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arXiv 2020年

作者： Flores, Ramón Kahrobaei, Delaram Koberda, Thomas Department of Geometry and Topology University of Seville Spain Department of Computer Science University of York United Kingdom New York University Tandon School of Engineering PhD Program in Computer Science CUNY Graduate Center Department of Mathematics University of Virginia CharlottesvilleVA22904 United States

The purpose of this article is to give a characterization of families of expander graphs via right-angled Artin groups. We prove that a sequence of simplicial graphs {Γi}i∈ forms a family of expander graphs if and only if a certain natural mini-max invariant arising from the cup product in the cohomology rings of the groups {A(Γi)}i∈ agrees with the Cheeger constant of the sequence of graphs, thus allowing us to characterize expander graphs via cohomology. This result is proved in the more general framework of vector space expanders, a novel structure consisting of sequences of vector spaces equipped with vector-space-valued bilinear pairings which satisfy a certain mini-max condition. These objects can be considered to be analogues of expander graphs in the realm of linear algebra, with a dictionary being given by the cup product in cohomology, and in this context represent a different approach to expanders that those developed by Lubotzky-Zelmanov and Bourgain-Yehudayoff. Copyright © 2020, The Authors. All rights reserved.

关键词： Vector spaces

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Imaging Atomic-Scale Chemistry from Fused Multi-Modal Electron Microscopy

arXiv

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arXiv 2022年

作者： Schwartz, Jonathan Di, Zichao Wendy Jiang, Yi Fielitz, Alyssa J. Ha, Don-Hyung Perera, Sanjaya D. Baggari, Ismail El Robinson, Richard D. Fessler, Jeffrey A. Ophus, Colin Rozeveld, Steve Hovden, Robert Department of Materials Science and Engineering University of Michigan Ann ArborMI United States Mathematics and Computer Science Division Argonne National Laboratory LemontIL United States Advanced Photon Source Facility Argonne National Laboratory LemontIL United States Dow Chemical Co. MidlandMI United States Department of Material Science and Engineering Cornell University IthacaNY United States School of Integrative Engineering Chung-Ang University Seoul Korea Republic of Department of Physics Cornell University IthacaNY United States The Rowland Institute at Harvard CambridgeMA United States Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI United States National Center for Electron Microscopy Molecular Foundry Lawrence Berkeley National Laboratory BerkeleyCA United States Applied Physics Program University of Michigan Ann ArborMI United States

Efforts to map atomic-scale chemistry at low doses with minimal noise using electron microscopes are fundamentally limited by inelastic interactions. Here, fused multi-modal electron microscopy offers high signal-to-noise ratio (SNR) recovery of material chemistry at nano- and atomic- resolution by coupling correlated information encoded within both elastic scattering (high-angle annular dark field (HAADF)) and inelastic spectroscopic signals (electron energy loss (EELS) or energy-dispersive x-ray (EDX)). By linking these simultaneously acquired signals, or modalities, the chemical distribution within nanomaterials can be imaged at significantly lower doses with existing detector hardware. In many cases, the dose requirements can be reduced by over one order of magnitude. This high SNR recovery of chemistry is tested against simulated and experimental atomic resolution data of heterogeneous nanomaterials. © 2022, CC BY.

关键词： Electron microscopy

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Worldsheet Correlators in Black Hole Microstates

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Physical Review Letters 2022年第12期129卷 121603-121603页

作者： Davide Bufalini Sergio Iguri Nicolas Kovensky David Turton Mathematical Sciences and STAG Research Centre University of Southampton Southampton SO17 1BJ United Kingdom Instituto de Astronomía y Física del Espacio CONICET-Universidad de Buenos Aires. C. C. 67 Sucursal 28 1428 Buenos Aires Argentina Mathematics with Computer Science Program Guangdong Technion—Israel Institute of Technology Shantou Guangdong 515063 People’s Republic of China Institut de Physique Théorique Université Paris Saclay CEA CNRS Orme des Merisiers 91191 Gif-sur-Yvette CEDEX France

Light probes interacting with heavy bound states such as black holes give rise to observables containing valuable dynamical information. Recently, a family of black hole microstates was shown to admit an exact string worldsheet description. We construct the physical vertex operators of these models, and compute an extensive set of novel heavy-light correlators. We then obtain the first match between worldsheet correlators in black hole microstates and the holographically dual conformal field theory. We conjecture a closed formula for correlators with an arbitrary number of light insertions. As an application, we compute the analogue of the Hawking radiation rate for these microstates.

