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The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

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The repertoire of mutational signatures in human cancer (vol 578, pg 94, 2020)

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NATURE 2023年第7948期614卷 E41-E41页

作者： Alexandrov, Ludmil B. Kim, Jaegil Haradhvala, Nicholas J. Huang, Mi Ni Ng, Alvin Wei Tian Wu, Yang Boot, Arnoud Covington, Kyle R. Gordenin, Dmitry A. Bergstrom, Erik N. Islam, S. M. Ashiqul Lopez-Bigas, Nuria Klimczak, Leszek J. McPherson, John R. Morganella, Sandro Sabarinathan, Radhakrishnan Wheeler, David A. Mustonen, Ville Getz, Gad Rozen, Steven G. Stratton, Michael R. Department of Cellular and Molecular Medicine Department of Bioengineering Moores Cancer Center University of California San Diego CA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Cellular and Molecular Medicine and Department of Bioengineering University of California San Diego La Jolla CA USA UC San Diego Moores Cancer Center San Diego CA USA University of California San Diego San Diego CA USA Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Massachusetts General Hospital Boston MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama Japan Computational Biology Program Ontario Institute for Cancer Research Toronto ON Canada Programme in Cancer & Stem Cell Biology Duke-NUS Medical School Singapore Singapore Centre for Computational Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Centre for Computational Biology Duke-NUS Medical School Singapore Singapore SingHealth Duke-NUS Institute of Precision Medicine National Heart Centre Singapore Singapore Singapore Cancer Science Institute of Singapore National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Singapore Singapore Laboratory of Cancer Epigenome Division of Medical Science National Cancer Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Dan L. Duncan Cancer Center Baylor College of Medicine Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Genome Integrity and Structural Biology Laboratory National Ins

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pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy

arXiv

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arXiv 2024年

作者： Iyer, Kartheik G. Yunus, Mikaeel O’Neill, Charles Ye, Christine Hyk, Alina McCormick, Kiera Ciucă, Ioana Wu, John F. Accomazzi, Alberto Astarita, Simone Chakrabarty, Rishabh Cranney, Jesse Field, Anjalie Ghosal, Tirthankar Ginolfi, Michele Huertas-Company, Marc Jablońska, Maja Kruk, Sandor Liu, Huiling Marchidan, Gabriel Mistry, Rohit Naiman, J.P. Peek, J.E.G. Polimera, Mugdha Rodríguez Méndez, Sergio J. Schawinski, Kevin Sharma, Sanjib Smith, Michael J. Ting, Yuan-Sen Walmsley, Mike Columbia Astrophysics Laboratory Columbia University 550 West 120th Street New YorkNY10027 United States Department of Physics and Astronomy Johns Hopkins University 3400 N. Charles Street BaltimoreMD21218 United States School of Computing TheAustralian National University 108 North Rd ActonACT2601 Australia Stanford University 450 Jane Stanford Way StanfordCA94305 United States School of Electrical Engineering and Computer Science Oregon State University 1500 SW Jefferson Way CorvallisOR97331 United States Department of Engineering Loyola University Maryland 4501 North Charles Street BaltimoreMD21210 United States Research School of Astronomy & Astrophysics Australian National University Cotter Rd. WestonACT2611 Australia School of Computing Australian National University ActonACT2601 Australia Kavli Institute for Particle Astrophysics and Cosmology Department of Physics Stanford University StanfordCA94305 United States Space Telescope Science Institute 3700 San Martin Drive BaltimoreMD21218 United States Center for Astrophysics Harvard & Smithsonian CambridgeMA02138 United States Camino Bajo del Castillo s/n Villanueva de la Cañada Madrid28692 Spain Paris France Astralis-AITC - Stromlo RSAA Australian National University Cotter Road WestonACT2600 Australia Department of Computer Science Johns Hopkins University 3400 North Charles Street BaltimoreMD21218 United States National Center for Computational Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Dipartimento di Fisica e Astronomia Universita di Firenze Via G. Sansone 1 Sesto Fiorentino Firenze50019 Italy INAF - Osservatorio Astrofisico di Arcetri Largo E. Fermi 5 FirenzeI-50125 Italy Instituto de Astrofisica de Canarias C. Via Lactea 1 Tenerife La LagunaE-38205 Spain Universidad de la Laguna dept. Astrofisica Tenerife La LagunaE-38206 Spain Universite Paris-Cite LERMA - Observatoire de Paris PSL Paris France SCIPP University of

