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arXiv 2024年

作者： Sales-Silva, J.V. Cunha, K. Smith, V.V. Daflon, S. Souto, D. Guerço, Rafael Queiroz, A. Chiappini, C. Hayes, C.R. Masseron, T. Hasselquist, Sten Horta, D. Prantzos, N. Zoccali, M. Prieto, C. Allende Barbuy, B. Beaton, R. Bizyaev, D. Fernández-Trincado, J.G. Frinchaboy, P.M. Holtzman, J.A. Johnson, J.A. Jönsson, Henrik Majewski, S.R. Minniti, D. Nidever, D.L. Schiavon, R.P. Schultheis, M. Sobeck, J. Stringfellow, G.S. Zasowski, G. Observatório Nacional/MCTI R. Gen. José Cristino 77 Rio de Janeiro20921-400 Brazil Steward Observatory University of Arizona 933 North Cherry Avenue TucsonAZ85721-0065 United States NOIRLab TucsonAZ85719 United States Departamento de Física Universidade Federal de Sergipe Av. Marechal Rondon S/N SE São Cristóvão49000-000 Brazil Instituto de Astrofísica de Canarias Tenerife La LagunaE-38200 Spain An der Sternwarte 16 Potsdam14482 Germany NRC Herzberg Astronomy and Astrophysics Research Centre 5071 West Saanich Road VictoriaBCV9E 2E7 Canada Tenerife La LagunaE-38205 Spain Departamento de Astrofísica Tenerife La Laguna38206 Spain Space Telescope Science Institute BaltimoreMD United States Center for Computational Astrophysics Flatiron Institute 162 Fifth Avenue New YorkNY10010 United States Institute d’Astrophysique de Paris UMR 7095 CNRS & Sorbonne Université 98 bis Blvd Arago Paris75014 France Instituto de Astrofísica Pontificia Universidad Católica de Chile Vicunã Mackenna 4860 Macul Casilla 306 Santiago22 Chile Nuncio Monseñor Sótero Sanz 100 Providencia Santiago Chile Universidade de São Paulo IAG Cidade Universitária Rua do Matão 1226 São Paulo05508-090 Brazil Apache Point Observatory New Mexico State University P.O. Box 59 SunspotNM88349-0059 United States Sternberg Astronomical Institute Moscow State University Moscow Russia Instituto de Astronomía Universidad Católica del Norte Av. Angamos 0610 Antofagasta Chile Department of Physics & Astronomy Texas Christian University TCU Box 298840 Fort WorthTX76129 United States New Mexico State University Las CrucesNM88003 United States The Department of Astronomy Center of Cosmology and Astro Particle Physics The Ohio State University ColumbusOH43210 United States Materials Science and Applied Mathematics Malmö University MalmöSE-205 06 Sweden Department of Astronomy University of Virginia CharlottesvilleVA22904-4325 United States Departamento de Fisi

This study probes the chemical abundances of the neutron-capture elements cerium and neodymium in the inner Milky Way from an analysis of a sample of ∼2000 stars in the Galactic Bulge/bar spatially contained within |... 详细信息

关键词： Galaxies

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Fundamental Physics Opportunities with the Next-Generation Event Horizon Telescope

