检索结果-内蒙古大学图书馆

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

引用

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

关键词：

来源：评论

学校读者我要写书评

暂无评论

Middle East and North African Health informatics Association (MENAHIA): A New Opportunity for the Region

引用

Yearbook of Medical informatics 2019年第1期28卷 292-296页

作者： Riyad Alshammari Najeeb Al-Shorbaji Zakiuddin Ahmed Zaid Al-Hamadan Abdulwahhab Alshammari Osama El Hassan Dari Alhuwail Salim Al Salmi Eiman Al-Jafar Hassan Ghazal College of Public Health and Health Informatics King Saud bin Abdulaziz University for Health Sciences Riyadh Saudi Arabia King Abdullah International Medical Research Center Riyadh Saudi Arabia Ministry of the National Guard- Health Affairs Riyadh Saudi Arabia President of the Saudi Health Informatics Association President of the eHealth Development Association of Jordan Program Director RAHAH King Saud University Project Director Riphah Institute of Health Improvement & Safety CEO Digital Care Pakistan Associate Professor Jordan University of Science and Technology College of Applied Medical Sciences King Saud bin Abdulaziz University for Health Sciences Riyadh Saudi Arabia Vice-Chair of Emirates Health Informatics Society Head of eHealth section at Dubai Health Authority Dubai United Arab Emirates Department of Information Science College of Computing Sciences and Engineering Kuwait University Kuwait Health Informatics Unit Dasman Diabetes Institute Kuwait Associate Deanship for Health Information Management Program Oman College of Health Sciences Muscat Sultanate of Oman Department of Health Informatics and Information Management Faculty of Allied Health Sciences Kuwait University Kuwait. National Center for Scientific and Technological Research Rabat and President of the Moroccan Society for Telemedicine and eHealth Rabat Morocco

During the 2018 IMIA General Assembly (GA) held on Oct 2018 in Sri Lanka, a new organization, the Middle East and North African Health informatics Association (MENAHIA) was established as a regional non-governmental organization to promote Health informatics in the region. Health informatics activities in applications, education, and research have been growing in the Middle East and North African region for many years. Over the past year, health informatics initiatives within the region focused on the education sector and the workforce. The need to enhance the education delivery and methods is essential in promoting Health informatics in the region as well as establishing master programs in many countries within the region. This paper provides an overview of the variety of initiatives that are occurring in the region and are endorsed by MENAHIA.

关键词： Saudi Arabia Pakistan Jordan United Arab Emirates Morocco Kuwait Oman Bahrain Health informatics the Middle East

来源：评论

学校读者我要写书评

暂无评论

Multiwavelength characterization of two flaring blazars: insight into the emission region of intermediate-synchrotron-peaked BL Lacs 38

Multiwavelength characterization of two flaring blazars: ins...