The exponential growth of astronomical literature poses significant challenges for researchers navigating and synthesizing general insights or even domain-specific knowledge. We present pathfinder, a machine learning framework designed to enable literature review and knowledge discovery in astronomy, focusing on semantic searching with natural language instead of syntactic searches with key-words. Utilizing state-of-the-art large language models (LLMs) and a corpus of 350,000 peer-reviewed papers from the Astrophysics Data System (ADS), pathfinder offers an innovative approach to scientific inquiry and literature exploration. Our framework couples advanced retrieval techniques with LLM-based synthesis to search astronomical literature by semantic context as a complement to currently existing methods that use key-words or citation graphs. It addresses complexities of jargon, named entities, and temporal aspects through time-based and citation-based weighting schemes. We demonstrate the tool’s versatility through case studies, showcasing its application in various research scenarios. The system’s performance is evaluated using custom benchmarks, including single-paper and multi-paper tasks. Beyond literature review, pathfinder offers unique capabilities for reformatting answers in ways that are accessible to various audiences (e.g. in a different language or as simplified text), visualizing research landscapes, and tracking the impact of observatories and methodologies. This tool represents a significant advancement in applying AI to astronomical research, aiding researchers at all career stages in navigating modern astronomy literature. © 2024, CC BY.

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The power grid library for benchmarking AC optimal power flow algorithms

arXiv

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arXiv 2019年

作者： Babaeinejadsarookolaee, Sogol Birchfield, Adam Christie, Richard D. Coffrin, Carleton DeMarco, Christopher Diao, Ruisheng Ferris, Michael Fliscounakis, Stéphane Greene, Scott Huang, Renke Josz, Cédric Korab, Roman Lesieutre, Bernard Maeght, Jean Molzahn, Daniel K. Overbye, Thomas J. Panciatici, Patrick Park, Byungkwon Snodgrass, Jonathan Zimmerman, Ray Electrical and Computer Engineering University of Wisconsin-Madison WI United States Electrical and Computer Engineering Texas A&M University TX United States Electrical and Computer Engineering University of Washington WA United States Advanced Network Science Initiative Los Alamos National Laboratory NM United States AI & System Analytics GEIRI North America San JoseCA United States Computer Sciences University of Wisconsin-Madison WI United States Paris France Electricity Infrastructure Group Pacific Northwest National Laboratory RichlandWA United States Industrial Engineering and Operations Research Columbia University New YorkNY United States Electrical Engineering Silesian University of Technology Gliwice Poland Electrical and Computer Engineering Georgia Institute of Technology GA United States Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN United States Applied Economics and Management Cornell University IthacaNY United States

In recent years, the power systems research community has seen an explosion of novel methods for formulating the AC power flow equations. Consequently, benchmarking studies using the seminal AC Optimal Power Flow (AC-OPF) problem have emerged as the primary method for evaluating these emerging methods. However, it is often difficult to directly compare these studies due to subtle differences in the AC-OPF problem formulation as well as the network, generation, and loading data that are used for evaluation. To help address these challenges, this IEEE PES Task Force report proposes a standardized AC-OPF mathematical formulation and the PGLib-OPF networks for benchmarking AC-OPF algorithms. A motivating study demonstrates some limitations of the established network datasets in the context of benchmarking AC-OPF algorithms and a validation study demonstrates the efficacy of using the PGLib-OPF networks for this purpose. In the interest of scientific discourse and future additions, the PGLib-OPF benchmark library is open-access and all the of network data is provided under a creative commons license. Copyright © 2019, The Authors. All rights reserved.

