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Input optics systems of the KAGRA detector during O3GK (vol 2023, 023F01, 2023)

PROGRESS OF THEORETICAL AND EXPERIMENTAL PHYSICS 2023年第5期2023卷

作者： Akutsu, T. Ando, M. Arai, K. Arai, Y. Araki, S. Araya, A. Aritomi, N. Asada, H. Aso, Y. Bae, S. Bae, Y. Baiotti, L. Bajpai, R. Barton, M. A. Cannon, K. Cao, Z. Capocasa, E. Chan, M. Chen, C. Chen, K. Chen, Y. Chiang, C-I Chu, H. Chu, Y-K Eguchi, S. Enomoto, Y. Flaminio, R. Fujii, Y. Fujikawa, Y. Fukunaga, M. Fukushima, M. Furuhata, T. Gao, D. Ge, G-G Ha, S. Hagiwara, A. Haino, S. Han, W-B Hasegawa, K. Hattori, K. Hayakawa, H. Hayama, K. Himemoto, Y. Hiranuma, Y. Hirata, N. Hirose, E. Hong, Z. Hsieh, B-H Huang, G-Z Huang, H-Y Huang, P. Huang, Y-C Huang, Y-J Hui, D. C. Y. Ide, S. Ikenoue, B. Imam, S. Inayoshi, K. Inoue, Y. Ioka, K. Ito, K. Itoh, Y. Izumi, K. Jeon, C. Jin, H-B Jung, K. Jung, P. Kaihotsu, K. Kajita, T. Kakizaki, M. Kamiizumi, M. Kanbara, S. Kanda, N. Kang, G. Kataoka, Y. Kawaguchi, K. Kawai, N. Kawasaki, T. Kim, C. Kim, J. Kim, J. C. Kim, Ws Kim, Y-M Kimura, N. Kita, N. Kitazawa, H. Kojima, Y. Kokeyama, K. Komori, K. Kong, A. K. H. Kotake, K. Kozakai, C. Kozu, R. Kumar, R. Kume, J. Kuo, C. Kuo, H-S Kuromiya, Y. Kuroyanagi, S. Kusayanagi, K. Kwak, K. Lee, H. K. Lee, H. W. Lee, R. Leonardi, M. Li, K. L. Lin, L. C-C Lin, C-Y Lin, F-K Lin, F-L Lin, H. L. Liu, G. C. Luo, L-W Majorana, E. Marchio, M. Michimura, Y. Mio, N. Miyakawa, O. Miyamoto, A. Miyazaki, Y. Miyo, K. Miyoki, S. Mori, Y. Morisaki, S. Moriwaki, Y. Nagano, K. Nagano, S. Nakamura, K. Nakano, H. Nakano, M. Nakashima, R. Nakayama, Y. Narikawa, T. Naticchioni, L. Negishi, R. Quynh, L. Nguyen Ni, W-T Nishizawa, A. Nozaki, S. Obuchi, Y. Ogaki, W. Oh, J. J. Oh, S. H. Ohashi, M. Ohishi, N. Ohkawa, M. Ohta, H. Okutani, Y. Okutomi, K. Oohara, K. Ooi, C. Oshino, S. Otabe, S. Pan, K-C Pang, H. Parisi, A. Park, J. Arellano, F. E. Pena Pinto, I. Sago, N. Saito, S. Saito, Y. Sakai, K. Sakai, Y. Sakuno, Y. Sato, S. Sato, T. Sawada, T. Sekiguchi, T. Sekiguchi, Y. Shao, L. Shibagaki, S. Shimizu, R. Shimoda, T. Shimode, K. Shinkai, H. Shishido, T. Shoda, A. Somiya, K. Son, E. J. Sotani, H. Sugimoto, R. Suresh, J. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H Gravitational Wave Science Project National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Institute for Cosmic Ray Research KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa City Chiba 277-8582 Japan Accelerator Laboratory High Energy Accelerator Research Organization (KEK) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Graduate School of Science and Technology Hirosaki University 3 Bunkyo-cho Hirosaki Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan 238 Higashi-Mozumi Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information 245 Daehak-ro Yuseong-gu Daejeon 34141 Republic of Korea National Institute for Mathematical Sciences 70 Yuseong-daero 1689 Beon-gil Yuseong-gu Daejeon 34047 Republic of Korea International College Osaka University 1-1 Machikaneyama-cho Toyonaka City Osaka 560-0043 Japan School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University Xinjiekouwai Street 19 Haidian District Beijing 100875 China Department of Applied Physics Fukuoka University 8-19-1 Nanakuma Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University No. 151 Yingzhuan Road Danshui Dist. New Taipei City 25137 Taiwan Department of Physics