引用

38th International Cosmic Ray Conference, ICRC 2023

作者： Loporchio, S. Bonnoli, G. Cerasole, D. Di Venere, L. Dominis Prester, D. Giordano, F. Lindfors, E. Manganaro, M. Pavletić, L. Abe, H. Abe, S. Abhir, J. Acciari, V.A. Agudo, I. Aniello, T. Ansoldi, S. Antonelli, L.A. Arbet Engels, A. Arcaro, C. Artero, M. Asano, K. Baack, D. Babić, A. Baquero, A. Barres de Almeida, U. Barrio, J.A. Batković, I. Baxter, J. Be-Cerra González, J. Bednarek, W. Bernardini, E. Bernardos, M. Bernete, J. Berti, A. Besenrieder, J. Bigongiari, C. Biland, A. Blanch, O. Bošnjak, Ž. Burelli, I. Busetto, G. Campoy-Ordaz, A. Carosi, A. Carosi, R. Carretero-Castrillo, M. Castro-Tirado, A.J. Ceribella, G. Chai, Y. Chilingarian, A. Cifuentes, A. Cikota, S. Colombo, E. Contreras, J.L. Cortina, J. Covino, S. D’Amico, G. D’Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. De Lotto, B. Del Popolo, A. Delfino, M. Delgado, J. Delgado Mendez, C. Depaoli, D. Di Pierro, F. Donini, A. Dorner, D. Doro, M. Elsaesser, D. Emery, G. Escudero, J. Fariña, L. Fattorini, A. Foffano, L. Font, L. Fröse, S. Fukami, S. Fukazawa, Y. García López, R.J. Garczarczyk, M. Gasparyan, S. Gaug, M. GiesbrechtPaiva, J.G. Giglietto, N. Gliwny, P. Godinović, N. Grau, R. Green, D. Green, J.G. Hadasch, D. Hahn, A. Hassan, T. Heckmann, L. Herrera, J. Hrupec, D. Hütten, M. Imazawa, R. Inada, T. Iotov, R. Ishio, K. Jiménez Martínez, I. Jormanainen, J. Kerszberg, D. Kluge, G.W. Kobayashi, Y. Kouch, P.M. Kubo, H. Kushida, J. LáinezLezáun, M. Lamastra, A. Lelas, D. Leone, F. Linhoff, L. Lombardi, S. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Lorini, A. Lyard, E. Machado de Oliveira Fraga, B. Majumdar, P. Makariev, M. Maneva, G. Mang, N. Mangano, S. Mannheim, K. Mariotti, M. Martínez, M. Martínez-Chicharro, M. Mas-Aguilar, A. Mazin, D. Menchiari, S. Mender, S. Mićanović, S. Miceli, D. Miener, T. Miranda, J.M. Mirzoyan, R. Molero González, M. Molina, E. Mondal, H.A. Moralejo, A. Morcuende, D. Nakamori, T. Nanci, C. Nava, L. Neustroev, V. The University of Tokyo Kashiwa Chiba277-8582 Japan ETH Zürich ZürichCH-8093 Switzerland Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna Tenerife La LagunaE-38200 Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain RomeI-00136 Italy Università di Udine INFN Trieste UdineI-33100 Italy Max-Planck-Institut für Physik MünchenD-80805 Germany Università di Padova INFN PadovaI-35131 Italy Bellaterra BarcelonaE-08193 Spain Technische Universität Dortmund DortmundD-44221 Germany Zagreb10000 Croatia IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain URCA RJ Rio de Janeiro22290-180 Brazil University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz90-236 Poland Centro de Investigaciones Energéticas Medioambientales y Tecnológicas MadridE-28040 Spain Departament de Física CERES-IEEC Universitat Autònoma de Barcelona BellaterraE-08193 Spain Università di Pisa INFN Pisa PisaI-56126 Italy Universitat de Barcelona ICCUB IEEC-UB BarcelonaE-08028 Spain Armenian MAGIC Group A. Alikhanyan National Science Laboratory Yerevan0036 Armenia Department for Physics and Technology University of Bergen Norway INFN MAGIC Group INFN Sezione di Catania Dipartimento di Fisica e Astronomia University of Catania CataniaI-95123 Italy INFN MAGIC Group INFN Sezione di Torino Università degli Studi di Torino TorinoI-10125 Italy INFN MAGIC Group INFN Sezione di Bari Dipartimento Interateneo di Fisica dell’Università e del Politecnico di Bari BariI-70125 Italy Croatian MAGIC Group University of Rijeka Faculty of Physics Rijeka51000 Croatia Universität Würzburg WürzburgD-97074 Germany University of Geneva Chemin d’Ecogia 16 VersoixCH-1290 Switzerland Japanese MAGIC Group: Physics Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima739-8526 Japan Ze

The blazars B2 1811+31 and GB6 J1058+2817 were found to be in flaring state during 2020 and 2021, respectively. The high states of the sources were registered by the Fermi-LAT at energies below 100 GeV, triggering observations at higher energies with the MAGIC telescopes, in the UV/X rays with the Swift satellite and with ground-based radio and optical telescopes. The observations in the very-high-energy (VHE, 100 GeV © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Synchrotrons

来源：评论

学校读者我要写书评

暂无评论

Ten quick tips for deep learning in biology

arXiv

引用

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

来源：评论

学校读者我要写书评

暂无评论

Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries (vol 55, pg 89, 2023)

