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51. $\mathrm{SL}_{4}(\mathbf{Z})$ is not purely matricial field

Author

Magee, Michael and de la Salle, Mikael

Subjects
Mathematics - Group Theory, Mathematics - Operator Algebras
Abstract

We prove that every finite dimensional unitary representation of $\mathrm{SL}_{4}(\mathbf{Z})$ contains a non-zero $\mathrm{SL}_{2}(\mathbf{Z})$-invariant vector. As a consequence, there is no sequence of finite-dimensional representations of $\mathrm{SL}_{4}(\mathbf{Z})$ that gives rise to an embedding of its reduced $C^*$-algebra into an ultraproduct of matrix algebras., Comment: v2: 9 pages; details added in proof, and example for SL3 made explicit. To appear in Comptes Rendus Math\'ematique

Published
2023

52. Breaking the Glass Ceiling: A Multiregional Study of Mentorship and Leadership in All-Women Surgical Teams

Author

Bustamante A, Salazar Lopez BB, Jones EM, Turk M, Tapia Arellano MF, Treminio S, Rata MJ, Msokera C, Daradkeh H, Barkhordarzadeh AD, Umutoni A, Bautista A, Naidu P, Munabi NCO, Magee III WP, Cote EA, Magee K, and Auslander A

Subjects
gender equity, healthcare workforce, surgery, global health, Public aspects of medicine, RA1-1270
Abstract

Atenas Bustamante,1 Barbara Beatriz Salazar Lopez,1,* Emily Marie Jones,1,* Marvee Turk,2 Maria Fernanda Tapia Arellano,1 Sonia Treminio,1 Mikyla Jade Rata,1 Chifundo Msokera,1,3,4 Hebah Daradkeh,1 Ainaz Dory Barkhordarzadeh,5 Alice Umutoni,1 Alyssa Bautista,1 Priyanka Naidu,2 Naikhoba C O Munabi,2 William P Magee III,1,2 Elizabeth A Cote,1 Kathy Magee,1 Allyn Auslander1 1Operation Smile Inc., Virginia Beach, VA, USA; 2Division of Plastic and Maxillofacial Surgery, Children’s Hospital Los Angeles, Los Angeles, CA, USA; 3Department of Clinical Medicine, University of Oxford, Oxford, England; 4Clinical Services, Ministry of Health, Lilongwe, Malawi; 5David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA*These authors contributed equally to this workCorrespondence: Allyn Auslander, Research and Innovation, Operation Smile Inc., Virginia Beach, VA, USA, Email allyn.auslander@operationsmile.orgBackground: Globally, billions of people lack access to safe surgical care. Women represent a valuable resource to tackle the healthcare workforce shortage which impedes the delivery of surgery. With women entering the global health workforce at an increasing rate, Operation Smile (OS) launched the Women in Medicine program to create women-led leadership and mentorship opportunities for women healthcare workers to empower them to become leaders in healthcare.Purpose: This multi-regional study aims to evaluate the experiences of healthcare providers on OS all-women surgical programs and the impact of participation on leadership and mentorship opportunities.Methods: In 2022, OS conducted four cleft surgical programs with all-women providers in Morocco, Peru, Malawi, and the Philippines. Providers from various specialties participating in the programs were surveyed. Participants were invited to complete the surveys anonymously in the final two days of each program. Analysis involved descriptive statistics and chi-square tests.Results: Across all programs, 215 providers from 36 countries were surveyed. Ninety-seven percent of participants reported improvement in their technical and non-technical skills. Eighty-two percent reported that the program motivated them to seek leadership positions, despite only 37% having prior leadership experience on an OS program. Participating in an all-women team motivated 96% to seek mentorship from another woman and 99% to mentor others. Overall, 98% of providers across all regions and specialties supported the importance of women leadership, and 95% endorsed women mentorship.Conclusion: Promoting gender equity is crucial to address the ongoing healthcare workforce shortage and improve access to safe surgical care. This study demonstrates the importance of mentorship between women to advance into leadership positions. Programs that provide women in healthcare with educational, mentorship, and leadership opportunities can effectively equip them with the skills needed to advance their careers and strengthen the global workforce.Keywords: gender equity, healthcare workforce, surgery, global health

Published
2024

61. The ultraviolet continuum slopes of high-redshift galaxies: evidence for the emergence of dust-free stellar populations at z > 10

Author

Cullen, F., McLeod, D. J., McLure, R. J., Dunlop, J. S., Donnan, C. T., Carnall, A. C., Keating, L. C., Magee, D., Arellano-Cordova, K. Z., Bowler, R. A. A., Begley, R., Flury, S. R., Hamadouche, M. L., and Stanton, T. M.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present an analysis of the ultraviolet (UV) continuum slopes ($\beta$) for a sample of $172$ galaxy candidates at $8 < z_{\mathrm{phot}} < 16$ selected from a combination of JWST NIRCam imaging and COSMOS/UltraVISTA ground-based near-infrared imaging. Focusing primarily on a new sample of $121$ galaxies at $\langle z \rangle \simeq 11$ selected from $\simeq 320$ arcmin$^2$ of public JWST imaging data across $15$ independent data sets, we investigate the evolution of $\beta$ in the galaxy population at $z \geq 9$. We find a significant trend between $\beta$ and redshift, with the inverse-variance weighted mean UV slope evolving from $\langle \beta \rangle = -2.17 \pm 0.06$ at $z = 9.5$ to $\langle \beta \rangle = -2.59 \pm 0.06$ at $z = 11.5$. Based on a comparison with stellar population models including nebular continuum emission, we find that at $z>10.5$ the average UV continuum slope is consistent with the intrinsic blue limit of dust-free stellar populations $(\beta_{\mathrm{int}} \simeq -2.6)$. These results suggest that the moderately dust-reddened galaxy population at $z < 10$ was essentially unattenuated at $z \simeq 11$. The extremely blue galaxies being uncovered at $z>10$ place important constraints on dust attenuation in galaxies in the early Universe, and imply that the already observed galaxy population is likely supplying an ionising photon budget capable of maintaining ionised IGM fractions of $\gtrsim 5$ per cent at $z\simeq11$., Comment: 18 pages, 12 figures, MNRAS accepted

Published
2023

62. The impact of selection biases on tests of general relativity with gravitational-wave inspirals

Author

Magee, Ryan, Isi, Maximiliano, Payne, Ethan, Chatziioannou, Katerina, Farr, Will M., Pratten, Geraint, and Vitale, Salvatore

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

Tests of general relativity with gravitational wave observations from merging compact binaries continue to confirm Einstein's theory of gravity with increasing precision. However, these tests have so far only been applied to signals that were first confidently detected by matched-filter searches assuming general relativity templates. This raises the question of selection biases: what is the largest deviation from general relativity that current searches can detect, and are current constraints on such deviations necessarily narrow because they are based on signals that were detected by templated searches in the first place? In this paper, we estimate the impact of selection effects for tests of the inspiral phase evolution of compact binary signals with a simplified version of the GstLAL search pipeline. We find that selection biases affect the search for very large values of the deviation parameters, much larger than the constraints implied by the detected signals. Therefore, combined population constraints from confidently detected events are mostly unaffected by selection biases, with the largest effect being a broadening at the $\sim10$ % level for the $-1$PN term. These findings suggest that current population constraints on the inspiral phase are robust without factoring in selection biases. Our study does not rule out a disjoint, undetectable binary population with large deviations from general relativity, or stronger selection effects in other tests or search procedures.

Published
2023
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63. (Re)framing Built Heritage through the Machinic Gaze

Author

Arora, Vanicka, Magee, Liam, and Munn, Luke

Subjects
Computer Science - Computers and Society, J.5, K.4.2
Abstract

Built heritage has been both subject and product of a gaze that has been sustained through moments of colonial fixation on ruins and monuments, technocratic examination and representation, and fetishisation by aglobal tourist industry. We argue that the recent proliferation of machine learning and vision technologies create new scopic regimes for heritage: storing and retrieving existing images from vast digital archives, and further imparting their own distortions upon its visual representation. We introduce the term `machinic gaze' to conceptualise the reconfiguration of heritage representation via AI models. To explore how this gaze reframes heritage, we deploy an image-text-image pipeline that reads, interprets, and resynthesizes images of several UNESCO World Heritage Sites. Employing two concepts from media studies -- heteroscopia and anamorphosis -- we describe the reoriented perspective that machine vision systems introduce. We propose that the machinic gaze highlights the artifice of the human gaze and its underlying assumptions and practices that combine to form established notions of heritage., Comment: 18 pages, 5 figures

Published
2023

64. Unveiling the hidden universe with JWST: The contribution of dust-obscured galaxies to the stellar mass function at $z\sim3-8$

Author

Gottumukkala, R., Barrufet, L., Oesch, P. A., Weibel, A., Allen, N., Pampliega, B. Alcalde, Nelson, E. J., Williams, C. C., Brammer, G., Fudamoto, Y., González, V., Heintz, K. E., Illingworth, G., Magee, D., Naidu, R. P., Shuntov, M., Stefanon, M., Toft, S., Valentino, F., and Xiao, M.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

