Energy Physics - Experiment
Abstract

We report the first detection of coherent elastic neutrino-nucleus scattering (CEvNS) on germanium, measured at the Spallation Neutron Source at Oak Ridge National Laboratory. The Ge-Mini detector of the COHERENT collaboration employs large-mass, low-noise, high-purity germanium spectrometers, enabling excellent energy resolution, and an analysis threshold of 1.5 keV electron-equivalent ionization energy. We observe a on-beam excess of 20.6$_{+7.1}^{-6.3}$ counts with a total exposure of 10.22 GWhkg and we reject the no-CEvNS hypothesis with 3.9 sigma significance. The result agrees with the predicted standard model of particle physics signal rate within 2 sigma., Comment: 7 pages, 5 figures

Published
2024

31. The Black Hole Explorer: Motivation and Vision

Author

Johnson, Michael D., Akiyama, Kazunori, Baturin, Rebecca, Bilyeu, Bryan, Blackburn, Lindy, Boroson, Don, Cardenas-Avendano, Alejandro, Chael, Andrew, Chan, Chi-kwan, Chang, Dominic, Cheimets, Peter, Chou, Cathy, Doeleman, Sheperd S., Farah, Joseph, Galison, Peter, Gamble, Ronald, Gammie, Charles F., Gelles, Zachary, Gomez, Jose L., Gralla, Samuel E., Grimes, Paul, Gurvits, Leonid I., Hadar, Shahar, Haworth, Kari, Hada, Kazuhiro, Hecht, Michael H., Honma, Mareki, Houston, Janice, Hudson, Ben, Issaoun, Sara, Jia, He, Jorstad, Svetlana, Kauffmann, Jens, Kovalev, Yuri Y., Kurczynski, Peter, Lafon, Robert, Lupsasca, Alexandru, Lehmensiek, Robert, Ma, Chung-Pei, Marrone, Daniel P., Marscher, Alan P., Melnick, Gary J., Narayan, Ramesh, Niinuma, Kotaro, Noble, Scott C., Palmer, Eric J., Palumbo, Daniel C. M., Paritsky, Lenny, Peretz, Eliad, Pesce, Dominic, Plavin, Alexander, Quataert, Eliot, Rana, Hannah, Ricarte, Angelo, Roelofs, Freek, Shtyrkova, Katia, Sinclair, Laura C., Small, Jeffrey, Kumara, Sridharan Tirupati, Srinivasan, Ranjani, Strominger, Andrew, Tiede, Paul, Tong, Edward, Wang, Jade, Weintroub, Jonathan, Wielgus, Maciek, Wong, George, and Zhang, Xinyue Alice

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract

We present the Black Hole Explorer (BHEX), a mission that will produce the sharpest images in the history of astronomy by extending submillimeter Very-Long-Baseline Interferometry (VLBI) to space. BHEX will discover and measure the bright and narrow "photon ring" that is predicted to exist in images of black holes, produced from light that has orbited the black hole before escaping. This discovery will expose universal features of a black hole's spacetime that are distinct from the complex astrophysics of the emitting plasma, allowing the first direct measurements of a supermassive black hole's spin. In addition to studying the properties of the nearby supermassive black holes M87* and Sgr A*, BHEX will measure the properties of dozens of additional supermassive black holes, providing crucial insights into the processes that drive their creation and growth. BHEX will also connect these supermassive black holes to their relativistic jets, elucidating the power source for the brightest and most efficient engines in the universe. BHEX will address fundamental open questions in the physics and astrophysics of black holes that cannot be answered without submillimeter space VLBI. The mission is enabled by recent technological breakthroughs, including the development of ultra-high-speed downlink using laser communications, and it leverages billions of dollars of existing ground infrastructure. We present the motivation for BHEX, its science goals and associated requirements, and the pathway to launch within the next decade., Comment: Proceedings for SPIE Astronomical Telescopes and Instrumentation