arXiv

引用

arXiv 2023年

作者： Ayzenberg, Dimitry Blackburn, Lindy Brito, Richard Britzen, Silke Broderick, Avery E. Carballo-Rubio, Raúl Cardoso, Vitor Chael, Andrew Chatterjee, Koushik Chen, Yifan Cunha, Pedro V.P. Davoudiasl, Hooman Denton, Peter B. Doeleman, Sheperd S. Eichhorn, Astrid Eubanks, Marshall Fang, Yun Foschi, Arianna Fromm, Christian M. Galison, Peter Ghosh, Sushant G. Gold, Roman Gurvits, Leonid I. Hadar, Shahar Held, Aaron Houston, Janice Hu, Yichao Johnson, Michael D. Kocherlakota, Prashant Natarajan, Priyamvada Olivares, Héctor Palumbo, Daniel Pesce, Dominic W. Rajendran, Surjeet Roy, Rittick Saurabh Shao, Lijing Tahura, Shammi Tamar, Aditya Tiede, Paul Vincent, Frédéric H. Visinelli, Luca Wang, Zhiren Wielgus, Maciek Xue, Xiao Yakut, Kadri Yang, Huan Younsi, Ziri Theoretical Astrophysics Eberhard-Karls Universität Tübingen TübingenD-72076 Germany Center for Astrophysics Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States Harvard University 20 Garden Street CambridgeMA02138 United States CENTRA Departamento de Física Instituto Superior Técnico – IST Universidade de Lisboa – UL Avenida Rovisco Pais 1 Lisboa1049-001 Portugal Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 BonnD-53121 Germany Perimeter Institute for Theoretical Physics 31 Caroline Street North WaterlooONN2L 2Y5 Canada Department of Physics and Astronomy University of Waterloo 200 University Avenue West WaterlooONN2L 3G1 Canada Waterloo Centre for Astrophysics University of Waterloo WaterlooONN2L 3G1 Canada CP3-Origins University of Southern Denmark Campusvej 55 Odense MDK-5230 Denmark Florida Space Institute University of Central Florida 12354 Research Parkway Partnership 1 OrlandoFL32826 United States Niels Bohr International Academy Niels Bohr Institute Blegdamsvej 17 Copenhagen2100 Denmark Princeton Gravity Initiative Jadwin Hall Princeton University PrincetonNJ08544 United States Department of Physics University of Maryland College ParkMD20742 United States Institute for Research in Electronics and Applied Physics University of Maryland College ParkMD20742 United States Harvard-Smithsonian Center for Astrophysics 60 Garden Street CambridgeMA02138 United States Campus de Santiago Aveiro3810-183 Portugal High Energy Theory Group Physics Department Brookhaven National Laboratory UptonNY11973 United States Asteroid Initiatives LLC United States Perimeter Institute for Theoretical Physics WaterlooONN2L2Y5 Canada Kavli Institute for Astronomy and Astrophysics Peking University Beijing100871 China Institut für Theoretische Physik und Astrophysik Universität Würzburg Emil-Fischer-Strasse 31 Würzburg97074 Germany Institut für Theoretische Physik Goethe Universität Frankfurt Max-von

The Event Horizon Telescope (EHT) Collaboration recently published the first images of the supermassive black holes in the cores of the Messier 87 and Milky Way galaxies. These observations have provided a new means to study supermassive black holes and probe physical processes occurring in the strong-field regime. We review the prospects of future observations and theoretical studies of supermassive black hole systems with the next-generation Event Horizon Telescope (ngEHT), which will greatly enhance the capabilities of the existing EHT array. These enhancements will open up several previously inaccessible avenues of investigation, thereby providing important new insights into the properties of supermassive black holes and their environments. This review describes the current state of knowledge for five key science cases, summarising the unique challenges and opportunities for fundamental physics investigations that the ngEHT will enable. Copyright © 2023, The Authors. All rights reserved.

关键词： Telescopes

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The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting

