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arXiv 2018年

作者： Zhang, Rongqing Cheng, Xiang Yang, Liuqing State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing China Department of Electrical and Computer Engineering Colorado State University CO United States Shenzhen Research Institute of Big Data Shenzhen Guangdong China

In this paper, we investigate flexible power transfer among electric vehicles (EVs) from a cooperative perspective in an EV system. First, the concept of cooperative EV-to- EV (V2V) charging is introduced, which enables active cooperation via charging/discharging operations between EVs as energy consumers and EVs as energy providers. Then, based on the cooperative V2V charging concept, a flexible energy management protocol with different V2V matching algorithms is proposed, which can help the EVs achieve more flexible and smarter charging/discharging behaviors. In the proposed energy management protocol, we define the utilities of the EVs based on the cost and profit through cooperative V2V charging and employ the bipartite graph to model the charging/discharging cooperation between EVs as energy consumers and EVs as energy providers. Based on the constructed bipartite graph, a max-weight V2V matching algorithm is proposed in order to optimize the network social welfare. Moreover, taking individual rationality into consideration, we further introduce the stable matching concepts and propose two stable V2V matching algorithms, which can yield the EV-consumer-optimal and EVprovider- optimal stable V2V matchings, respectively. Simulation results verify the efficiency of our proposed cooperative V2V charging based energy management protocol in improving the EV utilities and the network social welfare as well as reducing the energy consumption of the EVs. Copyright © 2018, The Authors. All rights reserved.

关键词： Electric vehicles

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Learning from learning machines: A new generation of AI technology to meet the needs of science

arXiv

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arXiv 2021年

作者： Pion-Tonachini, Luca Bouchard, Kristofer Martin, Hector Garcia Peisert, Sean Holtz, W. Bradley Aswani, Anil Dwivedi, Dipankar Wainwright, Haruko Pilania, Ghanshyam Nachman, Benjamin Marrone, Babetta L. Falco, Nicola Prabhat Arnold, Daniel Wolf-Yadlin, Alejandro Powers, Sarah Climer, Sharlee Jackson, Quinn Carlson, Ty Sohn, Michael Zwart, Petrus Kumar, Neeraj Justice, Amy Tomlin, Claire Jacobson, Daniel Micklem, Gos Gkoutos, Georgios V. Bickel, Peter J. Cazier, Jean-Baptiste Müller, Juliane Webb-Robertson, Bobbie-Jo Stevens, Rick Anderson, Mark Kreutz-Delgado, Ken Mahoney, Michael W. Brown, James B. Pattern Computer Inc. Friday HarborWA98250 United States Biosciences Area Lawrence Berkeley National Lab BerkeleyCA94803 United States Computational Research Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Helen Wils Neuroscience Institute Redwood Center for Theoretical Neuroscience Uc Berkeley BerkeleyCA94720 United States Doe Agile BioFoundry Lawrence Berkeley National Laboratory BerkeleyCA94803 United States Joint BioEnergy Institute Lawrence Berkeley National Laboratory BerkeleyCA94803 United States Bcam Basque Center for Applied Mathematics Bilbao48009 Spain Computer Science University of California Davis DavisCA95616 United States Cenic La MiradaCA90638 United States Health Informatics University of California Davis School of Medicine SacramentoCA95817 United States Berkeley Institute for Data Science University of California Berkeley BerkeleyCA94720 United States Industrial Engineering and Operations Research University of California Berkeley BerkeleyCA94720 United States Environmental & Earth Sciences Area Lawrence Berkeley National Laboratory BerkeleyCA94803 United States Nuclear Engineering University of California Berkeley BerkeleyCA94720 United States Materials Science and Technology Division Los Alamos National Laboratory Los AlamosNM87545 United States Physics Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Bioscience Division Los Alamos National Laboratory Los AlamosNM87545 United States Earth and Environmental Sciences Area Lawrence Berkeley National Lab BerkeleyCA94803 United States Energy Technologies Area Lawrence Berkeley National Lab BerkeleyCA94803 United States Computing and Computational Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Industrial & Systems Engineering The University of Tennessee KnoxvilleTN37996 United States Department of Computer Science University of Missouri-Saint Louis St. LouisMO63121 United

We outline emerging opportunities and challenges to enhance the utility of AI for scientific discovery. The distinct goals of AI for industry versus the goals of AI for science create tension between identifying patterns in data versus discovering patterns in the world from data. If we address the fundamental challenges associated with "bridging the gap" between domain-driven scientific models and data-driven AI learning machines, then we expect that these AI models can transform hypothesis generation, scientific discovery, and the scientific process itself. © 2021, CC BY.