With the advent of JWST, we can probe the rest-frame optical emission of galaxies at $z>3$ with high sensitivity and spatial resolution, making it possible to accurately characterise red, optically-faint galaxies and thus move towards a more complete census of the galaxy population at high redshifts. To this end, we present a sample of 148 massive, dusty galaxies from the JWST/CEERS survey, colour-selected using solely JWST bands. With deep JWST/NIRCam data from 1.15$\mu$m to 4.44$\mu$m and ancillary HST/ACS and WFC3 data, we determine the physical properties of our sample using spectral energy distribution fitting with BAGPIPES. We demonstrate that our selection method efficiently identifies massive ($\mathrm{\langle \log M_\star/M_\odot \rangle \sim 10}$) and dusty ($\mathrm{\langle A_V\rangle \sim 2.7\ mag}$) sources, with a majority at $z>3$ and predominantly lying on the galaxy main-sequence. The main results of this work are the stellar mass functions (SMF) of red, optically-faint galaxies from redshifts between $3

Published
2023
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65. Minimum Monotone Tree Decomposition of Density Functions Defined on Graphs

Author

Magee, Lucas and Wang, Yusu

Subjects
Computer Science - Data Structures and Algorithms, Computer Science - Computational Complexity, Computer Science - Computational Geometry
Abstract

Monotone trees - trees with a function defined on their vertices that decreases the further away from a root node one travels, are a natural model for a process that weakens the further one gets from its source. Given an aggregation of monotone trees, one may wish to reconstruct the individual monotone components. A natural representation of such an aggregation would be a graph. While many methods have been developed for extracting hidden graph structure from datasets, which makes obtaining such an aggregation possible, decomposing such graphs into the original monotone trees is algorithmically challenging. Recently, a polynomial time algorithm has been developed to extract a minimum cardinality collection of monotone trees (M-Tree Set) from a given density tree - but no such algorithm exists for density graphs that may contain cycles. In this work, we prove that extracting such minimum M-Tree Sets of density graphs is NP-Complete. We additionally prove three additional variations of the problem - such as the minimum M-Tree Set such that the intersection between any two monotone trees is either empty or contractible (SM-Tree Set) - are also NP-Complete. We conclude by providing some approximation algorithms, highlighted by a 3-approximation algorithm for computing the minimum SM-Tree Set for density cactus graphs.

Published
2023

66. The Web Epoch of Reionization Lyman-$\alpha$ Survey (WERLS) I. MOSFIRE Spectroscopy of $\mathbf{z \sim 7-8}$ Lyman-$\alpha$ Emitters

Author

Cooper, Olivia R., Casey, Caitlin M., Akins, Hollis B., Magee, Jake, Melendez, Alfonso, Fong, Mia, Stawinski, Stephanie M. Urbano, Kartaltepe, Jeyhan S., Finkelstein, Steven L., Larson, Rebecca L., Jung, Intae, Bista, Ash, Champagne, Jaclyn B., Ortiz, Oscar A. Chavez, Coffin, Sadie, Cooper, M. C., Drakos, Nicole, Faisst, Andreas L., Franco, Maximilien, Fujimoto, Seiji, Gillman, Steven, Gozaliasl, Ghassem, Harish, Santosh, Hutchison, Taylor A., Koekemoer, Anton M., Kokorev, Vasily, Lertprasertpong, Jitrapon, Liu, Daizhong, Long, Arianna S., Papovich, Casey, Rich, R. Michael, Robertson, Brant E., Talia, Margherita, Vanderhoof, Brittany N., Whitaker, Katherine E., and Zavala, Jorge A.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present the first results from the Web Epoch of Reionization Lyman-$\alpha$ Survey (WERLS), a spectroscopic survey of Lyman-$\alpha$ emission using Keck I/MOSFIRE and LRIS. WERLS targets bright ($J<26$) galaxy candidates with photometric redshifts of $5.5\lesssim z \lesssim 8$ selected from pre-JWST imaging embedded in the Epoch of Reionization (EoR) within three JWST deep fields: CEERS, PRIMER, and COSMOS-Web. Here, we report 11 $z\sim7-8$ Lyman-$\alpha$ emitters (LAEs; 3 secure and 8 tentative candidates) detected in the first five nights of WERLS MOSFIRE data. We estimate our observed LAE yield is $\sim13$%, broadly consistent with expectations assuming some loss from redshift uncertainty, contamination from sky OH lines, and that the Universe is approximately half-ionized at this epoch, whereby observable Lyman-$\alpha$ emission is unlikely for galaxies embedded in a neutral intergalactic medium. Our targets are selected to be UV-bright, and span a range of absolute UV magnitudes with $-23.1 < M_{\text{UV}} < -19.8$. With two LAEs detected at $z=7.68$, we also consider the possibility of an ionized bubble at this redshift. Future synergistic Keck+JWST efforts will provide a powerful tool for pinpointing beacons of reionization and mapping the large scale distribution of mass relative to the ionization state of the Universe., Comment: 27 pages, 8 figures; ApJ submitted

Published
2023

67. Accelerated Formation of Ultra-Massive Galaxies in the First Billion Years

Author

Xiao, Mengyuan, Oesch, Pascal, Elbaz, David, Bing, Longji, Nelson, Erica, Weibel, Andrea, Illingworth, Garth, van Dokkum, Pieter, Naidu, Rohan, Daddi, Emanuele, Bouwens, Rychard, Matthee, Jorryt, Wuyts, Stijn, Chisholm, John, Brammer, Gabriel, Dickinson, Mark, Magnelli, Benjamin, Leroy, Lucas, Schaerer, Daniel, Herard-Demanche, Thomas, Lim, Seunghwan, Barrufet, Laia, Endsley, Ryan, Fudamoto, Yoshinobu, Gómez-Guijarro, Carlos, Gottumukkala, Rashmi, Labbe, Ivo, Magee, Daniel, Marchesini, Danilo, Maseda, Michael, Qin, Yuxiang, Reddy, Naveen, Shapley, Alice, Shivaei, Irene, Shuntov, Marko, Stefanon, Mauro, Whitaker, Katherine, and Wyithe, J. Stuart

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Recent JWST observations have revealed an unexpected abundance of massive galaxy candidates in the early Universe, extending further in redshift and to lower luminosity than what had previously been found by sub-millimeter surveys. These JWST candidates have been interpreted as challenging the $\Lambda$CDM cosmology, but, so far, they have mostly relied only on rest-frame ultraviolet data and lacked spectroscopic confirmation of their redshifts. Here we report a systematic study of 36 massive dust-obscured galaxies with spectroscopic redshifts between $z_{\rm spec}=5-9$ from the JWST FRESCO survey. We find no tension with the $\Lambda$CDM model in our sample. However, three ultra-massive galaxies (log$M_{\star}/M_{\odot}$ $\gtrsim11.0$) require an exceptional fraction of 50% of baryons converted into stars -- two to three times higher than even the most efficient galaxies at later epochs. The contribution from an active nucleus is unlikely because of their extended emission. Ultra-massive galaxies account for as much as 17% of the total cosmic star formation rate density at $z\sim5-6$., Comment: Nature in press. Updated to the accepted version. 24 pages, 4 main figures, 7 supplementary figures, 3 supplementary tables

Published
2023

68. Diagnostic Accuracy of a Handheld Ultrasound vs a Cart-based Model: A Randomized Clinical Trial

Author

Gibbons, Ryan C., Jaeger, Daniel J., Berger, Matthew, Magee, Mark, Shaffer, Claire, and Costantino, Thomas G.

Subjects
point-of-care ultrasound, diagnostic accuracy, Handheld Ultrasound
Abstract

Introduction: Numerous studies have demonstrated the accuracy of point-of-care ultrasound (POCUS). Portable, handheld devices have expanded the clinical scope of POCUS at a fraction of the cost of traditional, cart-based models. There is a paucity of data assessing the diagnostic accuracy of portable devices. Our objective in this study was to compare the diagnostic accuracy of a portable device with a cart-based model.Methods: This was an institutional review board-approved, observational, prospective, randomized clinical trial (NCT05196776) of a convenience sample of adult patients who presented to a university-based health system. Patients who required a cardiac, lung, renal, aorta, or biliary POCUS were randomized to a portable device or to a cart-based model. We hypothesized that the cart-based model would have a 90% diagnostic accuracy vs 70% for the handheld device. To detect a 20% difference, the sample size was calculated to be 98, with 49 patients randomized to each arm. We used standard 2x2 tables to calculate test characteristics with 95% confidence intervals (CI).Results: A total of 110 patients were enrolled, with 56 patients randomized to the cart-based model and 54 to the handheld device. The sensitivity, specificity, and diagnostic accuracy of the cart-based vs handheld were 77.8% (40–97.2) vs 92.9% (66.1–99.8), 91.5% (79.6–97.6) vs 92.3% (79.1–98.4%), and 89.3% (78.1–96) vs 92.5% (81.8–97.9), respectively.Conclusion: The diagnostic accuracy of a portable, handheld device is similar to that of a cart-based model.