Published
2024
Full Text
View/download PDF

32. Probing the Scalar WIMP-Pion Coupling with the first LUX-ZEPLIN data

Author

Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Balashov, S., Bang, J., Barillier, E. E., Bargemann, J. W., Beattie, K., Benson, T., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Bishop, E. J., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Burdin, S., Buuck, M., Carmona-Benitez, M. C., Carter, M., Chawla, A., Chen, H., Cherwinka, J. J., Chin, Y. T., Chott, N. I., Converse, M. V., Cottle, A., Cox, G., Curran, D., Dahl, C. E., David, A., Delgaudio, J., Dey, S., deViveiros, L., DiFelice, L., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Eriksen, S. R., Fan, A., Fearon, N. M., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T. M. A., Gaitskell, R. J., Geffre, A., Genovesi, J., Ghag, C., Gibbons, R., Gokhale, S., Green, J., vanderGrinten, M. G. D., Haiston, J. J., Hall, C. R., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Hernandez, M. A., Hertel, S. A., Heuermann, G., Homenides, G. J., Horn, M., Huang, D. Q., Hunt, D., Jacquet, E., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., Kannichankandy, M., Khaitan, D., Khazov, A., Khurana, I., DKim, J., Kim, J., Kingston, J., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., Kudryavtsev, V. A., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Lopes, M. I., Lorenzon, W., Lu, C., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Maupin, C., McCarthy, M. E., McDowell, G., McKinsey, D. N., McLaughlin, J., McLaughlin, J. B., McMonigle, R., Miller, E. H., Mizrachi, E., Monte, A., Monzani, M. E., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naylor, A., Nelson, H. N., Neves, F., Nguyen, A., Nikoleyczik, J. A., Olcina, I., Oliver-Mallory, K. C., Orpwood, J., Palladino, K. J., Palmer, J., Pannifer, N. J., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Qie, Y., Reichenbacher, J., Rhyne, C. A., Riffard, Q., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Rushton, T., Rynders, D., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Siniscalco, J., Smith, R., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Szydagis, M., Taylor, W. C., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Tronstad, D. R., Vacheret, A., Vaitkus, A. C., Valentino, O., Velan, V., Wang, A., Wang, J. J., Wang, Y., Watson, J. R., Webb, R. C., Weeldreyer, L., Whitis, T. J., Williams, M., Wisniewski, W. J., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xiang, X., Xu, J., Yeh, M., and Zweig, E. A.

Subjects
High Energy Physics - Experiment
Abstract

Weakly interacting massive particles (WIMPs) may interact with a virtual pion that is exchanged between nucleons. This interaction channel is important to consider in models where the spin-independent isoscalar channel is suppressed. Using data from the first science run of the LUX-ZEPLIN dark matter experiment, containing 60 live days of data in a 5.5~tonne fiducial mass of liquid xenon, we report the results on a search for WIMP-pion interactions. We observe no significant excess and set an upper limit of $1.5\times10^{-46}$~cm$^2$ at a 90\% confidence level for a WIMP mass of 33~GeV/c$^2$ for this interaction.

Published
2024
Full Text
View/download PDF

33. Multi-Object Tracking based on Imaging Radar 3D Object Detection

Author

Palmer, Patrick, Krüger, Martin, Altendorfer, Richard, and Bertram, Torsten

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract

Effective tracking of surrounding traffic participants allows for an accurate state estimation as a necessary ingredient for prediction of future behavior and therefore adequate planning of the ego vehicle trajectory. One approach for detecting and tracking surrounding traffic participants is the combination of a learning based object detector with a classical tracking algorithm. Learning based object detectors have been shown to work adequately on lidar and camera data, while learning based object detectors using standard radar data input have proven to be inferior. Recently, with the improvements to radar sensor technology in the form of imaging radars, the object detection performance on radar was greatly improved but is still limited compared to lidar sensors due to the sparsity of the radar point cloud. This presents a unique challenge for the task of multi-object tracking. The tracking algorithm must overcome the limited detection quality while generating consistent tracks. To this end, a comparison between different multi-object tracking methods on imaging radar data is required to investigate its potential for downstream tasks. The work at hand compares multiple approaches and analyzes their limitations when applied to imaging radar data. Furthermore, enhancements to the presented approaches in the form of probabilistic association algorithms are considered for this task., Comment: Presented at: 9. International ATZ-Live Automated Driving 2024

Published
2024

34. Certifying Adapters: Enabling and Enhancing the Certification of Classifier Adversarial Robustness

Author

Deng, Jieren, Hong, Hanbin, Palmer, Aaron, Zhou, Xin, Bi, Jinbo, Mahmood, Kaleel, Hong, Yuan, and Aguiar, Derek