arXiv

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arXiv 2023年

作者： Kofler, Florian Steinbauer, Felix Meissen, Felix Graf, Robert Ehrlich, Stefan K. Reinke, Annika Oswald, Eva Waldmannstetter, Diana Hoelzl, Florian Horvath, Izabela Turgut, Oezguen Shit, Suprosanna Bukas, Christina Yang, Kaiyuan Paetzold, Johannes C. de da Rosa, Ezequiel Mekki, Isra Vinayahalingam, Shankeeth Kassem, Hasan Zhang, Juexin Chen, Ke Weng, Ying Durrer, Alicia Cattin, Philippe C. Wolleb, Julia Sadique, M.S. Rahman, M.M. Farzana, W. Temtam, A. Iftekharuddin, K.M. Adewole, Maruf Anwar, Syed Muhammad Baid, Ujjwal Janas, Anastasia Kazerooni, Anahita Fathi LaBella, Dominic Bran Li, Hongwei Moawad, Ahmed W. Conte, Gian-Marco Farahani, Keyvan Eddy, James Sheller, Micah Pati, Sarthak Karagyris, Alexandros Aristizabal, Alejandro Bergquist, Timothy Chung, Verena Shinohara, Russell Takeshi Dako, Farouk Wiggins, Walter Reitman, Zachary Wang, Chunhao Liu, Xinyang Jiang, Zhifan Johanson, Elaine Meier, Zeke Familiar, Ariana Davatzikos, Christos Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Colen, Rivka R. Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-André Mahajan, Abhishek Mohan, Suyash Mongan, John Hess, Christopher Cha, Soonmee Villanueva-Meyer, Javier Colak, Errol Crivellaro, Priscila Jakab, Andras Fatade, Abiodun Omidiji, Olubukola Akinola Lagos, Rachel Olatunji, O.O. Khanna, Goldey Kirkpatrick, John Alonso-Basanta, Michelle Rashid, Arif Bornhorst, Miriam Nabavizadeh, Ali Lepore, Natasha Palmer, Joshua Porras, Antonio Albrecht, Jake Anazodo, Udunna Aboian, Mariam Calabrese, Evan Rudie, Jeffrey David Linguraru, Marius George Iglesias, Juan Eugenio Van Leemput, Koen Bakas, Spyridon Wiestler, Benedikt Ezhov, Ivan Piraud, Marie Menze, Bjoern H. Helmholtz AI Germany Technical University of Munich Germany Helmholtz Munich Germany Klinikum Rechts der Isar Munich Germany SETLabs Research GmbH Healthcare Technologies Munich Germany Heidelberg Division of Intelligent Medical Systems Germany Heidelberg HI Helmholtz Imaging Germany Institute of Clinical Neuroimmunology Faculty of Medicine Ludwig Maximilian University Munich Germany University of Zurich Switzerland Helmholtz Research Center Munich Germany Imperial College London United Kingdom Icometrix Leuven Belgium Department of Oral and Maxillofacial Surgery Radboudumc Netherlands Department of Artificial Intelligence Radboud University Netherlands MLCommons University of Nottingham Ningbo China Ningbo315100 China Center for medical Image Analysis and Navigation Department of Biomedical Engineering University of Basel Allschwil Switzerland Old Dominion University NorfolkVA23529 United States Lab Crestview Radiology Lagos Nigeria Children's National Hospital WashingtonDC United States George Washington University WashingtonDC United States University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Yale University New HavenCT United States Children's Hospital of Philadelphia University of Pennsylvania PhiladelphiaPA United States Duke University Medical Center Department of Radiation Oncology United States Athinoula A Martinos Center for Biomedical Imaging Massachusetts General Hospital BostonMA United States Department of Neuroradiology Technical University of Munich Munich Germany Mercy Catholic Medical Center DarbyPA United States Department of Radiology Mayo Clinic RochesterMN United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 U

A myriad of algorithms for the automatic analysis of brain MR images is available to support clinicians in their decision-making. For brain tumor patients, the image acquisition time series typically starts with an already pathological scan. This poses problems, as many algorithms are designed to analyze healthy brains and provide no guarantee for images featuring lesions. Examples include but are not limited to algorithms for brain anatomy parcellation, tissue segmentation, and brain extraction. To solve this dilemma, we introduce the BraTS inpainting challenge. Here, the participants explore inpainting techniques to synthesize healthy brain scans from lesioned ones. The following manuscript contains the task formulation, dataset, and submission procedure. Later, it will be updated to summarize the findings of the challenge. The challenge is organized as part of the ASNR-BraTS MICCAI challenge. Copyright © 2023, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Estimation of Shear Wave Velocity of Darul Imarah District, Aceh Besar, Indonesia by Using 1D HVSR Inversion