引用

NATURE GENETICS 2023年第3期55卷 519-520页

作者： Fernandez-Rozadilla, Ceres Timofeeva, Maria Chen, Zhishan Law, Philip Thomas, Minta Schmit, Stephanie Diez-Obrero, Virginia Hsu, Li Fernandez-Tajes, Juan Palles, Claire Sherwood, Kitty Briggs, Sarah Svinti, Victoria Donnelly, Kevin Farrington, Susan Blackmur, James Vaughan-Shaw, Peter Shu, Xiao-ou Long, Jirong Cai, Qiuyin Guo, Xingyi Lu, Yingchang Broderick, Peter Studd, James Huyghe, Jeroen Harrison, Tabitha Conti, David Dampier, Christopher Devall, Mathew Schumacher, Fredrick Melas, Marilena Rennert, Gad Obon-Santacana, Mireia Martin-Sanchez, Vicente Moratalla-Navarro, Ferran Oh, Jae Hwan Kim, Jeongseon Jee, Sun Ha Jung, Keum Ji Kweon, Sun-Seog Shin, Min-Ho Shin, Aesun Ahn, Yoon-Ok Kim, Dong-Hyun Oze, Isao Wen, Wanqing Matsuo, Keitaro Matsuda, Koichi Tanikawa, Chizu Ren, Zefang Gao, Yu-Tang Jia, Wei-Hua Hopper, John Jenkins, Mark Win, Aung Ko Pai, Rish Figueiredo, Jane Haile, Robert Gallinger, Steven Woods, Michael Newcomb, Polly Duggan, David Cheadle, Jeremy Kaplan, Richard Maughan, Timothy Kerr, Rachel Kerr, David Kirac, Iva Bohm, Jan Mecklin, Lukka-Pekka Jousilahti, Pekka Knekt, Paul Aaltonen, Lauri Rissanen, Harri Pukkala, Eero Eriksson, Johan Cajuso, Tatiana Hanninen, Ulrika Kondelin, Johanna Palin, Kimmo Tanskanen, Tomas Renkonen-Sinisalo, Laura Zanke, Brent Mannisto, Satu Albanes, Demetrius Weinstein, Stephanie Ruiz-Narvaez, Edward Palmer, Julie Buchanan, Daniel Platz, Elizabeth Visvanathan, Kala Ulrich, Cornelia Siegel, Erin Brezina, Stefanie Gsur, Andrea Campbell, Peter Chang-Claude, Jenny Hoffmeister, Michael Brenner, Hermann Slattery, Martha Potter, John Tsilidis, Konstantinos Schulze, Matthias Gunter, Marc Murphy, Neil Castells, Antoni Castellvi-Bel, Sergi Moreira, Leticia Arndt, Volker Shcherbina, Anna Stern, Mariana Pardamean, Bens Bishop, Timothy Giles, Graham Southey, Melissa Idos, Gregory McDonnell, Kevin Abu-Ful, Zomoroda Greenson, Joel Shulman, Katerina Lejbkowicz, Flavio Offit, Kenneth Su, Yu-Ru Steinfelder, Robert Keku, Temitope van Guelpen, Bethany Hudson, Thomas Hampel, Heather Pearlman, 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 Department of Populat

Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and east Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high-confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Crosstissue analyses indicated that over a third of effector genes most probably act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies.

关键词： Colorectal cancer Epigenomics Genome-wide association studies Transcriptomics

来源：评论

学校读者我要写书评

暂无评论

Escada: Predicting Virtual Machine Network Bandwidth Demands for Elastic Provisioning in IaaS Clouds 4

Escada: Predicting Virtual Machine Network Bandwidth Demands...

引用

4th IEEE International Conference on Cloud and Autonomic computing, ICCAC 2017

作者： Marques, Jonatas Adilson Obelheiro, Rafael Rodrigues Institute of Informatics Federal University of Rio Grande Do sul Porto Alegre Brazil Graduate Program in Applied Computing Department of Computer Science Santa Catarina State University Joinville Brazil