Subjects
Computer Science - Machine Learning, Computer Science - Cryptography and Security, Computer Science - Computer Vision and Pattern Recognition
Abstract

Randomized smoothing has become a leading method for achieving certified robustness in deep classifiers against l_{p}-norm adversarial perturbations. Current approaches for achieving certified robustness, such as data augmentation with Gaussian noise and adversarial training, require expensive training procedures that tune large models for different Gaussian noise levels and thus cannot leverage high-performance pre-trained neural networks. In this work, we introduce a novel certifying adapters framework (CAF) that enables and enhances the certification of classifier adversarial robustness. Our approach makes few assumptions about the underlying training algorithm or feature extractor and is thus broadly applicable to different feature extractor architectures (e.g., convolutional neural networks or vision transformers) and smoothing algorithms. We show that CAF (a) enables certification in uncertified models pre-trained on clean datasets and (b) substantially improves the performance of certified classifiers via randomized smoothing and SmoothAdv at multiple radii in CIFAR-10 and ImageNet. We demonstrate that CAF achieves improved certified accuracies when compared to methods based on random or denoised smoothing, and that CAF is insensitive to certifying adapter hyperparameters. Finally, we show that an ensemble of adapters enables a single pre-trained feature extractor to defend against a range of noise perturbation scales.

Published
2024

35. The Data Acquisition System of the LZ Dark Matter Detector: FADR

Author

Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Balashov, S., Bang, J., Barillier, E. E., Bargemann, J. W., Beattie, K., Benson, T., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Bishop, E., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Buckley, J. H., Burdin, S., Buuck, M., Carmona-Benitez, M. C., Carter, M., Chawla, A., Chen, H., Cherwinka, J. J., Chin, Y. T., Chott, N. I., Converse, M. V., Cottle, A., Cox, G., Curran, D., Dahl, C. E., David, A., Delgaudio, J., Dey, S., de Viveiros, L., Di Felice, L., Dimino, T., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Eriksen, S. R., Fan, A., Fearon, N. M., Fieldhouse, N., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T. M. A., Gaitskell, R. J., Geffre, A., Gelfand, R., Genovesi, J., Ghag, C., Gibbons, R., Gokhale, S., Green, J., van der Grinten, M. G. D., Haiston, J. J., Hall, C. R., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Hernandez, M. A., Hertel, S. A., Heuermann, G., Homenides, G. J., Horn, M., Huang, D. Q., Hunt, D., Jacquet, E., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., Kannichankandy, M., Khaitan, D., Khazov, A., Khurana, I., Kim, J., Kim, Y. D., Kingston, J., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Koyuncu, M., Kraus, H., Kravitz, S., Kreczko, L., Kudryavtsev, V. A., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Loniewski, C., Lopes, M. I., Lorenzon, W., Lu, C., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Maupin, C., McCarthy, M. E., McDowell, G., McKinsey, D. N., McLaughlin, J., Mclaughlin, J. B., McMonigle, R., Miller, E. H., Mizrachi, E., Monte, A., Monzani, M. E., Moongweluwan, M., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naylor, A., Nelson, H. N., Neves, F., Nguyen, A., Nikoleyczik, J. A., Oh, H., Olcina, I., Olevitch, M. A., Oliver-Mallory, K. C., Orpwood, J., Palladino, K. J., Palmer, J., Pannifer, N. J., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Qie, Y., Reichenbacher, J., Rhyne, C. A., Riffard, Q., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Rushton, T., Rynders, D., Santone, D., Sarkis, R., Sazzad, A. B. M. R., Schnee, R. W., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Siniscalco, J., Skulski, W., Smith, R., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Szydagis, M., Taylor, W. C., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Tronstad, D. R., Vacheret, A., Vaitkus, A. C., Vaitkus, J., Valentino, O., Velan, V., Wang, A., Wang, J. J., Wang, Y., Watson, J. R., Webb, R. C., Weeldreyer, L., Whitis, T. J., Williams, M., Wisniewski, W. J., Wolfs, F. L. H., Wolfs, J. D., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xiang, X., Xu, J., Yeh, M., and Yin, J.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