关键词： Gauge-gravity dualities Quantum aspects of black holes Strings & branes

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Facilitating team-based data science: Lessons learned from the DSC-WAV project

arXiv

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arXiv 2021年

作者： Legacy, Chelsey Zieffler, Andrew Baumer, Benjamin S. Barr, Valerie Horton, Nicholas J. Department of Educational Psychology University of Minnesota MinneapolisMN55455 United States Program in Statistical & Data Sciences Smith College NorthamptonMA01063 United States Department of Computer Science Mount Holyoke College South HadleyMA01075 United States Department of Mathematics and Statistics Amherst College Amherst MA01002 United States

While coursework provides undergraduate data science students with some relevant analytic skills, many are not given the rich experiences with data and computing they need to be successful in the workplace. Additionally, students often have limited exposure to team-based data science and the principles and tools of collaboration that are encountered outside of school. In this paper, we describe the DSC-WAV program, an NSF-funded data science workforce development project in which teams of undergraduate sophomores and juniors work with a local non-profit organization on a data-focused problem. To help students develop a sense of agency and improve confidence in their technical and non-technical data science skills, the project promoted a team-based approach to data science, adopting several processes and tools intended to facilitate this collaboration. Evidence from the project evaluation, including participant survey and interview data, is presented to document the degree to which the project was successful in engaging students in team-based data science, and how the project changed the students’ perceptions of their technical and non-technical skills. We also examine opportunities for improvement and offer insight to other data science educators who may want to implement a similar team-based approach to data science projects at their own *** Codes 97K80, 97P99 Copyright © 2021, The Authors. All rights reserved.

关键词： Students

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Developing a Machine Learning Algorithm to Predict the Probability of Medical Staff Work Mode Using Human-Smartphone Interaction Patterns: Algorithm Development and Validation Study

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Journal of medical Internet research 2023年 25卷 e48834页

作者： Chen, Hung-Hsun Lu, Henry Horng-Shing Weng, Wei-Hung Lin, Yu-Hsuan Department of Mathematics Fu Jen Catholic University New Taipei City Taiwan Program of Artificial Intelligence & Information Security Fu-Jen Catholic University New Taipei City Taiwan Institute of Statistics National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Statistics and Data Science Cornell University Ithaca NY United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MN United States Institute of Population Health Sciences National Health Research Institutes Miaoli County Taiwan Department of Psychiatry National Taiwan University Hospital Taipei Taiwan Department of Psychiatry College of Medicine National Taiwan University Taipei Taiwan

BACKGROUND: Traditional methods for investigating work hours rely on an employee's physical presence at the worksite. However, accurately identifying break times at the worksite and distinguishing remote work outside the worksite poses challenges in work hour estimations. Machine learning has the potential to differentiate between human-smartphone interactions at work and off work. OBJECTIVE: In this study, we aimed to develop a novel approach called "probability in work mode," which leverages human-smartphone interaction patterns and corresponding GPS location data to estimate work hours. METHODS: To capture human-smartphone interactions and GPS locations, we used the "Staff Hours" app, developed by our team, to passively and continuously record participants' screen events, including timestamps of notifications, screen on or off occurrences, and app usage patterns. Extreme gradient boosted trees were used to transform these interaction patterns into a probability, while 1-dimensional convolutional neural networks generated successive probabilities based on previous sequence probabilities. The resulting probability in work mode allowed us to discern periods of office work, off-work, breaks at the worksite, and remote work. RESULTS: Our study included 121 participants, contributing to a total of 5503 person-days (person-days represent the cumulative number of days across all participants on which data were collected and analyzed). The developed machine learning model exhibited an average prediction performance, measured by the area under the receiver operating characteristic curve, of 0.915 (SD 0.064). Work hours estimated using the probability in work mode (higher than 0.5) were significantly longer (mean 11.2, SD 2.8 hours per day) than the GPS-defined counterparts (mean 10.2, SD 2.3 hours per day;P<.001). This discrepancy was attributed to the higher remote work time of 111.6 (SD 106.4) minutes compared to the break time of 54.7 (SD 74.5) minutes. CONCLUSIONS: Our