关键词： Convex optimization

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Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange

arXiv

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arXiv 2024年

作者： Evans, Matthew L. Bergsma, Johan Merkys, Andrius Andersen, Casper W. Andersson, Oskar B. Beltrán, Daniel Blokhin, Evgeny Boland, Tara M. Balderas, Rubén Castañeda Choudhary, Kamal Díaz, Alberto Díaz García, Rodrigo Domínguez Eckert, Hagen Eimre, Kristjan Montero, María Elena Fuentes Krajewski, Adam M. Mortensen, Jens Jørgen Duarte, José Manuel Nápoles Pietryga, Jacob Qi, Ji de Jesús Trejo Carrillo, Felipe Vaitkus, Antanas Yu, Jusong Zettel, Adam de Castro, Pedro Baptista Carlsson, Johan Cerqueira, Tiago F.T. Divilov, Simon Hajiyani, Hamidreza Hanke, Felix Jose, Kevin Oses, Corey Riebesell, Janosh Schmidt, Jonathan Winston, Donald Xie, Christen Yang, Xiaoyu Bonella, Sara Botti, Silvana Curtarolo, Stefano Draxl, Claudia Cobas, Luis Edmundo Fuentes Hospital, Adam Liu, Zi-Kui Marques, Miguel A.L. Marzari, Nicola Morris, Andrew J. Ong, Shyue Ping Orozco, Modesto Persson, Kristin A. Thygesen, Kristian S. Wolverton, Chris Scheidgen, Markus Toher, Cormac Conduit, Gareth J. Pizzi, Giovanni Gražulis, Saulius Rignanese, Gian-Marco Armiento, Rickard Chemin des Étoiles 8 Louvain-la-Neuve1348 Belgium Matgenix SRL 185 Rue Armand Bury Gozée6534 Belgium École Polytechnique Fédérale de Lausanne Avenue de Forel 3 Lausanne1015 Switzerland Institute of Biotechnology Life Sciences Center Vilnius University Sauletekio av. 7 VilniusLT-10257 Lithuania SINTEF P.O. Box 4760 Torgarden TrondheimNO-7465 Norway Materials Design and Informatics unit Department of Physics Chemistry and Biology Linköping University Sweden Baldiri i Reixac 10-12 Barcelona08028 Spain Tilde Materials Informatics Straßmannstraße 25 Berlin10249 Germany Materials Platform for Data Science Sepapaja 6 Tallinn15551 Estonia Computational Atomic-Scale Materials Design Technical University of Denmark Kgs. Lyngby Denmark Av. Miguel de Cervantes 120 Complejo Industrial Chihuahua Chihuahua Chih. 31136 Mexico Material Measurement Laboratory National Institute of Standards and Technology GaithersburgMD20899 United States Department of Mechanical Engineering and Materials Science Duke University DurhamNC27708 United States Center for Extreme Materials Duke University DurhamNC27708 United States École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Universidad Autónoma de Chihuahua Facultad de Ciencias Quimicas Chihuahua31125 Mexico Department of Materials Science and Engineering The Pennsylvania State University University ParkPA16802 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of NanoEngineering University of California 9500 Gilman Drive La Jolla San DiegoCA92093-0448 United States National Institute for Materials Science 1-2-1 Sengen Ibaraki Tsukuba305-0047 Japan Dassault Systèmes Germany GmbH Am Kabellager 11-13 Cologne51063 Germany CFisUC Department of Physics University of Coimbra Rua Larga Coimbra3004-516 Portugal Dassault Systèmes 22 Science Park CB4 0FJ United Kingdom Theory of Condensed Matter Cavendis

The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development. © 2024, CC BY.

