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arXiv 2021年

作者： Lee, Benjamin D. Gitter, Anthony Greene, Casey S. Raschka, Sebastian Maguire, Finlay Titus, Alexander J. Kessler, Michael D. Lee, Alexandra J. Chevrette, Marc G. Stewart, Paul Allen Britto-Borges, Thiago Cofer, Evan M. Yu, Kun-Hsing Carmona, Juan Jose Fertig, Elana J. Kalinin, Alexandr A. Signal, Beth Lengerich, Benjamin J. Triche, Timothy J. Boca, Simina M. In-Q-Tel Labs School of Engineering and Applied Sciences Harvard University Department of Genetics Harvard Medical School United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison MadisonWI United States Morgridge Institute for Research MadisonWI United States Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine AuroraCO United States Center for Health AI University of Colorado School of Medicine AuroraCO United States Department of Statistics University of Wisconsin Madison United States Faculty of Computer Science Dalhousie University Canada University of New Hampshire Bioeconomy.XYZ United States Department of Oncology Johns Hopkins University United States Institute for Genome Sciences University of Maryland School of Medicine United States Genomics and Computational Biology Graduate Program University of Pennsylvania United States Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania United States Wisconsin Institute for Discovery Department of Plant Pathology University of Wisconsin-Madison United States Department of Biostatistics and Bioinformatics Moffitt Cancer Center TampaFL United States Section of Bioinformatics and Systems Cardiology Klaus Tschira Institute for Integrative Computational Cardiology University Hospital Heidelberg Germany University Hospital Heidelberg Germany Lewis-Sigler Institute for Integrative Genomics Princeton University PrincetonNJ United States Graduate Program in Quantitative and Computational Biology Princeton University PrincetonNJ United States Department of Biomedical Informatics Harvard Medical School United States Department of Pathology Brigham and Women's Hospital United States Philips Healthcare CambridgeMA United States Philips Research

Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling. Artificial neural networks are a particular class of machine learning algorithms and models that evolved into what is now described as deep learning. Given the computational advances made in the last decade, deep learning can now be applied to massive data sets and in innumerable contexts. Therefore, deep learning has become its own subfield of machine learning. In the context of biological research, it has been increasingly used to derive novel insights from high-dimensional biological data. To make the biological applications of deep learning more accessible to scientists who have some experience with machine learning, we solicited input from a community of researchers with varied biological and deep learning interests. These individuals collaboratively contributed to this manuscript's writing using the GitHub version control platform and the Manubot manuscript generation toolset. The goal was to articulate a practical, accessible, and concise set of guidelines and suggestions to follow when using deep learning. In the course of our discussions, several themes became clear: the importance of understanding and applying machine learning fundamentals as a baseline for utilizing deep learning, the necessity for extensive model comparisons with careful evaluation, and the need for critical thought in interpreting results generated by deep learning, among others. © 2021, CC BY.

关键词： Learning algorithms

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Publisher Correction: Global estimates on the number of people blind or visually impaired by cataract: a meta-analysis from 2000 to 2020

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Eye (London, England) 2024年第11期38卷 2229-2231页