ISBN: (纸本)9781538619391

In Infrastructure as a Service clouds, customers lease virtual resources (e.g., CPU, memory, network) offered by cloud providers, paying for the allocated capacity of resources, regardless of their effective use. In this context, it is in the interest of the customers to reserve resources with sufficient capacity so that their applications achieve good performance while, at the same time, minimizing their expenses with idle capacities. The correct provisioning of resources is also invaluable to providers, who seek to maximize the resource usage of their physical infrastructures, avoiding spending maintenance costs with unused hardware such as high capacity servers and networking devices. We introduce Escada, a novel model for network bandwidth prediction to guide the provisioning of virtual machines. Escada is application-oblivious and dynamically adapts to changes in a virtual machine workload profile. The network flows of a virtual machine are monitored and used to estimate its total required bandwidth over a time period. A prediction algorithm is then applied to the entire history of estimates to predict the virtual machine future required bandwidth. Our experimental evaluation shows that the estimates provided by Escada are useful for guiding the prediction of network bandwidth requirements, providing accurate bandwidth estimates even when the network is under-provisioned. Furthermore, Escada correctly adjusts its prediction algorithm faster than the state-of-the-art model and predicts more reliably during the adjusting period. © 2017 IEEE.

关键词： Virtual machine

来源：评论

学校读者我要写书评

暂无评论

Development of an advanced SiPM camera for the large size telescope of the Cherenkov telescope array observatory

arXiv

引用

arXiv 2021年

作者： Heller, Matthieu Armstrong, T. Bellato, M. Bergnoli, A. Bernardos, M. Bernasconi, E. Biland, A. Charbon, E. Corti, D. Dalchenko, M. della Volpe, D. Depaoli, D. Di Pierro, F. Emery, G. Gascón, D. Gómez, S. López-Coto, R. Mariotti, M. Miranda, L.D.M. Montaruli, T. Nagai, A. Rando, R. Saito, T. Tajima, H. Zietara, K. 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 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. DPNC - Université de Genève 24 Quai Ernest Ansermet GenèveCH-1211 Switzerland Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France INFN Sezione di Padova Via Marzolo Padova8 - 35131 Italy INFN Sezione di Torino via P. Giuria Torino1 - 10125 Italy Università degli Studi di Torino Dipartimento di Fisica via P. Giuria Torino1 - 10125 Italy Institute for Space–Earth Environmental Research and Kobayashi–Maskawa Institute for the Origin of Particles and the Universe Nagoya University Nagoya464-8601 Japan AQUA EPFL Neuchâtel Switzerland ETH Zurich Institute for Particle Physics Otto-Stern-Weg 5 Zurich8093 Switzerland Institute of Cosmos Sciencies - University of Barcelona Martí i Franquès 1 Barcelona08028 Spain Institute for Cosmic Ray Research The University of Tokyo Japan Astronomical Observatory Jagiellonian University ul. Orla 171 Kraków30-244 Poland 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 The 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 nucléair

Silicon photomultipliers (SiPMs) have become the baseline choice for cameras of the small-sized telescopes (SSTs) of the Cherenkov Telescope Array (CTA). On the other hand, SiPMs are relatively new to the field and covering large surfaces and operating at high data rates still are challenges to outperform photomultipliers (PMTs). The higher sensitivity in the near infra-red and longer signals compared to PMTs result in higher night sky background rate for SiPMs. However, the robustness of the SiPMs represents a unique opportunity to ensure long-term operation with low maintenance and better duty cycle than PMTs. The proposed camera for large size telescopes will feature 0.05◦ pixels, low power and fast front-end electronics and a fully digital readout. In this work, we present the status of dedicated simulations and data analysis for the performance estimation. The design features and the different strategies identified, so far, to tackle the demanding requirements and the improved performance are described. Copyright © 2021, The Authors. All rights reserved.

关键词： Photomultipliers

来源：评论

学校读者我要写书评

暂无评论

Deep-learning-driven event reconstruction applied to simulated data from a single Large-Sized Telescope of CTA

arXiv

引用

arXiv 2021年

作者： Grespan, Pietro Jacquemont, Mikael López-Coto, Rubèn Miener, Tjark Nieto-Castaño, Daniel Vuillaume, Thomas 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, Pietro Gunji, S. Hackfeld, J. Hadasch, D. Hahn, A. Hassan, T. Hayashi, Lo 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, Mikael 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, Rubèn 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, Tjark Miranda, J.M. Miranda, L.D.M. Mirzoyan, R. Mizuno, T. Molina, E. Montaruli, T. Monteiro, I. Moralejo, A. Istituto Nazionale di Fisica Nucleare Sezione di Padova PadovaI-35131 Italy 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 Polytech Annecy-Chambéry 5 chemin de bellevue Annecy74940 France Instituto de Física de Partículas y del Cosmos Departamento de EMFTEL Universidad Complutense de Madrid Madrid Spain 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 The 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 d

