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2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016

作者： Wanderley, Gregory Moro Puppi Abel, Marie-Helene Barthes, Jean-Paul Paraiso, Emerson Cabrera Sorbonne Universités Université de Technologie de Compiègne CNRS UMR 7253 Heudiasyc Compiègne France Pontifícia Universidade Católica Do Paraná PPGIa Graduate Program in Informatics Curitiba Brazil

ISBN: (纸本)9781509018970

Collaborative software development is a complex activity. An important factor that needs to receive attention in collaborative software development is software quality. High quality software reduces the development and the maintenance;improves delivery schedules;and reduces repairs and rework. In order to measure, evaluate, control and improve the software quality, software metrics can be used. In this research we present an advanced collaborative environment for software development currently being built, called ACE4SD, which intends to support the improvement of the code quality during collaborative software development. ACE4SD is a system of systems composed of a software development environment, a multi-agent system and a platform to capitalize and manage knowledge, all of them being integrated in the same environment. ACE4SD can provide personalized support to team members to improve the code quality and encourage its reuse, it can answer questions or doubts arisen during the development, record document problems and solutions, and improve the awareness and collaboration between the participants. © 2016 IEEE.

关键词： Multi agent systems

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GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture

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Nature genetics 2023年第9期55卷 1471-1482页

作者： Remi Stevelink Dorothee Kasteleijn-Nolst Trenite Bobby P. C. Koeleman Dick Lindhout Anja C. M. Sonsma Ciarán Campbell Gianpiero L. Cavalleri Norman Delanty Hany El-Naggar Austin Lacey Peter Widdess-Walsh Colin P. Doherty Siwei Chen Claire Churchhouse Mark J. Daly Yen-Chen A. Feng Daniel P. Howrigan Mitja I. Kurki Benjamin M. Neale Aarno Palotie Wei Zhou Namrata Gupta Henrike O. Heyne Bassel Abou-Khalil Kevin F. Haas R. S. Taneja Oluyomi M. Adesoji Michael Nothnagel Peter Nürnberg Thomas Sander Zaid Afawi Ilan Blatt Amos D. Korczyn Elisabetta Amadori Ganna Balagura Antonella Riva Marcello Scala Paolo Scudieri Pasquale Striano Federico Zara Michele Iacomino Francesca Madia Alison Anderson Patrick Kwan Terence J. O’Brien Slavé Petrovski K. Meng Tan Marian Todaro Joseph Anderson Danielle M. Andrade Quratulain Zulfiqar Ali Grazia Annesi Pauls Auce Andreja Avbersek Simona Balestrini Vera Braatz Claudia B. Catarino Krishna Chinthapalli Jennifer Jamnadas-Khoda Dalia Kasperavičiūte Costin Leu Josemir W. Sander Sanjay M. Sisodiya Sara Zagaglia Melanie Bahlo Karen L. Oliver Mark D. Baker Beata Fonferko-Shadrach William O. Pickrell Carmen Barba Claudia Bianchini Viola Doccini Renzo Guerrini Davide Mei Martino Montomoli Elena Parrini Annalisa Vetro Karen Barboza Fabrice Bartolomei Thomas Bast Bernhard J. Steinhoff Larry Baum Stacey S. Cherny Pak Sham Tobias Baumgartner Christian E. Elger Kerstin Hallmann Wolfram S. Kunz Rainer Surges Randi von Wrede Gábor Zsurka Betül Baykan Nerses Bebek Yeşim Kesim Albert J. Becker Susanne Schoch Felicitas Becker Caitlin A. Bennett Samuel F. Berkovic Stephanie L. Leech Brigid M. Regan Ingrid E. Scheffer Bianca Berghuis Ahmad Beydoun Wassim Nasreddine Francesca Bisulli Lidia Di Vito Lorenzo Ferri Tania Giangregorio Laura Licchetta Raffaella Minardi Barbara Mostacci Carlotta Stipa Paolo Tinuper Lorenzo Muccioli Federica Pondrelli Dheeraj R. Bobbili Emadeldin Hassanin Roland Krause Zied Landoulsi Patrick May Ingo Borggraefe Christian Bosselmann Christian Hengsbach Josua Kegele Stephen Lauxmann Department of Genetics University Medical Center Utrecht Utrecht The Netherlands Stichting Epilepsie Instellingen Nederland (SEIN) Heemstede The Netherlands School of Pharmacy and Biomolecular Sciences The Royal College of Surgeons in Ireland Dublin Ireland The FutureNeuro Research Centre Dublin Ireland Department of Neurology Beaumont Hospital Dublin Ireland Department of Neurology St. James’s Hospital Dublin Ireland Analytic and Translational Genetics Unit Department of Medicine Massachusetts General Hospital and Harvard Medical School Boston MA USA Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Stanley Center for Psychiatric Research Broad Institute of Harvard and M.I.T Cambridge MA USA Institute for Molecular Medicine Finland (FIMM) University of Helsinki Helsinki Finland Psychiatric & Neurodevelopmental Genetics Unit Department of Psychiatry Massachusetts General Hospital and Harvard Medical School Boston MA USA Division of Biostatistics Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan Hasso Plattner Institute Digital Health Center University of Potsdam Potsdam Germany Hasso Plattner Institute Mount Sinai School of Medicine New York City NY USA Department of Neurology Vanderbilt University Medical Center Nashville TN USA Cologne Center for Genomics (CCG) University of Cologne Faculty of Medicine and University Hospital Cologne Cologne Germany University Hospital Cologne Cologne Germany Department of Neurology Charité Universitaetsmedizin Berlin Campus Virchow-Clinic Berlin Germany Tel-Aviv University Sackler Faculty of Medicine Ramat Aviv Israel Department of Neurology Sheba Medical Center Ramat Gan Israel Department of Neurosciences Rehabilitation Ophthalmology Genetics Maternal and Child Health University of Genova Genova Italy IRCCS Istituto Giannina Gaslini Genova Italy Department of Medicine University of Melbour

Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here we report a multi-ancestry genome-wide association study including 29,944 cases, stratified into three broad categories and seven subtypes of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants explain between 39.6% and 90% of genetic risk for GGE and its subtypes. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analyses of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current antiseizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment.

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Automatic Detection of Atrial Fibrillation Using Basic Shannon Entropy of RR Interval Feature

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Journal of Physics: Conference Series 2017年第1期795卷 012038-012038页

作者： Afdala, Adfal Nuryani, Nuryani Nugroho, Anto Satriyo Physics Department of Post Graduate Program SebelasMaret University Informatics Department of Under Graduate Program SebelasMaret University Jl. Ir. Sutami 36A KentinganJebres Surakarta 57126 INDONESIA.

Atrial Fibrillation is one of heart disease, that common characterized by irregularity heart beat. Atrial fibrillation leads to severe complications such as cardiac failure with the subsequent risk of a stroke. A method to detect atrial fibrillation is needed to prevent a risk of atrial fibrillation. This research uses data from physionet in atrial fibrillation database category. The performance of Shannon entropy has the highest accuracy if a threshold is 0.5 with accuracy 89.79%, sensitivity 91.04% and specificity 89.01%. Based on the result we get a conclusion, the ability of Shannon entropy to detect atrial fibrillation is good.

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Author Correction: Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries

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Nature genetics 2023年第3期55卷 519-520页