关键词： deep learning digital phenotyping extreme gradient-boosted trees human-smartphone interaction machine learning one-dimensional convolutional neural network probability in work mode work hours

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Extending discrete exterior calculus to a fractional derivative

arXiv

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arXiv 2019年

作者： Crum, Justin Levine, Joshua A. Gillette, Andrew Program in Applied Mathematics University of Arizona Department of Computer Science University of Arizona Department of Mathematics University of Arizona

Fractional partial differential equations (FDEs) are used to describe phenomena that involve a "non-local" or "long-range" interaction of some kind. Accurate and practical numerical approximation of their solutions is challenging due to the dense matrices arising from standard discretization procedures. In this paper, we begin to extend the well-established computational toolkit of Discrete Exterior Calculus (DEC) to the fractional setting, focusing on proper discretization of the fractional derivative. We define a Caputo-like fractional discrete derivative, in terms of the standard discrete exterior derivative operator from DEC, weighted by a measure of distance between p-simplices in a simplicial complex. We discuss key theoretical properties of the fractional discrete derivative and compare it to the continuous fractional derivative via a series of numerical experiments. Copyright © 2019, The Authors. All rights reserved.

关键词： Calculations

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Increasing accuracy of classification physical activity based on smartphone using ensemble logistic regression with boosting method 3

Increasing accuracy of classification physical activity base...

引用

3rd International Conference on science, ICOS 2019

作者： Lawi, A. Aziz, F. Wungo, S.L. Department of Computer Science Universitas Hasanuddin Makassar90245 Indonesia Faculty of Mathematics and Natural Sciences Universitas Pancasakti Makassar90132 Indonesia Program Study Informatics Engineering STMIK Kreatindo Monokwari98300 Indonesia

At present, the smartphone is equipped with several sensors such as Accelerometer, Gravity sensor, and Gyroscope which can be used to recognize human physical activities such as walking upstair and walking downstairs etc. Machine learning is needed to group data and get information. Statistical methods have poor performance in classifying because procedures must be met. To overcome this, an ensemble technique was used. This study proposes the application of the gradientboost ensemble method to classify walking upstair and walking downstairs. The *** system is designed for data retrieval using a smartphone. Then, the dataset will be partitioned into 70% training data and 30% test data. The results show that the performance of the ensemble boosting method produces 81.82% accuracy, 86.11% sensitivity and 77.50% specificity. © Published under licence by IOP Publishing Ltd.

关键词： Smartphones

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Galaxy clusters at z ∼ 1 imaged by ALMA with the Sunyaev–Zel’dovich effect

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Publications of the Astronomical Society of Japan 2023年第2期75卷 311-337页

作者： Kitayama, Tetsu Ueda, Shutaro Okabe, Nobuhiro Akahori, Takuya Hilton, Matt Hughes, John P. Ichinohe, Yuto Kohno, Kotaro Komatsu, Eiichiro Lin, Yen-Ting Miyatake, Hironao Oguri, Masamune Sifón, Cristóbal Takakuwa, Shigehisa Takizawa, Motokazu Tsutsumi, Takahiro van Marrewijk, Joshiwa Wollack, Edward J. Department of Physics Toho University 2-2-1 Miyama Chiba Funabashi274-8510 Japan No. 1 Section 4 Roosevelt Road Taipei10617 Taiwan Institute of Astronomy National Tsing Hua University Hsinchu30013 Taiwan Department of Physics Hiroshima University 1-3-1 Kagamiyama Higashi-Hiroshima Hiroshima739-8526 Japan Astrophysical Science Center Hiroshima University 1-3-1 Kagamiyama Higashi-Hiroshima Hiroshima739-8526 Japan Core Research for Energetic Universe Department of Physics Hiroshima University 1-3-1 Kagamiyama Higashi-Hiroshima Hiroshima739-8526 Japan Physics Program Graduate School of Advanced Science and Engineering Hiroshima University 1-3-1 Kagamiyama Higashi-Hiroshima Hiroshima739-8526 Japan Mizusawa VLBI observatory National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Operation Division SKA Observatory Jodrell Bank Lower Withington MacclesfieldSK11 9DL United Kingdom Astrophysics Research Centre University of KwaZulu-Natal Westville Campus Durban4041 South Africa School of Mathematics Statistics & Computer Science University of KwaZulu-Natal Westville Campus Durban4041 South Africa Wits Centre for Astrophysics School of Physics University of the Witwatersrand Private Bag 3 Johannesburg2050 South Africa Department of Physics and Astronomy Rutgers The State University of New Jersey PiscatawayNJ08854-8019 United States Department of Physics Rikkyo University 3-34-1 Nishi-Ikebukuro Toshima-ku Tokyo171-8501 Japan Institute of Astronomy School of Science The University of Tokyo 2-21-1 Osawa Mitaka Tokyo181-0015 Japan Research Center for the Early Universe School of Science The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-0033 Japan Max-Planck-Institut für Astrophysik Karl-Schwarzschild Str. 1 GarchingD-85741 Germany The University of Tokyo Institutes for Advanced Study The University of Tokyo 5-1-5 Kashiwanoha Chiba Kashiwa277-8583 Japan Nagoya University Furo-cho Chikusa-