关键词： Learning systems

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Galactic transient sources with the Cherenkov Telescope Array Observatory

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Monthly Notices of the Royal Astronomical Society 2025年第1期540卷 205–238页

作者： Abe, K Abe, S Abhir, J Abhishek, A Acero, F Acharyya, A Adam, R Aguasca-Cabot, A Agudo, I Aguirre-Santaella, A Alfaro, J Alfaro, R Alvarez-Crespo, N Alves Batista, R Amans, J-P Amato, E Ambrosi, G Ambrosino, F Angüner, E O Antonelli, L A Aramo, C Arcaro, C Arnesen, T T H Asano, K Ascasibar, Y Aschersleben, J Ashkar, H Augusto Stuani, L Baack, D Backes, M Balazs, C Balbo, M Baquero Larriva, A Barbosa Martins, V Barres de Almeida, U Barrio, J A Barrios-Jiménez, L Batković, I Batzofin, R Baxter, J Becerra González, J Becker Tjus, J Belmont, R Benbow, W Bernete, J Bernlöhr, K Berti, A Bertucci, B Beshley, V Bhattacharjee, P Bhattacharyya, S Bigongiari, C Bissaldi, E Blanch, O Blazek, J Bocchino, F Boisson, C Bolmont, J Bonnoli, G Bonollo, A Bordas, P Bosnjak, Z Bottacini, E Böttcher, M Bradascio, F Bronzini, E Brown, A M Brunelli, G Bulgarelli, A Burelli, I Burger-Scheidlin, C Burmistrov, L Burton, M Buscemi, M Cailleux, J Campoy-Ordaz, A Cantlay, B K Capasso, G Caproni, A Capuzzo-Dolcetta, R Caraveo, P Caroff, S Carosi, A Carosi, R Carquin, E Carrasco, M-S Cascone, E Cassol, F Castaldini, L Castrejon, N Castro-Tirado, A J Cerasole, D Ceribella, G Cerruti, M Chadwick, P M Chaty, S Chen, A W Chernyakova, M Chiavassa, A Chudoba, J Chytka, L Cicciari, G M Cifuentes, A Coimbra Araujo, C H Colapietro, M Conforti, V Contreras, J L Cortina, J Costa, A Costantini, H Cotter, G Cristofari, P Cuevas, O Curtis-Ginsberg, Z D’Aì, A D’Amico, G D’Ammando, F Dai, S Dazzi, F de Bony de Lavergne, M De Caprio, V De Cesare, G De Frondat Laadim, F de Gouveia Dal Pino, E M De Lotto, B De Lucia, M de Martino, D de Menezes, R de Naurois, M de Ona Wilhelmi, E de Souza, V del Peral, L del Valle, M V Delgado, C Dell’aiera, M Della Valle, M della Volpe, D Depaoli, D Devin, J Di Girolamo, T Di Piano, A Di Pierro, F Di Tria, R Di Venere, L Diebold, S Dignam, C Dima, R Dinesh, A Djuvsland, J Dominik, R M Dominis Prester, D Donini, A Dorner, D Dörner, J Doro, M Dubos, C Ducci, L Dwarkadas, V V Ebr, J Eckner, C Egberts, K Einecke, S Elsässer, D Emery Department of Physics Tokai University 4-1-1 Kita-Kaname Hiratsuka Kanagawa 259-1292 Japan Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-ha Kashiwa Chiba 277-8582 Japan ETH Zürich Institute for Particle Physics and Astrophysics Otto-Stern-Weg 5 CH-8093 Zürich Switzerland INFN and Università degli Studi di Siena Dipartimento di Scienze Fisiche della Terra e dell’Ambiente (DSFTA) Sezione di Fisica Via Roma 56 I-53100 Siena Italy Université Paris-Saclay Université Paris Cité CEA CNRS AIM F-91191 Gif-sur-Yvette Cedex France FSLAC IRL 2009 CNRS/IAC E-38205 La Laguna Tenerife Spain University of Alabama Tuscaloosa Department of Physics and Astronomy Gallalee Hall Box 870324 Tuscaloosa AL 35487-0324 USA Université Côte d’Azur Observatoire de la Côte d’Azur CNRS Laboratoire Lagrange UF 06304 Nice France Laboratoire Leprince-Ringuet CNRS/IN2P3 École Polytechnique Institut Polytechnique de Paris F-91120 Palaiseau France Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Martí i Franquès 1 E-08028 Barcelona Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n E-18008 Granada Spain Institute for Computational Cosmology and Department of Physics Durham University South Road Durham DH1 3LE UK Pontificia Universidad Católica de Chile Av. Libertador Bernardo O’Higgins 340 8331150 Santiago Chile Universidad Nacional Autónoma de México Delegación Coyoacán 04510 Ciudad de México Mexico IPARCOS-UCM Instituto de Física de Partículas y del Cosmos and EMFTEL Department Universidad Complutense de Madrid E-28040 Madrid Spain Instituto de Física Teórica UAM/CSIC and Departamento de Física Teórica Universidad Autónoma de Madrid c/ Nicolás Cabrera 13-15 Campus de Cantoblanco UAM E-28049 Madrid Spain LUTH GEPI and LERMA Observatoire de Paris Université PSL Université Paris Cité CNRS 5 place Jules Janssen F-92190 Meudon France INAF – Osservatorio