关键词： Electronic data interchange

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Genomic basis for RNA alterations in cancer (vol 578, pg 129, 2020)

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NATURE 2023年第7948期614卷 E37-E37页

作者： Calabrese, Claudia Davidson, Natalie R. Demircioglu, Deniz Fonseca, Nuno A. He, Yao Lehmann, Kjong-Van Liu, Fenglin Shiraishi, Yuichi Soulette, Cameron M. Urban, Lara Greger, Liliana Li, Siliang Liu, Dongbing Perry, Marc D. Xiang, Qian Zhang, Fan Zhang, Junjun Bailey, Peter Erkek, Serap Hoadley, Katherine A. Hou, Yong Huska, Matthew R. Kilpinen, Helena Korbel, Jan O. Marin, Maximillian G. Markowski, Julia Nandi, Tannistha Pan-Hammarstrom, Qiang Pedamallu, Chandra Sekhar Siebert, Reiner Stark, Stefan G. Su, Hong Tan, Patrick Waszak, Sebastian M. Yung, Christina Zhu, Shida Awadalla, Philip Creighton, Chad J. Meyerson, Matthew Ouellette, B. F. Francis Wu, Kui Yang, Huanming Brazma, Alvis Brooks, Angela N. Goke, Jonathan Ratsch, Gunnar Schwarz, Roland F. Stegle, Oliver Zhang, Zemin European Molecular Biology Laboratory European Bioinformatics Institute Hinxton UK European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany CIBIO/InBIO - Research Center in Biodiversity and Genetic Resources Universidade do Porto Vairão Portugal Berlin Institute for Medical Systems Biology Max Delbruck Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) partner site Berlin Germany German Cancer Research Center (DKFZ) Heidelberg Germany Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) Partner site Berlin Berlin Germany European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Division of Computational Genomics and Systems Genetics German Cancer Research Center (DKFZ) Heidelberg Germany ETH Zurich Zurich Switzerland Memorial Sloan Kettering Cancer Center New York NY USA Weill Cornell Medical College New York NY USA SIB Swiss Institute of Bioinformatics Lausanne Switzerland University Hospital Zurich Zurich Switzerland Computational Biology Center Memorial Sloan Kettering Cancer Center New York NY USA Department of Biology ETH Zurich Zürich Switzerland Department of Computer Science ETH Zurich Zurich Switzerland Korea University Seoul South Korea Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine New York NY USA National University of Singapore Singapore Singapore Genome Institute of Singapore Singapore Singapore Computational and Systems Biology Genome Institute of Singap

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Correction:Adaptive optical quantitative phase imaging based on annular illumination Fourier ptychographic microscopy

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PhotoniX 2022年第1期3卷 73-73页

作者： Yefeng Shu Jiasong Sun Jiaming Lyu Yao Fan Ning Zhou Ran Ye Guoan Zheng Qian Chen Chao Zuo Smart Computational Imaging Laboratory(SCILab) School of Electronic and Optical EngineeringNanjing University of Science and Technolog210094 NanjingJiangsu ProvincePeople’s Republic of China Smart Computational Imaging Research Institute(SCIRI)of Nanjing University of Science and Technology 210019 NanjingJiangsu ProvincePeople’s Republic of China Jiangsu Key Laboratory of Spectral Imaging Intelligent Sense 210094 NanjingJiangsu ProvincePeople’s Republic of China Terahertz Technology Innovation Research Institute University of Shanghai for Science and Technology200093 ShanghaiPeople’s Republic of China School of Computer and Electronic Information Nanjing Normal University210023 NanjingJiangsu ProvincePeople’s Republic of China Department of Biomedical Engineering University of ConnecticutStorrsConnecticut 06269USA.

In the original publication of this article[1],the video in the additional file 2 was uploaded mistakenly due to a typesetting error,and needs to be updated with the correct *** original article[1]was updated.