作者： Konrad Pesudovs Hugh R. Taylor Tabassom Sedighi Rupert R. A. Bourne Shahina Pardhan Van Charles Lansingh John H. Kempen Ian Tapply Arthur G. Fernandes Maria Vittoria Cicinelli Alessandro Arrigo Nicolas Leveziel Serge Resnikoff Seth Flaxman Mukkharram M. Bikbov Tasanee Braithwaite Alain Bron Ching-Yu Cheng Monte A. Del Monte Joshua R. Ehrlich Leon B. Ellwein David Friedman João M. Furtado Gus Gazzard Ronnie George M. Elizabeth Hartnett Jost B. Jonas Rim Kahloun Moncef Khairallah Rohit C. Khanna Janet Leasher Julie-Anne Little Vinay Nangia Michal Nowak Tunde Peto Pradeep Ramulu Fotis Topouzis Mitiadis Tsilimbaris Ya Xing Wang Ningli Wang Paul Svitil Briant Theo Vos Katrin Burkart Kaleb Coberly Xiaochen Dai Stephen S. Lim Tomislav Mestrovic Ali H. Mokdad Christopher J. L. Murray Jaimie D. Steinmetz Awoke Misganaw Yohannes Habtegiorgis Abate Mohammad Abdollahi Mozhan Abdollahi Ayele Mamo Abebe Olumide Abiodun Richard Gyan Aboagye Woldu Aberhe Abrha Hasan Abualruz Hiwa Abubaker Ali Eman Abu-Gharbieh Salahdein Aburuz Tadele Girum Girum Adal Mesafint Molla Adane Isaac Yeboah Addo Qorinah Estiningtyas Sakilah Adnani Muhammad Sohail Afzal Muhammad Umair Shahin Aghamiri Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Ali Ahmadi Siamak Sabour Ayman Ahmed Haroon Ahmed Ahmad Samir Alfaar Abid Ali Syed Shujait Shujait Ali Awais Altaf Hubert Amu Emmanuel Manu Sofia Androudi Rodrigo Anguita Abhishek Anil Rimple Jeet Kaur Muhammad Aaqib Shamim Saeid Anvari Anayochukwu Edward Anyasodor Francis Appiah Jalal Arabloo Haleh Ayatollahi Mosab Arafat Damelash Areda Reza Arefnezhad Brhane Berhe Aregawi Akeza Awealom Asgedom Tahira Ashraf Seyyed Shamsadin Athari Bantalem Tilaye Tilaye Atinafu Birhan Tsegaw Taye Maha Moh’d Wahbi Atout Alok Atreya Ahmed Y. Azzam Hassan Babamohamadi Sara Bagherieh Yogesh Bahurupi Atif Amin Baig Shumaila Nargus Biswajit Banik Mainak Bardhan Saurav Basu Kavita Batra Nebiyou Simegnew Bayileyegn Fatemeh Bazvand Addisu Shunu Beyene Awoke Masrie Asrat Derese Devidas S. Bhagat Akshaya Srikanth Bhagavathula Pankaj Bh Medicine & Health University of New South Wales Sydney NSW Australia School of Optometry and Vision Science University of New South Wales Sydney NSW Australia School of Population and Global Health University of Melbourne Carlton VIC Australia Vision and Eye Research Institute Anglia Ruskin University Cambridge UK HelpMeSee Instituto Mexicano de Oftalmologia Santiago de Querétaro Mexico University of Miami Gables FL USA University of Utah Salt Lake City UT USA Chief Medical Office HelpMeSee New York NY USA Mexican Institute of Ophthalmology Queretaro Mexico Department of Ophthalmology Massachusetts Eye and Ear/Shepens Eye Research Institute/Harvard Medical School Boston MA USA Eye Unit MyungSung Christian Medical Center (MCM) Comprehensive Specialized Hospital and MyungSun Medical College Addis Ababa Ethiopia Department of Ophthalmology Addis Ababa University Addis Ababa Ethiopia Sight for Souls Bellevue WA USA Department of Ophthalmology Harvard University Boston MA USA Eye Unit MyungSung Medical College Addis Ababa Ethiopia Addenbrooke’s Hospital Cambridge UK Department of Ophthalmology Cambridge University Hospitals Cambridge UK Federal University of Sao Paolo Sao Paolo SP Brazil University of Calgary Calgary AB Canada Department of Ophthalmology and Visual Sciences Federal University of São Paulo Sao Paulo Brazil School of Medicine Vita-Salute San Raffaele University Milan Italy Department of Ophthalmology IRCCS San Raffaele Scientific Institute Milan Italy Department of Ophthalmology San Raffaele Scientific Institute Milano Italy IRCCS San Raffaele Scientific Institute Vita-Salute University Milan Italy Scientific Institute San Raffaele Hospital Vita-Salute University Milan Italy University of Poitiers Poitiers France CHU de Poitiers Poitiers France Ophthalmology Department CHU de Poitiers (Poitiers University Hospital) Poitiers France Unité 1084 National Institute of Health and Medical Research (INSERM) Poitiers France

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Measurement of Ξcc++ production in pp collisions at s1/2=13 TeV

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Chinese Physics C 2020年第2期44卷 13-23页