A wide variety of Galactic sources show transient emission at soft and hard X-ray energies: low- and high-mass X-ray binaries containing compact objects, isolated neutron stars exhibiting extreme variability as magnetars as well as pulsar-wind nebulae. Although most of them can show emission up to MeV and/or GeV energies, many have not yet been detected in the TeV domain by Imaging Atmospheric Cherenkov Telescopes. In this paper, we explore the feasibility of detecting new Galactic transients with the Cherenkov Telescope Array Observatory (CTAO) and the prospects for studying them with Target of Opportunity observations. We show that CTAO will likely detect new sources in the TeV regime, such as the massive microquasars in the Cygnus region, low-mass X-ray binaries with low-viewing angle, flaring emission from the Crab pulsar-wind nebula or other novae explosions, among others. Since some of these sources could also exhibit emission at larger time-scales, we additionally test their detectability at longer exposures. We finally discuss the multiwavelength synergies with other instruments and large astronomical facilities.

关键词： binaries: general stars: magnetars novae cataclysmic variables pulsars: general gamma-rays: general

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Molecular geometry prediction using a deep generative graph neural network

arXiv

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arXiv 2019年

作者： Mansimov, Elman Mahmood, Omar Kang, Seokho Cho, Kyunghyun Department of Computer Science Courant Institute of Mathematical Sciences New York University 60 5th Avenue New YorkNY10011 United States Center for Data Science New York University 60 5th Avenue New YorkNY10011 United States Department of Systems Management Engineering Sungkyunkwan University 2066 Seobu-ro Jangan-gu Suwon16419 Korea Republic of Facebook AI Research 770 Broadway New YorkNY10003 United States CIFAR Azrieli Global Scholar Canadian Institute for Advanced Research 661 University Avenue TorontoONM5G 1M1 Canada

A molecule’s geometry, also known as conformation, is one of a molecule’s most important properties, determining the reactions it participates in, the bonds it forms, and the interactions it has with other molecules. Conventional conformation generation methods minimize hand-designed molecular force field energy functions that are often not well correlated with the true energy function of a molecule observed in nature. They generate geometrically diverse sets of conformations, some of which are very similar to the lowest-energy conformations and others of which are very different. In this paper, we propose a conditional deep generative graph neural network that learns an energy function by directly learning to generate molecular conformations that are energetically favorable and more likely to be observed experimentally in data-driven manner. On three large-scale datasets containing small molecules, we show that our method generates a set of conformations that on average is far more likely to be close to the corresponding reference conformations than are those obtained from conventional force field methods. Our method maintains geometrical diversity by generating conformations that are not too similar to each other, and is also computationally faster. We also show that our method can be used to provide initial coordinates for conventional force field methods. On one of the evaluated datasets we show that this combination allows us to combine the best of both methods, yielding generated conformations that are on average close to reference conformations with some very similar to reference conformations. Copyright © 2019, The Authors. All rights reserved.

关键词： Molecules

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Non-volatile Optical Switch Based on a GST-Loaded Directional Coupler

Non-volatile Optical Switch Based on a GST-Loaded Directiona...