关键词： illumination annular phase

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Author Correction: Constrained catecholamines gain β2AR selectivity through allosteric effects on pocket dynamics

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Nature Communications 2023年第1期14卷 1页

作者： Xinyu Xu Xiangyu Liu Jeremy Shonberg Jonas Kaindl Anne Stößel Luis Maul Harald Hübner Peter Gmeiner Mary J. Clark Daniel Mayer Roger K. Sunahara Kunio Hirata A. J. Venkatakrishnan Ron O. Dror Brian K. Kobilka State Key laboratory of Membrane Biology Tsinghua-Peking Center for Life Sciences School of Pharmaceutical Sciences Tsinghua University Beijing 100084 China Beijing Frontier Research Center for Biological Structure Beijing Advanced Innovation Center for Structural Biology Tsinghua University Beijing 100084 China Beijing Key Laboratory of Cardiovascular Receptors Research Peking University Beijing China Department of Chemistry and Pharmacy Medicinal Chemistry Friedrich-Alexander University Erlangen-Nurnberg Nikolaus-Fiebiger-Straße 10 91058 Erlangen Germany Department of Pharmacology University of California San Diego School of Medicine 9500 Gilman Drive La Jolla California 92093 USA Advanced Photon Technology Division Research Infrastructure Group SR Life Science Instrumentation Unit RIKEN/SPring-8 Center 1-1-1 Kouto Sayo-cho Sayo-gun Hyogo 679-5148 Japan Precursory Research for Embryonic Science and Technology (PRESTO) Japan Science and Technology Agency 4-1-8 Honcho Kawaguchi Saitama 332-0012 Japan Department of Computer Science Stanford University Stanford CA 94305 USA Department of Molecular and Cellular Physiology Stanford University School of Medicine Stanford CA 94305 USA Department of Structural Biology Stanford University School of Medicine Stanford CA 94305 USA Institute for Computational and Mathematical Engineering Stanford University Stanford CA 94305 USA

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CEPC Technical Design Report - Accelerator (v2)

