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International Joint Conference on Neural Networks

作者： Diego Guarnieri Corrêa Fabrício Enembreck Carlos N. Silla Graduate Program in Informatics (PPGI) - Federal University of Technology of Paraná (UTFPR) Cornélio Procópio PR Brazil 86300-000 Graduate Program in Computer Science (PPGIa) - Pontifical Catholic University of Paraná (PUCPR) Curitiba PR Brazil 80215-901

ISBN: (纸本)9781509061839

Intrusion detection in computer networks is a important topic in information security. Due to numerous cases of security breaches that caused economic and social losses in recent years, this topic has been the subject of several studies in order to mitigate problems related to network intrusion and computer attacks. Information security systems have been using different techniques for network intrusion detection. However, with the development of communication mechanisms and consequently with the increase in data traffic, some techniques used for intrusion detection lost their information processing capability. The emergence of new forms of attacks on computer systems also contribute to the depreciation of some of the existing tools. In this scenario, new techniques capable of processing large amounts of information and that perform proactive discovery of new attack vectors are necessary. This paper presents a study on the use of a data stream mining technique known as Hoeffding Adaptive Tree to create a predictive model for network intrusion detection. The experiments performed in this work show the effectiveness of this technique when applied to a database of computer network attacks.

关键词： Intrusion detection Data mining Tools Computers Databases Prediction algorithms Adaptation models

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Search for Gamma-Ray Spectral Lines from Dark Matter Annihilation up to 100 TeV toward the Galactic Center with MAGIC

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Physical Review Letters 2023年第6期130卷 061002-061002页

作者： H. Abe S. Abe V. A. Acciari T. Aniello S. Ansoldi L. A. Antonelli A. Arbet Engels C. Arcaro M. Artero K. Asano D. Baack A. Babić A. Baquero U. Barres de Almeida J. A. Barrio I. Batković J. Baxter J. Becerra González W. Bednarek E. Bernardini M. Bernardos A. Berti J. Besenrieder W. Bhattacharyya C. Bigongiari A. Biland O. Blanch G. Bonnoli Ž. Bošnjak I. Burelli G. Busetto R. Carosi M. Carretero-Castrillo G. Ceribella Y. Chai A. Chilingarian S. Cikota E. Colombo J. L. Contreras J. Cortina S. Covino G. D’Amico V. D’Elia P. Da Vela F. Dazzi A. De Angelis B. De Lotto A. Del Popolo M. Delfino J. Delgado C. Delgado Mendez D. Depaoli F. Di Pierro L. Di Venere E. Do Souto Espiñeira D. Dominis Prester A. Donini D. Dorner M. Doro D. Elsaesser G. Emery V. Fallah Ramazani L. Fariña A. Fattorini L. Font C. Fruck S. Fukami Y. Fukazawa R. J. García López M. Garczarczyk S. Gasparyan M. Gaug J. G. Giesbrecht Paiva N. Giglietto F. Giordano P. Gliwny N. Godinović J. G. Green D. Green