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Optoelectronics Global Conference (OGC)

作者： Hanyu Zhang Linjie Zhou Liangjun Lu Jianping Chen B. M. A. Rahman Shanghai Institute for Advanced Communication and Data Science Shanghai Key Lab of Navigation and Location Services State Key Laboratory of Advanced Optical Communication Systems and Networks SJTU Shanghai China Department of Electrical and Electronic Engineering University of London London U.K.

We present a non-volatile optical switch based on a directional coupler comprising a silicon-Ge2Sb2Te5 (GST) hybrid waveguide. The non-volatility of GST makes it attractive for reducing static power consumption in optical switching. Experimental results show that the optical switch has an extinction ratio of >20 dB in the bar state and >25 dB in the cross state around 1578 nm wavelength. The insertion loss is 2 dB and 7 dB for the bar and cross states, respectively.

关键词： Optical waveguides Silicon Optical switches Directional couplers Optical refraction Optical variables control Photonics

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First characterization of the emission behavior of Mrk421 from radio to VHE gamma rays with simultaneous X-ray polarization measurements

arXiv

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arXiv 2023年

作者： Abe, S. Abhir, J. Acciari, V.A. Agudo, I. Aniello, T. Ansoldi, S. Antonelli, L.A. Arbet Engels, A. Arcaro, C. Artero, M. Asano, K. Babić, A. Baquero, A. Barres de Almeida, U. Barrio, J.A. Batković, I. Baxter, J. Becerra González, J. Bednarek, W. Bernardini, E. Bernete, J. Berti, A. Besenrieder, J. Bigongiari, C. Biland, A. Blanch, O. Bonnoli, G. Bošnjak, Ž. Burelli, I. Busetto, G. Campoy-Ordaz, A. Carosi, A. Carosi, R. Carretero-Castrillo, M. Castro-Tirado, A.J. Ceribella, G. Chai, Y. Cifuentes, A. Cikota, S. Colombo, E. Contreras, J.L. Cortina, J. Covino, S. D'Ammando, F. D'Amico, G. D'Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. De Lotto, B. de Menezes, R. Del Popolo, A. Delgado, J. Delgado Mendez, C. Di Pierro, F. Di Venere, L. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsaesser, D. Emery, G. Escudero, J. Fariña, L. Fattorini, A. Foffano, L. Font, L. Fröse, S. Fukami, S. Fukazawa, Y. García López, R.J. Garczarczyk, M. Gasparyan, S. Gaug, M. Giesbrecht Paiva, J.G. Giglietto, N. Giordano, F. Gliwny, P. Godinović, N. Gradetzke, T. Grau, R. Green, D. Green, J.G. Günther, P. Hadasch, D. Hahn, A. Hassan, T. Heckmann, L. Herrera, J. Hrupec, D. Hütten, M. Imazawa, R. Inada, T. Ishio, K. Jiménez Martínez, I. Jormanainen, J. Kerszberg, D. Kluge, G.W. Kobayashi, Y. Kouch, P.M. Kubo, H. Kushida, J. Láinez Lezáun, M. Lamastra, A. Leone, F. Lindfors, E. Linhoff, L. Lombardi, S. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Loporchio, S. Lorini, A. Machado de Oliveira Fraga, B. Majumdar, P. Makariev, M. Maneva, G. Mang, N. Manganaro, M. Mangano, S. Mannheim, K. Mariotti, M. Martínez, M. Martínez-Chicharro, M. Mas-Aguilar, A. Mazin, D. Menchiari, S. Mender, S. Miceli, D. Miener, T. Miranda, J.M. Mirzoyan, R. Molero González, M. Molina, E. Mondal, H.A. Moralejo, A. Morcuende, D. Nakamori, T. Nanci, C. Nava, L. Neustroev, V. Nickel, L. Nievas Rosillo, M. Nigro, C. Nikolić, L. Nilsson, K. Nishijima, K. Njoh Ekoume, T. Noda, K. Nozaki, S. The University of Tokyo Chiba Kashiwa277-8582 Japan ETH Zürich ZürichCH-8093 Switzerland Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna Tenerife La LagunaE-38200 Spain Instituto de Astrofísica de Andalucía CSIC Glorieta de la As-tronomía s/n Granada18008 Spain RomeI-00136 Italy Università di Udine INFN Trieste UdineI-33100 Italy Max-Planck-Institut für Physik MünchenD-80805 Germany Università di Padova INFN PadovaI-35131 Italy Bellaterra BarcelonaE-08193 Spain Zagreb10000 Croatia IPARCOS Institute EMFTEL Department Universidad Com-plutense de Madrid MadridE-28040 Spain URCA RJ Rio de Janeiro22290-180 Brazil University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz90-236 Poland Centro de Investigaciones Energéticas Medioambientales y Tecnológicas MadridE-28040 Spain Departament de Física CERES IEEC Universitat Autònoma de Barcelona BellaterraE-08193 Spain Università di Pisa INFN Pisa PisaI-56126 Italy Universitat de Barcelona ICCUB IEEC-UB BarcelonaE-08028 Spain Department for Physics and Technology University of Bergen Norway INFN MAGIC Group INFN Sezione di Torino Università degli Studi di Torino TorinoI-10125 Italy INFN MAGIC Group INFN Sezione di Catania Dipartimento di Fisica e Astronomia University of Catania CataniaI-95123 Italy INFN MAGIC Group INFN Sezione di Bari Dipartimento In-terateneo di Fisica Università e del Politecnico di Bari BariI-70125 Italy Croatian MAGIC Group University of Rijeka Faculty of Physics Rijeka51000 Croatia Technische Universität Dortmund DortmundD-44221 Germany University of Geneva Chemin d'Ecogia 16 VersoixCH-1290 Switzerland Japanese MAGIC Group: Physics Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima739-8526 Japan ZeuthenD-15738 Germany Armenian MAGIC Group: ICRANet-Armenia Yerevan0019 Armenia Split21000 Croatia Universität Würzburg Würzb