作者： R.Aaij C.Abellán Beteta T.Ackernley B.Adeva M.Adinolfi H.Afsharnia C.A.Aidala S.Aiola Z.Ajaltouni S.Akar P.Albicocco J.Albrecht F.Alessio M.Alexander A.Alfonso Albero G.Alkhazov P.Alvarez Cartelle A.A.Alves Jr S.Amato Y.Amhis L.An L.Anderlini G.Andreassi M.Andreotti F.Archilli A.Artamonov M.Artuso K.Arzymatov E.Aslanides M.Atzeni B.Audurier S.Bachmann J.J.Back S.Baker V.Balagura W.Baldini A.Baranov R.J.Barlow S.Barsuk W.Barter M.Bartolini F.Baryshnikov J.M.Basels G.Bassi V.Batozskaya B.Batsukh A.Battig A.Bay M.Becker F.Bedeschi I.Bediaga A.Beiter L.J.Bel V.Belavin S.Belin V.Bellee K.Belous I.Belyaev G.Bencivenni E.Ben-Haim S.Benson S.Beranek A.Berezhnoy *** D.Berninghoff H.C.Bernstein C.Bertella E.Bertholet A.Bertolin C.Betancourt F.Betti M.O.Bettler Ia.Bezshyiko S.Bhasin J.Bhom M.S.Bieker S.Bifani P.Billoir A.Bizzeti M.Bjørn M.P.Blago T.Blake F.Blanc S.Blusk D.Bobulska V.Bocci O.Boente Garcia T.Boettcher A.Boldyrev A.Bondar N.Bondar S.Borghi M.Borisyak M.Borsato J.T.Borsuk T.J.V.Bowcock C.Bozzi M.J.Bradley S.Braun A.Brea Rodriguez M.Brodski J.Brodzicka A.Brossa Gonzalo D.Brundu E.Buchanan A.Buonaura C.Burr A.Bursche A.Butkevich J.S.Butter J.Buytaert W.Byczynski S.Cadeddu H.Cai R.Calabrese L.Calero Diaz S.Cali R.Calladine M.Calvi M.Calvo Gomez P.Camargo Magalhaes A.Camboni P.Campana D.H.Campora Perez A.F.Campoverde Quezada L.Capriotti A.Carbone G.Carboni R.Cardinale A.Cardini I.Carli P.Carniti K.Carvalho Akiba A.Casais Vidal G.Casse M.Cattaneo G.Cavallero S.Celani R.Cenci J.Cerasoli M.G.Chapman M.Charles Ph.Charpentier G.Chatzikonstantinidis M.Chefdeville V.Chekalina C.Chen S.Chen A.Chernov S.-G.Chitic V.Chobanova S.Cholak M.Chrzaszcz A.Chubykin P.Ciambrone M.F.Cicala X.Cid Vidal G.Ciezarek F.Cindolo P.E.L.Clarke M.Clemencic H.V.Cliff J.Closier J.L.Cobbledick V.Coco J.A.B.Coelho J.Cogan E.Cogneras L.Cojocariu P.Collins T.Colombo A.Comerma-Montells A.Contu N.Cooke G.Coombs S.Coquereau G.Corti C.M.Costa Sobral B.Couturier D.C.Craik J.Crkovska A.Crocombe M.Cruz Torres R.Currie C.L.Da Silva E.Dall'Occo J.Dalseno C.D' Centro Brasileiro de Pesquisas Físicas(CBPF) Rio de JaneiroBrazil Universidade Federal do Rio de Janeiro(UFRJ) Rio de JaneiroBrazil Center for High Energy Physics Tsinghua UniversityBeijingChina School of Physics State Key Laboratory of Nuclear Physics and Technology Peking UniversityBeijingChina University of Chinese Academy of Sciences BeijingChina Institute Of High Energy Physics(IHEP) BeijingChina Institute of Particle Physics Central China Normal UniversityWuhanHubeiChina Univ.Grenoble Alpes Univ.Savoie Mont BlancCNRSIN2P3-LAPPAnnecyFrance UniversitéClermont Auvergne CNRS/IN2P3LPCClermont-FerrandFrance Aix Marseille Univ CNRS/IN2P3CPPMMarseilleFrance LAL Univ.Paris-SudCNRS/IN2P3UniversitéParis-SaclayOrsayFrance LPNHE Sorbonne UniversitéParis Diderot Sorbonne Paris CitéCNRS/IN2P3ParisFrance I.Physikalisches Institut RWTH Aachen UniversityAachenGermany Fakultät Physik Technische Universität DortmundDortmundGermany Max-Planck-Institut für Kernphysik(MPIK) HeidelbergGermany Physikalisches Institut Ruprecht-Karls-Universität HeidelbergHeidelbergGermany School of Physics University College DublinDublinIreland INFN Sezione di Bari BariItaly INFN Sezione di Bologna BolognaItaly INFN Sezione di Ferrara FerraraItaly INFN Sezione di Firenze FirenzeItaly INFN Laboratori Nazionali di Frascati FrascatiItaly INFN Sezione di Genova GenovaItaly INFN Sezione di Milano-Bicocca MilanoItaly INFN Sezione di Milano MilanoItaly INFN Sezione di Cagliari MonserratoItaly INFN Sezione di Padova PadovaItaly INFN Sezione di Pisa PisaItaly INFN Sezione di Roma Tor Vergata RomaItaly INFN Sezione di Roma La Sapienza RomaItaly Nikhef National Institute for Subatomic Physics AmsterdamNetherlands Nikhef National Institute for Subatomic Physics and VU University Amsterdam AmsterdamNetherlands Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences KrakówPoland AGH-University of Science and Technology Faculty of Physics and Applied Computer ScienceKrakówPoland Nationa

The production of ■baryons in proton-proton collisions at a centre-of-mass energy of √s = 13 TeV is measured in the transverse-momentum range 4<pT<15GeV/c and the rapidity range2.0<y<*** data used in thi... 详细信息

The production of ■baryons in proton-proton collisions at a centre-of-mass energy of √s = 13 TeV is measured in the transverse-momentum range 4data used in this measurement correspond to an integrated luminosity of 1.7fb^-1,recorded by the LHCb experiment during *** ratio of the ■ production cross-section times the branching fraction of the■→∧^+cK^-π^+ π^+decay relative to the prompt ∧^+c production cross-section is found to be(2.22±0.27±0.29)×10^-4,assuming the central value of the measured lifetime,where the first uncertainty is statistical and the second systematic.