KAGRA, the underground and cryogenic gravitational-wave detector, was operated for its solo observation from February 25 to March 10, 2020, and its first joint observation with the GEO 600 detector from April 7 to April 21, 2020 (O3GK). This study presents an overview of the input optics systems of the KAGRA detector, which consist of various optical systems, such as a laser source, its intensity and frequency stabilization systems, modulators, a Faraday isolator, mode-matching telescopes, and a high-power beam dump. These optics were successfully delivered to the KAGRA interferometer and operated stably during the observations. The laser frequency noise was observed to limit the detector sensitivity above a few kilohertz, whereas the laser intensity did not significantly limit the detector sensitivity.

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computer AIDS FOR SHIP DESIGN, INTEGRATION AND CONTROL

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NAVAL ENGINEERS JOURNAL 1980年第2期92卷 73-87页

作者： CARLSON, CM JOHNSON, RA HELMING, FW Mr. Craig M. Carlson received his B.S. degree in Naval Architecture and Marine Engineering from the University of Michigan in 1970 and began his career with the Department of the Navy at the Naval Ship Engineering Center (NAVSEC). In 1972. he returned to the University of Michigan under the NAVSEC Long Term Training Program and received his M.S. degree in Naval Architecture and Marine Engineering. After returning to the Ship Arrangements Branch at NAVSEC. he was assigned as Task Leader for General Arrangements for the PGG PCG PHM. and MCM ship designs and was awarded Outstanding Performance Awards in 1974 and 1975. In addition he was Manager of the Arrangement Subsystem of the Navy's Computer-Aided Ship Design and Construction Program (CASDAC). In October 1979. he became Manager of the CASDAC Hull Design System. Currently. he also is enrolled in the M.S. of Computer Science Program at Johns Hopkins University. Mr. Carlson previously has presented technical papers at ASNE Day 1974 and 1978 as well as at the 1979 DOD Manufacturing Technology Advisory Group Conference. Besides ASNE. which he joined in 1972. he is a member of SNAME. ASE. and the U.S. Naval Institute. Mr. Robert A. Johnson is a Naval Architect in Surface Combatants Design (SEA 03D3). Ship Design Integration Directorate Naval Sea Systems Command. He received an Associate in Engineering degree in Drafting and Design Technology in 1959. his B.S. degree in Aerospace Engineering in 1965. and his M.S. degree in Engineering Mechanics in 1970. all from the Pennsylvania State University. In 1973. he was selected for the NA VSEC Hull Division s Long Term Training Program at the University of Michigan subsequently receiving his M.S.E. degree in Naval Architecture in 1974. Mr. Johnson began his career with the Ordnance Research Laboratory at Pennsylvania State University in 1959 where he worked. on the design of hydroelastic submarine models and conducted research in the area of flow induced structural vibrations. In 1967 he joined HRB-Singer at State Colle

This paper presents an integrated approach to computer-Aided Ship Design for U.S. Navy preliminary and contract design. An integrated Hull Design System (HDS), currently under development by the Hull Group of the Naval Sea Systems Command (NAVSEA 32). is the vehicle for the discussion. This paper is directed toward practicing ship design professionals and the managers of the ship design process. Primary emphasis of this paper, and of the development effort currently under way, is on aiding ship design professionals in their work. Focus is on integration and management control of the extremely complex set of processes which make up naval ship design. The terminology of the Ship Designer and Design Manager is used. The reader needs no familiarity with the technologies of computer science.