Published
2024

69. Fatty Liver Education Promotes Physical Activity in Vulnerable Groups, Including Those With Unhealthy Alcohol Use

Author

Patel, Shyam, Kim, Rebecca G, Shui, Amy M, Magee, Catherine, Lu, Maggie, Chen, Jennifer, Tana, Michele, Huang, Chiung-Yu, and Khalili, Mandana

Subjects
Biomedical and Clinical Sciences, Public Health, Health Sciences, Clinical Sciences, Minority Health, Health Disparities, Women's Health, Alcoholism, Alcohol Use and Health, Liver Disease, Prevention, Clinical Research, Substance Misuse, Behavioral and Social Science, Physical Activity, Social Determinants of Health, Digestive Diseases, Oral and gastrointestinal, Good Health and Well Being, Alcohol-Associated Liver Disease, Exercise, Lifestyle Modification, Nonalcoholic Fatty Liver Disease, Steatotic liver disease, Underserved Populations
Abstract

Background and aimsFatty liver disease (FLD), alcohol-associated and metabolically associated, often coexists. Increase in physical activity is associated with metabolic health and decreased FLD. We aimed to identify factors associated with physical activity and its improvement following FLD education in a racially diverse, vulnerable population.MethodsFrom February 19, 2020 to December 30, 2022, 314 adults with FLD at safety-net hepatology clinics in San Francisco were surveyed at baseline, immediately after FLD education, and at 6-month follow-up. After collecting clinical and sociodemographic data, logistic regression (adjusted for age, sex, and race/ethnicity) assessed factors associated with physical activity at baseline and its improvement following education.ResultsParticipant characteristics in those without vs with any physical activity were median age 49 vs 55 years, 64% vs 56% female, 66% vs 53% Hispanic race/ethnicity, 75% vs 55% obese, and 30% vs 22% consumed heavy alcohol, respectively. On multivariable analysis, older age was the only significant factor associated with physical activity at baseline (relative risk ratio 1.37 per decade increase, 95% confidence interval [CI] 1.07-1.75). Hispanic (vs non-Hispanic) participants had a significantly higher odds of improvement in physical activity (vs no change) 6 months after education (odds ratio 2.36, 95% CI 1.27-4.39). Among those with suboptimal or no physical activity at baseline, participants who consumed heavy alcohol (vs no drinking) had a significantly higher likelihood of achieving optimal physical activity following education (relative risk ratio 1.98, 95% CI 1.05-3.74).ConclusionDespite social and structural barriers, FLD education increased uptake of physical activity in vulnerable populations, especially among Hispanic individuals and those consuming heavy alcohol. Implementation of patient-centered education is important for FLD management.

Published
2024

71. Cross‐sectional study on stigma and motivation to adhere to lifestyle modification among vulnerable populations with fatty liver disease

Author

Medina, Sheyla P, Kim, Rebecca G, Magee, Catherine, Stapper, Noah, and Khalili, Mandana

Subjects
Health Services and Systems, Biomedical and Clinical Sciences, Health Sciences, Liver Disease, Behavioral and Social Science, Prevention, Digestive Diseases, Clinical Research, Nutrition, Substance Misuse, Brain Disorders, Alcoholism, Alcohol Use and Health, Good Health and Well Being, alcohol-associated liver disease, behavioral modification, metabolic syndrome, NAFLD, underserved populations, alcohol‐associated liver disease, Nutrition and dietetics, Allied health and rehabilitation science
Abstract

ObjectivesAdherence to lifestyle modification (diet, exercise, and alcohol cessation) for fatty liver disease (FLD) management remains challenging. The study examined stigma, barriers, and factors associated with motivation to adhere to lifestyle modification in a diverse and vulnerable population with FLD.MethodsFrom 2/19/2020 to 2/28/2022, 249 FLD patients within San Francisco safety-net hepatology clinics were surveyed along with clinical data taken from medical records. Multivariable modeling assessed factors associated with motivation to adhere to lifestyle modification in a cross-sectional study.ResultsMedian age was 53 years, 59% female, 59% Hispanic, 25% Asian/Pacific Islander, 9% White, and 2% Black, 79% were non-English speakers, 64% had ≤ high school education, and 82% reported high school (coef 1.41, 95% CI 0.34-2.48), stigma (coef 0.34, 95% CI 0.07-0.62), and depression (coef -1.52, 95% CI -2.79 to -0.26) were associated with motivation.ConclusionsStigma is commonly reported among FLD patients. Interventions to enhance patient education and mental health support are critical to FLD management, especially in vulnerable populations.

Published
2023

72. HIV co-infection increases the risk of post-tuberculosis mortality among persons who initiated treatment for drug-resistant tuberculosis

Author

Argita D. Salindri, Maia Kipiani, Nino Lomtadze, Nestani Tukvadze, Zaza Avaliani, Henry M. Blumberg, Katherine E. Masyn, Richard B. Rothenberg, Russell R. Kempker, and Matthew J. Magee

Subjects
Tuberculosis, Post-TB mortality, Comorbidities, HIV co-infection, Diabetes, Hepatitis C, Medicine, Science
Abstract

Abstract Little is known regarding the relationship between common comorbidities in persons with tuberculosis (TB) (including human immunodeficiency virus [HIV], diabetes, and hepatitis C virus [HCV]) and post-TB mortality. We conducted a retrospective cohort study among persons who initiated treatment for rifampicin-resistant or multi/extensively drug-resistant (RR or M/XDR) TB reported to the country of Georgia’s TB surveillance during 2009–2017. Exposures included HIV serologic status, diabetes, and HCV status. Our outcome was all-cause post-TB mortality determined by cross-validating vital status with Georgia’s death registry through November 2019. We estimated adjusted hazard rate ratios (aHR) and 95% confidence intervals (CI) of post-TB mortality among participants with and without comorbidities using cause-specific hazard regressions. Among 1032 eligible participants, 34 (3.3%) died during treatment and 87 (8.7%) died post-TB treatment. The median time to post-TB death was 21 months (interquartile range 7–39) after TB treatment. After adjusting for confounders, the hazard rates of post-TB mortality were higher among participants with HIV co-infection (aHR = 3.74, 95%CI 1.77–7.91) compared to those without HIV co-infection. In our cohort, post-TB mortality occurred most commonly in the first 3 years post-TB treatment. Linkage to care for common TB comorbidities post-treatment may reduce post-TB mortality rates.

Published
2024
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73. Demonstrating the Efficacy of Dual Energy Computer Tomography with Gemstone Spectral Imaging Software to Determine Mixed and Single Composition ex vivo Urolithiasis

Author

Magee D, Jeewa F, Chau MVHD, Loh PL, Ballesta Martinez B, Saluja M, Aw IH, Lozinskiy M, Lee S, Rosenberg M, and Yuiminaga Y

Subjects
endourology, basic research, dual energy computer tomography, dect, gsi, gemstone spectral imaging, Diseases of the genitourinary system. Urology, RC870-923
Abstract

Daniel Magee,1 Feroza Jeewa,1 Matthew Vinh-Hoan Dinh Chau,1 Pamphila Lovelle Loh,1 Begona Ballesta Martinez,1– 3 Manmeet Saluja,1 Ivan H Aw,1 Mikhail Lozinskiy,1 Sunny Lee,1 Melanie Rosenberg,4 Yuigi Yuiminaga1 1Department of Urology, Royal Perth Hospital, Perth, WA, Australia; 2Department of Urology, University of Patras, Patras, Greece; 3University of La Laguna, SC de Tenerife, Spain; 4Senior Radiographer, Department of Radiology, Royal Perth Hospital, Perth, WA, AustraliaCorrespondence: Daniel Magee, Department of Urology, Royal Perth Hospital, Wellington Street, Perth, WA, 6000, Australia, Tel +61 9224 2931, Email danielmagee05@gmail.comObjective: To assess the capability of determining the mixed chemical composition of urinary stones using spectral imaging properties of Dual Energy Computed Tomography (DECT) Gemstone Spectral Imaging (GSI) software.Material and Methods: Twenty-six single and 24 mixed composition ex vivo urinary stones with known chemical composition determined by Fourier-transform infrared spectroscopy (FTIR) prior to this project were scanned with DECT imaging and GSI in vitro. The major components of the stones included Uric Acid (UA), Calcium Oxalate (CaOx), Calcium Phosphate (CaP), Magnesium Ammonium Phosphate (MAP), and Cystine (Cys). A histogram to display the distribution of the effective atomic number (Z-eff) of each pixel of the tested area, spectral curve (40– 140 keV, with 10 keV interval) and Hounsfield Units (HU) of each stone scanned was provided with analysis of monochromatic images at 140 keV in the axial plane.Results: The overall pooled sensitivity, specificity, and accuracy of DECT for identifying major stone composition were 0.802, 0.831, and 0.807, respectively, with a 95% confidence interval. Accuracy was 100% for identifying UA and Cys stones.Conclusion: DECT is a superior imaging modality when compared to low dose computed tomography kidney ureter bladder scans. It allows for improved characterization of major components of urinary stones, in an accurate, non-invasive approach to pre-treatment. This can translate to urologists having greater confidence in determining patient suitability for medical or surgical management of their renal stones, in clinical practice.Keywords: endourology, basic research, dual energy computer tomography, DECT, GSI, gemstone spectral imaging

Published
2024

74. Is a Diverse Sample of College Students Motivated by Compassionate, Neutral, or Fear-Inducing Language in COVID-19 Crisis Messages?

Author

Jan Mohlman, Corey H. Basch, Gregory Bartoszek, and Sofia Magee

Abstract

Objective: During public health emergencies such as the ongoing COVID-19 illness pandemic, it is essential to rapidly disseminate crisis messages which often contain embedded health directives. This study investigated which of three variants of the same messages (neutral tone, positive/compassionate tone, negative/fear-inducing tone) were most likely to motivate readers to engage in the health behavior proscribed in the message. Participants: Participants were 87 female and 41 male undergraduates at an urban university in the northeast U.S. Methods: A survey with three versions of eight different COVID messages containing health directives was administered. Results: Those who indicated stronger influence of positive/compassionate crisis messages (i.e., had higher Crisis Messages Survey scores) had higher adaptive health engagement scores, lower worry scores, and were likely to have had a past diagnosis of COVID-19. Moreover, a regression model including COVID-19 status and worry scores accounted for a significant proportion of variance in Crisis Messages Survey scores. Conclusions: Findings indicate that the use of neutral and compassionate language is optimal in motivating health behaviors embedded in university crisis messages.