D. Hadasch A. Hahn T. Hassan L. Heckmann J. Herrera D. Hrupec M. Hütten R. Imazawa T. Inada R. Iotov K. Ishio I. Jiménez Martínez J. Jormanainen D. Kerszberg Y. Kobayashi H. Kubo J. Kushida A. Lamastra D. Lelas F. Leone E. Lindfors L. Linhoff S. Lombardi F. Longo R. López-Coto M. López-Moya A. López-Oramas S. Loporchio A. Lorini E. Lyard B. Machado de Oliveira Fraga P. Majumdar M. Makariev G. Maneva N. Mang M. Manganaro S. Mangano K. Mannheim M. Mariotti M. Martínez A. Mas Aguilar D. Mazin S. Menchiari S. Mender S. Mićanović D. Miceli T. Miener J. M. Miranda R. Mirzoyan E. Molina H. A. Mondal A. Moralejo D. Morcuende V. Moreno T. Nakamori C. Nanci L. Nava V. Neustroev M. Nievas Rosillo C. Nigro K. Nilsson K. Nishijima T. Njoh Ekoume K. Noda S. Nozaki Y. Ohtani T. Oka J. Otero-Santos S. Paiano M. Palatiello D. Paneque R. Paoletti J. M. Paredes L. Pavletić M. Persic M. Pihet F. Podobnik P. G. Prada Moroni E. Prandini G. Principe C. Priyadarshi I. Puljak W. Rhode M. Ribó J. Rico C. Righi A. Rugliancich N. Sahakyan T. Saito S. Sakurai K. Satalecka F. G. Sat Japanese MAGIC Group: Institute for Cosmic Ray Research (ICRR) The University of Tokyo Kashiwa 277-8582 Chiba Japan Instituto de Astrofísica de Canarias and Departamento de Astrofísica Universidad de La Laguna E-38200 La Laguna Tenerife Spain National Institute for Astrophysics (INAF) I-00136 Rome Italy Università di Udine and INFN Trieste I-33100 Udine Italy Max-Planck-Institut für Physik D-80805 München Germany Università di Padova and INFN I-35131 Padova Italy Institut de Física d’Altes Energies (IFAE) The Barcelona Institute of Science and Technology (BIST) E-08193 Bellaterra (Barcelona) Spain Technische Universität Dortmund D-44221 Dortmund Germany Croatian MAGIC Group: University of Zagreb Faculty of Electrical Engineering and Computing (FER) 10000 Zagreb Croatia IPARCOS Institute and EMFTEL Department Universidad Complutense de Madrid E-28040 Madrid Spain Centro Brasileiro de Pesquisas Físicas (CBPF) 22290-180 URCA Rio de Janeiro (RJ) Brazil University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics 90-236 Lodz Poland Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n 18008 Granada Spain Deutsches Elektronen-Synchrotron (DESY) D-15738 Zeuthen Germany ETH Zürich CH-8093 Zürich Switzerland Università di Pisa and INFN Pisa I-56126 Pisa Italy Universitat de Barcelona ICCUB IEEC-UB E-08028 Barcelona Spain Armenian MAGIC Group: A. Alikhanyan National Science Laboratory 0036 Yerevan Armenia Centro de Investigaciones Energéticas Medioambientales y Tecnológicas E-28040 Madrid Spain Department for Physics and Technology University of Bergen Norway INFN MAGIC Group: INFN Sezione di Catania and Dipartimento di Fisica e Astronomia University of Catania I-95123 Catania Italy INFN MAGIC Group: INFN Sezione di Torino and Università degli Studi di Torino I-10125 Torino Italy INFN MAGIC Group: INFN Sezione di Bari and Dipartimento Interateneo di Fisica dell’Università e del Politecnico di Bari I-70125 Bari Italy