The Data Acquisition System (DAQ) for the LUX-ZEPLIN (LZ) dark matter detector is described. The signals from 745 PMTs, distributed across three subsystems, are sampled with 100-MHz 32-channel digitizers (DDC-32s). A basic waveform analysis is carried out on the on-board Field Programmable Gate Arrays (FPGAs) to extract information about the observed scintillation and electroluminescence signals. This information is used to determine if the digitized waveforms should be preserved for offline analysis. The system is designed around the Kintex-7 FPGA. In addition to digitizing the PMT signals and providing basic event selection in real time, the flexibility provided by the use of FPGAs allows us to monitor the performance of the detector and the DAQ in parallel to normal data acquisition. The hardware and software/firmware of this FPGA-based Architecture for Data acquisition and Realtime monitoring (FADR) are discussed and performance measurements are described., Comment: 18 pages, 24 figures

Published
2024

36. Expected Gamma-Ray Burst Detection Rates and Redshift Distributions for the BlackCAT CubeSat Mission

Author

Colosimo, Joseph M., Fox, Derek B., Falcone, Abraham D., Palmer, David M., Hancock, Frederic, Betts, Michael, Bevidas Jr., William A., Buffington, Jacob C., Burrows, David N., Catlin, Zachary E., Emeigh, Timothy, Forstmeier, Thomas, Nizam, Kadri M., Reichard, Collin, Scigliani, Ana C., Stone, Lukas R., Thornton, Ian, Wages, Mitchell, Washington, Daniel, and Zugger, Michael E.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

We report the results of an extensive set of simulations exploring the sensitivity of the BlackCAT CubeSat to long-duration gamma-ray bursts (GRBs). BlackCAT is a NASA APRA-funded CubeSat mission for the detection and real-time sub-arcminute localization of high-redshift ($z\gtrsim 3.5$) GRBs. Thanks to their luminous and long-lived afterglow emissions, GRBs are uniquely valuable probes of high-redshift star-forming galaxies and the intergalactic medium. In addition, each detected GRB with a known redshift serves to localize a region of high-redshift star formation in three dimensions, enabling deep follow-on searches for host galaxies and associated local and large-scale structures. We explore two distinct models for the GRB redshift distribution and luminosity function, both consistent with Swift observations. We find that, for either model, BlackCAT is expected to detect a mean of 42 bursts per year on-orbit, with 6.7% to 10% of these at $z>3.5$. BlackCAT bursts will be localized to $r_{90} \lesssim 55^{\prime\prime}$ precision and reported to the community within seconds. Due to the mission orbit and pointing scheme, bursts will be located in the night sky and well-placed for deep multiwavelength follow-up observations. BlackCAT is on schedule to achieve launch readiness in 2025., Comment: 10 pages, 4 figures, 3 tables; Published in ApJ

Published
2024
Full Text
View/download PDF

37. Mechanics and morphology of proliferating cell collectives with self-inhibiting growth

Author

Weady, Scott, Palmer, Bryce, Lamson, Adam, Kim, Taeyoon, Farhadifar, Reza, and Shelley, Michael J.

Subjects
Physics - Biological Physics, Condensed Matter - Soft Condensed Matter
Abstract

We study the dynamics of proliferating cell collectives whose microscopic constituents' growth is inhibited by macroscopic growth-induced stress. Discrete particle simulations of a growing collective show the emergence of concentric-ring patterns in cell size whose spatio-temporal structure is closely tied to the individual cell's stress response. Motivated by these observations, we derive a multiscale continuum theory whose parameters map directly to the discrete model. Analytical solutions of this theory show the concentric patterns arise from anisotropically accumulated resistance to growth over many cell cycles. This work shows how purely mechanical processes can affect the internal patterning and morphology of cell collectives, and provides a concise theoretical framework for connecting the micro- to macroscopic dynamics of proliferating matter.

Published
2024

38. Adapting Abstract Meaning Representation Parsing to the Clinical Narrative -- the SPRING THYME parser

Author

Cai, Jon Z., Wright-Bettner, Kristin, Palmer, Martha, Savova, Guergana K., and Martin, James H.