Published
2024
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75. Co-Creation Solutions and the Three Co's Framework for Applying Co-Creation

Author

Gemma Pearce and Paul Magee

Abstract

Purpose: A sense of collective free-thinking with tangible goals makes co-creation an enlightening experience. Yet despite the freedom and organic flow of the methodology, there remain barriers to deploying co-creation in the real-world context. The aim was to understand the barriers and solutions to co-creation, reflect on applying co-creation in practice and co-create an applicable framework for co-creation. Design/methodology/approach: These reflections and conceptual developments were completed using a Participatory Action Research Approach through the co-creation of the Erasmus+ funded Co-creating Welfare course. Findings: Results presented are centric to the experiences in the United Kingdom but led to application at an international level. Problem formulation led to solutions devised about who should co-create, what co-creation aims to achieve, how to receive management buy-in, co-creating beyond the local face to face context and evaluation. Originality/value: The Three Co's Framework is proposed using the outline of: Co-Define, Co-Design and Co-Refine. Those who take part in co-creation processes are recommended to be called co-creators, with less focus on "empowerment" and more about facilitating people to harness the power they already have. Utilising online and hybrid delivery methods can be more inclusive, especially in response to the COVID-19 pandemic. The use of co-creation needs to be evaluated more moving forwards, as well as the output co-created.

Published
2024
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79. Intersectional Inquiry, on the Ground and in the Algorithm

Author

Robertson, Shanthi, Magee, Liam, and Soldatić, Karen

Subjects
Computer Science - Computers and Society, K.4.2
Abstract

This article makes two key contributions to methodological debates in automation research. First, we argue for and demonstrate how methods in this field must account for intersections of social difference, such as race, class, ethnicity, culture, and disability, in more nuanced ways. Second, we consider the complexities of bringing together computational and qualitative methods in an intersectional methodological approach while also arguing that in their respective subjects (machines and human subjects) and conceptual scope they enable a specific dialogue on intersectionality and automation to be articulated. We draw on field reflections from a project that combines an analysis of intersectional bias in language models with findings from a community workshop on the frustrations and aspirations produced through engagement with everyday AI-driven technologies in the context of care.

Published
2023
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80. A Joint Fermi-GBM and Swift-BAT Analysis of Gravitational-Wave Candidates from the Third Gravitational-wave Observing Run