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROscience 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROscience 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Worldwide Soundscapes: A Synthesis of Passive Acoustic Monitoring Across Realms

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Global Ecology and Biogeography 2025年第5期34卷

作者： Kevin F. A. Darras Rodney A. Rountree Steven L. Van Wilgenburg Anna F. Cord Frederik Pitz Youfang Chen Lijun Dong Agnès Rocquencourt Camille Desjonquères Patrick Mauritz Diaz Tzu-Hao Lin Théophile Turco Louise Emmerson Tom Bradfer-Lawrence Amandine Gasc Sarah Marley Marcus Salton Laura Schillé Paul J. Wensveen Shih-Hung Wu Adriana C. Acero-Murcia Orlando Acevedo-Charry Matyáš Adam Jacopo Aguzzi Irmak Akoglu M. Clara P. Amorim Mina Anders Michel André Alexandre Antonelli Leandro Aparecido Do Nascimento Giulliana Appel Stephanie Archer Christos Astaras Andrey Atemasov Jamieson Atkinson Joël Attia Emanuel Baltag Luc Barbaro Fritjof Basan Carly Batist Julio Ernesto Baumgarten Just T. Bayle Sempere Kristen Bellisario Asaf Ben David Oded Berger-Tal Frédéric Bertucci Matthew G. Betts Iqbal S. Bhalla Thiago Bicudo Marta Bolgan Sara Bombaci Gerard Bota Martin Boullhesen Robert A. Briers Susannah Buchan Michal Budka Katie Burchard Giuseppa Buscaino Alice Calvente Marconi Campos-Cerqueira Maria Isabel Carvalho Gonçalves Maria Ceraulo Maite Cerezo-Araujo Gunnar Cerwén Adams A. Chaskda Maria Chistopolova Christopher W. Clark Kieran D. Cox Benjamin Cretois Chapin Czarnecki Luis P. da Silva Wigna da Silva Laurence H. De Clippele David de la Haye Ana Silvia de Oliveira Tissiani Devin de Zwaan M. Eugenia Degano Jessica Deichmann Joaquin del Rio Christian Devenish Ricardo Díaz-Delgado Pedro Diniz Dorgival Diógenes Oliveira-Júnior Thiago Dorigo Saskia Dröge Marina Duarte Adam Duarte Kerry Dunleavy Robert Dziak Simon Elise Hiroto Enari Haruka S. Enari Florence Erbs Britas Klemens Eriksson Pınar Ertör-Akyazi Nina C. Ferrari Luane Ferreira Abram B. Fleishman Paulo J. Fonseca Bárbara Freitas Nicholas R. Friedman Jérémy S. P. Froidevaux Svetlana Gogoleva Carolina Gonzaga José Miguel González Correa Eben Goodale Benjamin Gottesman Ingo Grass Jack Greenhalgh Jocelyn Gregoire Samuel Haché Jonas Hagge William Halliday Antonia Hammer Tara Hanf-Dressler Sylvain Haupert Samara Haver Becky Heath Daniel Hending Jose Hernandez-Blanco Dennis Higgs EFNO ECODIV INRAE Domaine des Barres Nogent-sur-Vernisson France Sustainable Agricultural Systems & Engineering Lab School of Engineering Westlake University Hangzhou Zhejiang China Chair of Computational Landscape Ecology Faculty of Environmental Sciences Dresden University of Technology Dresden Germany Biology Department University of Victoria Victoria British Columbia Canada The Fish Listener Waguoit Massachusetts USA Terrestrial Unit Prairie Region Canadian Wildlife Service Environment & Climate Change Canada Prairie & Northern Wildlife Research Centre Saskatoon Saskatchewan Canada Agro-ecological Modeling Group Faculty of Agriculture University of Bonn Bonn Germany Marine Mammal and Marine Bioacoustics Laboratory Department of Deep Sea Science Institute of Deep-sea Science and Engineering Chinese Academy of Sciences Sanya Hainan China Institut de Systématique Évolution Biodiversité Muséum National d’Histoire Naturelle Paris France Université Grenoble Alpes Université Savoie Mont Blanc CNRS LECA Grenoble France Climate Change and Biodiversity Hanns R. Neumann Stiftung Indonesia Muaradua Indonesia Biodiversity Research Center Academia Sinica Nankang Taipei Taiwan ENES Bioacoustics Research Laboratory University of Saint-Etienne CRNL CNRS UMR 5292 Inserm UMR_S 1028 Saint-Etienne France Australian Antarctic Division Science Branch Department of Climate Change Energy Environment and Water Channel Highway Kingston Tasmania Australia Biological and Environmental Sciences University of Stirling Stirling Scotland Centre for Conservation Science RSPB Edinburgh UK IMBE Aix Marseille Univ Avignon Univ CNRS IRD Aix-en-Provence France Scotland's Rural College Craibstone Estate Aberdeen UK BIOGECO INRAE University of Bordeaux Cestas France Westman Islands Research Centre University of Iceland Vestmannaeyjar Iceland Qigu Research Center Taiwan Biodiversity Research Institute Nantou County Taiwan Programa de Pós-graduação em Ecologia