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

This paper is dedicated to the design and evaluation of the first AMR parser tailored for clinical notes. Our objective was to facilitate the precise transformation of the clinical notes into structured AMR expressions, thereby enhancing the interpretability and usability of clinical text data at scale. Leveraging the colon cancer dataset from the Temporal Histories of Your Medical Events (THYME) corpus, we adapted a state-of-the-art AMR parser utilizing continuous training. Our approach incorporates data augmentation techniques to enhance the accuracy of AMR structure predictions. Notably, through this learning strategy, our parser achieved an impressive F1 score of 88% on the THYME corpus's colon cancer dataset. Moreover, our research delved into the efficacy of data required for domain adaptation within the realm of clinical notes, presenting domain adaptation data requirements for AMR parsing. This exploration not only underscores the parser's robust performance but also highlights its potential in facilitating a deeper understanding of clinical narratives through structured semantic representations., Comment: Accepted to the 6th Clinical NLP Workshop at NAACL, 2024

Published
2024

39. SCI 3.0: A Web-based Schema Curation Interface for Graphical Event Representations

Author

Suchocki, Reece, Martin, Mary, Palmer, Martha, and Brown, Susan

Subjects
Computer Science - Computation and Language
Abstract

To understand the complexity of global events, one must navigate a web of interwoven sub-events, identifying those most impactful elements within the larger, abstract macro-event framework at play. This concept can be extended to the field of natural language processing (NLP) through the creation of structured event schemas which can serve as representations of these abstract events. Central to our approach is the Schema Curation Interface 3.0 (SCI 3.0), a web application that facilitates real-time editing of event schema properties within a generated graph e.g., adding, removing, or editing sub-events, entities, and relations directly through an interface.

Published
2024

40. To Trust or Not to Trust: Towards a novel approach to measure trust for XAI systems

Author

Miró-Nicolau, Miquel, Moyà-Alcover, Gabriel, Jaume-i-Capó, Antoni, González-Hidalgo, Manuel, Campello, Maria Gemma Sempere, and Sancho, Juan Antonio Palmer

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

The increasing reliance on Deep Learning models, combined with their inherent lack of transparency, has spurred the development of a novel field of study known as eXplainable AI (XAI) methods. These methods seek to enhance the trust of end-users in automated systems by providing insights into the rationale behind their decisions. This paper presents a novel approach for measuring user trust in XAI systems, allowing their refinement. Our proposed metric combines both performance metrics and trust indicators from an objective perspective. To validate this novel methodology, we conducted a case study in a realistic medical scenario: the usage of XAI system for the detection of pneumonia from x-ray images.

Published
2024

41. Compact and finite-type support in the homology of big mapping class groups

Author

Palmer, Martin and Wu, Xiaolei

Subjects
Mathematics - Geometric Topology, Mathematics - Algebraic Topology, Mathematics - Group Theory, 57K20, 20J06
Abstract

For any infinite-type surface $S$, a natural question is whether the homology of its mapping class group contains any non-trivial classes that are supported on (i) a compact subsurface or (ii) a finite-type subsurface. Our purpose here is to study this question, in particular giving an almost-complete answer when the genus of $S$ is positive (including infinite) and a partial answer when the genus of $S$ is zero. Our methods involve the notion of shiftable subsurfaces as well as homological stability for mapping class groups of finite-type surfaces., Comment: 23 pages, 5 figures. v2: statements of results have been clarified to carefully disambiguate the three distinct questions that we answer. Comments welcome!

Published
2024

42. Lifting Directional Fields to Minimal Sections

Author

Palmer, David, Chern, Albert, and Solomon, Justin

Subjects
Computer Science - Graphics, I.3.5, G.1.6, G.1.8
Abstract

Directional fields, including unit vector, line, and cross fields, are essential tools in the geometry processing toolkit. The topology of directional fields is characterized by their singularities. While singularities play an important role in downstream applications such as meshing, existing methods for computing directional fields either require them to be specified in advance, ignore them altogether, or treat them as zeros of a relaxed field. While fields are ill-defined at their singularities, the graphs of directional fields with singularities are well-defined surfaces in a circle bundle. By lifting optimization of fields to optimization over their graphs, we can exploit a natural convex relaxation to a minimal section problem over the space of currents in the bundle. This relaxation treats singularities as first-class citizens, expressing the relationship between fields and singularities as an explicit boundary condition. As curvature frustrates finite element discretization of the bundle, we devise a hybrid spectral method for representing and optimizing minimal sections. Our method supports field optimization on both flat and curved domains and enables more precise control over singularity placement., Comment: 20 pages, 21 figures; to appear at SIGGRAPH 2024