Author

Fletcher, C., Wood, J., Hamburg, R., Veres, P., Hui, C. M., Bissaldi, E., Briggs, M. S., Burns, E., Cleveland, W. H., Giles, M. M., Goldstein, A., Hristov, B. A., Kocevski, D., Lesage, S., Mailyan, B., Malacaria, C., Poolakkil, S., von Kienlin, A., Wilson-Hodge, C. A., Team, The Fermi Gamma-ray Burst Monitor, Crnogorčević, M., DeLaunay, J., Tohuvavohu, A., Caputo, R., Cenko, S. B., Laha, S., Parsotan, T., Abbott, R., Abe, H., Acernese, F., Ackley, K., Adhikari, N., Adhikari, R. X., Adkins, V. K., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Agatsuma, K., Aggarwal, N., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Allocca, A., Altin, P. A., Amato, A., Anand, C., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andríc, T., Angelova, S. V., Ansoldi, S., Antelis, J. M., Antier, S., Apostolatos, T., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Arène, M., Aritomi, N., Arnaud, N., Arogeti, M., Aronson, S. M., Arun, K. G., Asada, H., Asali, Y., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Austin, C., Babak, S., Badaracco, F., Bader, M. K. M., Badger, C., Bae, S., Bae, Y., Baer, A. M., Bagnasco, S., Bai, Y., Baird, J., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Balsamo, A., Baltus, G., Banagiri, S., Banerjee, B., Bankar, D., Barayoga, J. C., Barbieri, C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartlett, J., Barton, M. A., Bartos, I., Basak, S., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Becher, B. R., Becsy, B., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belahcene, I., Benedetto, V., Beniwal, D., Benjamin, M. G., Bennett, T. F., Bentley, J. D., BenYaala, M., Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bhandare, R., Bhandari, A. V., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Bini, S., Birney, R., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Biswas, B., Bitossi, M., Bizouard, M. A., Blackburn, J. K., Blair, C. D., Blair, D. G., Blair, R. M., Bobba, F., Bode, N., Boër, M., Bogaert, G., Boldrini, M., Bolingbroke, G. N., Bonavena, L. D., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., Boom, B. A., Bork, R., Boschi, V., Bose, N., Bose, S., Bossilkov, V., Boudart, V., Bouffanais, Y., Bozzi, A., Bradaschia, C., Brady, P. R., Bramley, A., Branch, A., Branchesi, M., Brau, J. E., Breschi, M., Briant, T., Briggs, J. H., Brillet, A., Brinkmann, M., Brockill, P., Brooks, A. F., Brooks, J., Brown, D. D., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., 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., Caesar, M., Cagnoli, G., Cahillane, C., Bustillo, J. Calderòn, Callaghan, J. D., Callister, T. A., Calloni, E., Cameron, J., Camp, J. B., Canepa, M., Canevarolo, S., Cannavacciuolo, M., Cannon, K. C., Cao, H., Cao, Z., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carney, M. F., Carpinelli, M., Carrillo, G., Carullo, G., Carver, T. L., Díaz, J. Casanueva, Casentini, C., Castaldi, G., Caudill, S., Cavaglià, M., Cavalier, F., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Subrahmanya, S. Chalathadka, Champion, E., Chan, C. H., Chan, C., Chan, C. L., Chan, K., Chan, M., Chandra, K., Chang, I. P., Chanial, P., Chao, S., Chapman-Bird, C., Charlton, P., Chase, E. A., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, C., Chen, D., Chen, H. Y., Chen, J., Chen, K., Chen, X., Chen, Y. B., Chen, Y. R., Chen, Z., Cheng, H., Cheong, C. K., Cheung, H. Y., Chia, H. Y., Chiadini, F., Chiang, C. Y., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Choudhary, R. K., Choudhary, S., Christensen, N., Chu, Q., Chu, Y. K., Chua, S. S. Y., Chung, K. W., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Cipriano, F., Clara, F., Clark, J. A., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Codazzo, E., Cohadon, P. F., Cohen, D. E., Colleoni, M., Collette, C. G., Colombo, A., Colpi, M., Compton, C. M., Constancio Jr., M., Conti, L., Cooper, S. J., Corban, P., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Corley, K. R., Cornish, N. J., Corre, D., Corsi, A., Cortese, S., Costa, C. A., Cotesta, R., Cottingham, R., Coughlin, M. W., Coulon, J. P., Countryman, S. T., Cousins, B., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Creighton, J. D. E., Creighton, T. D., Criswell, A. W., Croquette, M., Crowder, S. G., Cudell, J. R., Cullen, T. J., Cumming, A., Cummings, R., Cunningham, L., Cuoco, E., lo, M. Cury, Dabadie, P., Canton, T. Dal, Dall'Osso, S., Dálya, G., Dana, A., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darsow-Fromm, C., Dasgupta, A., Datrier, L. E. H., Datta, Sayak, Datta, Sayantani, Dattilo, V., Dave, I., Davier, M., Davis, D., Davis, M. C., Daw, E. J., Dean, R., DeBra, D., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., Del Favero, V., De Lillo, F., De Lillo, N., Dell'Aquila, D., Del Pozzo, W., DeMarchi, L. M., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., De Simone, R., Dhurandhar, S., D'iaz, M. C., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giorgio, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Di Lieto, A., Di Michele, A., Ding, B., Di Pace, S., Di Palma, I., Di Renzo, F., Divakarla, A. K., Dmitriev, A., Doctor, Z., Donahue, L., D'Onofrio, L., Donovan, F., Dooley, K. L., Doravari, S., Drago, M., Driggers, J. C., Drori, Y., Ducoin, J. G., Dupej, P., Dupletsa, U., Durante, O., D'Urso, D., Duverne, P. A., Dwyer, S. E., Eassa, C., Easter, P. J., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eguchi, S., Eichholz, J., Eikenberry, S. S., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Engelby, E., Enomoto, Y., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etienne, Z., Etzel, T., Evans, M., Evans, T. M., Evstafyeva, T., Ewing, B. E., Fabrizi, F., Faedi, F., Fafone, V., Fair, H., Fairhurst, S., Fan, P. C., Farah, A. M., Farinon, S., Farr, B., Farr, W. M., Fauchon-Jones, E. J., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Fenyvesi, E., Ferguson, D. L., Fernandez-Galiana, A., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Floden, E., Fong, H. K., Font, J. A., Fornal, B., Forsyth, P. W. F., Franke, A., Frasca, S., Frasconi, F., Freed, J. P., Frei, Z., Freise, A., Freitas, O., Frey, R., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fujii, Y., Fujikawa, Y., Fujimoto, Y., Fulda, P., Fyffe, M., Gabbard, H. A., Gabella, W. E., Gadre, B. U., Gair, J. R., Gais, J., Galaudage, S., Gamba, R., Ganapathy, D., Ganguly, A., Gao, D., Gaonkar, S. G., Garaventa, B., Núñez, C. García, García-Quirós, C., Garufi, F., Gateley, B., Gayathri, V., Ge, G. G., Gemme, G., Gennai, A., George, J., Gerberding, O., Gergely, L., Gewecke, P., Ghonge, S., Ghosh, Abhirup, Ghosh, Archisman, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Tathagata, Giacomazzo, B., Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gier, C., Giesler, M., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Gleckl, A. E., Godwin, P., Goetz, E., Goetz, R., Gohlke, N., Golomb, J., Goncharov, B., Gonzalez, G., Gosselin, M., Gouaty, R., Gould, D. W., Goyal, S., Grace, B., Grado, A., Graham, V., Granata, M., Granata, V., Grant, A., Gras, S., Grassia, P., Gray, C., Gray, R., Greco, G., Green, A. C., Green, R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimes, E., Grimm, S. J., Grote, H., Grunewald, S., Gruning, P., Gruson, A. S., Guerra, D., Guidi, G. M., Guimaraes, A. R., Guixe, G., Gulati, H. K., Gunny, A. M., Guo, H. K., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, I. M., Gupta, P., Gupta, S. K., Gustafson, R., Guzman, F., Ha, S., Hadiputrawan, I. P. W., Haegel, L., Haino, S., Halim, O., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O., Hansen, H., Hansen, T. J., Hanson, J., Harder, T., Haris, K., Harms, J., Harry, G. M., Harry, I. W., Hartwig, D., Hasegawa, K., Haskell, B., Haster, C. J., Hathaway, J. S., Hattori, K., Haughian, K., Hayakawa, H., Hayama, K., Hayes, F. J., Healy, J., Heidmann, A., Heidt, 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., Hennig, M. H., Henshaw, C., Hernandez, A. G., Vivanco, F. Hernandez, Heurs, M., Hewitt, A. L., Higginbotham, S., Hild, S., Hill, P., Himemoto, Y., Hines, A. S., Hirata, N., Hirose, C., Ho, T. C., Hochheim, S., Hofman, D., Hohmann, J. N., Holcomb, D. G., Holland, N. A., Hollows, I. J., Holmes, Z. J., Holt, K., Holz, D. E., Hong, Q., Hough, J., Hourihane, S., Howell, E. J., Hoy, C. G., Hoyland, D., Hreibi, A., Hsieh, B. H., Hsieh, H. F., Hsiung, C., Hsu, Y., Huang, H. Y., Huang, P., Huang, Y. C., Huang, Y. J., Huang, Yiting, Huang, Yiwen, Hübner, M. T., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V., Husa, S., Huttner, S. H., Huxford, R., Huynh-Dinh, T., Ide, S., Idzkowski, B., Iess, A., Inayoshi, K., Inoue, Y., Iosif, P., Isi, M., Isleif, K., Ito, K., Itoh, Y., Iyer, B. R., JaberianHamedan, V., Jacqmin, T., Jacquet, P. E., Jadhav, S. J., Jadhav, S. P., Jain, T., James, A. L., Jan, A. Z., Jani, K., Janquart, J., Janssens, K., Janthalur, N. N., Jaranowski, P., Jariwala, D., Jaume, R., Jenkins, A. C., Jenner, K., Jeon, C., Jia, W., Jiang, J., Jin, H. B., Johns, G. R., Johnston, R., Jones, A. W., Jones, D. I., Jones, P., Jones, R., Joshi, P., Ju, L., Jue, A., Jung, P., Jung, K., Junker, J., Juste, V., Kaihotsu, K., Kajita, T., Kakizaki, M., Kalaghatgi, C. V., Kalogera, V., Kamai, B., Kamiizumi, M., Kanda, N., Kandhasamy, S., Kang, G., Kanner, J. B., Kao, Y., Kapadia, S. J., Kapasi, D. P., Karathanasis, C., Karki, S., Kashyap, R., Kasprzack, M., Kastaun, W., Kato, T., Katsanevas, S., Katsavounidis, E., Katzman, W., Kaur, T., Kawabe, K., Kawaguchi, K., Kéfélian, F., Keitel, D., Key, J. S., Khadka, S., Khalili, F. Y., Khan, S., Khanam, T., Khazanov, E. A., Khetan, N., Khursheed, M., Kijbunchoo, N., Kim, A., Kim, C., Kim, J. C., Kim, J., Kim, K., Kim, W. S., Kim, Y. M., Kimball, C., Kimura, N., Kinley-Hanlon, M., Kirchhoff, R., Kissel, J. S., Klimenko, S., Klinger, T., Knee, A. M., Knowles, T. D., Knust, N., Knyazev, E., Kobayashi, Y., Koch, P., Koekoek, G., Kohri, K., Kokeyama, K., Koley, S., Kolitsidou, P., Kolstein, M., Komori, K., Kondrashov, V., Kong, A. K. H., Kontos, A., Koper, N., Korobko, M., Kovalam, M., Koyama, N., Kozak, D. B., Kozakai, C., Kringel, V., Krishnendu, N. V., Królak, A., Kuehn, G., Kuei, F., Kuijer, P., Kulkarni, S., Kumar, A., Kumar, Prayush, Kumar, Rahul, Kumar, Rakesh, Kume, J., Kuns, K., Kuromiya, Y., Kuroyanagi, S., Kwak, K., Lacaille, G., Lagabbe, P., Laghi, D., Lalande, E., Lalleman, M., Lam, T. L., Lamberts, A., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Leavey, S., LeBohec, S., Lecoeuche, Y. K., Lee, E., Lee, H. M., Lee, H. W., Lee, K., Lee, R., Legred, I. N., Lehmann, J., Lemaitre, A., Lenti, M., Leonardi, M., Leonova, E., Leroy, N., Letendre, N., Levesque, C., Levin, Y., Leviton, J. N., Leyde, K., Li, A. K. Y., Li, B., Li, J., Li, K. L., Li, P., Li, T. G. F., Li, X., Lin, C. Y., Lin, E. T., Lin, F. K., Lin, F. L., Lin, H. L., Lin, L. C. C., Linde, F., Linker, S. D., Linley, J. N., Littenberg, T. B., Liu, G. C., Liu, J., Liu, K., Liu, X., Llamas, F., Lo, R. K. L., Lo, T., London, L. T., Longo, A., Lopez, D., Portilla, M. Lopez, Lorenzini, M., Loriette, V., Lormand, M., Losurdo, G., Lott, T. P., Lough, J. D., Lousto, C. O., Lovelace, G., Lucaccioni, J. F., Lück, H., Lumaca, D., Lundgren, A. P., Luo, L. W., Lynam, J. E., Maarif, M., Macas, R., Machtinger, J. B., MacInnis, M., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Hernandez, I. Magaña, Magazzù, C., Magee, R. M., Maggiore, R., Magnozzi, M., Mahesh, S., Majorana, E., Maksimovic, I., Maliakal, S., Malik, A., Man, N., Mandic, V., Mangano, V., Mansell, G. L., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Pina, D. Marín, Marion, F., Mark, Z., 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, M., Martinez, V. A., Martinez, V., Martinovic, K., Martynov, D. V., Marx, E. J., Masalehdan, H., Mason, K., Massera, E., Masserot, A., Masso-Reid, M., Mastrogiovanni, S., Matas, A., Mateu-Lucena, M., Matichard, F., Matiushechkina, M., Mavalvala, N., McCann, J. J., McCarthy, R., McClelland, D. E., McClincy, P. K., McCormick, S., McCuller, L., McGhee, G. I., McGuire, S. C., McIsaac, C., McIver, J., McRae, T., McWilliams, S. T., Meacher, D., Mehmet, M., Mehta, A. K., Meijer, Q., Melatos, A., Melchor, D. A., Mendell, G., Menendez-Vazquez, A., Menoni, C. S., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Merritt, J. D., Merzougui, M., Meshkov, S., Messenger, C., Messick, C., Meyers, P. M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Mihaylov, D. P., Milano, L., Miller, A. L., Miller, A., Miller, B., Millhouse, M., Mills, J. C., Milotti, E., Minenkov, Y., Mio, N., Mir, Ll. M., Miravet-Tenés, M., Mishkin, A., Mishra, C., Mishra, T., Mistry, T., Mitra, S., Mitrofanov, V. P., Mitselmakher, G., Mittleman, R., Miyakawa, O., Miyo, K., Miyoki, S., Mo, Geoffrey, Modafferi, L. M., Moguel, E., Mogushi, K., Mohapatra, S. R. P., Mohite, S. R., Molina, I., Molina-Ruiz, M., Mondin, M., Montani, M., Moore, C. J., Moragues, J., Moraru, D., Morawski, F., More, A., Moreno, C., Moreno, G., Mori, Y., Morisaki, S., Morisue, N., Moriwaki, Y., Mours, B., Mow-Lowry, C. M., Mozzon, S., Muciaccia, F., Mukherjee, Arunava, Mukherjee, D., Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Muniz, E. A., Murray, P. G., Musenich, R., Muusse, S., Nadji, S. L., Nagano, K., Nagar, A., Nakamura, K., Nakano, H., Nakano, M., Nakayama, Y., Napolano, V., Nardecchia, I., Narola, H., Naticchioni, L., Nayak, B., Nayak, R. K., Neil, B. F., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Neubauer, P., Neunzert, A., Ng, K. Y., Ng, S. W. S., Nguyen, C., Nguyen, P., Nguyen, T., Quynh, L. Nguyen, Ni, J., Ni, W. T., Nichols, S. A., Nishimoto, T., Nishizawa, A., Nissanke, S., Nitoglia, E., Nocera, F., Norman, M., North, C., Nozaki, S., Nurbek, G., Nuttall, L. K., Obayashi, Y., Oberling, J., O'Brien, B. D., O'Dell, J., Oelker, E., Ogaki, W., Oganesyan, G., Oh, J. J., Oh, K., Oh, S. H., Ohashi, M., Ohashi, T., Ohkawa, M., Ohme, F., Ohta, H., Okada, M. A., Okutani, Y., Olivetto, C., Oohara, K., Oram, R., O'Reilly, B., Ormiston, R. G., Ormsby, N. D., O'Shaughnessy, R., O'Shea, E., Oshino, S., Ossokine, S., Osthelder, C., Otabe, S., Ottaway, D. J., Overmier, H., Pace, A. E., Pagano, G., Pagano, R., Page, M. A., Pagliaroli, G., Pai, A., Pai, S. A., Pal, S., Palamos, J. R., Palashov, O., Palomba, C., Pan, H., Pan, K. C., Panda, P. K., Pang, P. T. H., Pankow, C., Pannarale, F., Pant, B. C., Panther, F. H., Paoletti, F., Paoli, A., Paolone, A., Pappas, G., Parisi, A., Park, H., Park, J., Parker, W., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passuello, D., Patel, M., Pathak, M., Patricelli, B., Patron, A. 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A., Prokhorov, L., Prosposito, P., Prudenzi, L., Puecher, A., Punturo, M., Puosi, F., Puppo, P., Purrer, M., Qi, H., Quartey, N., Quetschke, V., Quinonez, P. J., Quitzow-James, R., Raab, F. J., Raaijmakers, G., Radkins, H., Radulesco, N., Raffai, P., Rail, S. X., Raja, S., Rajan, C., Ramirez, K. E., Ramirez, T. D., Ramos-Buades, A., Rana, J., Rapagnani, P., Ray, A., Raymond, V., Raza, N., Razzano, M., Read, J., Rees, L. A., Regimbau, T., Rei, L., Reid, S., Reid, S. W., Reitze, D. H., Relton, P., Renzini, A., Rettegno, P., Revenu, B., Reza, A., Rezac, M., Ricci, F., Richards, D., Richardson, J. W., Richardson, L., Riemenschneider, G., Riles, K., Rinaldi, S., Rink, K., Robertson, N. A., Robie, R., Robinet, F., Rocchi, A., Rodriguez, S., Rolland, L., Rollins, J. G., Romanelli, M., Romano, R., Romel, C. L., Romero, A., Romero-Shaw, I. M., Romie, J. H., Ronchini, S., Rosa, L., Rose, C. A., Rosinska, D., Ross, M. P., Rowan, S., Rowlinson, S. 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Z., Sun, L., Sunil, S., Sur, A., Suresh, J., Sutton, P. J., Suzuki, Takamasa, Suzuki, Takanori, Suzuki, Toshikazu, Swinkels, B. L., Szczepańczyk, M. J., Szewczyk, P., Tacca, M., Tagoshi, H., Tait, S. C., Takahashi, H., Takahashi, R., Takano, S., Takeda, H., Takeda, M., Talbot, C. J., Talbot, C., Tanaka, K., Tanaka, Taiki, Tanaka, Takahiro, Tanasijczuk, A. J., Tanioka, S., Tanner, D. B., Tao, D., Tao, L., Tapia, R. D., Martin, E. N. Tapia San, Taranto, C., Taruya, A., Tasson, J. D., Tenorio, R., Terhune, J. E. S., Terkowski, L., Thirugnanasambandam, M. P., Thomas, M., Thomas, P., Thompson, E. E., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tiwari, Shubhanshu, Tiwari, Srishti, Tiwari, V., Toivonen, A. M., Tolley, A. E., Tomaru, T., Tomura, T., Tonelli, M., Tornasi, Z., Torres-Forne, A., Torrie, C. I., Melo, I. Tosta e, Toyra, D., Trapananti, A., Travasso, F., Traylor, G., Trevor, M., Tringali, M. C., Tripathee, A., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. 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E., Wade, M., Wagner, K. J., Walet, R. C., Walker, M., Wallace, G. S., Wallace, L., Wang, J., Wang, J. Z., Wang, W. H., Ward, R. L., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watchi, J., 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., Wilken, D., Williams, D., Williams, M. J., Williamson, A. R., Willis, J. L., Willke, B., Wilson, D. J., Wipf, C. C., Wlodarczyk, T., Woan, G., Woehler, J., Wofford, J. K., Wong, D., Wong, I. C. F., Wright, M., Wu, C., Wu, D. S., Wu, H., Xiao, D. M. Wysocki L., Yamada, T., Yamamoto, 288 H., Yamamoto, K., Yamamoto, T., Yamashita, K., Yamazaki, R., Yang, F. W., Yang, K. Z., Yang, L., Yang, Y. C., Yang, Y., Yang, Yang, Yap, M. J., Yeeles, D. W., Yeh, S. W., Yelikar, A. B., Ying, M., Yokoyama, J., Yokozawa, T., Yoo, J., Yoshioka, T., Yu, Hang, Yu, Haocun, Yuzurihara, H., Zadrozny, A., Zanolin, M., Zeidler, S., Zelenova, T., Zendri, J. P., Zevin, M., Zhan, M., Zhang, H., Zhang, J., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, G., Zhao, Y., Zhao, Yue, Zhou, R., Zhou, Z., Zhu, X. J., Zhu, Z. H., Zimmerman, A. B., Zucker, M. E., Zweizig, J., Collaboration, The LIGO Scientific, Collaboration, the Virgo, and Collaboration, the KAGRA