arXiv

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arXiv 2023年

作者： Abdallah, Waleed De Freitas, Tiago Carlos Adorno Afanaciev, Konstantin Ahmad, Shakeel Ahmed, Ijaz Ai, Xiaocong Aleem, Abid Altmannshofer, Wolfgang Alves, Fabio An, Weiming An, Rui Anderle, Daniele Paolo Antusch, Stefan Arai, Yasuo Arbuzov, Andrej Arhrib, Abdesslam Ashry, Mustafa Bai, Sha Bai, Yu Bai, Yang Bairathi, Vipul Balazs, Csaba Bambade, Philip Ban, Yong Bandyopadhyay, Triparno Bao, Shou-Shan Barber, Desmond P. Bat, Ayse Batozskaya, Varvara Behera, Subash Chandra Belyaev, Alexander Bertucci, Michele Bi, Xiao-Jun Bi, Yuanjie Bian, Tianjian Bianchi, Fabrizio Biekötter, Thomas Biglietti, Michela Bilanishvili, Shalva Binglin, Deng Bodrov, Denis Bogomyagkov, Anton Bondarenko, Serge Boogert, Stewart Boonekamp, Maarten Borri, Marcello Bosotti, Angelo Boudry, Vincent Boukidi, Mohammed Boyko, Igor Bozovic, Ivanka Bozzi, Giuseppe Brient, Jean-Claude Budzinskaya, Anastasiia Bukhari, Masroor Bytev, Vladimir Cacciapaglia, Giacomo Cai, Hua Cai, Wenyong Cai, Wujun Cai, Yijian Cai, Yizhou Cai, Yuchen Cai, Haiying Cai, Huacheng Calibbi, Lorenzo Cang, Junsong Cao, Guofu Cao, Jianshe Chance, Antoine Chang, Xuejun Chang, Yue Chang, Zhe Chang, Xinyuan Chao, Wei Chatrabhuti, Auttakit Che, Yimin Che, Yuzhi Chen, Bin Chen, Danping Chen, Fuqing Chen, Fusan Chen, Gang Chen, Guoming Chen, Hua-Xing Chen, Huirun Chen, Jinhui Chen, Ji-Yuan Chen, Kai Chen, Mali Chen, Mingjun Chen, Mingshui Chen, Ning Chen, Shanhong Chen, Shanzhen Chen, Shao-Long Chen, Shaomin Chen, Shiqiang Chen, Tianlu Chen, Wei Chen, Xiang Chen, Xiaoyu Chen, Xin Chen, Xun Chen, Xurong Chen, Ye Chen, Ying Chen, Yukai Chen, Zelin Chen, Zilin Chen, Boping Chen, Chunhui Cheng, Hok Chuen Cheng, Huajie Cheng, Shan Cheng, Tongguang Chi, Yunlong Chimenti, Pietro Chiu, Wen Han Cho, Guk Chu, Ming-Chung Chu, Xiaotong Chu, Ziliang Coloretti, Guglielmo Crivellin, Andreas Cui, Hanhua Cui, Xiaohao Cui, Zhaoyuan D'Anzi, Brunella Dai, Ling-Yun Dai, Xinchen Dai, Xuwen De Maria, Antonio De Filippis, Nicola De La Taille, Christophe De Mori, Francesca De Sio, Chiara Del Core, Elisa Deng, S Agh University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Anhui University Anhui Hefei China Applied Physics Department Federal Urdu University of Arts Science and Technology Islamabad Pakistan Banaras Hindu University Institute of Science Varanasi India Bandirma Onyedi Eylul University Bandirma Turkey Beihang University Beijing China Beijing Computational Science Research Center Beijing China Beijing Conveyi Ltd Beijing China Beijing Glass Research Institute Co. Ltd Beijing China Beijing Institute of Technology Beijing China Beijing Normal University Beijing China Brown University ProvidenceRI United States Budker Institute of Nuclear Physics Novosibirsk Russia Cadi Ayyad University Laboratory of Fundamental and Applied Physics Polydisciplinary Faculty Marrakech Morocco Cairo University Giza Egypt Center for Theory and Computation National Tsing Hua University Hsinchu Taiwan Central China Normal University Hubei Wuhan China Central South University Hunan Changsha China Centro de Fisica Teorica de Particulas Universidade Tecnica de Lisboa Lisboa Portugal Chengdu KaitengSifang Digital Radio & Tv Equipment Co. Ltd Sichuan Chengdu China China Academy of Engineering Physics Sichuan Mianyang China China Building Materials Academy Beijing China China Center of Advanced Science and Technology Beijing China China Institute of Atomic Energy Beijing China China Jiliang University Zhejiang Hangzhou China China Nuclear Instrument CO. Ltd Beijing China China University of Geosciences Beijing China China University of Geosciences Hubei Wuhan China China University of Mining and Technology Jiangsu Xuzhou China China West Normal University Sichuan Nanchong China Chongqing University Department of Physics Chongqing China Chulalongkorn University Bangkok Thailand City University of Hong Kong Department of Physics Hong Kong Cockcroft Institute Daresbury United Kingdom Cornell University IthacaNY