Linelike features in TeV γ rays constitute a “smoking gun” for TeV-scale particle dark matter and new physics. Probing the Galactic Center region with ground-based Cherenkov telescopes enables the search for TeV spectral features in immediate association with a dense dark matter reservoir at a sensitivity out of reach for satellite γ-ray detectors, and direct detection and collider experiments. We report on 223 hours of observations of the Galactic Center region with the MAGIC stereoscopic telescope system reaching γ-ray energies up to 100 TeV. We improved the sensitivity to spectral lines at high energies using large-zenith-angle observations and a novel background modeling method within a maximum-likelihood analysis in the energy domain. No linelike spectral feature is found in our analysis. Therefore, we constrain the cross section for dark matter annihilation into two photons to ⟨σv⟩≲5×10−28 cm3 s−1 at 1 TeV and ⟨σv⟩≲1×10−25 cm3 s−1 at 100 TeV, achieving the best limits to date for a dark matter mass above 20 TeV and a cuspy dark matter profile at the Galactic Center. Finally, we use the derived limits for both cuspy and cored dark matter profiles to constrain supersymmetric wino models.

关键词： Dark matter Gamma ray astronomy Particle dark matter Milky Way Cosmic ray & astroparticle detectors Cosmic rays & astroparticles Electromagnetic radiation astronomy Telescopes

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Transient stabilization, rather than inhibition, of MYC amplifies extrinsic apoptosis and therapeutic responses in refractory B-cell lymphoma (vol 33, pg 2429, 2019)

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LEUKEMIA 2020年第5期34卷 1485-1485页

作者： Harrington, Colleen T. Sotillo, Elena Robert, Aude Hayer, Katharina E. Bogusz, Agata M. Psathas, James Yu, Duonan Taylor, Deanne Dang, Chi V. Klein, Peter S. Hogarty, Michael D. Geoerger, Birgit El-Deiry, Wafik S. Wiels, Joelle Thomas-Tikhonenko, Andrei Division of Cancer Pathobiology Children’s Hospital of Philadelphia Philadelphia USA Cell & Molecular Biology Graduate Group Perelman School of Medicine at the University of Pennsylvania Philadelphia USA Stanford Cancer Institute Stanford USA CNRS UMR 8126 Univ Paris-Sud - Université Paris-Saclay Institut Gustave Roussy Villejuif France Department of Biomedical and Health Informatics Children’s Hospital of Philadelphia Philadelphia USA Department of Pathology and Laboratory Medicine Perelman School of Medicine at the University of Pennsylvania Philadelphia USA The Janssen Pharmaceutical Companies of Johnson & Johnson Malvern USA Noncoding RNA Center Yangzhou University Yangzhou China Department of Pediatrics Perelman School of Medicine at the University of Pennsylvania Philadelphia USA Molecular and Cellular Oncogenesis Program The Wistar Institute Philadelphia USA Department of Medicine Perelman School of Medicine at the University of Pennsylvania Philadelphia USA Division of Oncology Children’s Hospital of Philadelphia Philadelphia USA CNRS UMR 8203 Univ Paris-Sud - Université Paris-Saclay Institut Gustave Roussy Villejuif France Department of Pediatric and Adolescent Oncology Univ Paris-Sud - Université Paris-Saclay Institut Gustave Roussy Villejuif France Department of Pathology and Laboratory Medicine Brown University Medical School Providence USA

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Retracted: Design of Decision Support System Determination of Inventory Inventory Using Single Exponential Smoothing Forecasting Method

Retracted: Design of Decision Support System Determination o...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, Computer Science, Information Systems, and Information Technology, WMA-Mathcomtech 2018

作者： Iqbal, Muhammad Abdullah, Dahlan Hartono, H. Erliana, Cut Ita Sriadhi, S. Nurmawati, N. Prasnowo, M Adhi Hasibuan, Abdurrozzaq Iskandar, Akbar Saddhono, Kundharu Abdussakir, A. Musa, Hastuti Setiawan, Muhammad Ikhsan Sagala, Youmeni Siahaan, Rumiris Sinaga, Eka Mayastika Syahputri, Anggraini Milanie, Feby Aspan, Henry Khaddafi, Muammar Department of Computer System Universitas Pembangunan Panca Budi Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Department of Industrial Engineering Universitas Maarif Hasyim Latif Sidoarjo Indonesia Faculty of Engineering Universitas Islam Sumatera UtaraMedan Indonesia Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Mathematics Education State Islamic University of Malang Malang Indonesia Department of Mathematics Universitas Muhammadiyah Parepare Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia STIE Bina Karya Tebing Tinggi Indonesia Universitas Pembangunan Panca Budi Medan Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

The development of information and communication technology at this time has touched all sides of life. Almost no side of human life is not touched by this information technology, which is more synonymous with the world of computerization. No exception also with the computerization that is popular in the corporate environment and government agencies. If in ancient times everything was still done manually. However, at this time all leaders and management have realized the importance of this information technology products that can facilitate them in carrying out the day-to-day corporate functions. Decision Making System of goods purchasing is one of the determinants of the accumulation of goods. If the decision is taken right then stockpiling of goods can be avoided. In this thesis the authors designed a web-based system that helps Management in making the decision of the purchase amount of goods. the system was developed by using Microsoft Visual Studio 2010 and using SQL Server database processing applications. The end result of system design is expected to help minimize the accumulation of goods. © Published under licence by IOP Publishing Ltd.