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

We present Fermi Gamma-ray Burst Monitor (Fermi-GBM) and Swift Burst Alert Telescope (Swift-BAT) searches for gamma-ray/X-ray counterparts to gravitational wave (GW) candidate events identified during the third observing run of the Advanced LIGO and Advanced Virgo detectors. Using Fermi-GBM on-board triggers and sub-threshold gamma-ray burst (GRB) candidates found in the Fermi-GBM ground analyses, the Targeted Search and the Untargeted Search, we investigate whether there are any coincident GRBs associated with the GWs. We also search the Swift-BAT rate data around the GW times to determine whether a GRB counterpart is present. No counterparts are found. Using both the Fermi-GBM Targeted Search and the Swift-BAT search, we calculate flux upper limits and present joint upper limits on the gamma-ray luminosity of each GW. Given these limits, we constrain theoretical models for the emission of gamma-rays from binary black hole mergers.

Published
2023

81. Unprecedented early flux excess in the hybrid 02es-like type Ia supernova 2022ywc indicates interaction with circumstellar material

Author

Srivastav, Shubham, Moore, T., Nicholl, M., Magee, M. R., Smartt, S. J., Fulton, M. D., Sim, S. A., Pollin, J. M., Galbany, L., Inserra, C., Kozyreva, A., Moriya, Takashi J., Callan, F. P., Sheng, X., Smith, K. W., Sommer, J. S., Anderson, J. P., Deckers, M., Gromadzki, M., Müller-Bravo, T. E., Pignata, G., Rest, A., and Young, D. R.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics
Abstract

We present optical photometric and spectroscopic observations of the 02es-like type Ia supernova (SN) 2022ywc. The transient occurred in the outskirts of an elliptical host galaxy and showed a striking double-peaked light curve with an early excess feature detected in the ATLAS orange and cyan bands. The early excess is remarkably luminous with an absolute magnitude $\sim -19$, comparable in luminosity to the subsequent radioactively-driven second peak. The spectra resemble the hybrid 02es-like SN 2016jhr, that is considered to be a helium shell detonation candidate. We investigate different physical mechanisms that could power such a prominent early excess and rule out massive helium shell detonation, surface $^{56}$Ni distribution and ejecta-companion interaction. We conclude that SN ejecta interacting with circumstellar material (CSM) is the most viable scenario. Semi-analytical modelling with MOSFiT indicates that SN ejecta interacting with $\sim 0.05\,$M$_{\odot}$ of CSM at a distance of $\sim 10^{14}$ cm can explain the extraordinary light curve. A double-degenerate scenario may explain the origin of the CSM, either by tidally-stripped material from the secondary white dwarf, or disk-originated matter launched along polar axes following the disruption and accretion of the secondary white dwarf. A non-spherical CSM configuration could suggest that a small fraction of 02es-like events viewed along a favourable line of sight may be expected to display a very conspicuous early excess like SN 2022ywc., Comment: Accepted to ApJL after minor revision

Published
2023

82. Low-latency gravitational wave alert products and their performance at the time of the fourth LIGO-Virgo-KAGRA observing run

Author

Chaudhary, Sushant Sharma, Toivonen, Andrew, Waratkar, Gaurav, Mo, Geoffrey, Chatterjee, Deep, Antier, Sarah, Brockill, Patrick, Coughlin, Michael W., Essick, Reed, Ghosh, Shaon, Morisaki, Soichiro, Baral, Pratyusava, Baylor, Amanda, Adhikari, Naresh, Brady, Patrick, Davies, Gareth Cabourn, Canton, Tito Dal, Cavaglià, Marco, Creighton, Jolien, Choudhary, Sunil, Chu, Yu-Kuang, Clearwater, Patrick, Davis, Luke, Dent, Thomas, Drago, Marco, Ewing, Becca, Godwin, Patrick, Guo, Weichangfeng, Hanna, Chad, Huxford, Rachel, Harry, Ian, Katsavounidis, Erik, Kovalam, Manoj, Li, Alvin K. Y., Magee, Ryan, Marx, Ethan, Meacher, Duncan, Messick, Cody, Morice-Atkinson, Xan, Pace, Alexander, De Pietri, Roberto, Piotrzkowski, Brandon, Roy, Soumen, Sachdev, Surabhi, Singer, Leo P., Singh, Divya, Szczepanczyk, Marek, Tang, Daniel, Trevor, Max, Tsukada, Leo, Villa-Ortega, Verónica, Wen, Linqing, and Wysocki, Daniel