We present high angular resolution measurements of the thermal Sunyaev–Zel’dovich effect (SZE) toward two galaxy clusters, RCS J2319+0038 at z = 0.9 and HSC J0947−0119 at z = 1.1, by the Atacama Large Millimeter/submillimeter Array (ALMA) in Band 3. They are supplemented with available Chandra X-ray data, optical data taken by Hyper Suprime-Cam on Subaru, and millimeter-wave SZE data from the Atacama Cosmology Telescope. Taking into account departures from spherical symmetry, we have reconstructed non-parametrically the inner pressure profile of two clusters as well as electron temperature and density profiles for RCS J2319+0038. This is one of the first such measurements for an individual cluster at z 0.9. We find that the inner pressure profile of both clusters is much shallower than that of local cool-core clusters. Our results consistently suggest that RCS J2319+0038 hosts a weak cool core, where radiative cooling is less significant than in local cool cores. On the other hand, HSC J0947−0119 exhibits an even shallower pressure profile than RCS J2319+0038 and is more likely to be a non-cool-core cluster. The SZE centroid position is offset by more than 140 h−170 kpc from the peaks of galaxy distribution in HSC J0947−0119, suggesting a stronger influence of mergers in this cluster. We conclude that these distant clusters are at a very early stage of developing the cool cores typically found in clusters at lower redshifts. © The Author(s) 2023. Published by Oxford University Press on behalf of the Astronomical Society of Japan.

关键词： Millimeter waves

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Shape Anisotropy-Governed High-Performance Nanomagnetosol for In Vivo Magnetic Particle Imaging of Lungs

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Small 2024年第5期20卷 2305300-2305300页

作者： Nigam, Saumya Mohapatra, Jeotikanta Makela, Ashley V. Hayat, Hanaan Rodriguez, Jessi Mercedes Sun, Aixia Kenyon, Elizabeth Redman, Nathan A. Spence, Dana Jabin, George Gu, Bin Ashry, Mohamed Sempere, Lorenzo F. Mitra, Arijit Li, Jinxing Chen, Jiahui Wei, Guo-Wei Bolin, Steven Etchebarne, Brett Liu, J. Ping Contag, Christopher H. Wang, Ping Precision Health Program Michigan State University East LansingMI48824 United States Department of Radiology College of Human Medicine Michigan State University East LansingMI48824 United States Department of Physics The University of Texas at Arlington ArlingtonTX76019 United States Michigan State University East LansingMI48824 United States Department of Biomedical Engineering College of Engineering Michigan State University East LansingMI48824 United States Human Biology Program College of Natural Science Michigan State University East LansingMI48824 United States Department of Obstetrics Gynecology and Reproductive Sciences College of Human Medicine Michigan State University East LansingMI48824 United States Department of Materials Science and Engineering National Cheng Kung University Tainan City701 Taiwan Department of Mathematics College of Natural Science Michigan State U niversity East LansingMI48824 United States Department of Electrical and Computer Engineering College of Engineering Michigan State University East LansingMI48824 United States Department of Biochemistry and Molecular Biology College of Natural Science Michigan State University East LansingMI48824 United States Department of Pathobiology and Diagnostic Investigation College of Veterinary Medicine Michigan State University East LansingMI48824 United States Osteopathic Medical Specialties College of Osteopathic Medicine Michigan State University East LansingMI48824 United States Department of Microbiology and Molecular Genetics Michigan State University East LansingMI48824 United States

Caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease 2019 (COVID-19) has shown extensive lung manifestations in vulnerable individuals, putting lung imaging and monitoring at the forefront of early detection and treatment. Magnetic particle imaging (MPI) is an imaging modality, which can bring excellent contrast, sensitivity, and signal-to-noise ratios to lung imaging for the development of new theranostic approaches for respiratory diseases. Advances in MPI tracers would offer additional improvements and increase the potential for clinical translation of MPI. Here, a high-performance nanotracer based on shape anisotropy of magnetic nanoparticles is developed and its use in MPI imaging of the lung is demonstrated. Shape anisotropy proves to be a critical parameter for increasing signal intensity and resolution and exceeding those properties of conventional spherical nanoparticles. The 0D nanoparticles exhibit a 2-fold increase, while the 1D nanorods have a > 5-fold increase in signal intensity when compared to VivoTrax. Newly designed 1D nanorods displayed high signal intensities and excellent resolution in lung images. A spatiotemporal lung imaging study in mice revealed that this tracer offers new opportunities for monitoring disease and guiding intervention. © 2023 The Authors. Small published by Wiley-VCH GmbH.

关键词： Nanorods

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Challenges in coverage of future hepatitis C vaccines: Review and potential solutions

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Vaccine 2025年 59卷 127256-127256页

作者： Gandhi, Keshav Vijay, Yash Page, Kimberly Dahari, Harel Gutfraind, Alexander Department of Mathematics Statistics Computer Science University of Illinois at Chicago 851 S. Morgan St. Chicago 60607 IL United States The Program for Experimental & Theoretical Modeling Division of Hepatology Department of Medicine Stritch School of Medicine Loyola University Chicago 2160 S. First Ave. Maywood 60153 IL United States Department of Internal Medicine The University of New Mexico School of Medicine University of New Mexico MSC10 5550 Albuquerque 87131 NM United States Division of Epidemiology and Biostatistics School of Public Health University of Illinois at Chicago 1603 W. Taylor St. Chicago 60612 IL United States

Background: Motivated by the high mortality burden of hepatitis C virus (HCV) and the unprecedented rapid development of the COVID-19 and respiratory syncytial virus (RSV) vaccines, we note that a prompt HCV vaccine rollout may streamline the World Health Organization's goal to eliminate HCV before 2030. While progress in the development of HCV vaccine candidates has rapidly flourished, vaccine hesitancy and HCV incidence are both particularly prevalent in people who inject drugs (PWID). The aim of this paper is to document several potential challenges in HCV vaccine uptake and provide a set of preliminary recommendations for public and community health professionals to improve acceptance. Methods: We conducted a forward-looking integrative narrative review and identified relevant articles from PubMed. We survey literature discussing barriers to vaccine acceptance in past rollouts (e.g., COVID-19, hepatitis B) and barriers to HCV management, particularly in PWID. Results: Six key challenges were identified: (1) structural and social barriers affecting PWID, (2) vaccine safety, efficacy, and relevance concerns, (3) multiple-dose attrition and vaccine fatigue, (4) media presentation and misinformation, (5) awareness and attitude towards infection, and (6) information framing and primary care linkage. Four possible recommendations were also identified: (1) vaccine promotion in targeted educational and outreach campaigns, (2) community-level support programs integrated with vaccine rollout, (3) rollout of a pan-genotypic, multivalent, or combination vaccine, and (4) cost-benefit analysis supporting the vaccine. Conclusion: This forward-looking paper offers several recommendations to address potential gaps in HCV vaccination—from linkage with syringe exchange programs to economic analysis of vaccination program costs. © 2024

关键词： Hepatitis C People who inject drugs Vaccination Vaccination campaign Vaccine hesitancy

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