Published
2024
Full Text
View/download PDF

43. The Design, Implementation, and Performance of the LZ Calibration Systems

Author

Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Balashov, S., Bang, J., Barillier, E. E., Bargemann, J. W., Beattie, K., Benson, T., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Bishop, E., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Burdin, S., Buuck, M., Carmona-Benitez, M. C., Carter, M., Chawla, A., Chen, H., Cherwinka, J. J., Chin, Y. T., Chott, N. I., Converse, M. V., Cottle, A., Cox, G., Curran, D., Dahl, C. E., David, A., Delgaudio, J., Dey, S., de Viveiros, L., Di Felice, L., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Eriksen, S. R., Fan, A., Fearon, N. M., Fieldhouse, N., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T. M. A., Gaitskell, R. J., Geffre, A., Genovesi, J., Ghag, C., Gibbons, R., Gokhale, S., Green, J., van der Grinten, M. G. D., Haiston, J. J., Hall, C. R., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Hernandez, M. A., Hertel, S. A., Heuermann, G., Homenides, G. J., Horn, M., Huang, D. Q., Hunt, D., Jacquet, E., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., Kannichankandy, M., Khaitan, D., Khazov, A., Khurana, I., Kim, J., Kim, Y. D., Kingston, J., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., Kudryavtsev, V. A., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Lopes, M. I., Lorenzon, W., Lu, C., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Maupin, C., McCarthy, M. E., McDowell, G., McKinsey, D. N., McLaughlin, J., Mclaughlin, J. B., McMonigle, R., Miller, E. H., Mizrachi, E., Monte, A., Monzani, M. E., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naylor, A., Nelson, H. N., Neves, F., Nguyen, A., Nikoleyczik, J. A., Olcina, I., Oliver-Mallory, K. C., Orpwood, J., Palladino, K. J., Palmer, J., Pannifer, N. J., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Qie, Y., Reichenbacher, J., Rhyne, C. A., Riffard, Q., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Rushton, T., Rynders, D., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Siniscalco, J., Smith, R., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Szydagis, M., Taylor, W. C., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Tronstad, D. R., Vacheret, A., Vaitkus, A. C., Valentino, O., Velan, V., Wang, A., Wang, J. J., Wang, Y., Watson, J. R., Webb, R. C., Weeldreyer, L., Whitis, T. J., Williams, M., Wisniewski, W. J., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xiang, X., Xu, J., and Yeh, M.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

LUX-ZEPLIN (LZ) is a tonne-scale experiment searching for direct dark matter interactions and other rare events. It is located at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, USA. The core of the LZ detector is a dual-phase xenon time projection chamber (TPC), designed with the primary goal of detecting Weakly Interacting Massive Particles (WIMPs) via their induced low energy nuclear recoils. Surrounding the TPC, two veto detectors immersed in an ultra-pure water tank enable reducing background events to enhance the discovery potential. Intricate calibration systems are purposely designed to precisely understand the responses of these three detector volumes to various types of particle interactions and to demonstrate LZ's ability to discriminate between signals and backgrounds. In this paper, we present a comprehensive discussion of the key features, requirements, and performance of the LZ calibration systems, which play a crucial role in enabling LZ's WIMP-search and its broad science program. The thorough description of these calibration systems, with an emphasis on their novel aspects, is valuable for future calibration efforts in direct dark matter and other rare-event search experiments.

Published
2024
Full Text
View/download PDF

44. Generalized Ramsey-Tur\'an Numbers

Author

Balogh, József, Magnan, Van, and Palmer, Cory

Subjects
Mathematics - Combinatorics
Abstract

The Ramsey-Tur\'an problem for $K_p$ asks for the maximum number of edges in an $n$-vertex $K_p$-free graph with independence number $o(n)$. In a natural generalization of the problem, cliques larger than the edge $K_2$ are counted. Let {\bf RT}$(n,\#K_q,K_p,o(n))$ denote the maximum number of copies of $K_q$ in an $n$-vertex $K_p$-free graph with independence number $o(n)$. Balogh, Liu and Sharifzadeh determined the asymptotics of {\bf RT}$(n,\# K_3,K_p,o(n))$. In this paper we will establish the asymptotics for counting copies of $K_4$, $K_5$, and for the case $p \geq 5q$. We also provide a family of counterexamples to a conjecture of Balogh, Liu and Sharifzadeh., Comment: Fixed an icorrect row in Table 1 and corresponding computation in proof of Theorem 1.5