Aim The urgency for remote, reliable and scalable biodiversity monitoring amidst mounting human pressures on ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), which can track life underwater and on land. However, we lack a unified methodology to report this sampling effort and a comprehensive overview of PAM coverage to gauge its potential as a global research and monitoring tool. To address this gap, we created the Worldwide Soundscapes project, a collaborative network and growing database comprising metadata from 416 datasets across all realms (terrestrial, marine, freshwater and subterranean). Location Worldwide, 12,343 sites, all ecosystem types. Time Period 1991 to present. Major Taxa Studied All soniferous taxa. Methods We synthesise sampling coverage across spatial, temporal and ecological scales using metadata describing sampling locations, deployment schedules, focal taxa and audio recording parameters. We explore global trends in biological, anthropogenic and geophysical sounds based on 168 selected recordings from 12 ecosystems across all realms. Results Terrestrial sampling is spatially denser (46 sites per million square kilometre—Mkm 2 ) than aquatic sampling (0.3 and 1.8 sites/Mkm 2 in oceans and fresh water) with only two subterranean datasets. Although diel and lunar cycles are well sampled across realms, only marine datasets (55%) comprehensively sample all seasons. Across the 12 ecosystems selected for exploring global acoustic trends, biological sounds showed contrasting diel patterns across ecosystems, declined with distance from the Equator, and were negatively correlated with anthropogenic sounds. Main Conclusions PAM can inform macroecological studies as well as global conservation and phenology syntheses, but representation can be improved by expanding terrestrial taxonomic scope, sampling coverage in the high seas and subterranean ecosystems, and spatio-temporal replication in freshwater habitats. Overall, this

关键词： ARU automated sound recorder biodiversity conservation biology ecoacoustics IUCN GET realm Passive Acoustic Monitoring phenology soundscape ecology

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FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

arXiv

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arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

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THE UNITED STATES NAVY'S “DESIGN WORK STUDY” APPROACH TO THE DEVELOPMENT OF SHIPBOARD CONTROL SYSTEMS

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Naval Engineers Journal 1976年第6期88卷 62-74页