关键词： doubly charmed baryons hadron production QCD

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Changing life expectancy in European countries 1990–2021: a subanalysis of causes and risk factors from the Global Burden of Disease Study 2021

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The Lancet Public Health 2025年第3期10卷 e172-e188页

作者： Steel, Nicholas Bauer-Staeb, Clarissa Maria Mercedes Ford, John A. Abbafati, Cristiana Abdalla, Mohammed Altigani Abdelkader, Atef Abdi, Parsa Zuñiga, Roberto Ariel Abeldaño Abiodun, Olugbenga Olusola Abolhassani, Hassan Abu-Gharbieh, Eman Abukhadijah, Hana J. Abu-Zaid, Ahmed Addo, Isaac Yeboah Addolorato, Giovanni Adekanmbi, Victor Adetunji, Juliana Bunmi Adeyeoluwa, Temitayo Esther Agardh, Emilie E. Agyemang-Duah, Williams Ahmad, Danish Ahmed, Ayman Ahmed, Syed Anees Akinosoglou, Karolina Akkaif, Mohammed Ahmed Al Awaidy, Salah Al Hasan, Syed Mahfuz Al Zaabi, Omar Ali Mohammed Aldridge, Robert W. Algammal, Abdelazeem M. Al-Gheethi, Adel Ali Saeed Ali, Abid Ali, Mohammed Usman Ali, Syed Shujait Ali, Waad Alicandro, Gianfranco Alif, Sheikh Mohammad Al-Jumaily, Adel Allebeck, Peter Alrawashdeh, Ahmad Al-Rifai, Rami H. Alsabri, Mohammed A. Alshahrani, Najim Z. Aluh, Deborah Oyine Al-Wardat, Mohammad Al-Zyoud, Walid A. Amiri, Sohrab Anderlini, Deanna Andrei, Catalina Liliana Anil, Abhishek Anvari, Saeid Anyasodor, Anayochukwu Edward Appiah, Seth Christopher Yaw Aquilano, Michele Arabloo, Jalal Arafat, Mosab Areda, Demelash Aremu, Abdulfatai Armani, Keivan Armocida, Benedetta Ärnlöv, Johan Asaduzzaman, Muhammad Astell-Burt, Thomas Aujayeb, Avinash Ausloos, Marcel Azadnajafabad, Sina Aziz, Shahkaar Azzam, Ahmed Y. Babu, Giridhara Rathnaiah Badache, Andreea Corina Badiye, Ashish D. Bahramian, Saeed Baig, Atif Amin Baker, Jennifer L. Bansal, Hansi Bärnighausen, Till Winfried Barone, Mark Thomaz Ugliara Barrow, Amadou Barteit, Sandra Bashir, Shahid Bashiru, Hameed Akande Basso, João Diogo Bastan, Mohammad-Mahdi Basu, Sanjay Batra, Kavita Bauckneht, Matteo Baune, Bernhard T. Beghi, Massimiliano Beiranvand, Maryam Béjot, Yannick Bell, Michelle L. Bello, Olorunjuwon Omolaja Belo, Luis Beloukas, Apostolos Beneke, Alice A. Bettencourt, Paulo J.G. Bhagavathula, Akshaya Srikanth Bhala, Neeraj Bhaskar, Sonu Bisulli, Francesca Bjørge, Tone Bodunrin, Aadam Olalekan Carvajal, Alejandro Botero Bouaoud, Souad Brayne, Carol Brenner, H Department of Primary Care and Public Health University of East Anglia Norwich United Kingdom Office for Health Improvement and Disparities Department of Health and Social Care London United Kingdom Department of Legal and Economic Studies La Sapienza University Rome Italy Rome Italy Hull York Medical School University of Hull Hull United Kingdom Department of Mathematics and Sciences Ajman University Ajman United Arab Emirates Department of Medicine Memorial University St. John's NL Canada Postgraduate Department University of Sierra Sur Miahuatlan de Porfirio Diaz Mexico Yhteiskuntadatatieteen keskus (Centre for Social Data Science) Helsinki Finland Department of Internal Medicine Federal Medical Centre Abuja Nigeria Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Medical Biochemistry and Biophysics Karolinska Institutet (Karolinska Institute) Stockholm Sweden Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Department of Biopharmaceutics and Clinical Pharmacy University of Jordan Amman Jordan Medical Research Center Hamad Medical Corporation Doha Qatar Department of Biochemistry and Molecular Medicine Alfaisal University Riyadh Saudi Arabia College of Graduate Health Sciences University of Tennessee Memphis TN United States School of Medicine Sydney NSW Australia Centre for Social Research in Health University of New South Wales Sydney NSW Australia Internal Medicine and Alcohol Related Disease Unit Fondazione Policlinico Universitario A. Gemelli IRCCS Rome Italy Department of Medical and Surgical Sciences Università Cattolica di Roma (Catholic University of Rome) Rome Italy Department of Obstetrics and Gynecology University of Texas Medical Branch Galveston TX United States Department of Biochemistry Osun State University Osogbo Nigeria Department of Pharmacology and Therapeutics University of Medical Sciences Ondo Ondo Nigeria Department of Veteri

Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factors and cause-specific death rates in different European countries related to changes in life expectancy in those countries before and during the COVID-19 pandemic. Methods: We used data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to compare changes in life expectancy at birth, causes of death, and population exposure to risk factors in 16 European Economic Area countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, and Sweden) and the four UK nations (England, Northern Ireland, Scotland, and Wales) for three time periods: 1990–2011, 2011–19, and 2019–21. Changes in life expectancy and causes of death were estimated with an established life expectancy cause-specific decomposition method, and compared with summary exposure values of risk factors for the major causes of death influencing life expectancy. Findings: All countries showed mean annual improvements in life expectancy in both 1990–2011 (overall mean 0·23 years [95% uncertainty interval [UI] 0·23 to 0·24]) and 2011–19 (overall mean 0·15 years [0·13 to 0·16]). The rate of improvement was lower in 2011–19 than in 1990–2011 in all countries except for Norway, where the mean annual increase in life expectancy rose from 0·21 years (95% UI 0·20 to 0·22) in 1990–2011 to 0·23 years (0·21 to 0·26) in 2011–19 (difference of 0·03 years). In other countries, the difference in mean annual improvement between these periods ranged from –0·01 years in Iceland (0·19 years [95% UI 0·16 to 0·21] vs 0·18 years [0·09 to 0·26]), to –0·18 years in England (0·25 years [0·24 to 0·25] vs 0·07 years [0·06 to 0·08]). In 2019–21, there was an overall decrease in mean annual life expectancy a

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Interoperability and security challenges of Industrie 4.0 47

Interoperability and security challenges of Industrie 4.0

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47. Jahrestagung der Gesellschaft fur Informatik, Informatik 2017 - 47th Annual Meeting of the German Informatics Society (GI), Informatics 2017

作者： Watson, Venesa Tellabi, Asmaa Sassmannshausen, Jochen Lou, Xinxin University of Siegen Faculty of Science and Engineering Chair for Data Communication Systems Hölderlinstraße 3 Siegen57068 Germany Bielefeld University Department of Computer Networks and Distributed Systems Universitätsstraße 25 Bielefeld33615 Germany

ISBN: (纸本)9783885796695

Industrie 4.0 (I4.0) is the fourth industrial revolution, which will see the digital transformation of manufacturing, through the integration on Industrial Internet of Things (IIoT), data and Services, and the convergence of Information Technology (IT) and Operational Technology (OT). With any such transformation, there exists challenges that must first be addressed for a successful outcome. For I4.0, these are interoperability and security, which respectively arise from the interconnection of devices from different manufacturers and/or with different communication protocols;and the interconnection of networks with competing critical and non-critical traffic, and the increased access to initially isolated networks. This paper presents an overview of standards, such as IEC 62443, the ISO 27000 series, IEC 62541 Open Connectivity Unified Architecture (OPC UA) and Time Sensitive Networks (TSN) (IEEE 1722-2016), which addresses these challenges. © 2017 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Interoperability

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Benchmarking solutions to the T-cell receptor epitope prediction problem: IMMREP22 workshop report

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ImmunoInformatics 2023年 9卷

作者： Pieter Meysman Justin Barton Barbara Bravi Liel Cohen-Lavi Vadim Karnaukhov Elias Lilleskov Alessandro Montemurro Morten Nielsen Thierry Mora Paul Pereira Anna Postovskaya María Rodríguez Martínez Jorge Fernandez-de-Cossio-Diaz Alexandra Vujkovic Aleksandra M. Walczak Anna Weber Rose Yin Anne Eugster Virag Sharma AUDACIS University of Antwerp Antwerp Belgium ADREM data lab Department of Computer Science University of Antwerp Antwerp Belgium Institute of Structural and Molecular Biology University of London London United Kingdom Department of Mathematics Imperial College London London United Kingdom National Institute for Biotechnology in the Negev Ben-Gurion University of the Negev Beer-Sheva Israel Department of Industrial Engineering and Management Ben-Gurion University of the Negev Beer-Sheva Israel INSERM U932 PSL University Institut Curie Paris 75005 France Laboratoire de physique de l'Ecole normale superieure CNRS PSL University Sorbonne Universite Universite Paris-Cité Paris 75005 France Department of Physics University of Washington Seattle WA USA Department of Health Technology Technical University of Denmark Lyngby DK-2800 Denmark Sanofi R&D Chilly-Mazarin 91380 France Clinical Virology Unit Institute of Tropical Medicine Antwerp Belgium IBM Research Europe Säumerstrasse 4 Rüschlikon 8803 Switzerland Department of Chemical Engineering Massachusetts Institute of Technology Cambridge Massachusetts USA Center for Regenerative Therapies Dresden Faculty of Medicine TU Dresden Dresden Germany Department of Chemical Sciences School of Natural Sciences University of Limerick Limerick V94 T9PX Ireland