作者： Ceres Fernandez-Rozadilla Maria Timofeeva Zhishan Chen Philip Law Minta Thomas Stephanie Schmit Virginia Díez-Obrero Li Hsu Juan Fernandez-Tajes Claire Palles Kitty Sherwood Sarah Briggs Victoria Svinti Kevin Donnelly Susan Farrington James Blackmur Peter Vaughan-Shaw Xiao-Ou Shu Jirong Long Qiuyin Cai Xingyi Guo Yingchang Lu Peter Broderick James Studd Jeroen Huyghe Tabitha Harrison David Conti Christopher Dampier Mathew Devall Fredrick Schumacher Marilena Melas Gad Rennert Mireia Obón-Santacana Vicente Martín-Sánchez Ferran Moratalla-Navarro Jae Hwan Oh Jeongseon Kim Sun Ha Jee Keum Ji Jung Sun-Seog Kweon Min-Ho Shin Aesun Shin Yoon-Ok Ahn Dong-Hyun Kim Isao Oze Wanqing Wen Keitaro Matsuo Koichi Matsuda Chizu Tanikawa Zefang Ren Yu-Tang Gao Wei-Hua Jia John Hopper Mark Jenkins Aung Ko Win Rish Pai Jane Figueiredo Robert Haile Steven Gallinger Michael Woods Polly Newcomb David Duggan Jeremy Cheadle Richard Kaplan Timothy Maughan Rachel Kerr David Kerr Iva Kirac Jan Böhm Lukka-Pekka Mecklin Pekka Jousilahti Paul Knekt Lauri Aaltonen Harri Rissanen Eero Pukkala Johan Eriksson Tatiana Cajuso Ulrika Hänninen Johanna Kondelin Kimmo Palin Tomas Tanskanen Laura Renkonen-Sinisalo Brent Zanke Satu Männistö Demetrius Albanes Stephanie Weinstein Edward Ruiz-Narvaez Julie Palmer Daniel Buchanan Elizabeth Platz Kala Visvanathan Cornelia Ulrich Erin Siegel Stefanie Brezina Andrea Gsur Peter Campbell Jenny Chang-Claude Michael Hoffmeister Hermann Brenner Martha Slattery John Potter Konstantinos Tsilidis Matthias Schulze Marc Gunter Neil Murphy Antoni Castells Sergi Castellví-Bel Leticia Moreira Volker Arndt Anna Shcherbina Mariana Stern Bens Pardamean Timothy Bishop Graham Giles Melissa Southey Gregory Idos Kevin McDonnell Zomoroda Abu-Ful Joel Greenson Katerina Shulman Flavio Lejbkowicz Kenneth Offit Yu-Ru Su Robert Steinfelder Temitope Keku Bethany van Guelpen Thomas Hudson Heather Hampel Rachel Pearlman Sonja Berndt Richard Hayes Marie Elena Martinez Sushma Thomas Douglas Corley Paul Pharoah Susanna Larsson Yun Yen Heinz-Jo Edinburgh Cancer Research Centre Institute of Genomics and Cancer University of Edinburgh Edinburgh UK. Genomic Medicine Group Instituto de Investigacion Sanitaria de Santiago Santiago de Compostela Spain. Colon Cancer Genetics Group Medical Research Council Human Genetics Unit Institute of Genetics and Cancer University of Edinburgh Edinburgh UK. Danish Institute for Advanced Study Department of Public Health University of Southern Denmark Odense Denmark. Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University Medical Center Nashville TN USA. Division of Genetics and Epidemiology Institute of Cancer Research London UK. Public Health Sciences Division Fred Hutchinson Cancer Research Center Seattle WA USA. Genomic Medicine Institute Cleveland Clinic Cleveland OH USA. Population and Cancer Prevention Program Case Comprehensive Cancer Center Cleveland OH USA. Colorectal Cancer Group ONCOBELL Program Bellvitge Biomedical Research Institute Barcelona Spain. Oncology Data Analytics Program Catalan Institute of Oncology Barcelona Spain. Consortium for Biomedical Research in Epidemiology and Public Health Madrid Madrid Spain. Department of Clinical Sciences Faculty of Medicine University of Barcelona Barcelona Spain. Department of Biostatistics School of Public Health University of Washington Seattle WA USA. Institute of Cancer and Genomic Sciences College of Medical and Dental Sciences University of Birmingham Birmingham UK. Department of Public Health Richard Doll Building University of Oxford Oxford UK. Department of Biomedical Informatics Vanderbilt University School of Medicine Nashville TN USA. Department of Preventive Medicine USC Norris Comprehensive Cancer Center Keck School of Medicine University of Southern California Los Angeles CA USA. Center for Public Health Genomics Department of Public Health Sciences University of Virginia Charlottesville VA USA. De

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Highly accurate model for prediction of lung nodule malignancy with ct scans

arXiv

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arXiv 2018年

作者： Causey, Jason Zhang, Junyu Ma, Shiqian Jiang, Bo Qualls, Jake Politte, David G. Prior, Fred Zhang, Shuzhong Huang, Xiuzhen Department of Computer Science Arkansas State University JonesboroAR72467 United States Department of Industrial and Systems Engineering University of Minnesota MinneapolisMN55455 United States Department of Systems Engineering and Engineering Management Chinese University of Hong Kong Shatin N.T. Hong Kong Research Center for Management Science and Data Analytics School of Information Management and Engineering Shanghai University of Finance and Economics Shanghai200433 China Mallinckrodt Institute of Radiology Washington University St. LouisMO63110 United States Department of Biomedical Informatics University of Arkansas for Medical Sciences Little RockAR72205 United States UALR/UAMS Joint Graduate Program in Bioinformatics Little RockAR72204 United States

Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve performance comparable to experienced radiologists. Here we present NoduleX, a systematic approach to predict lung nodule malignancy from CT data, based on deep learning convolutional neural networks (CNN). For training and validation, we analyze >1000 lung nodules in images from the LIDC/IDRI cohort. All nodules were identified and classified by four experienced thoracic radiologists who participated in the LIDC project. NoduleX achieves high accuracy for nodule malignancy classification, with an AUC of ~0.99. This is commensurate with the analysis of the dataset by experienced radiologists. Our approach, NoduleX, provides an effective framework for highly accurate nodule malignancy prediction with the model trained on a large patient population. Our results are replicable with software available at http://***/NoduleX. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

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A Hybrid Model to Support the Early Diagnosis of Breast Cancer

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Procedia Computer Science 2016年 91卷 927-934页

作者： Davi Carvalho Plácido Rogerio Pinheiro Mirian Calíope Dantas Pinheiro University of Fortaleza Graduate Program in Applied Informatics Av. Washington Soares 1321 - Bl J Sl 30 - 60.811-905 Fortaleza Brazil

Decision-making is a human behavior aiming at the selection of an alternative from groups of real alternatives. Breast Cancer is top cancer of a woman both in developed and developing the world, furthermore breast cancer is the second most frequent cause of death for women in the United States as well as in Asia. Moreover, the early diagnosis is vital to a treatment with a better chance of success. Multiple variables are involved in the process of diagnosis. This study aims to use a Hybrid model to support the early diagnosis of breast cancer. We have proposed the utilization of a hybrid model structured in methodologies build a Bayesian Network to calculate the condition probability of a given person having breast cancer and to support decision (Multi-Criteria Decision Analysis - MCDA) with the goal to achieve optimal to identify the most influential attributes and have a more accurate result than using Bayesian Network alone.

关键词： Breast Cancer Bayesian Networks Multicriteria Analysis

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A Multi-Criteria Model in Information Technology Infrastructure Problems

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Procedia Computer Science 2016年 91卷 642-651页

作者： Carolina Ferreira Andrea Nery Placido Rogerio Pinheiro University of Fortaleza Graduate Program in Applied Informatics Av. Washington Soares 1321 - Bl J Sl 30 Fortaleza 60.811-905 Brazil

Technology has become a vital component for organizations. Therefore, it is necessary to ensure quality and efficient IT solutions in order to meet the expectations of the business areas. In this scenario, we have realized the need to align the technology areas of management practices with organizational strategies and thus ensure the availability of solutions. This paper aims to propose a model to optimize the decision-making of the problem management process based on the best practices proposed by the ITIL (IT Infrastructure Library), using the concepts of a multi-criteria methodology. The model suggests the prioritization of problems that cause a most negative impact on the business of an organization, in order to reduce or prevent damage.

关键词： Problem management Information Technology Infrastructure Library (ITIL) Multi-criteria approach.

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Performance of the joint LST-1 and MAGIC observations evaluated with Crab Nebula data