作者： PLATO, ARTIS I. GAMBREL, WILLIAM DAVID Artis I. Plato:is Head of the Design Work Study/ Shipboard Manning/Human Factors Engineering Section Systems Engineering and Analysis Branch Naval Ship Engineering Center (NAVSEC). He graduated from the City College of New York in 1956 receiving his Bachelor of Mechanical Engineering degree. Following this he started work at the New York Naval Shipyard in the Internal Combustion Engine and Cargo Elevator Section. During 1957 and 1958 he was called up for active duty with the U.S. Army Corps of Engineers and served in Europe with a Construction Engineer Battalion. After release from active duty he returned to the shipyard where he remained until 1961 when he transferred to the Naval Supply Research and Development Facility Bayonne New Jersey. Initially he was in charge of an Engineering Support Test Group and the drafting services for the whole Facility. Later he became a Project Engineer in the Food Services Facilities Branch with duties that included planning and designing new afloat and ashore messing facilities for the Navy. In 1966 he transferred to NAVSEC as a Project Engineer in the Design Work Study Section and in this capacity worked on selected projects and manning problems for new construction and also developed a computer program (Manpower Determination Model) that makes accurate crew predictions for feasibility studies. In 1969 he became Head of the Section. He has been active in the U.S. Army Reserve since his release from active duty and his duties have included command of an Engineer Company various Staff positions and his present assignment as Operations Officer for a Civil Affairs Group. He has completed the U. S. A rmy Corps of Engineers Career Course and the Civil Affairs Career Course and is presently enrolled in the U.S. Army Command and General Staff College non-resident course. Additionally he completed graduate studies at American University Washington D.C in 1972 receiving his MSTM degree in Technology of Management and is a member of ASE ASME CAA U. S. Naval Instit

The purpose of this paper is to discuss a system analysis technique called “Design Work Study”, that is used by the U.S. Navy for the development of improved ship control systems. The Design Work Study approach is one which brings about the most efficient and cost effective man‐machine combination for the ship control functions. Adherence to this process insures that the advantages of automation are balanced against incurred operational and maintenance expense. At present, U.S. Navy doctrine requires that certain ship operating stations, such as steering and propulsion control, be manned at specified ship conditions of readiness. Therefore, if personnel are needed to fulfill these combat environment obligations, excessive automation may only result in unnecessary additional acquisition costs and increased personnel skill requirements. The Design Work Study process can be applied to establish the required fine balance between the degree of built‐in automation and the shipboard manpower levels. In order to explain the techniques that are used for this process, the Authors will present a brief summary of the Design Work Study approach for optimizing shipboard control systems, including an explanation of the formal procedural tools that are applicable. In addition, a practical case study of ship control system design for one of the latest classes of Navy destroyers will be presented. This example will illustrate the resultant savings and benefits that can be realized by a judicious application of this technique. © 1976 American Society of Naval Engineers

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Influence of human engineering on manning levels and human performance on ships

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NAVAL ENGINEERS JOURNAL 1997年第5期109卷 67-76页

作者： Anderson, DE Oberman, FR Malone, TB Baker, CC David E. Anderson:has a bachelor of science degree in environmental engineering from Florida Technological University and a master's degree in environmental engineering from the University of Central Florida. He is a graduate of the Naval Sea Systems Command's Engineer-In-Training (EIT) Program. Mr. Anderson was instrumental in introducing the collective protection system (CPS) in the U.S. Navy developing the initial forward-fit package for the USS Gunston Hall and the engineering change proposal (ECP) for the USS Wasp. In 1990 he joined the Human Systems Integration (HSI) Division (SEA 55W5) where he was task leader for auxiliary ships. He is currently the HSI manager for the future technology variant of the SeaLift ship and the future carrier. Association of Scientists and Engineers 33rdAnnual Technical Symposium 26 April 1996. Fred R. Oberman:has B.A. and M.A. degrees from the University of Chicago and Loyola University (experimental psychology) and an M.S. degree in industrial engineering and operations research from Virginia Polytechnic Institute (VPI). He has more than 30 years experience in HSI management planning research analysis design and testing in government and private sector positions. He is currently responsible for NavSea HSI generic research and tool development efforts. He is responsible for Human Engineering Specifications and Standards (Commercial Hypertext) and is the NavSea 03D7 representative on HSI in Performance Specifications and for integration of HSI within Integrated Logistic Support (ILS). He has served as DoD HSI SubTAG chair and member of the Simulation and Modeling Test and Evaluation Display and Control Systems Human Computer Interaction Specifications and Standards and Systems Design Sub Tags as a member of the Society of Naval Architects and Marine Engineers (SNAME) Systems Safety Panel and a member of NATO RSG 14 on man-machine analysis. Thomas B. Malone: CHFEP received a Ph.D. in experimental psychology from Fordham University in 1964. He is president of Carlow