Published
2024

45. Probing the scalar WIMP-pion coupling with the first LUX-ZEPLIN data

Author

Zweig, EA, Yeh, M, Xu, J, Xiang, X, Xia, Q, Wright, CJ, Woodward, D, Woodford, S, Wolfs, FLH, Wisniewski, WJ, Williams, M, Whitis, TJ, Weeldreyer, L, Webb, RC, Watson, JR, Wang, Y, Wang, JJ, Wang, A, Velan, V, Valentino, O, Vaitkus, AC, Vacheret, A, Tronstad, DR, Tripathi, M, Trask, M, Tranter, J, Tovey, DR, Tong, Z, Timalsina, M, Tiedt, DR, Taylor, WC, Szydagis, M, Sumner, TJ, Suerfu, B, Stifter, K, Stevens, A, Stancu, I, Soria, J, Sorensen, P, Solovov, VN, Smith, R, Siniscalco, J, Sinev, G, Silva, C, Silk, JJ, Shutt, T, Shaw, S, Schnee, RW, Sazzad, ABMR, Santone, D, Rynders, D, Rushton, T, Rosero, R, Riyat, HS, Rischbieter, GRC, Riffard, Q, Rhyne, CA, Reichenbacher, J, Qie, Y, Piepke, A, Pershing, T, Perry, E, Pereira, G, Penning, B, Patton, SJ, Parveen, N, Pannifer, NJ, Palmer, J, Palladino, KJ, Orpwood, J, Oliver-Mallory, KC, Olcina, I, Nikoleyczik, JA, Nguyen, A, Neves, F, Nelson, HN, Naylor, A, Murphy, ASJ, Murdy, M, Mount, BJ, Morrison, E, Morales Mendoza, JD, Monzani, ME, Monte, A, Mizrachi, E, Miller, EH, McMonigle, R, McLaughlin, JB, McLaughlin, J, McKinsey, DN, McDowell, G, McCarthy, ME, Maupin, C, Mannino, RL, Manalaysay, A, Majewski, PA, Luitz, S, Lu, C, Lorenzon, W, and Lopes, MI

Subjects
Nuclear and Plasma Physics, Particle and High Energy Physics, Physical Sciences, Engineering, Mathematical sciences, Physical sciences
Abstract

Weakly interacting massive particles (WIMPs) may interact with a virtual pion that is exchanged between nucleons. This interaction channel is important to consider in models where the spin-independent isoscalar channel is suppressed. Using data from the first science run of the LUX-ZEPLIN dark matter experiment, containing 60 live days of data in a 5.5 tonne fiducial mass of liquid xenon, we report the results on a search for WIMP-pion interactions. We observe no significant excess and set an upper limit of 1.5 × 10−46 cm2 at a 90% confidence level for a WIMP mass of 33 GeV/c2 for this interaction.

Published
2024

46. Mental Wellbeing among Higher Education Students in England during the Pandemic: A Longitudinal Study of COVID-19 Experiences, Social Connectedness and Greenspace Use

Author

Anaïs Lemyre, Benjamin W. Chrisinger, Emma Palmer-Cooper, and Jane P. Messina

Abstract

The COVID-19 pandemic control measures substantially impacted the life of university students in the UK. While multiple studies investigated early stages of the pandemic, focusing on risk factors for depression and anxiety, fewer studies assessed later phases of the pandemic or examined positive protective factors for mental wellbeing. Our longitudinal study investigated changes and associations between COVID-19 experiences, lifestyle behaviours, social connectedness and mental wellbeing in the second year of the pandemic. The validated Warwick-Edinburgh Mental Wellbeing Scale was used to measure the primary outcome mental wellbeing. Self-reported data from 161 university students (18-35-year-old) in England was obtained. Data collection took place across two time points with contrasting COVID-19 epidemiological and countermeasure attributes. T1 occurred in the spring of 2021, during the tail end of the third national lockdown when indoor household mixing was prohibited and vaccination rates were low among 18-35 year olds. T2 took place 6 months later, in the autumn of 2021, when restrictions had ended and vaccination rates were high. Within-participant changes in students showed that mental wellbeing significantly improved over 6 months, suggesting positive adjustment. Fear of COVID-19 and engagement in COVID-19 protective behaviours significantly decreased as pandemic restrictions eased. Physical activity levels were high and did not change over time, while greenspace visits significantly diminished. Social support remained the same and group membership significantly increased over time. Hierarchal regressions revealed that social support was the most critical contributor to mental wellbeing. We discuss lessons for mental wellbeing promotion strategies: encouraging the use of greenspace as locations for distanced social interaction and physical activity in times of lockdown constraints.