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Multi-messenger searches for BNS and NSBH mergers are currently one of the most exciting areas of astronomy. The search for joint electromagnetic and neutrino counterparts to GWs has resumed with O4. To support this effort, public semi-automated data products are sent in near real-time and include localization and source properties to guide complementary observations. In preparation for O4, we have conducted a study using a simulated population of compact binaries and a MDC in the form of a real-time replay to optimize and profile the software infrastructure and scientific deliverables. End-to-end performance was tested, including data ingestion, running online search pipelines, performing annotations, and issuing alerts to the astrophysics community. We present an overview of the low-latency infrastructure and the performance of the data products that are now being released during O4 based on the MDC. We report the expected median latency for the preliminary alert of full bandwidth searches (29.5s) and show consistency and accuracy of released data products using the MDC. For the first time, we report the expected median latency for triggers from early warning searches (-3.1s), which are new in O4 and target neutron star mergers during inspiral phase. This paper provides a performance overview for LVK low-latency alert infrastructure and data products using the MDC and serves as a useful reference for the interpretation of O4 detections.

Published
2023
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83. Search for Eccentric Black Hole Coalescences during the Third Observing Run of LIGO and Virgo

Author

The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abe, H., 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., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Almualla, M., Altin, P. A., Álvarez-López, S., Amato, A., Amez-Droz, L., Amorosi, A., Anand, S., Ananyeva, A., Andersen, R., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Apostolatos, T., 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., Arun, K. G., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Babak, S., Badalyan, A., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bai, Y., Baier, J. G., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Baltus, G., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barber, J., 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., 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., Bhandari, A. V., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bianchi, A., Bilenko, I. A., Bilicki, M., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boër, M., Bogaert, G., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonnand, R., Booker, P., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., 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., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cadonati, L., Cagnoli, G., Cahillane, C., Cain III, H. W., 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., 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., Chalathadka-Subrahmanya, S., Chan, C., Chan, J. C. L., Chan, K. H. M., Chan, M., Chan, W. L., Chandra, K., Chang, I. P., Chang, R. -J., Chang, W., Chanial, P., Chao, S., Chapman-Bird, C., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chastain, L., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chatziioannou, K., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, X., Chen, Y. -R., Chen, Y., Cheng, H., Chessa, P., 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., 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., Cowburn, B. D., Coyne, D. C., Coyne, R., Craig, K., Creighton, J. D. E., Creighton, T. D., 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., Curyło, M., 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., Darsow-Fromm, C., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Dave, I., Davenport, A., Davier, M., Davis, D., Davis, M. C., Daw, E. J., Dax, M., 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., De Pietri, R., De Rosa, R., De Rossi, C., De Simone, R., Dhurandhar, S., Diab, R., Diamond, P. Z., Díaz, M. C., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Lieto, A., 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. 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D., Martín, E. N. Tapia San, Tarafder, R., Taranto, C., Taruya, A., Tasson, J. D., Teloi, M., Tenorio, R., Terkowski, L., Themann, H., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tissino, J., Tiwari, Shubhanshu, Tiwari, Srishti, Tiwari, V., Toivonen, A. M., Tolley, A. E., Tomaru, T., Tomita, K., Tomura, T., Tonelli, M., Toriyama, A., 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., Tse, M., 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., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., 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., 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., Venneberg, J., Verdier, P., Verkindt, D., Verma, P., Verma, Y., Vermeulen, S. M., Veske, D., Vetrano, F., Veutro, A., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, 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., Ward, R. L., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watada, K., 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., Williamson, A. R., Willis, J. L., Willke, B., Wils, M., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wong, D., Wong, H. T., Wong, I. C. F., Wright, M., Wu, C., Wu, D. S., Wu, H., Wysocki, D. M., Xiao, L., Xu, V. A., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, M., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yang, F. W., Yang, K. Z., Yang, L. -C., Yang, Y. -C., Yang, Yang, Yang, Yi, Yap, M. J., Yarbrough, Z., Yeh, S. -W., Yelikar, A. B., Yeung, S. M. C., Yeung, T. Y., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuzurihara, H., Zadrożny, A., Zannelli, A. J., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zevin, M., Zhang, J., Zhang, L., Zhang, R., Zhang, T., Zhang, Yanqi, Zhang, Ya, Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhou, R., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass $M>70$ $M_\odot$) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities $0 < e \leq 0.3$ at $0.33$ Gpc$^{-3}$ yr$^{-1}$ at 90\% confidence level., Comment: 24 pages, 5 figures

Published
2023

84. Strongly convergent unitary representations of right-angled Artin groups

Author

Magee, Michael and Thomas, Joe

Subjects
Mathematics - Group Theory, Mathematics - Operator Algebras, Mathematics - Probability, Mathematics - Representation Theory, Mathematics - Spectral Theory, 46L54, 22D10, 58J50, 20F36
Abstract

We prove using a novel random matrix model that all right-angled Artin groups have a sequence of finite dimensional unitary representations that strongly converge to the regular representation. We deduce that this result applies also to: the fundamental group of a closed hyperbolic manifold that is either three dimensional or standard arithmetic type, any Coxeter group, and any word-hyperbolic cubulated group. One strong consequence of these results is that any closed hyperbolic three-manifold has a sequence of finite dimensional flat Hermitian vector bundles with bottom of the spectrum of the Laplacian asymptotically at least 1., Comment: 39 pages, 1 figure. v2: added a proof overview

Published
2023

85. Lensed type Ia supernovae in light of SN Zwicky and iPTF16geu

Author

de Murieta, Ana Sainz, Collett, Thomas E., Magee, Mark R., Weisenbach, Luke, Krawczyk, Coleman M., and Enzi, Wolfgang

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

Strong gravitationally lensed supernovae (glSNe) are a powerful probe to obtain a measure of the expansion rate of the Universe, but they are also extremely rare. To date, only two glSNe with multiple images strongly lensed by galaxies have been found, but their short time delays make them unsuitable for cosmography. Here, we simulate a realistic catalogue of lensed supernovae and study the characteristics of the population of detectable systems for different surveys. Compared to previous studies, our simulations also account for the effect of microlensing and its impact on the glSNe yields. We show that the properties of glSNe in shallow surveys (such as the Zwicky Transient Facility; ZTF) are determined by the need for large magnifications, which favours systems of four images with short time delays and low image separations. This picture is consistent with the properties of iPTF16geu and SN Zwicky, but is not representative of the population found in deeper surveys, which are limited by the volume of the Universe that is strongly lensed. For deeper surveys, such as the Legacy Survey of Space and Time (LSST), glSNe show longer time delays and greater angular separations, and the inclusion of microlensing results in 8$\%$ of glSNe becoming demagnified under the detection threshold. In the 10 years of the survey LSST should be able to find $\approx$ 180 systems, of which 70 will be suited for cosmography enabling a $\approx$ 1.2$\%$ precision $H_0$ measurement with LSST glSNe., Comment: 12 pages, 9 figures. Submitted

Published
2023

86. Unmaking AI Imagemaking: A Methodological Toolkit for Critical Investigation

Author

Munn, Luke, Magee, Liam, and Arora, Vanicka

Subjects
Computer Science - Computers and Society, K.4.1, K.2, J.5
Abstract

AI image models are rapidly evolving, disrupting aesthetic production in many industries. However, understanding of their underlying archives, their logic of image reproduction, and their persistent biases remains limited. What kind of methods and approaches could open up these black boxes? In this paper, we provide three methodological approaches for investigating AI image models and apply them to Stable Diffusion as a case study. Unmaking the ecosystem analyzes the values, structures, and incentives surrounding the model's production. Unmaking the data analyzes the images and text the model draws upon, with their attendant particularities and biases. Unmaking the output analyzes the model's generative results, revealing its logics through prompting, reflection, and iteration. Each mode of inquiry highlights particular ways in which the image model captures, "understands," and recreates the world. This accessible framework supports the work of critically investigating generative AI image models and paves the way for more socially and politically attuned analyses of their impacts in the world., Comment: 14 pages, 4 figures

Published
2023

87. On the surprising effectiveness of a simple matrix exponential derivative approximation, with application to global SARS-CoV-2

Author

Didier, Gustavo, Glatt-Holtz, Nathan E., Holbrook, Andrew J., Magee, Andrew F., and Suchard, Marc A.