The objectives of Human Engineering (HE) are generally viewed as increasing human performance, reducing human error, enhancing personnel and equipment safety, and reducing training and related personnel costs. There are other benefits that are thoroughly consistent with the direction of the Navy of the future, chief among these is reduction of required numbers of personnel to operate and maintain Navy ships. The Naval Research Advisory Committee (NRAC) report on Man-Machine technology in the Navy estimated that one of the benefits from increased application of man-machine technology to Navy ship design is personnel reduction as well as improving system availability, effectiveness, and safety The objective of this paper is to discuss aspects of the human engineering design of ships and systems that affect manning requirements, and impact human-performance and safety The paper will also discuss how the application of human engineering leads to improved performance, and crew safety, and reduced workload, all of which influence manning levels. Finally, the paper presents a discussion of tools and case studies of good human engineering design practices which reduce manning.

关键词： Human engineering

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Overview of KAGRA : Data transfer and management

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Progress of Theoretical and Experimental Physics 2023年第10期2023卷

作者： Akutsu, T Ando, M Arai, K Arai, Y Araki, S Araya, A Aritomi, N Asada, H Aso, Y Bae, S Bae, Y Baiotti, L Bajpai, R Barton, M A Cannon, K Cao, Z Capocasa, E Chan, M Chen, C Chen, K Chen, Y Chiang, C-Y Chu, H Chu, Y-K Eguchi, S Enomoto, Y Flaminio, R Fujii, Y Fujikawa, Y Fukunaga, M Fukushima, M Gao, D Ge, G Ha, S Hagiwara, A Haino, S Han, W-B Hasegawa, K Hattori, K Hayakawa, H Hayama, K Himemoto, Y Hiranuma, Y Hirata, N Hirose, E Hong, Z Hsieh, B Huang, G-Z Huang, H-Y Huang, P Huang, Y-C Huang, Y Hui, D C Y Ide, S Ikenoue, B Imam, S Inayoshi, K Inoue, Y Ioka, K Ito, K Itoh, Y Izumi, K Jeon, C Jin, H-B Jung, K Jung, P Kaihotsu, K Kajita, T Kakizaki, M Kamiizumi, M Kanda, N Kang, G Kawaguchi, K Kawai, N Kawasaki, T Kim, C Kim, J Kim, J C Kim, W S Kim, Y-M Kimura, N Kita, N Kitazawa, H Kobayashi, Y Kojima, Y Kokeyama, K Komori, K Kong, A K H Kotake, K Kozakai, C Kozu, R Kumar, R Kume, J Kuo, C Kuo, H-S Kuromiya, Y Kuroyanagi, S Kusayanagi, K Kwak, K Lee, H K Lee, H W Lee, R Leonardi, M Li, K L Lin, L C-C Lin, C-Y Lin, F-K Lin, F-L Lin, H L Liu, G C Luo, L-W Majorana, E Marchio, M Michimura, Y Mio, N Miyakawa, O Miyamoto, A Miyazaki, Y Miyo, K Miyoki, S Mori, Y Morisaki, S Moriwaki, Y Nagano, K Nagano, S Nakamura, K Nakano, H Nakano, M Nakashima, R Nakayama, Y Narikawa, T Naticchioni, L Negishi, R Quynh, L Nguyen Ni, W-T Nishizawa, A Nozaki, S Obuchi, Y Ogaki, W Oh, J J Oh, K Oh, S H Ohashi, M Ohashi, T Ohishi, N Ohkawa, M Ohta, H Okutani, Y Okutomi, K Oohara, K Ooi, C Oshino, S Otabe, S Pan, K Pang, H Parisi, A Park, J Arellano, F E Peña Pinto, I Sago, N Saito, S Saito, Y Sakai, K Sakai, Y Sakuno, Y Sasaki, Y Sato, S Sato, T Sawada, T Sekiguchi, T Sekiguchi, Y Shao, L Shibagaki, S Shimizu, R Shimoda, T Shimode, K Shinkai, H Shishido, T Shoda, A Somiya, K Son, E J Sotani, H Sugimoto, R Suresh, J Suzuki, T Tagoshi, H Takahashi, H Takahashi, R Takamori, A Takano, S Takeda, H Takeda, M Tanaka, H Tanaka, K Tanaka, T Tanioka, S Martin, E N Tapia San Telada, S Tomaru, T Tomigami, Y Tomura, T Travasso, F Trozzo, L Tsang, T Ts Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe (RESCEU) The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Institute for Cosmic Ray Research (ICRR) KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa City Chiba 277-8582 Japan Accelerator Laboratory High Energy Accelerator Research Organization (KEK) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Hirosaki University 3 Bunkyo-cho Hirosaki City Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan (NAOJ) 238 Higashi-Mozumi Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information (KISTI) 245 Daehak-ro Yuseong-gu Daejeon 34141 Korea National Institute for Mathematical Sciences 70 Yuseong-daero 1689 Beon-gil Yuseong-gu Daejeon 34047 Korea International College Osaka University 1-1 Machikaneyama-cho Toyonaka City Osaka 560-0043 Japan School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University No. 19 Xinjiekou Street Beijing 100875 China Department of Applied Physics Fukuoka University 8-19-1 Nanakuma Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University No. 151 Yingzhuan Rd. Danshui Dist. New Taipei City 25137 Taiwan Department of Physics and Institute of Astronomy Nation