Published
2024
Full Text
View/download PDF

47. C?haracterizing Pedagogical Innovation in Higher Education

Author

Michael S. Palmer and Judith A. Giering

Abstract

To help higher education instructors, academic support personnel, and institutional leadership better identify, encourage, incentivize, fund, support and assess pedagogical innovation, we describe herein a valid taxonomy capable of precisely characterizing the range of pedagogical innovations in higher education. The Taxonomy of Pedagogical Innovation in Higher Education probes the "Focus of Innovation," "Degree of Innovation," "Intended Outcomes," "Barriers to Adoption," "Risks of Adoption," and direct and indirect "Costs." Using two scenarios, we illustrate how to apply the taxonomy to a pedagogical innovation with different sets of contextual factors. We conclude by discussing how the taxonomy might help provide a shared vocabulary for and understanding of pedagogical innovation, align pedagogical innovation to priorities, inform investment strategy, characterize an institution's innovation culture, and help to guide efforts to assess the impact of pedagogical innovations.

Published
2024
Full Text
View/download PDF

48. Surviving and Thriving in School Psychology through Community Building and Storytelling: A Collaborative Autoethnography

Author

Lisa N. Aguilar, Karina Mojica, Hanna S. Lim, Maria D. L. Ruiz-Montoya, Ja'Toria S. Palmer, Carissa B. Serratos, and Jaylin M. Soto

Abstract

As marginalized graduate students and faculty, we have stories to tell about our experiences within school psychology. Many of these stories center our oppression, trauma, and exclusion but some of them also center our joy and resistance. The purpose of this collaborative autoethnographic project was to create a counterspace in which we, BIWOC faculty and graduate students, could come together to engage in storytelling and build community amongst one another as a way to survive and thrive in academia. As a result of the counterspace, we are able to provide critical feedback and recommendations for school psychology programs to better support marginalized students and faculty. And we also offer critical hope and knowledge to marginalized graduate students and faculty who are currently in the field.

Published
2024
Full Text
View/download PDF

49. Middle Leaders Pursuing Teacher Safety against Learner Victimization: A Policy Document Analysis

Author

Edwin Darrell de Klerk and June Monica Palmer

Abstract

Various scholars have confirmed that teacher safety against learner victimization is a growing concern worldwide, and this problem is exacerbated by a lack of understanding and readiness to implement policies to address this matter. In this regard, policy implementation by middle leaders (MLs) in creating safe school environments has attracted much less interest as a possible way of addressing issues of teacher safety and the prevention of learner victimization. MLs are regarded as individuals who have the potential to lead, plan, inspire and persuade, and in so doing, they are in an ideal position to translate policy into practice. As such, this paper provides a qualitative policy document analysis of The National School Safety Framework (NSSF) premised on the theory that every individual in the school experiences safety in dissimilar ways and has unique safety needs. The NSSF is endorsed by the Department of Basic Education to guide in addressing issues of violence and safety in South African schools. Underpinned by the rational choice theory and utilizing policy document analysis, texts in the NSSF were analysed and interpreted to propose transformative policy strategies that can assist MLs in managing teachers' safety at schools more effectively. The findings suggest that administrative duties and a lack of time make it difficult for MLs to create a safe and supportive learning environment in schools. Another finding was that there is no clear plan outlined in the NSSF to guide MLs to pursue teacher safety against learner victimization in schools. To assist MLs, this paper proposes transformative policy strategies that can assist them in promoting teacher safety and preventing learner victimization in schools. The paper recommends that more explicit interpretation and implementation strategies be communicated with schools to assist them in fighting the war against violence in schools.

Published
2024
Full Text
View/download PDF

50. An Overview of Black Males and Mental Health in Higher Education: Implications for Practice and Research

Author

Robert T. Palmer and Tryan L. McMickens

Abstract

This article discusses some critical underlying factors that facilitate mental health concerns for Black males in higher education. This article also focuses on the role that student affairs practitioners and faculty can play in supporting Black males on college campuses with mental health needs. This article concludes with recommendations and critical research to further research and practice.

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results