关键词： Decision support systems

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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The Huanan Seafood Wholesale Market in Wuhan was the early epicenter of the COVID-19 pandemic

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四川生理科学杂志 2022年第7期44卷 1246-1246页

作者： Michael Worobey Department of Ecology and Evolutionary Biology University of Arizona Tucson AZ 85721 USA Department of Immunology and Microbiology The Scripps Research Institute La Jolla CA 92037 USA W. Harry Feinstone Department of Molecular Microbiology and Immunology Johns Hopkins Bloomberg School of Public Health Baltimore MD 21205 USA Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla CA 92093 USA Department of Biomedical Informatics University of California San Diego La Jolla CA 92093 USA Department of Human Genetics University of Utah School of Medicine Salt Lake City UT 84112 USA Vaccine and Infectious Disease Organization University of Saskatchewan Saskatoon SK S7N 5E3 Canada Center for Global Health Science and Security Georgetown University Washington DC 20057 USA Department of Zoology University of Oxford Oxford OX1 3SZ UK Wildlife Conservation Research Unit Department of Zoology The Recanati-Kaplan Centre University of Oxford Oxford OX13 5QL UK Pandemic and Disaster Preparedness Centre Erasmus University Medical Center 3015 CE Rotterdam Netherlands Department of Viroscience Erasmus University Medical Center 3015 CE Rotterdam Netherlands Department of Biostatistics Fielding School of Public Health University of California Los Angeles Los Angeles CA 90095 USA Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA 90095 USA Department of Computational Medicine David Geffen School of Medicine University of California Los Angeles Los Angeles CA 90095 USA Department of Medicine University of California San Diego La Jolla CA 92093 USA Department of Microbiology Immunology and Transplantation Rega Institute for Medical Research KU Leuven 3000 Leuven Belgium Global Virus Network (GVN) Baltimore MD 21201 USA MRC-University of Glasgow Center for Virus Research Glasgow G61 1QH UK Tulane University School of Medicine Department of Microbiology and Immu

Understanding how severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)emerged in 2019 is critical to preventing zoonotic outbreaks before they become the next *** Huanan Seafood Wholesale Market in Wuhan,China,was identified as a likely source of cases in early reports but later this conclusion became *** show the earliest known COVID-19 cases from December 2019,including those without reported direct links,were geographically centered on this *** report that live SARS-CoV-2 susceptible mammals were sold at the market in late 2019 and,within the market,SARS-CoV-2-positive environmental samples were spatially associated with vendors selling live mammals.

关键词： Market likely Wuhan

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Analysis of the cherenkov telescope array first large-sized telescope real data using convolutional neural networks