KAGRA is a newly built gravitational wave observatory, a laser interferometer with a 3 km arm length, located in Kamioka, Gifu prefecture, Japan. In this article, we describe the KAGRA data management system, i.e., recording of data, transfer from the KAGRA experiment site to computing resources, as well as data distribution to tier sites, including international sites in Taiwan and Korea. The amount of KAGRA data exceeded 1.0 PiB and increased by about 1.5 TB per day during operation in 2020. Our system has succeeded in data management, and has achieved performance that can withstand observations after 2023, that is, a transfer rate of 20 MB s-1or more and file storage of sufficient capacity for petabyte class. We also discuss the sharing of data between the global gravitational-wave detector network with other experiments, namely LIGO and Virgo. The latency, which consists of calculation of calibrated strain data and transfer time within the global network, is very important from the view of multi-messenger astronomy using gravitational waves. Real-time calbrated data delivered from the KAGRA detector site and other detectors to our computing system arrive with about 4–15 seconds of latency. These latencies are sufficiently short compared to the time taken for gravitational wave event search computations. We also established a high-latency exchange of offline calibrated data that was aggregated with a better accuracy compared with real-time data.

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Search for Gravitational Waves Associated with Fast Radio Bursts Detected by CHIME/FRB during the LIGO-Virgo Observing Run O3a

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Astrophysical Journal 2023年第2期955卷 155-155页