When very-high-energy gamma rays interact high in the Earth’s atmosphere, they produce cascades of particles that induce flashes of Cherenkov light. Imaging Atmospheric Cherenkov Telescopes (IACTs) detect these flashes and convert them into shower images that can be analyzed to extract the properties of the primary gamma ray. The dominant background for IACTs is comprised of air shower images produced by cosmic hadrons, with typical noise-to-signal ratios of several orders of magnitude. The standard technique adopted to differentiate between images initiated by gamma rays and those initiated by hadrons is based on classical machine learning algorithms, such as Random Forests, that operate on a set of handcrafted parameters extracted from the images. Likewise, the inference of the energy and the arrival direction of the primary gamma ray is performed using those parameters. State-of-the-art deep learning techniques based on convolutional neural networks (CNNs) have the potential to enhance the event reconstruction performance, since they are able to autonomously extract features from raw images, exploiting the pixel-wise information washed out during the parametrization process. Here we present the results obtained by applying deep learning techniques to the reconstruction of Monte Carlo simulated events from a single, next-generation IACT, the Large-Sized Telescope (LST) of the Cherenkov Telescope Array (CTA). We use CNNs to separate the gamma-ray-induced events from hadronic events and to reconstruct the properties of the former, comparing their performance to the standard reconstruction technique. Three independent implementations of CNN-based event reconstruction models have been utilized in this work, producing consistent results. © 2021, CC BY-SA.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Long term study of the blazar S5 0716+714: investigating a turbulent jet at all wavelengths 38

Long term study of the blazar S5 0716+714: investigating a t...

引用

38th International Cosmic Ray Conference, ICRC 2023

作者： Podobnik, F. Manganaro, M. Jormanainen, J. Lindfors, E. Bonnoli, G. Paoletti, R. Jorstad, S. Kiehlmann, S. Agudo, I. Elsasser, D. Lorey, C. Raiteri, C. Villata, M. Redhead, A.C. Marscher, A. Abe, H. Abe, S. Abhir, J. Acciari, V.A. Aniello, T. Ansoldi, S. Antonelli, L.A. Arbet Engels, A. Arcaro, C. Artero, M. Asano, K. Baack, D. Babić, A. Baquero, A. Barres de Almeida, U. Barrio, J.A. Batković, I. Baxter, J. Becerra González, J. Bednarek, W. Bernardini, E. Bernardos, M. Bernete, J. Berti, A. Besenrieder, J. Bigongiari, C. Biland, A. Blanch, O. Bošnjak, Ž. Burelli, I. Busetto, G. Campoy-Ordaz, A. Carosi, A. Carosi, R. Carretero-Castrillo, M. Castro-Tirado, A.J. Ceribella, G. Chai, Y. Chilingarian, A. Cifuentes, A. Cikota, S. Colombo, E. Contreras, J.L. Cortina, J. Covino, S. D’Amico, G. D’Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. De Lotto, B. Del Popolo, A. Delfino, M. Delgado, J. Delgado Mendez, C. Depaoli, D. Di Pierro, F. Di Venere, L. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsaesser, D. Emery, G. Escudero, J. Fariña, L. Fattorini, A. Foffano, L. Font, L. Fröse, S. Fukami, S. Fukazawa, Y. García López, R.J. Garczarczyk, M. Gasparyan, S. Gaug, M. Giesbrecht Paiva, J.G. Giglietto, N. Giordano, F. Gliwny, P. Godinović, N. Grau, R. Green, D. Green, J.G. Hadasch, D. Hahn, A. Hassan, T. Heckmann, L. Herrera, J. Hrupec, D. Hütten, M. Imazawa, R. Inada, T. Iotov, R. Ishio, K. Jiménez Martínez, I. Kerszberg, D. Kluge, G.W. Kobayashi, Y. Kouch, P.M. Kubo, H. Kushida, J. Láinez Lezáun, M. Lamastra, A. Lelas, D. Leone, F. Linhoff, L. Lombardi, S. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Loporchio, S. Lorini, A. Lyard, E. Machado de Oliveira Fraga, B. Majumdar, P. Makariev, M. Maneva, G. Mang, N. Manganaro, M. Mangano, S. Mannheim, K. Mariotti, M. Martínez, M. Martínez-Chicharro, M. Mas-Aguilar, A. Mazin, D. Menchiari, S. Mender, S. Mićanović, S. Miceli, D. Miener, T. Miranda, J.M. Università di Siena INFN Pisa Via Roma 56 SienaI-53100 Italy Faculty of Physics University of Rijeka Radmile Matječić 2 Rijeka51000 Croatia Finnish MAGIC Group Finnish Centre for Astronomy with ESO University of Turku TurkuFI-20014 Finland RomeI-00136 Italy Institute of Astrophysics Foundation for Research and Technology-Hellas HeraklionGR-71110 Greece Instituto de Astrofisica de Andalucia-CSIC Glorieta de la Astronomía Granada18008 Spain Department of Physics Otto-Hahn-Str. 4a Dortmund44227 Germany Hans-Haffner-Sternwarte Naturwissenschaftliches Labor für Schüler am FKG Friedrich-Koenig-Gymnasium WürzburgD-97082 Germany INAF Osservatorio Astrofisico di Torino via Osservatorio 20 Pino TorineseI-10025 Italy Caltech The Division of Physics Mathematics and Astronomy 1200 E California Blvd PasadenaCA91125 United States Institute for Astrophysical Research Boston University 725 Commonwealth Avenue BostonMA02215 United States The University of Tokyo Kashiwa Chiba 277-8582 Japan ETH Zürich ZürichCH-8093 Switzerland Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna Tenerife La LagunaE-38200 Spain Università di Udine INFN Trieste UdineI-33100 Italy Max-Planck-Institut für Physik MünchenD-80805 Germany Università di Padova INFN PadovaI-35131 Italy Bellaterra BarcelonaE-08193 Spain Technische Universität Dortmund DortmundD-44221 Germany Zagreb10000 Croatia IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain URCA RJ Rio de Janeiro22290-180 Brazil University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz90-236 Poland Centro de Investigaciones Energéticas Medioambientales y Tecnológicas MadridE-28040 Spain Departament de Física CERES-IEEC Universitat Autònoma de Barcelona BellaterraE-08193 Spain Università di Pisa INFN Pisa PisaI-56126 Italy Universitat de Barcelona ICCUB IEEC-UB BarcelonaE-08028 S