引用

IOP Conference Series: Materials Science and Engineering 2020年第1期846卷

作者： Y Yusran Aulia Khalqillah Umar Muksin Muhammad Syukri Syamsul Rizal Nazli Ismail Doctoral Program of Mathematics and Applied Sciences Universitas Syiah Kuala Banda Aceh Indonesia Education of Physics Universitas Islam Negeri Ar-Raniry Banda Aceh Indonesia Department of Physics Universitas Syiah Kuala Banda Aceh Indonesia Tsunami and Disaster Mitigation Research Center (TDMRC) Universitas Syiah Kuala Banda Aceh Indonesia Department of Marine Sciences Universitas Syiah Kuala Banda Aceh Indonesia

A total of 19 locations of Horizontal to Vertical Spectral Ratio (HVSR) measurements was conducted in Darul Imarah District, Aceh Besar, Indonesia. The objective of the research is to investigate the shear wave velocity (Vs) structure. This survey is important to analyze a structural characteristic through a Vs, considering the measurement points intersect to Aceh Segment Fault. One of the methods to obtain Vs is 1D HVSR inversion. In this paper, we analyzed only four of 19 measurement points of HVSR data to estimate Vs, they are AB03, AB08, AB09 and AB19 points. The inversion results show that the four points have four layers with different Vs. The average of Vs30 of AB03, AB08, AB09 and AB19 were calculated, they are 150.90 m/s, 197.16 m/s, 150.45 m/s and 316.80 m/s, respectively. The AB09 has the lowest average of Vs30 (highest amplification) than the other points and has soft soil composition. Furthermore, based on the average of Vs30 and amplification, the subsurface of AB03, AB08 and AB19 may have combination soft soil and stiff soil in 30 m depth. The complete analysis of average of Vs30 structure will be conducted at all sites including a 3D velocity structure will be derived from the interpolation of 1D velocity.

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Author Correction: Hysteresis control of epithelial-mesenchymal transition dynamics conveys a distinct program with enhanced metastatic ability

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Nature communications 2019年第1期10卷 527页

作者： Toni Celià-Terrassa Caleb Bastian Daniel D Liu Brian Ell Nicole M Aiello Yong Wei Jose Zamalloa Andres M Blanco Xiang Hang Dmitriy Kunisky Wenyang Li Elizabeth D Williams Herschel Rabitz Yibin Kang Department of Molecular Biology Princeton University Princeton NJ 08544 USA. Cancer Program IMIM (Hospital del Mar Medical Research Institute) 08003 Barcelona Spain. Program in Applied and Computational Mathematics Princeton University Princeton NJ 08544 USA. cbastian@princeton.edu. Lewis-Sigler Institute of Integrative Genomics Princeton University Princeton NJ 08544 USA. Department of Mathematics Princeton University Princeton NJ 08544 USA. School of Biomedical Sciences Translational Research Institute Queensland University of Technology (QUT) Brisbane QLD 4102 Australia. Program in Applied and Computational Mathematics Princeton University Princeton NJ 08544 USA. Department of Chemistry Princeton University Princeton NJ 08544 USA. Department of Molecular Biology Princeton University Princeton NJ 08544 USA. ykang@princeton.edu.

The original version of this Article contained an error in the spelling of the author Daniel D. Liu, which was incorrectly given as Daniel Liu. This has now been corrected in both the PDF and HTML versions of the Arti...