arXiv

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arXiv 2021年

作者： Vuillaume, Thomas Jacquemont, Mikaël de Bony de Lavergne, Mathieu Sanchez, David A. Poireau, Vincent Maurin, Gilles Benoit, Alexandre Lambert, Patrick Lamanna, Giovanni Abe, H. Aguasca, A. Agudo, I. Antonelli, L.A. Aramo, C. Armstrong, T. Artero, M. Asano, K. Ashkar, H. Aubert, P. Baktash, A. Bamba, A. Baquero Larriva, A. Baroncelli, L. Barres de Almeida, U. Barrio, J.A. Batkovic, I. Becerra González, J. Bernardos, M.I. Berti, A. Biederbeck, N. Bigongiari, C. Blanch, O. Bonnoli, G. Bordas, P. Bose, D. Bulgarelli, A. Burelli, I. Buscemi, M. Cardillo, M. Caroff, S. Carosi, A. Cassol, F. Cerruti, M. Chai, Y. Cheng, K. Chikawa, M. Chytka, L. Contreras, J.L. Cortina, J. Costantini, H. Dalchenko, M. de Angelis, A. de Bony de Lavergne, M. Deleglise, G. Delgado, C. Delgado Mengual, J. della Volpe, D. Depaoli, D. Di Pierro, F. Di Venere, L. Díaz, C. Dominik, R.M. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsässer, D. Emery, G. Escudero, J. Fiasson, A. Foffano, L. Fonseca, M.V. Freixas Coromina, L. Fukami, S. Fukazawa, Y. Garcia, E. Garcia López, R. Giglietto, N. Giordano, F. Gliwny, P. Godinovic, N. Green, D. Grespan, P. Gunji, S. Hackfeld, J. Hadasch, D. Hahn, A. 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. Inada, T. Inome, Y. Iori, M. Ishio, K. Iwamura, Y. Jacquemont, M. Jimenez Martinez, I. Jouvin, L. Jurysek, J. Kagaya, M. Karas, V. Katagiri, H. Kataoka, J. Kerszberg, D. Kobayashi, Y. Kong, A. Kubo, H. Kushida, J. Lamanna, G. Lamastra, A. Le Flour, T. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Luque-Escamilla, P.L. Majumdar, P. Makariev, M. Mandat, D. Manganaro, M. Mannheim, K. Mariotti, M. Marquez, P. Marsella, G. Martí, J. Martinez, O. Martínez, G. Martínez, M. Marusevec, P. Mas, A. Maurin, G. Mazin, D. Mestre Guillen, E. Micanovic, S. Miceli, D. Miener, T. Miranda, J.M. Miranda, L.D.M. Mirzoyan, R. Mizuno, T. Molina, E. Montaruli, T. Laboratoire d’Annecy de Physique des Particules Univ. Grenoble Alpes Univ. Savoie Mont Blanc CNRS LAPP 9 chemin de bellevue Annecy74940 France LISTIC Université Savoie Mont-Blanc PolytechAnnecy-Chambéry 5 chemin de bellevue Annecy74940 France Institute for Cosmic Ray Research University of Tokyo Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Instituto de Astrofísica de Andalucía-CSIC INAF - Osservatorio Astronomico di Roma INFN Sezione di Napoli Aix Marseille Univ CNRS/IN2P3 CPPM Barcelona Institute of Science and Technology IRFU CEA Université Paris-Saclay LAPP Univ. Grenoble Alpes Univ. Savoie Mont Blanc CNRS-IN2P3 Annecy France Universität Hamburg Institut für Experimentalphysik Graduate School of Science University of Tokyo EMFTEL department IPARCOS Universidad Complutense de Madrid INAF - Osservatorio di Astrofisica e Scienza dello spazio di Bologna Centro Brasileiro de Pesquisas Físicas INFN Sezione di Padova Università degli Studi di Padova Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Max-Planck-Institut für Physik Department of Physics TU Dortmund University Saha Institute of Nuclear Physics INFN Sezione di Trieste Università degli Studi di Udine INFN Sezione di Catania University of Geneva Département de physique nucléaire et corpusculaire Palacky University Olomouc Faculty of Science CIEMAT Port d’Informació Científica INFN Sezione di Torino Dipartimento di Fisica - Universitá degli Studi di Torino INFN Sezione di Bari Università di Bari University of Rijeka Department of Physics Institute for Theoretical Physics and Astrophysics Universität Würzburg Physics Program Graduate School of Advanced Science and Engineering Hiroshima University INFN Sezione di Bari Politecnico di Bari Faculty of Physics and Applied Informatics University of Lodz University of Split FESB Croatia Department of Physics Yamagata University Institut für Theoretische Physik Leh

The Cherenkov Telescope Array (CTA) is the future ground-based gamma-ray observatory and will be composed of two arrays of imaging atmospheric Cherenkov telescopes (IACTs) located in the Northern and Southern hemispheres respectively. The first CTA prototype telescope built on-site, the Large-Sized Telescope (LST-1), is under commissioning in La Palma and has already taken data on numerous known sources. IACTs detect the faint flash of Cherenkov light indirectly produced after a very energetic gamma-ray photon has interacted with the atmosphere and generated an atmospheric shower. Reconstruction of the characteristics of the primary photons is usually done using a parameterization up to the third order of the light distribution of the images. In order to go beyond this classical method, new approaches are being developed using state-of-the-art methods based on convolutional neural networks (CNN) to reconstruct the properties of each event (incoming direction, energy and particle type) directly from the telescope images. While promising, these methods are notoriously difficult to apply to real data due to differences (such as different levels of night sky background) between Monte Carlo (MC) data used to train the network and real data. The GammaLearn project, based on these CNN approaches, has already shown an increase in sensitivity on MC simulations for LST-1 as well as a lower energy threshold. This work applies the GammaLearn network to real data acquired by LST-1 and compares the results to the classical approach that uses random forests trained on extracted image parameters. The improvements on the background rejection, event direction, and energy reconstruction are discussed in this contribution. © 2021, CC BY.