Aims. We perform the first broadband study of Mrk 421 from radio to TeV gamma rays with simultaneous measurements of the X-ray polarization from IXPE. Methods. The data were collected within an extensive multiwavelength campaign organized between May and June 2022 using MAGIC, FermiLAT, NuSTAR, XMM-Newton, Swift, and several optical and radio telescopes to complement IXPE. Results. During the IXPE exposures, the measured 0.2-1 TeV flux is close to the quiescent state and ranges from 25% to 50% of the Crab Nebula without intra-night variability. Throughout the campaign, the VHE and X-ray emission are positively correlated at a 4σ significance level. The IXPE measurements unveil a X-ray polarization degree that is a factor of 2-5 higher than in the optical/radio bands;that implies an energy-stratified jet in which the VHE photons are emitted co-spatially with the X-rays, in the vicinity of a shock front. The June 2022 observations exhibit a rotation of the X-ray polarization angle. Despite no simultaneous VHE coverage being available during a large fraction of the swing, the Swift-XRT monitoring unveils an X-ray flux increase with a clear spectral hardening. It suggests that flares in high synchrotron peaked blazars can be accompanied by a polarization angle rotation, as observed in some flat spectrum radio quasars. Finally, during the polarization angle rotation, NuSTAR data reveal two contiguous spectral hysteresis loops in opposite directions (clockwise and counter-clockwise), implying important changes in the particle acceleration efficiency on ∼hour timescales. Copyright © 2023, The Authors. All rights reserved.

关键词： Gamma rays

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Author Correction: Genetic effects on the timing of parturition and links to fetal birth weight

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Nature genetics 2023年第7期55卷 1250页