arXiv

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arXiv 2023年

作者： Abe, H. Abe, K. Abe, S. Acciari, V.A. Aguasca-Cabot, A. Agudo, I. Crespo, N. Alvarez Aniello, T. Ansoldi, S. Antonelli, L.A. Aramo, C. Arbet-Engels, A. Arcaro, C. Artero, M. Asano, K. Aubert, P. Baack, D. Babić, A. Baktash, A. Bamba, A. Larriva, A. Baquero Baroncelli, L. de Almeida, U. Barres Barrio, J.A. Batković, I. Baxter, J. González, J. Becerra Bednarek, W. Bernardini, E. Bernardos, M.I. Medrano, J. Bernete Berti, A. Besenrieder, J. Bhattacharjee, P. Biederbeck, N. Bigongiari, C. Biland, A. Bissaldi, E. Blanch, O. Bonnoli, G. Bordas, P. Bošnjak, Ž. Bulgarelli, A. Burelli, I. Burmistrov, L. Buscemi, M. Busetto, G. Ordaz, A. Campoy Cardillo, M. Caroff, S. Carosi, A. Carosi, R. Carrasco, M.S. Carretero-Castrillo, M. Cassol, F. Castro-Tirado, A.J. Cauz, D. Cerasole, D. Ceribella, G. Chai, Y. Cheng, K. Chiavassa, A. Chikawa, M. Chytka, L. Cifuentes, A. Cikota, S. Colombo, E. Contreras, J.L. Cornelia, A. Cortina, J. Costantini, H. Covino, S. D’Amico, G. D’Elia, V. Da Vela, P. Dalchenko, M. Dazzi, F. De Angelis, A. de Bony de Lavergne, M. De Lotto, B. De Lucia, M. de Menezes, R. Del Peral, L. DelPopolo, A. Deleglise, G. Delfino, M. Mendez, C. Delgado Mengual, J. Delgado Volpe, D. della Dellaiera, M. Depaoli, D. De Angelis, A. Di Piano, A. Di Pierro, F. Di Pilato, A. Di Tria, R. Di Venere, L. Dominik, R.M. Prester, D. Dominis Donini, A. Dorner, D. Doro, M. Díaz, C. Eisenberger, L. Elsässer, D. Emery, G. Escudero, J. Ramazani, V. Fallah Fariña, L. Fattorini, A. Ferrara, G. Ferrarotto, F. Fiasson, A. Foffano, L. Font, L. Coromina, L. Freixas Fröse, S. Fukami, S. Fukazawa, Y. López, R.J. Garcia Garcia, E. Garczarczyk, M. López, R.J. García Gasbarra, C. Gasparrini, D. Gasparyan, S. Gaug, M. Geyer, D. Paiva, J.G. Giesbrecht Giglietto, N. Giordano, F. Gliwny, P. Godinović, N. Grau, R. Green, D. Green, J.G. Gunji, S. Günther, P. Hackfeld, J. Hadasch, D. Hahn, A. Hashiyama, K. Hassan, T. Hayashi, K. Heckmann, L. Heller, M. Llorente, J. Herrera Hirotani, K. Hoffmann, D. Horns, D. Houles, J. Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-ha Chiba Kashiwa277-8582 Japan Department of Physics Tokai University 4-1-1 Kita-Kaname Kanagawa Hiratsuka259-1292 Japan Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Tenerife La Laguna Spain Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Martí i Franquès 1 Barcelona08028 Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain Grupo de Electronica Universidad Complutense de Madrid Av. Complutense s/n Madrid28040 Spain RomeI-00136 Italy INFN Sezione di Trieste Università degli studi di Udine via delle scienze 206 Udine33100 Italy Rome Italy INAF - Osservatorio Astronomico di Roma Via di Frascati 33 Monteporzio Catone00040 Italy INFN Sezione di Napoli Via Cintia ed. G Napoli80126 Italy Max-Planck-Institut für Physik Föhringer Ring 6 München80805 Germany Università di Padova INFN PadovaI-35131 Italy The Barcelona Institute of Science and Technology Campus UAB Bellaterra08193 Spain Univ. Savoie Mont Blanc CNRS Laboratoire d’Annecy de Physique des Particules - IN2P3 Annecy74000 France Department of Physics TU Dortmund University Otto-Hahn-Str. 4 Dortmund44227 Germany Zagreb10000 Croatia Universität Hamburg Institut für Experimentalphysik Luruper Chaussee 149 Hamburg22761 Germany Graduate School of Science University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan IPARCOS-UCM Instituto de Física de Partículas y del Cosmos EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain Faculty of Science and Technology Universidad del Azuay Cuenca Ecuador INAF - Osservatorio di Astrofisica e Scienza dello spazio di Bologna Via Piero Gobetti 93/3 Bologna40129 Italy Centro Brasileiro de Pesquisas Físicas Rua Xavier Sigaud 150 RJ Rio de Janeiro22290-180 Brazil INFN Sezione di Padova