Many different solutions to predicting the cognate epitope target of a T-cell receptor (TCR) have been proposed. However several questions on the advantages and disadvantages of these different approaches remain unresolved, as most methods have only been evaluated within the context of their initial publications and data sets. Here, we report the findings of the first public TCR-epitope prediction benchmark performed on 23 prediction models in the context of the ImmRep 2022 TCR-epitope specificity workshop. This benchmark revealed that the use of paired-chain alpha-beta, as well as CDR1/2 or V/J information, when available, improves classification obtained with CDR3 data, independent of the underlying approach. In addition, we found that straight-forward distance-based approaches can achieve a respectable performance when compared to more complex machine-learning models. Finally, we highlight the need for a truly independent follow-up benchmark and provide recommendations for the design of such a next benchmark.

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An Energy-Efficient VM Consolidation Algorithm for Cloud data Centers

An Energy-Efficient VM Consolidation Algorithm for Cloud Dat...

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ISCC 2017-the 5th International Conference on Information science and Cloud Computing

作者： Xiaodong Wu Faculty of Mathematics and Computer Science Quanzhou Normal University Fujian Provincial Key Laboratory of Data Intensive Computing

Cloud data centers consume vast amounts of electrical energy all over the world. Energy conservation in data centers has become a severe problem. This paper presents an energyefficient virtual machine（VM） consolidation algorithm for cloud data centers. The proposed policy exploits the average utilization of each VM to estimate the expected utilization of physical hosts. Then, the expected utilization, the actual utilization and the static threshold are combined together to determine whether a host is at the status of overloading or not. Some VM（s） on the overloading hosts are then selected for migration to avoid Service Level Agreements（SLA） violations. The results of the experiment show that the proposed algorithm can effectively reduce energy consumption while guarantee SLAs.

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The construction of winter wheat smart water saving irrigation system based on big data and internet of things

The construction of winter wheat smart water saving irrigati...

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International Journal of High Performance Systems Architecture

作者： Zhang, Peng Zhang, Qian Liu, Fusheng Cao, Ning Song, Changqing Li, Junqing Liu, Yanmin Yang, Cuinan Higgs, Russell O'hare, Gregory M.P. Xu, Lina College of Water Conservancy and Civil Engineering Shandong Agricultural University Taian China College of Information Engineering Qingdao Binhai University Qingdao China Agricultural Big Data Centre Shandong Agricultural University Taian China Faculty of Computer Science Dalhousie University HalifaxNS Canada School of Mathematics and Statistics University College Dublin Ireland School of Computer Science University College Dublin Ireland

The advent of emerging big data and internet of things, a large number of agriculture data such as the seeding condition, soil moisture, fertiliser, water, pests and meteorology, which could be effectively analysed to guide the smart agriculture. In this paper, the winter wheat smart water saving irrigation system is established based on technologies including big data and internet of things. Through the automatic monitor system of winter wheat growing environment, the big data centre intelligently stores, screens, calibrates, mines and extracts the monitoring data, a system of winter wheat irrigation and fertilisation decision-making based on big data was built. According to the testing data and the weather forecast data, this system can forecast the water requirement of winter wheat in different growth periods and make decisions on automatic irrigation and fertilisation, leading to the timely and proper irrigation of crops. Copyright © 2017 Inderscience Enterprises Ltd.

关键词： Big data Crops data mining Decision making Internet of things Irrigation Monitoring Seed Soil moisture Water conservation Weather forecasting Agriculture data Automatic irrigation Automatic monitors Growing environments High performance systems Smart agricultures Water requirements Water saving irrigation

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Measurements of ψ(2S) and χc1(3872) production within fully reconstructed jets