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Physiological response of premature infants due to the administration of pseudostem banana nest innovation to the incubator

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Journal of Physics: Conference Series 2019年第1期1179卷

作者： W Hapsari M N Widyawati S Suryono Diploma III of Midwifery Purwokerto PoltekkesKemenkes Semarang Indonesia Postgraduate Applied Science Midwifery Program PoltekkesKemenkes Semarang Indonesia Department of Physics Faculty of Science and Mathematics Diponegoro University Semarang Indonesia

In this study, innovation of banana pseudostem nest was conducted to assess the physiological response of premature infants due to the provision of pseudostem banana nest innovation in the incubator. This innovation is needed because premature babies need conditions that promote physiological response functions to increase body temperature, gain weight and assess changes in oxygen saturation. Unfortunately, so far there is no temperature stabilizer in the incubator, the incubator is made of electric and heating elements only so that some physical parameters cannot be accommodated with the incubator. Therefore, this paper proposes the innovation of pseudostem banana nest because it has a 400% water absorption level, a higher temperature stabilization on the fibers in commonly used materials. This study measures physiological responses. The research procedure begins with the manufacture of dried banana pseudostem ingredients, making pseudostem banana nest from banana midribs and coated with a cloth shaped like a hand containment. This research uses a quasi-experimental design method with pre-post test control group design. The sampling technique used was nonprobability sampling by consecutive sampling. A sample of 30 preterm infants was divided into 15 control group samples, 15 intervention group samples. Action procedure, the researcher treated the intervention group by placing nest pseudostem banana in the incubator until it surrounded the premature baby for three consecutive days. Measurements were made on parameters of body temperature, weight, oxygen saturation before and after intervention in the control group and intervention group for three consecutive days. The results of this study were obtained significant differences in body temperature, oxygen saturation before and after given nest pseudostem banana with a p-value of 0.001; 0.003. In this study, there were no significant differences in body weight before and after being given nest pseudostem banana with a

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Multilevel network item response modeling for discovering differences between innovation and regular school systems in Korea

arXiv

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arXiv 2018年

作者： Jin, Ick Hoon Jeon, Minjeong Schweinberger, Michael Yun, Jonghyun Lin, Lizhen Department Of Applied Statistics Yonsei University Korea Republic of Department Of Statistics And Data Science Yonsei University Korea Republic of School Of Education And Information Studies University Of California Los Angeles United States Department Of Statistics University Of Missouri Columbia United States Institute Of Statistical Data Intelligence Department Of Applied And Computational Mathematics And Statistics University Of Notre Dame United States

The innovation school system in South Korea has been developed in response to the traditional high-pressure school system in South Korea, with a view to cultivating a bottom-up and student-centered educational culture. Despite its ambitious goals, questions have been raised about the success of the innovation school system. Leveraging data from the Gyeonggi Education Panel Study (GEPS) along with advances in the statistical analysis of network data and educational data, we compare the two school systems in more depth. We find that some schools are indeed different from others, and those differences are not detected by conventional multilevel models. Having said that, we do not find much evidence that the innovation school system differs from the regular school system in terms of self-reported mental well-being, although we do detect differences among some schools that appear to be unrelated to the school system. Copyright © 2018, The Authors. All rights reserved.

关键词： Regression analysis

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Group synchronization on grids

arXiv

引用

arXiv 2017年

作者： Abbe, Emmanuel Massoulie, Laurent Montanari, Andrea Sly, Allan Srivastava, Nikhil Program in Applied and Computational Mathematics EE Department Princeton University Inria MSR-Inria Joint Centre Department of Electrical Engineering Department of Sttistics Stanford University Department of Mathematics Princeton University Department of Mathematics University of California Berkeley United States

Group synchronization requires to estimate unknown elements (θv)v∈V of a compact group G associated to the vertices of a graph G = (V, E), using noisy observations of the group differences associated to the edges. This model is relevant to a variety of applications ranging from structure from motion in computer vision to graph localization and positioning, to certain families of community detection problems. We focus on the case in which the graph G is the d-dimensional grid. Since the unknowns θv are only determined up to a global action of the group, we consider the following weak recovery question. Can we determine the group difference θ−u1θv between far apart vertices u, v better than by random guessing? We prove that weak recovery is possible (provided the noise is small enough) for d ≥ 3 and, for certain finite groups, for d ≥ 2. Viceversa, for some continuous groups, we prove that weak recovery is impossible for d = 2. Finally, for strong enough noise, weak recovery is always impossible. Copyright © 2017, The Authors. All rights reserved.