作者： Pol Solé-Navais Christopher Flatley Valgerdur Steinthorsdottir Marc Vaudel Julius Juodakis Jing Chen Triin Laisk Abigail L LaBella David Westergaard Jonas Bacelis Ben Brumpton Line Skotte Maria C Borges Øyvind Helgeland Anubha Mahajan Matthias Wielscher Frederick Lin Catherine Briggs Carol A Wang Gunn-Helen Moen Robin N Beaumont Jonathan P Bradfield Abin Abraham Gudmar Thorleifsson Maiken E Gabrielsen Sisse R Ostrowski Dominika Modzelewska Ellen A Nohr Elina Hypponen Amit Srivastava Octavious Talbot Catherine Allard Scott M Williams Ramkumar Menon Beverley M Shields Gardar Sveinbjornsson Huan Xu Mads Melbye William Lowe Luigi Bouchard Emily Oken Ole B Pedersen Daniel F Gudbjartsson Christian Erikstrup Erik Sørensen Rolv T Lie Kari Teramo Mikko Hallman Thorhildur Juliusdottir Hakon Hakonarson Henrik Ullum Andrew T Hattersley Line Sletner Mario Merialdi Sheryl L Rifas-Shiman Thora Steingrimsdottir Denise Scholtens Christine Power Jane West Mette Nyegaard John A Capra Anne H Skogholt Per Magnus Ole A Andreassen Unnur Thorsteinsdottir Struan F A Grant Elisabeth Qvigstad Craig E Pennell Marie-France Hivert Geoffrey M Hayes Marjo-Riitta Jarvelin Mark I McCarthy Deborah A Lawlor Henriette S Nielsen Reedik Mägi Antonis Rokas Kristian Hveem Kari Stefansson Bjarke Feenstra Pål Njolstad Louis J Muglia Rachel M Freathy Stefan Johansson Ge Zhang Bo Jacobsson Department of Obstetrics and Gynaecology Sahlgrenska Academy Institute of Clinical Science University of Gothenburg Gothenburg Sweden. pol.sole.navais@gu.se. Department of Obstetrics and Gynaecology Sahlgrenska Academy Institute of Clinical Science University of Gothenburg Gothenburg Sweden. deCODE genetics/Amgen Reykjavik Iceland. Center for Diabetes Research Department of Clinical Science University of Bergen Bergen Norway. Division of Biomedical Informatics Cincinnati Children's Hospital Medical Center Cincinnati OH USA. Department of Pediatrics University of Cincinnati College of Medicine Cincinnati OH USA. Estonian Genome Centre Institute of Genomics University of Tartu Tartu Estonia. Department of Biological Sciences Vanderbilt University Nashville TN USA. Novo Nordisk Foundation Center for Protein Research University of Copenhagen Copenhagen Denmark. Department of Obstetrics and Gynaecology Copenhagen University Hospital Hvidovre Hvidovre Denmark. Methods and Analysis Statistics Denmark Copenhagen Denmark. K.G. Jebsen Center for Genetic Epidemiology Department of Public Health and Nursing Norwegian University of Science and Technology Trondheim Norway. Department of Epidemiology Research Statens Serum Institut Copenhagen Denmark. MRC Integrative Epidemiology Unit University of Bristol Bristol UK. Population Health Sciences Bristol Medical School University of Bristol Bristol UK. Department of Genetics and Bioinformatics Health Data and Digitalization Norwegian Institute of Public Health Oslo Norway. Wellcome Trust Centre for Human Genetics University of Oxford Oxford UK. Genentech South San Francisco CA USA. Department of Epidemiology and Biostatistics MRC-PHE Centre for Environment and Health School of Public Health Imperial College London London UK. Department of Dermatology Medical University of Vienna Vienna Austria. Northwestern University Feinberg School of Medicine Chicago IL USA. Department of Population Medicine Harvard M

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Author Correction: Inferring structural variant cancer cell fraction

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Nature communications 2022年第1期13卷 7568页

作者： Marek Cmero Ke Yuan Cheng Soon Ong Jan Schröder Niall M Corcoran Tony Papenfuss Christopher M Hovens Florian Markowetz Geoff Macintyre Department of Surgery Division of Urology Royal Melbourne Hospital and University of Melbourne Parkville VIC 3050 Australia. cmerom@unimelb.edu.au. The Epworth Prostate Centre Epworth Hospital Richmond VIC 3121 Australia. cmerom@unimelb.edu.au. Department of Computing and Information Systems University of Melbourne Parkville VIC 3010 Australia. cmerom@unimelb.edu.au. Bioinformatics Division The Walter and Eliza Hall Institute of Medical Research Parkville VIC Australia. cmerom@unimelb.edu.au. Murdoch Children's Research Institute Parkville VIC 3052 Australia. cmerom@unimelb.edu.au. School of Computing Science University of Glasgow Sir Alwyn Williams Building Glasgow G12 8RZ UK. Cancer Research UK Cambridge Institute University of Cambridge Cambridge CB2 0RE UK. Electrical and Electronic Engineering University of Melbourne Parkville VIC 3010 Australia. Machine Learning Research Group Data61 Canberra ACT 2601 Australia. Research School of Computer Science Australian National University Canberra ACT 2601 Australia. Bioinformatics Division The Walter and Eliza Hall Institute of Medical Research Parkville VIC Australia. Department of Surgery Division of Urology Royal Melbourne Hospital and University of Melbourne Parkville VIC 3050 Australia. The Epworth Prostate Centre Epworth Hospital Richmond VIC 3121 Australia. Department of Computing and Information Systems University of Melbourne Parkville VIC 3010 Australia. geoff.macintyre@cruk.cam.ac.uk. Cancer Research UK Cambridge Institute University of Cambridge Cambridge CB2 0RE UK. geoff.macintyre@cruk.cam.ac.uk.