arXiv

引用

arXiv 2024年

作者： Aaij, R. Abdelmotteleb, A.S.W. Abellán Beteta, C. Abudinen Gallego, F.J. Ackernley, T. Adeva, B. Adinolfi, M. Afsharnia, H. Agapopoulou, C. Aidala, C.A. Aiola, S. Ajaltouni, Z. Akar, S. Albrecht, J. Alessio, F. Alexander, M. Alfonso Albero, A. Aliouche, Z. Alkhazov, G. Alvarez Cartelle, P. Amato, S. Amey, J.L. Amhis, Y. An, L. Anderlini, L. Andreianov, A. Andreotti, M. Archilli, F. Artamonov, A. Artuso, M. Arzymatov, K. Aslanides, E. Atzeni, M. Audurier, B. Bachmann, S. Bachmayer, M. Back, J.J. Baladron Rodriguez, P. Balagura, V. Baldini, W. Baptista Leite, J. Barbetti, M. Barlow, R.J. Barsuk, S. Barter, W. Bartolini, M. Baryshnikov, F. Basels, J.M. Bashir, S. Bassi, G. Batsukh, B. Battig, A. Bay, A. Beck, A. Becker, M. Bedeschi, F. Bediaga, I. Beiter, A. Belavin, V. Belin, S. Bellee, V. Belous, K. Belov, I. Belyaev, I. Bencivenni, G. Ben-Haim, E. Berezhnoy, A. Bernet, R. Berninghoff, D. Bernstein, H.C. Bertella, C. Bertolin, A. Betancourt, C. Betti, F. Bezshyiko, Ia. Bhasin, S. Bhom, J. Bian, L. Bieker, M.S. Bifani, S. Billoir, P. Birch, M. Bishop, F.C.R. Bitadze, A. Bizzeti, A. Bjørn, M. Blago, M.P. Blake, T. Blanc, F. Blusk, S. Bobulska, D. Boelhauve, J.A. Boente Garcia, O. Boettcher, T. Boldyrev, A. Bondar, A. Bondar, N. Borghi, S. Borisyak, M. Borsato, M. Borsuk, J.T. Bouchiba, S.A. Bowcock, T.J.V. Boyer, A. Bozzi, C. Bradley, M.J. Braun, S. Brea Rodriguez, A. Brodzicka, J. Brossa Gonzalo, A. Brundu, D. Buonaura, A. Buonincontri, L. Burke, A.T. Burr, C. Bursche, A. Butkevich, A. Butter, J.S. Buytaert, J. Byczynski, W. Cadeddu, S. Cai, H. Calabrese, R. Calefice, L. Calero Diaz, L. Cali, S. Calladine, R. Calvi, M. Calvo Gomez, M. Camargo Magalhaes, P. Campana, P. Campoverde Quezada, A.F. Capelli, S. Capriotti, L. Carbone, A. Carboni, G. Cardinale, R. Cardini, A. Carli, I. Carniti, P. Carus, L. Carvalho Akiba, K. Casais Vidal, A. Casse, G. Cattaneo, M. Cavallero, G. Celani, S. Cerasoli, J. Cervenkov, D. Chadwick, A.J. Chapman, M.G. Charles, M. Rio de Janeiro Brazil Rio de Janeiro Brazil Center for High Energy Physics Tsinghua University Beijing China Beijing China School of Physics State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China University of Chinese Academy of Sciences Beijing China Institute of Particle Physics Central China Normal University Hubei Wuhan China Univ. Savoie Mont Blanc CNRS IN2P3-LAPP Annecy France Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS/IN2P3 Paris France I. Physikalisches Institut RWTH Aachen University Aachen Germany Fakultät Physik Technische Universität Dortmund Dortmund Germany Heidelberg Germany Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany School of Physics University College Dublin Dublin Ireland INFN Sezione di Bari Bari Italy INFN Sezione di Bologna Bologna Italy INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Firenze Firenze Italy INFN Laboratori Nazionali di Frascati Frascati Italy INFN Sezione di Genova Genova Italy INFN Sezione di Milano Milano Italy INFN Sezione di Milano-Bicocca Milano Italy INFN Sezione di Cagliari Monserrato Italy Universita degli Studi di Padova Universita e INFN Padova Padova Italy INFN Sezione di Pisa Pisa Italy INFN Sezione di Roma La Sapienza Roma Italy INFN Sezione di Roma Tor Vergata Roma Italy Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Nikhef National Institute for Subatomic Physics VU University Amsterdam Amsterdam Netherlands AGH University of Science and Technology Faculty of Physics and Applied Computer Science Kraków Poland Henryk Niewodniczanski Institute of Nuclear Physics Polish

This paper presents the first measurement of ψ(2S) and χc1(3872) meson production within fully reconstructed jets. Each quarkonium state (tag) is reconstructed via its decay to the J/ψ(→µ+µ−)π+π− final state in the forward region using proton-proton collision data collected by the LHCb experiment at the center-of-mass-energy of 13 TeV in 2016, corresponding to an integrated luminosity of 1.64 fb−1. The fragmentation function, presented as the ratio of the quarkonium-tag transverse momentum to the full jet transverse momentum (pT(tag)/pT(jet)), is measured differentially in pT(jet) and pT(tag) bins. The distributions are separated into promptly produced quarkonia from proton-proton collisions and quarkonia produced from displaced b-hadron decays. While the displaced quarkonia fragmentation functions are in general well described by parton-shower predictions, the prompt quarkonium distributions differ significantly from fixed-order non-relativistic QCD (NRQCD) predictions followed by a QCD parton shower. © 2024, CC BY.