关键词： Recovery

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Transient crosslinking kinetics optimize gene cluster interactions

arXiv

引用

arXiv 2018年

作者： Walker, Benjamin Taylor, Dane Lawrimore, Josh Hult, Caitlin Adalsteinsson, David Bloom, Kerry Gregory Forest, M. Department of Mathematics University of North Carolina at Chapel Hill Department of Mathematics University at Buffalo State University of New York Computational and Data Enabled Science and Engineering University at Buffalo State University of New York Department of Microbiology and Immunology University of Michigan Medical School Department of Chemical Engineering University of Michigan Departments of Applied Physical Sciences and Biomedical Engineering University of North Carolina at Chapel Hill Department of Biology University of North Carolina at Chapel Hill

Our understanding of how chromosomes structurally organize and dynamically interact has been revolutionized through the lens of long-chain polymer physics. Major protein contributors to chromosome structure and dynamics are condensin and cohesin that stochastically generate loops within and between chains, and entrap proximal strands of sister chromatids. In this paper, we explore the ability of transient, protein-mediated, gene-gene crosslinks to induce clusters of genes, thereby dynamic architecture, within the highly repeated ribosomal DNA that comprises the nucleolus of budding yeast. We implement three approaches: live cell microscopy;computational modeling of the full genome during G1 in budding yeast, exploring four decades of timescales for transient crosslinks between 5kbp domains (genes) in the nucleolus on Chromosome XII;and, temporal network models with automated community (cluster) detection algorithms applied to the full range of 4D modeling datasets. The data analysis tools detect and track gene clusters, their size, number, persistence time, and their plasticity (deformation). Of biological significance, our analysis reveals an optimal mean crosslink lifetime that promotes pairwise and cluster gene interactions through "flexible" clustering. In this state, large gene clusters self-assemble yet frequently interact (merge and separate), marked by gene exchanges between clusters, which in turn maximizes global gene interactions in the nucleolus. This regime stands between two limiting cases each with far less global gene interactions: with shorter crosslink lifetimes, "rigid" clustering emerges with clusters that interact infrequently;with longer crosslink lifetimes, there is a dissolution of clusters. These observations are compared with imaging experiments on a normal yeast strain and two condensin-modified mutant cell strains. We apply the same image analysis pipeline to the experimental and simulated datasets, providing support for the modeling pred

关键词： Genes

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Modeling Compositional Regression With Uncorrelated and Correlated Errors: A Bayesian Approach

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Journal of Data Science 2018年第2期16卷 221-249页

作者： Taciana K. O. Shimizu Francisco Louzada Adriano K. Suzuki Ricardo S. Ehlers Inter Program of Graduate Statistics Federal University of São Carlos and University of São Paulo Avenida Trabalhador São-carlense 400 São Carlos São Paulo Brazil Department of Applied Mathematics & Statistics Sciences Institute of Mathematics and Computers ICMC University of São Paulo Avenida Trabalhador São-carlense 400 São Carlos São Paulo Brazil

Compositional data consist of known compositions vectors whose components are positive and defined in the interval (0,1) representing proportions or fractions of a ＂whole＂. The sum of these components must be equal to one. Compositional data is present in different knowledge areas, as in geology, economy, medicine among many others. In this paper, we propose a new statistical tool for volleyball data, i.e., we introduce a Bayesian anal-ysis for compositional regression applying additive log-ratio (ALR) trans- formation and assuming uncorrelated and correlated errors. The Bayesian inference procedure based on Markov Chain Monte Carlo Methods (MCMC). The methodology is applied on an artificial and a real data set of volleyball.

关键词： Compositional data additive log-ratio transformation inference Bayesian correlated errors MCMC

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