Aims. LST-1, the prototype of the Large-Sized Telescope for the upcoming Cherenkov Telescope Array Observatory, is concluding its commissioning in Observatorio del Roque de los Muchachos on the island of La Palma. The proximity of LST-1 (Large-Sized Telescope 1) to the two MAGIC (Major Atmospheric Gamma Imaging Cherenkov) telescopes permits observations of the same gamma-ray events with both systems. Methods. We describe the joint LST-1+MAGIC analysis pipeline and use simultaneous Crab Nebula observations and Monte Carlo simulations to assess the performance of the three-telescope system. The addition of the LST-1 telescope allows the recovery of events in which one of the MAGIC images is too dim to survive analysis quality cuts. Results. Thanks to the resulting increase in the collection area and stronger background rejection, we find a significant improvement in sensitivity, allowing the detection of 30% weaker fluxes in the energy range between 200 GeV and 3 TeV. The spectrum of the Crab Nebula, reconstructed in the energy range ∼60 GeV to ∼10 TeV, is in agreement with previous measurements. Copyright © 2023, The Authors. All rights reserved.

关键词： Telescopes

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Towards the Applied Hybrid Model in Requirements Prioritization

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Procedia Computer Science 2016年 91卷 909-918页

作者： Rômulo Santos Adriano Albuquerque Plácido Rogerio Pinheiro University of Fortaleza Graduate Program in Applied Informatics Av. Washington Soares 1321 - Bl J Sl 30 Fortaleza 60.811-905 Brazil

Although there are numerous prioritization techniques, few satisfy the quality criteria such as scalability, efficiency and easiness of usage. This research presents a case study of Commercial Off-The-Shelf (COTS) software requirements prioritization to be potentially used by thousands of users. The HCV(Hierarchical Cumulative Voting) requirements prioritization technique was addressed and applied through a web questionnaire directly to potential users to analyze the benefit of the requirement criteria. Another aspects discussed were volatility of the requirements and market competition. In the end, eighty respondents sent in the questionnaire and a score of requirements in ratio scale of measurement was obtained, and the criteria have been consolidated through the Macbeth approach. It was found that the method could respond positively to the needs and characteristics of Market-Driven Software Development, in similar situations to those described.

关键词： Multicriteria Analysis Requirements Prioritization Hierarchical Cumulative Voting

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Observations of the Crab Nebula and Pulsar with the Large-Sized Telescope Prototype of the Cherenkov Telescope Array