Subjects
Statistics - Computation, Mathematics - Probability
Abstract

The continuous-time Markov chain (CTMC) is the mathematical workhorse of evolutionary biology. Learning CTMC model parameters using modern, gradient-based methods requires the derivative of the matrix exponential evaluated at the CTMC's infinitesimal generator (rate) matrix. Motivated by the derivative's extreme computational complexity as a function of state space cardinality, recent work demonstrates the surprising effectiveness of a naive, first-order approximation for a host of problems in computational biology. In response to this empirical success, we obtain rigorous deterministic and probabilistic bounds for the error accrued by the naive approximation and establish a "blessing of dimensionality" result that is universal for a large class of rate matrices with random entries. Finally, we apply the first-order approximation within surrogate-trajectory Hamiltonian Monte Carlo for the analysis of the early spread of SARS-CoV-2 across 44 geographic regions that comprise a state space of unprecedented dimensionality for unstructured (flexible) CTMC models within evolutionary biology., Comment: To appear in the Proceedings of the National Academy of Sciences

Published
2023

88. Demonstration of Machine Learning-assisted real-time noise regression in gravitational wave detectors

Author

Saleem, Muhammed, Gunny, Alec, Chou, Chia-Jui, Yang, Li-Cheng, Yeh, Shu-Wei, Chen, Andy H. Y., Magee, Ryan, Benoit, William, Nguyen, Tri, Fan, Pinchen, Chatterjee, Deep, Marx, Ethan, Moreno, Eric, Omer, Rafia, Raikman, Ryan, Rankin, Dylan, Sharma, Ritwik, Coughlin, Michael, Harris, Philip, and Katsavounidis, Erik

Subjects
General Relativity and Quantum Cosmology
Abstract

Real-time noise regression algorithms are crucial for maximizing the science outcomes of the LIGO, Virgo, and KAGRA gravitational-wave detectors. This includes improvements in the detectability, source localization and pre-merger detectability of signals thereby enabling rapid multi-messenger follow-up. In this paper, we demonstrate the effectiveness of \textit{DeepClean}, a convolutional neural network architecture that uses witness sensors to estimate and subtract non-linear and non-stationary noise from gravitational-wave strain data. Our study uses LIGO data from the third observing run with injected compact binary signals. As a demonstration, we use \textit{DeepClean} to subtract the noise at 60 Hz due to the power mains and their sidebands arising from non-linear coupling with other instrumental noise sources. Our parameter estimation study on the injected signals shows that \textit{DeepClean} does not do any harm to the underlying astrophysical signals in the data while it can enhances the signal-to-noise ratio of potential signals. We show that \textit{DeepClean} can be used for low-latency noise regression to produce cleaned output data at latencies $\sim 1-2$\, s. We also discuss various considerations that may be made while training \textit{DeepClean} for low latency applications.

Published
2023

89. When to Point Your Telescopes: Gravitational Wave Trigger Classification for Real-Time Multi-Messenger Followup Observations

Author

Ray, Anarya, Niu, Wanting, Sakon, Shio, Ewing, Becca, Creighton, Jolien D. E., Hanna, Chad, Adhicary, Shomik, Baral, Pratyusava, Baylor, Amanda, Cannon, Kipp, Caudill, Sarah, Cousins, Bryce, Fong, Heather, George, Richard N., Godwin, Patrick, Harada, Reiko, Huang, Yun-Jing, Huxford, Rachael, Joshi, Prathamesh, Kapadia, Shasvath, Kennington, James, Kuwahara, Soichiro, Li, Alvin K. Y., Magee, Ryan, Meacher, Duncan, Messick, Cody, Morisaki, Soichiro, Mukherjee, Debnandini, Pace, Alex, Posnansky, Cort, Sachdev, Surabhi, Singh, Divya, Tapia, Ron, Tsukada, Leo, Tsutsui, Takuya, Ueno, Koh, Viets, Aaron, Wade, Leslie, and Wade, Madeline

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

We develop a robust and self-consistent framework to extract and classify gravitational wave candidates from noisy data, for the purpose of assisting in real-time multi-messenger follow-ups during LIGO-Virgo-KAGRA's fourth observing run~(O4). Our formalism implements several improvements to the low latency calculation of the probability of astrophysical origin~(\PASTRO{}), so as to correctly account for various factors such as the sensitivity change between observing runs, and the deviation of the recovered template waveform from the true gravitational wave signal that can strongly bias said calculation. We demonstrate the high accuracy with which our new formalism recovers and classifies gravitational wave triggers, by analyzing replay data from previous observing runs injected with simulated sources of different categories. We show that these improvements enable the correct identification of the majority of simulated sources, many of which would have otherwise been misclassified. We carry out the aforementioned analysis by implementing our formalism through the \GSTLAL{} search pipeline even though it can be used in conjunction with potentially any matched filtering pipeline. Armed with robust and self-consistent \PASTRO{} values, the \GSTLAL{} pipeline can be expected to provide accurate source classification information for assisting in multi-messenger follow-up observations to gravitational wave alerts sent out during O4., Comment: v2 upload was accidental. revert back to v1

Published
2023

90. Catholic School Enrollment Boomed during COVID. Let's Make It More than a One-Time Bump. Issue Brief

Author

Manhattan Institute (MI), Porter-Magee, Kathleen, Smith, Annie, and Klausmeier, Matt

Abstract

The 2022 National Catholic Educational Association (NCEA) data provide a window into how the landscape of American education has shifted over the past two years in response to COVID-19-related school disruption. Between 2020 and 2022--a period marred not only by the health and safety worries that COVID brought but also by the heated debates about how schools should serve students amid a pandemic. In early spring 2020, many Catholic schools were the first to close, responding quickly to the threat that was still not fully understood. Then in fall 2020, Catholic schools, far more so than either public or charter schools, stood apart again by finding a way to reopen safely for in-person learning. The 2022 NCEA enrollment results reveal a historic 3.8% nationwide enrollment increase for all Catholic elementary and secondary schools. In order to understand whether the 2022 rebound represents a true reversal of the previous decline in Catholic school enrollment, it's important to dive deeper to understand where the increases were concentrated and what can be learned from them. To that end, analyzing the numbers by grade level provides some insight into just what may have changed and where. Pre-K, for instance, accounts for 40% (or 44,584 students) of the 2021 enrollment decline and 66% (41,190 students) of the 2022 rebound. K-8 Catholic school enrollment, by contrast, rose by 2.4% (23,100 students) between 2021 and 2022, and secondary school enrollment saw a modest 0.4% (2,164 students) decline from 2021 to 2022.

Published
2022

91. Integration of Genomic Sequencing Drives Therapeutic Targeting of PDGFRA in T-Cell Acute Lymphoblastic Leukemia/Lymphoblastic Lymphoma.

Author

Ocasio-Martinez, Nicole, Tsai, Harrison, Li, Yuting, Robichaud, Amanda, Khalid, Delan, Hatton, Charlie, Gillani, Riaz, Polonen, Petri, Dilig, Anthony, Gotti, Giacomo, Kavanagh, Julia, Adhav, Asmani, Gow, Sean, Tsai, Jonathan, Li, Yen, Ebert, Benjamin, Van Allen, Eliezer, Bledsoe, Jacob, Kim, Annette, Tasian, Sarah, Cooper, Stacy, Cooper, Todd, Hijiya, Nobuko, Sulis, Maria, Shukla, Neerav, Magee, Jeffrey, Mullighan, Charles, Burke, Michael, Luskin, Marlise, Mar, Brenton, Harris, Marian, Stegmaier, Kimberly, Place, Andrew, Pikman, Yana, Paolino, Jonathan, Dimitrov, Boris, Apsel Winger, Beth, Sandoval-Perez, Angelica, Jacobson, Matthew, and Rangarajan, Amith

Subjects
Humans, Child, Animals, Mice, Precursor T-Cell Lymphoblastic Leukemia-Lymphoma, Receptor, Platelet-Derived Growth Factor alpha, Mutation, Receptor Protein-Tyrosine Kinases, Precursor Cell Lymphoblastic Leukemia-Lymphoma, T-Lymphocytes
Abstract

PURPOSE: Patients with relapsed or refractory T-cell acute lymphoblastic leukemia (T-ALL) or lymphoblastic lymphoma (T-LBL) have limited therapeutic options. Clinical use of genomic profiling provides an opportunity to identify targetable alterations to inform therapy. EXPERIMENTAL DESIGN: We describe a cohort of 14 pediatric patients with relapsed or refractory T-ALL enrolled on the Leukemia Precision-based Therapy (LEAP) Consortium trial (NCT02670525) and a patient with T-LBL, discovering alterations in platelet-derived growth factor receptor-α (PDGFRA) in 3 of these patients. We identified a novel mutation in PDGFRA, p.D842N, and used an integrated structural modeling and molecular biology approach to characterize mutations at D842 to guide therapeutic targeting. We conducted a preclinical study of avapritinib in a mouse patient-derived xenograft (PDX) model of FIP1L1-PDGFRA and PDGFRA p.D842N leukemia. RESULTS: Two patients with T-ALL in the LEAP cohort (14%) had targetable genomic alterations affecting PDGFRA, a FIP1-like 1 protein/PDGFRA (FIP1L1-PDGFRA) fusion and a novel mutation in PDGFRA, p.D842N. The D842N mutation resulted in PDGFRA activation and sensitivity to tested PDGFRA inhibitors. In a T-ALL PDX model, avapritinib treatment led to decreased leukemia burden, significantly prolonged survival, and even cured a subset of mice. Avapritinib treatment was well tolerated and yielded clinical benefit in a patient with refractory T-ALL. CONCLUSIONS: Refractory T-ALL has not been fully characterized. Alterations in PDGFRA or other targetable kinases may inform therapy for patients with refractory T-ALL who otherwise have limited treatment options. Clinical genomic profiling, in real time, is needed for fully informed therapeutic decision making.

Published
2023

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