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Stochastic Proximal Gradient Consensus over Random Networks

Stochastic Proximal Gradient Consensus over Random Networks

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作者： Hong, Mingyi Chang, Tsung-Hui Department of Industrial and Manufacturing Systems Engineering Iowa State University AmesIA50021 United States School of Science and Engineering Chinese University of Hong Kong Shenzhen518172 China Shenzhen Research Institute of Big Data Shenzhen China

We consider solving a convex optimization problem with possibly stochastic gradient, and over a randomly time-varying multiagent network. Each agent has access to some local objective function, and it only has unbiased estimates of the gradients of the smooth component. We develop a dynamic stochastic proximal-gradient consensus algorithm, with the following key features: 1) it works for both the static and certain randomly time-varying networks;2) it allows the agents to utilize either the exact or stochastic gradient information;3) it is convergent with provable rate. In particular, the proposed algorithm converges to a global optimal solution, with a rate of \mathcal O(1/r) [resp. \mathcal O(1/r) when the exact (resp. stochastic) gradient is available, where r is the iteration counter. Interestingly, the developed algorithm establishes a close connection among a number of (seemingly unrelated) distributed algorithms, such as the EXTRA, the PG-EXTRA, the IC/IDC-ADMM, the DLM, and the classical distributed subgradient method. © 2017 IEEE.

关键词： Time varying networks

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Publisher Correction: An international perspective on the future of systemic sclerosis research

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Nature reviews. Rheumatology 2025年第4期21卷 249页

作者： David J Abraham Carol M Black Christopher P Denton Jörg H W Distler Robyn Domsic Carol Feghali-Bostwick Pravitt Gourh Monique Hinchcliff Fred Kolling Masataka Kuwana Robert Lafyatis Ulf Landegren J Matthew Mahoney Javier Martin Marco Matucci-Cerinic Zsuzsanna H McMahan Ana L Mora Luc Mouthon Marlene Rabinovitch Mauricio Rojas Kristofer Rubin Maria Trojanowska John Varga Michael L Whitfield Armando Gabrielli Thomas Krieg Department of Inflammation and Rare Diseases UCL Centre for Rheumatology UCL Division of Medicine Royal Free Hospital Campus London UK. david.abraham@ucl.ac.uk. Department of Inflammation and Rare Diseases UCL Centre for Rheumatology UCL Division of Medicine Royal Free Hospital Campus London UK. Department of Rheumatology University Hospital Düsseldorf Medical Faculty of the Heinrich-Heine University Düsseldorf Germany. Hiller Research Center University Hospital Düsseldorf Medical Faculty of Heinrich Heine University Düsseldorf Germany. Division of Rheumatology Department of Internal Medicine University of Pittsburgh Pittsburgh PA USA. Department of Medicine Division of Rheumatology and Immunology Medical University of South Carolina Charleston SC USA. Scleroderma Genomics and Health Disparities Unit National Institute of Arthritis and Musculoskeletal and Skin Diseases National Institutes of Health Bethesda MD USA. Division of Rheumatology Allergy and Immunology Department of Internal Medicine Yale School of Medicine New Haven CT USA. Geisel School of Medicine at Dartmouth Hanover NH USA. Department of Allergy and Rheumatology. Nippon Medical School Graduate School of Medicine Tokyo Japan. Division of Rheumatology and Clinical Immunology. University of Pittsburgh School of Medicine Pittsburgh PA USA. Department of Immunology Genetics and Pathology Research programme: Molecular Tools and Functional Genomics Uppsala University Uppsala Sweden. The Jackson Laboratory Bar Harbour ME USA. Department of Cell Biology and Immunology Institute of Parasitology and Biomedicine López-Neyra CSIC Granada Spain. Unit of Immunology Rheumatology Allergy and Rare Diseases and Inflammation fibrosis and aging Initiative IRCCS Ospedle San Raffaele and Vita Salute University San Raffaele Milan Italy. Department of Internal Medicine Division of Rheumatology UTHealth Houston Houston TX USA. Division of Pulmonary Critical Care and Sleep Medicine Davis Heart and Lung r

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