The Circular Electron Positron Collider (CEPC) is a large scientific projectinitiated and hosted by China, fostered through extensive collaboration withinternational partners. The complex comprises four accelerators: a 30 GeVLinac, a 1.1 GeV Damping Ring, a Booster capable of achieving energies up to180 GeV, and a Collider operating at varying energy modes (Z, W, H, and ttbar).The Linac and Damping Ring are situated on the surface, while the Booster andCollider are housed in a 100 km circumference underground tunnel, strategicallyaccommodating future expansion with provisions for a Super Proton ProtonCollider (SPPC). The CEPC primarily serves as a Higgs factory. In its baselinedesign with synchrotron radiation (SR) power of 30 MW per beam, it can achievea luminosity of 5e34 /cm^2/s^1, resulting in an integrated luminosity of 13 /abfor two interaction points over a decade, producing 2.6 million Higgs *** the SR power to 50 MW per beam expands the CEPC\'s capability togenerate 4.3 million Higgs bosons, facilitating precise measurements of Higgscoupling at sub-percent levels, exceeding the precision expected from theHL-LHC by an order of magnitude. This Technical Design Report (TDR) follows thePreliminary Conceptual Design Report (Pre-CDR, 2015) and the Conceptual DesignReport (CDR, 2018), comprehensively detailing the machine\'s layout andperformance, physical design and analysis, technical systems design, R&D andprototyping efforts, and associated civil engineering aspects. Additionally, itincludes a cost estimate and a preliminary construction timeline, establishinga framework for forthcoming engineering design phase and site selectionprocedures. Construction is anticipated to begin around 2027-2028, pendinggovernment approval, with an estimated duration of 8 years. The commencement ofexperiments could potentially initiate in the mid-2030s. © 2023, CC BY-NC-SA.

关键词： Synchrotron radiation

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Understanding metric-related pitfalls in image analysis validation

arXiv

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arXiv 2023年

作者： Reinke, Annika Tizabi, Minu D. Baumgartner, Michael Eisenmann, Matthias Heckmann-Nötzel, Doreen Kavur, A. Emre Rädsch, Tim Sudre, Carole H. Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Benis, Arriel Blaschko, Matthew B. Buettner, Florian Cardoso, M. Jorge Cheplygina, Veronika Chen, Jianxu Christodoulou, Evangelia Cimini, Beth A. Collins, Gary S. Farahani, Keyvan Ferrer, Luciana Galdran, Adrian van Ginneken, Bram Glocker, Ben Godau, Patrick Haase, Robert Hashimoto, Daniel A. Hoffman, Michael M. Huisman, Merel Isensee, Fabian Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kenngott, Hannes Kleesiek, Jens Kofler, Florian Kooi, Thijs Kopp-Schneider, Annette Kozubek, Michal Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Petersen, Jens Rafelski, Susanne M. Rajpoot, Nasir Reyes, Mauricio Riegler, Michael A. Rieke, Nicola Saez-Rodriguez, Julio Sánchez, Clara I. Shetty, Shravya Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. van Calster, Ben Varoquaux, Gaël Yaniv, Ziv R. Jäger, Paul F. Maier-Hein, Lena Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Intelligent Medical Systems Germany NCT Heidelberg A Partnership Between DKFZ University Medical Center Heidelberg Germany Heidelberg Division of Medical Image Computing Germany Heidelberg Division of Intelligent Medical Systems Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montreal Canada Division of Computational Pathology Dept of Pathology & Laboratory Medicine Indiana University School of Medicine IU Health Information and Translational Sciences Building Indianapolis United States University of Pennsylvania Richards Medical Research Laboratories FL7 PhiladelphiaPA United States Department of Digital Medical Technologies Holon Institute of Technology Holon Israel European Federation for Medical Informatics Le Mont-sur-Lausanne Switzerland Center for Processing Speech and Images Department of Electrical Engineering KU Leuven Leuven Belgium partner site Frankfurt/Mainz a partnership between DKFZ and UCT Frankfurt Marburg Germany Heidelberg Germany Goethe University Frankfurt Department of Medicine Germany Goethe University Frankfurt Department of Informatics Germany and Frankfurt Cancer Insititute Germany Department of Computer Science IT University of Copenhagen Copenhagen Denmark Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Imaging Platform Broad Institute of MIT and Harvard CambridgeMA United States Centre for Statistics in Medicine University of Oxford Oxford United Kingdom Center for Biomedical In

Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately. While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. While focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation. © 2023, CC BY.

关键词： computer vision

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