arXiv

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arXiv 2023年

作者： Abe, H. Abe, K. Abe, S. Aguasca-Cabot, A. Agudo, I. Alvarez Crespo, N. Antonelli, L.A. Aramo, C. Arbet-Engels, A. Arcaro, C. Artero, M. Asano, K. Aubert, P. Baktash, A. Bamba, A. Baquero Larriva, A. Baroncelli, L. Barres de Almeida, U. Barrio, J.A. Batkovic, I. Baxter, J. Becerra González, J. Bernardini, E. Bernardos, M.I. Bernete Medrano, J. Berti, A. Bhattacharjee, P. Biederbeck, N. Bigongiari, C. Bissaldi, E. Blanch, O. Bonnoli, G. Bordas, P. Borghese, A. Bulgarelli, A. Burelli, I. Buscemi, M. Cardillo, M. Caroff, S. Carosi, A. Cassol, F. Cauz, D. Ceribella, G. Chai, Y. Cheng, K. Chiavassa, A. Chikawa, M. Chytka, L. Cifuentes, A. Contreras, J.L. Cortina, J. Costantini, H. D'Amico, G. Dalchenko, M. De Angelis, A. de Bony de Lavergne, M. De Lotto, B. de Menezes, R. Deleglise, G. Delgado, C. Delgado Mengual, J. della Volpe, D. Dellaiera, M. Depaoli, D. Di Piano, A. Di Pierro, F. Di Tria, R. Di Venere, L. Díaz, C. Dominik, R.M. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsässer, D. Emery, G. Escudero, J. Fallah Ramazani, V. Ferrara, G. Ferrarotto, F. Fiasson, A. Freixas Coromina, L. Fröse, S. Fukami, S. Fukazawa, Y. Garcia, E. Garcia López, R. Gasbarra, C. Gasparrini, D. Geyer, F. Giesbrecht Paiva, J. Giglietto, N. Giordano, F. Giro, E. Gliwny, P. Godinovic, N. Grau, R. Green, D. Green, J. Gunji, S. Hackfeld, J. Hadasch, D. Hahn, A. Hashiyama, K. Hassan, T. Hayashi, K. Heckmann, L. Heller, M. Herrera Llorente, J. Hirotani, K. Hoffmann, D. Horns, D. Houles, J. Hrabovsky, M. Hrupec, D. Hui, D. Hütten, M. Iarlori, M. Imazawa, R. Inada, T. Inome, Y. Ioka, K. Iori, M. Ishio, K. Iwamura, Y. Jacquemont, M. Jimenez Martinez, I. Jurysek, J. Kagaya, M. Karas, V. Katagiri, H. Kataoka, J. Kerszberg, D. Kobayashi, Y. Kong, A. Kubo, H. Kushida, J. Lainez, M. Lamanna, G. Lamastra, A. Le Flour, T. Linhoff, M. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Loporchio, S. Lorini, A. Luque-Escamilla, P.L. Majumdar, P. Makariev, M. Mandat, D. Manganaro, M. Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-ha Chiba Kashiwa277-8582 Japan Department of Physics Tokai University 4-1-1 Kita-Kaname Kanagawa Hiratsuka259-1292 Japan Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Martí i Franquès 1 Barcelona08028 Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain IPARCOS-UCM Instituto de Física de Partículas y del Cosmos EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain INAF - Osservatorio Astronomico di Roma Via di Frascati 33 Monteporzio Catone00040 Italy INFN Sezione di Napoli Via Cintia ed. G Napoli80126 Italy Max-Planck-Institut für Physik Föhringer Ring 6 München80805 Germany INFN Sezione di Padova Università degli Studi di Padova Via Marzolo 8 Padova35131 Italy The Barcelona Institute of Science and Technology Campus UAB Bellaterra Barcelona08193 Spain Univ. Savoie Mont Blanc CNRS Laboratoire d'Annecy de Physique des Particules - IN2P3 Annecy74000 France Universität Hamburg Institut für Experimentalphysik Luruper Chaussee 149 Hamburg22761 Germany Graduate School of Science University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Faculty of Science and Technology Universidad del Azuay Cuenca Ecuador INAF - Osservatorio di Astrofisica e Scienza dello Spazio di Bologna Via Piero Gobetti 93/3 Bologna40129 Italy Centro Brasileiro de Pesquisas Físicas Rua Xavier Sigaud 150 RJ Rio de Janeiro22290-180 Brazil Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Tenerife La Laguna Spain CIEMAT Avda. Complutense 40 Madrid28040 Spain Department of Physics TU Dortmund University Otto-Hahn-Str. 4 Dortmund44227 Germany INFN Sezione di Bari Politecnico di Bari via Orabona 4 Bari70124 Italy INAF - Osservatorio Astronomico di Brera Via Brera 28 Milano20121 Italy Campus UAB Carrer de Ca

CTA (Cherenkov Telescope Array) is the next-generation ground-based observatory for gamma-ray astronomy at very-high energies. The Large-Sized Telescope prototype (LST-1) is located at the CTA-North site, on the Canary Island of La Palma. LSTs are designed to provide optimal performance in the lowest part of the energy range covered by CTA, down to 20 GeV. LST-1 started performing astronomical observations in November 2019, during its commissioning phase, and it has been taking data since then. We present the first LST-1 observations of the Crab Nebula, the standard candle of very-high energy gamma-ray astronomy, and use them, together with simulations, to assess the performance of the telescope. LST-1 has reached the expected performance during its commissioning period - only a minor adjustment of the preexisting simulations was needed to match the telescope behavior. The energy threshold at trigger level is around 20 GeV, rising to 30 GeV after data analysis. Performance parameters depend strongly on energy, and on the strength of the gamma-ray selection cuts in the analysis: angular resolution ranges from 0.12 to 0.40 degrees, and energy resolution from 15 to 50%. Flux sensitivity is around 1.1% of the Crab Nebula flux above 250 GeV for a 50-h observation (12% for 30 minutes). The spectral energy distribution (in the 0.03-30 TeV range) and the light curve obtained for the Crab Nebula agree with previous measurements, considering statistical and systematic uncertainties. A clear periodic signal is also detected from the pulsar at the center of the Nebula. Copyright © 2023, The Authors. All rights reserved.

关键词： Pulsars

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