关键词： Telescopes

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Polygenic risk modeling for prediction of epithelial ovarian cancer risk (vol 30, pg 349, 2021)

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EUROPEAN JOURNAL OF HUMAN GENETICS 2022年第5期30卷 630-631页

作者： Dareng, Eileen O. Tyrer, Jonathan P. Barnes, Daniel R. Jones, Michelle R. Yang, Xin Aben, Katja K. H. Adank, Muriel A. Agata, Simona Andrulis, Irene L. Anton-Culver, Hoda Antonenkova, Natalia N. Aravantinos, Gerasimos Arun, Banu K. Augustinsson, Annelie Balmana, Judith Bandera, Elisa V. Barkardottir, Rosa B. Barrowdale, Daniel Beckmann, Matthias W. Beeghly-Fadiel, Alicia Benitez, Javier Bermisheva, Marina Bernardini, Marcus Q. Bjorge, Line Black, Amanda Bogdanova, Natalia V. Bonanni, Bernardo Borg, Ake Brenton, James D. Budzilowska, Agnieszka Butzow, Ralf Buys, Saundra S. Cai, Hui Caligo, Maria A. Campbell, Ian Cannioto, Rikki Cassingham, Hayley Chang-Claude, Jenny Chanock, Stephen J. Chen, Kexin Chiew, Yoke-Eng Chung, Wendy K. Claes, Kathleen B. M. Colonna, Sarah Cook, Linda S. Couch, Fergus J. Daly, Mary B. Dao, Fanny Davies, Eleanor de la Hoya, Miguel de Putter, Robin Dennis, Joe DePersia, Allison Devilee, Peter Diez, Orland Ding, Yuan Chun Doherty, Jennifer A. Domchek, Susan M. Dork, Thilo du Bois, Andreas Durst, Matthias Eccles, Diana M. Eliassen, Heather A. Engel, Christoph Evans, Gareth D. Fasching, Peter A. Flanagan, James M. Fortner, Renee T. Machackova, Eva Friedman, Eitan Ganz, Patricia A. Garber, Judy Gensini, Francesca Giles, Graham G. Glendon, Gord Godwin, Andrew K. Goodman, Marc T. Greene, Mark H. Gronwald, Jacek Hahnen, Eric Haiman, Christopher A. Hakansson, Niclas Hamann, Ute Hansen, Thomas V. O. Harris, Holly R. Hartman, Mikael Heitz, Florian Hildebrandt, Michelle A. T. Hogdall, Estrid Hogdall, Claus K. Hopper, John L. Huang, Ruea-Yea Huff, Chad Hulick, Peter J. Huntsman, David G. Imyanitov, Evgeny N. Isaacs, Claudine Jakubowska, Anna James, Paul A. Janavicius, Ramunas Jensen, Allan Johannsson, Oskar Th. John, Esther M. Jones, Michael E. Kang, Daehee Karlan, Beth Y. Karnezis, Anthony Kelemen, Linda E. Khusnutdinova, Elza Kiemeney, Lambertus A. Kim, Byoung-Gie Kjaer, Susanne K. Komenaka, Ian Kupryjanczyk, Jolanta Kurian, Allison W. Kwong, Ava Lambrechts, Diether Larson, Melissa C. Lazaro, Conxi L University of Cambridge Centre for Cancer Genetic Epidemiology Department of Public Health and Primary Care Cambridge UK University of Cambridge Centre for Cancer Genetic Epidemiology Department of Oncology Cambridge UK Center for Bioinformatics and Functional Genomics Cedars-Sinai Medical Center Los Angeles CA USA Radboud University Medical Center Radboud Institute for Health Sciences Nijmegen The Netherlands Netherlands Comprehensive Cancer Organisation Utrecht The Netherlands The Netherlands Cancer Institute—Antoni van Leeuwenhoek hospital Family Cancer Clinic Amsterdam The Netherlands Veneto Institute of Oncology IOV—IRCCS Immunology and Molecular Oncology Unit Padua Italy Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital Fred A. Litwin Center for Cancer Genetics Toronto ON Canada University of Toronto Department of Molecular Genetics Toronto ON Canada University of California Irvine Department of Epidemiology Genetic Epidemiology Research Institute Irvine CA USA N.N. Alexandrov Research Institute of Oncology and Medical Radiology Minsk Belarus ‘Agii Anargiri’ Cancer Hospital Athens Greece University of Texas MD Anderson Cancer Center Department of Breast Medical Oncology Houston TX USA Lund University Department of Cancer Epidemiology Clinical Sciences Lund Sweden Vall d’Hebron Institute of Oncology Hereditary cancer Genetics Group Barcelona Spain University Hospital of Vall d’Hebron Department of Medical Oncology Barcelona Spain Rutgers Cancer Institute of New Jersey Cancer Prevention and Control Program New Brunswick NJ USA Landspitali University Hospital Department of Pathology Reykjavik Iceland University of Iceland BMC (Biomedical Centre) Faculty of Medicine Reykjavik Iceland University Hospital Erlangen Friedrich-Alexander-University Erlangen-Nuremberg Department of Gynecology and Obstetrics Comprehensive Cancer Center ER-EMN Erlangen Germany Vanderbilt University School of Medicine Division of Epidemiology Department