关键词： Bosons

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Amplitude analysis of the radiative decay Bs0 → K+K−γ

arXiv

引用

arXiv 2024年

作者： Aaij, R. Abdelmotteleb, A.S.W. Abellán Beteta, C. Abudinen Gallego, F.J. Ackernley, T. Adeva, B. Adinolfi, M. Afsharnia, H. Agapopoulou, C. Aidala, C.A. Aiola, S. Ajaltouni, Z. Akar, S. Albrecht, J. Alessio, F. Alexander, M. Alfonso Albero, A. Aliouche, Z. Alkhazov, G. Alvarez Cartelle, P. Amato, S. Amey, J.L. Amhis, Y. An, L. Anderlini, L. Andreianov, A. Andreotti, M. Archilli, F. Artamonov, A. Artuso, M. Arzymatov, K. Aslanides, E. Atzeni, M. Audurier, B. Bachmann, S. Bachmayer, M. Back, J.J. Baladron Rodriguez, P. Balagura, V. Baldini, W. Baptista Leite, J. Barbetti, M. Barlow, R.J. Barsuk, S. Barter, W. Bartolini, M. Baryshnikov, F. Basels, J.M. Bashir, S. Bassi, G. Batsukh, B. Battig, A. Bay, A. Beck, A. Becker, M. Bedeschi, F. Bediaga, I. Beiter, A. Belavin, V. Belin, S. Bellee, V. Belous, K. Belov, I. Belyaev, I. Bencivenni, G. Ben-Haim, E. Berezhnoy, A. Bernet, R. Berninghoff, D. Bernstein, H.C. Bertella, C. Bertolin, A. Betancourt, C. Betti, F. Bezshyiko, Ia. Bhasin, S. Bhom, J. Bian, L. Bieker, M.S. Bifani, S. Billoir, P. Birch, M. Bishop, F.C.R. Bitadze, A. Bizzeti, A. Bjørn, M. Blago, M.P. Blake, T. Blanc, F. Blusk, S. Bobulska, D. Boelhauve, J.A. Boente Garcia, O. Boettcher, T. Boldyrev, A. Bondar, A. Bondar, N. Borghi, S. Borisyak, M. Borsato, M. Borsuk, J.T. Bouchiba, S.A. Bowcock, T.J.V. Boyer, A. Bozzi, C. Bradley, M.J. Braun, S. Brea Rodriguez, A. Brodzicka, J. Brossa Gonzalo, A. Brundu, D. Buonaura, A. Buonincontri, L. Burke, A.T. Burr, C. Bursche, A. Butkevich, A. Butter, J.S. Buytaert, J. Byczynski, W. Cadeddu, S. Cai, H. Calabrese, R. Calefice, L. Calero Diaz, L. Cali, S. Calladine, R. Calvi, M. Calvo Gomez, M. Camargo Magalhaes, P. Campana, P. Campoverde Quezada, A.F. Capelli, S. Capriotti, L. Carbone, A. Carboni, G. Cardinale, R. Cardini, A. Carli, I. Carniti, P. Carus, L. Carvalho Akiba, K. Casais Vidal, A. Casse, G. Cattaneo, M. Cavallero, G. Celani, S. Cerasoli, J. Cervenkov, D. Chadwick, A.J. Chapman, M.G. Charles, M. Rio de Janeiro Brazil Rio de Janeiro Brazil Center for High Energy Physics Tsinghua University Beijing China Beijing China School of Physics State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China University of Chinese Academy of Sciences Beijing China Institute of Particle Physics Central China Normal University Hubei Wuhan China Univ. Savoie Mont Blanc CNRS IN2P3-LAPP Annecy France Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS/IN2P3 Paris France I. Physikalisches Institut RWTH Aachen University Aachen Germany Fakultät Physik Technische Universität Dortmund Dortmund Germany Heidelberg Germany Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany School of Physics University College Dublin Dublin Ireland INFN Sezione di Bari Bari Italy INFN Sezione di Bologna Bologna Italy INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Firenze Firenze Italy INFN Laboratori Nazionali di Frascati Frascati Italy INFN Sezione di Genova Genova Italy INFN Sezione di Milano Milano Italy INFN Sezione di Milano-Bicocca Milano Italy INFN Sezione di Cagliari Monserrato Italy Universita degli Studi di Padova Universita e INFN Padova Italy INFN Sezione di Pisa Pisa Italy INFN Sezione di Roma La Sapienza Roma Italy INFN Sezione di Roma Tor Vergata Roma Italy Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Nikhef National Institute for Subatomic Physics VU University Amsterdam Amsterdam Netherlands AGH University of Science and Technology Faculty of Physics and Applied Computer Science Kraków Poland Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy

A search for radiative decay of Bs0 mesons to orbitally excited K+K− states is performed using proton proton collisions recorded by the LHCb experiment, corresponding to an integrated luminosity of 9 fb−1. The dikaon spectrum in the mass range mKK 2 is dominated by the (1020) resonance that accounts for almost 70% of the decay rate. Considering the possible contributions of f2(1270), f2′ (1525) and f2(2010) meson states, the overall tensor contribution to the amplitude is measured to be © 2024, CC BY.

关键词： Bosons

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