作者： Abbott, R. Abbott, T.D. Acernese, F. Ackley, K. Adams, C. Adhikari, N. Adhikari, R.X. 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. 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. Andrić, T. Angelova, S.V. Ansoldi, S. Antelis, J.M. Antier, S. Appert, S. Arai, Koya Arai, Y. Araki, S. Araya, A. Araya, M.C. Areeda, J.S. Arène, M. Aritomi, N. Arnaud, N. Aronson, S.M. Arun, K.G. Asada, H. Asali, Y. Ashton, G. Aso, Y. Assiduo, M. Aston, S.M. Astone, P. Aubin, F. Austin, C. Babak, S. Badaracco, F. Bader, M.K.M. Badger, C. Bae, S. Bae, Y. Baer, A.M. Bagnasco, S. Bai, Y. Baiotti, L. Baird, J. Bajpai, R. Ball, M. Ballardin, G. Ballmer, S.W. Balsamo, A. Baltus, G. Banagiri, S. 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. Bassiri, R. Basti, A. Bawaj, M. Bayley, J.C. Baylor, A.C. Bazzan, M. Bécsy, B. Bedakihale, V.M. Bejger, M. Belahcene, I. Benedetto, V. Beniwal, D. Bennett, T.F. Bentley, J.D. BenYaala, M. Bergamin, F. Berger, B.K. Bernuzzi, S. Berry, C.P.L. Bersanetti, D. Bertolini, A. Betzwieser, J. Beveridge, D. Bhandare, R. Bhardwaj, U. Bhattacharjee, D. Bhaumik, S. 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. Boer, M. Bogaert, G. Boldrini, M. 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. Boumerdassi, A. 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. Buchanan, J. B LIGO Laboratory California Institute of Technology Pasadena 91125 CA United States Louisiana State University Baton Rouge 70803 LA United States Dipartimento di Farmacia Università di Salerno Fisciano Salerno I-84084 Italy INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Napoli I-80126 Italy OzGrav School of Physics & Astronomy Monash University Clayton 3800 VIC Australia LIGO Livingston Observatory Livingston 70754 LA United States University of Wisconsin-Milwaukee Milwaukee 53201 WI United States OzGrav Australian National University Canberra 0200 ACT Australia Max Planck Institute for Gravitational Physics (Albert Einstein Institute) Hannover D-30167 Germany Leibniz Universität Hannover Hannover D-30167 Germany Inter-University Centre for Astronomy and Astrophysics Pune 411007 India University of Cambridge Cambridge CB2 1TN United Kingdom Theoretisch-Physikalisches Institut Friedrich-Schiller-Universität Jena Jena D-07743 Germany University of Birmingham Birmingham B15 2TT United Kingdom Center for Interdisciplinary Exploration & Research in Astrophysics (CIERA) Northwestern University Evanston 60208 IL United States Instituto Nacional de Pesquisas Espaciais São Paulo São José dos Campos 12227-010 Brazil Gravity Exploration Institute Cardiff University Cardiff CF24 3AA United Kingdom INFN Sezione di Pisa Pisa I-56127 Italy International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bengaluru 560089 India Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan INFN Sezione di Torino Torino I-10125 Italy Università di Napoli “Federico II Complesso Universitario di Monte S. Angelo Napoli I-80126 Italy Université de Lyon Université Claude Bernard Lyon 1 CNRS Institut Lumière Matière Villeurbanne F-69622

We search for gravitational-wave (GW) transients associated with fast radio bursts (FRBs) detected by the Canadian Hydrogen Intensity Mapping Experiment Fast Radio Burst Project, during the first part of the third observing run of Advanced LIGO and Advanced Virgo (2019 April 1 15:00 UTC-2019 October 1 15:00 UTC). Triggers from 22 FRBs were analyzed with a search that targets both binary neutron star (BNS) and neutron star-black hole (NSBH) mergers. A targeted search for generic GW transients was conducted on 40 FRBs. We find no significant evidence for a GW association in either search. Given the large uncertainties in the distances of our FRB sample, we are unable to exclude the possibility of a GW association. Assessing the volumetric event rates of both FRB and binary mergers, an association is limited to 15% of the FRB population for BNS mergers or 1% for NSBH mergers. We report 90% confidence lower bounds on the distance to each FRB for a range of GW progenitor models and set upper limits on the energy emitted through GWs for a range of emission scenarios. We find values of order 10⁵¹-10⁵⁷ erg for models with central GW frequencies in the range 70-3560 Hz. At the sensitivity of this search, we find these limits to be above the predicted GW emissions for the models considered. We also find no significant coincident detection of GWs with the repeater, FRB 20200120E, which is the closest known extragalactic FRB. © 2023. The Author(s). Published by the American Astronomical Society.

关键词： Gravitational wave astronomy Radio transient sources

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