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

关键词： Clinical genetics Genetic markers Risk factors Biomedicine general Human Genetics Bioinformatics Gene Expression Cytogenetics

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Free vibration of orthotropic Levy-type solution plates by using SEM

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IOP Conference Series: Materials Science and Engineering 2019年第1期615卷

作者： S Kiryu S W Alisjahbana I Alisjahbana A L Han B S Gan Department of Architecture Graduate School of Engineering Nihon University Koriyama Japan Faculty of Engineering and Informatics Bakrie University Jakarta Indonesia Department of Civil and Environmental Engineering Master Program Student Stanford University California USA Civil Engineering Department Faculty of Engineering Universitas Diponegoro Semarang Indonesia Department of Architecture College of Engineering Nihon University Koriyama Japan

Orthotropic Levy-type solution plates considering shear deformation were solved by using the Spectral Element Method (SEM). In SEM, the exact solution of structural dynamic related problems can be solved by using the frequency-dependent shape functions. The solutions of SEM are accurate in decreasing the amount of Degree Of Freedoms (DOF) to discard the cost and computational disadvantages in the Finite Element Method (FEM). This study investigates the free vibration problems of orthotropic Levy-type solution plates solutions based on the two variable Refined Plate Theory (RPT). SEM for orthotropic Levy-type solution plates in the frequency domain was formulated to solve free vibration problems. The differential governing equations of the orthotropic plate element in SEM are formulated into the form of transcendental stiffness matrices. The boundary conditions of the spectral element model consist of four edge-type DOFs at each side of the orthotropic Levy-type solution plates. The natural frequencies of the plate are calculated by means of the Wittrick-Williams procedure. The numerical investigations are presented to show the accuracy, efficiency, and effectiveness of SEM without any discretization scheme.

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Physics performance of the large-sized telescope prototype of the cherenkov telescope array

arXiv

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arXiv 2021年

作者： López-Coto, R. Moralejo, A. Artero, M. Baquero, A. Bernardos, M. Contreras, J.L. Di Pierro, F. García, E. Kerszberg, D. López-Moya, M. MasAguilar, A. Morcuende, D. Noethe, M. Nozaki, S. Ohtani, Y. Priyadarshi, C. Suda, Y. Vuillaume, T. Abe, H. Aguasca, A. Agudo, I. Antonelli, L.A. Aramo, C. Armstrong, T. Artero, M. Asano, K. Ashkar, H. Aubert, P. Baktash, A. Bamba, A. Larriva, A. Baquero Baroncelli, L. de Almeida, U. Barres Barrio, J.A. Batkovic, I. González, J. Becerra Bernardos, M.I. Berti, A. Biederbeck, N. Bigongiari, C. Blanch, O. Bonnoli, G. Bordas, P. Bose, D. Bulgarelli, A. Burelli, I. Buscemi, M. Cardillo, M. Caroff, S. Carosi, A. Cassol, F. Cerruti, M. Chai, Y. Cheng, K. Chikawa, M. Chytka, L. Contreras, J.L. Cortina, J. Costantini, H. Dalchenko, M. de Angelis, A. de Bony de Lavergne, M. Deleglise, G. Delgado, C. Delgado Mengual, J. della Volpe, D. Depaoli, D. Di Venere, L. Díaz, C. Dominik, R.M. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsässer, D. Emery, G. Escudero, J. Fiasson, A. Foffano, L. Fonseca, M.V. Coromina, L. Freixas Fukami, S. Fukazawa, Y. Garcia, E. Garcia López, R. Giglietto, N. Giordano, F. Gliwny, P. Godinovic, N. Green, D. Grespan, P. Gunji, S. Hackfeld, J. Hadasch, D. Hahn, A. Hassan, T. Hayashi, lo K. Heckmann, L. Heller, M. Llorente, J. Herrera Hirotani, K. Hoffmann, D. Horns, D. Houles, J. Hrabovsky, M. Hrupec, D. Hui, D. Hütten, M. Inada, T. Inome, Y. Iori, M. Ishio, K. Iwamura, Y. Jacquemont, M. Martinez, I. Jimenez Jouvin, L. Jurysek, J. Kagaya, M. Karas, V. Katagiri, H. Kataoka, J. Kerszberg, D. Kobayashi, Y. Kong, A. Kubo, H. Kushida, J. Lamanna, G. Lamastra, A. Le Flour, T. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Luque-Escamilla, P.L. Majumdar, P. Makariev, M. Mandat, D. Manganaro, M. Mannheim, K. Mariotti, M. Marquez, P. Marsella, G. Martí, J. Martinez, O. Martínez, G. Martínez, M. Marusevec, P. Mas, A. Maurin, G. Mazin, D. Guillen, E. Mestre Micanovic, S. Istituto Nazionale di Fisica Nucleare Sezione di Padova PadovaI-35131 Italy Instituto de Astrofísica de Andalucía CSIC Granada18080 Spain 08193 Spain IPARCOS Department of EMFTEL Universidad Complutense de Madrid MadridE-28040 Spain Università degli Studi di Padova Via Marzolo 8 Padova35131 Italy INFN Sezione di Torino via P. Giuria 1 Torino10125 Italy LAPP Univ. Grenoble Alpes Univ. Savoie Mont Blanc CNRS-IN2P3 Annecy74000 France 9 Chemin de Bellevue - BP 110 Annecy Cedex74941 France Department of Physics TU Dortmund University Otto-Hahn-Str. 4 Dortmund44221 Germany Division of Physics and Astronomy Graduate School of Science Kyoto University Sakyoku Kyoto606-8502 Japan Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-ha Chiba Kashiwa277-8582 Japan Max-Planck-Institut für Physik München80805 Germany Institute for Cosmic Ray Research University of Tokyo Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Instituto de Astrofísica de Andalucía-CSIC INAF - Osservatorio Astronomico di Roma INFN Sezione di Napoli Aix Marseille Univ CNRS/IN2P3 CPPM Barcelona Institute of Science and Technology IRFU CEA Université Paris-Saclay LAPP Univ. Grenoble Alpes Univ. Savoie Mont Blanc CNRS-IN2P3 Annecy France Universität Hamburg Institut für Experimentalphysik Graduate School of Science University of Tokyo EMFTEL department IPARCOS Universidad Complutense de Madrid INAF - Osservatorio di Astrofisica e Scienza dello spazio di Bologna Centro Brasileiro de Pesquisas Físicas INFN Sezione di Padova Università degli Studi di Padova Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Max-Planck-Institut für Physik Department of Physics TU Dortmund University Saha Institute of Nuclear Physics INFN Sezione di Trieste Università degli Studi di Udine INFN Sezione di Catania University of Geneva Département de physique nucléaire et corpusculaire P

The Large-Sized Telescope (LST) prototype of the future Cherenkov Telescope Array (CTA) is located at the Northern site of CTA, on the Canary Island of La Palma. It is designed to provide optimal performance in the lowest part of the energy range covered by CTA, observing gamma rays down to energies of tens of GeV. The LST prototype started performing astronomical observations in November 2019 during the commissioning of the telescope and it has been taking data since then. In this contribution, we will present the tuning of the characteristics of the telescope in the Monte Carlo (MC) simulations to describe the data obtained, the estimation of its angular and energy resolution, and an evaluation of its sensitivity, both with simulations and with observations of the Crab Nebula. © 2021, CC BY.

关键词： Telescopes

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