The blazar S5 0716+714 is an intermediate BL Lacertae object remarkable for its variability in many energy bands. It was discovered by MAGIC in the very-high-energy (VHE) gamma-ray range in 2008. Later in 2015 an impressive electric vector polarization angle (EVPA) swing was detected in connection with a multiwavelength flaring event including the VHE gamma-ray band. This generated interest in further studies of the jet of this source and its electromagnetic emission at all wavelengths. Since then, MAGIC has monitored the source in coordination with other observatories and here we present the long-term study using data from 2015 to 2022 in a MWL context. The data set also includes the extraordinary flaring activity of 2017, so far the historical maximum detected for this source in the optical and VHE gamma-ray band. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Gamma rays

来源：评论

学校读者我要写书评

暂无评论

The Cosmic-ray Electron and Positron Spectrum Measured with MAGIC 38

The Cosmic-ray Electron and Positron Spectrum Measured with ...

引用

38th International Cosmic Ray Conference, ICRC 2023

作者： Chai, Yating Ishio, Kazuma Kerszberg, Daniel Mangano, Salvatore Abe, H. Abe, S. Abhir, J. Acciari, V.A. Agudo, I. Aniello, T. Ansoldi, S. Antonelli, L.A. Arbet Engels, A. Arcaro, C. Artero, M. Asano, K. Baack, D. Babić, A. Baquero, A. Barres de Almeida, U. Barrio, J.A. Batković, I. Baxter, J. Becerra González, J. Bednarek, W. Bernardini, E. Bernardos, M. Bernete, J. Berti, A. Besenrieder, J. Bigongiari, C. Biland, A. Blanch, O. Bonnoli, G. Bošnjak, Ž. Burelli, I. Busetto, G. Campoy-Ordaz, A. Carosi, A. Carosi, R. Carretero-Castrillo, M. Castro-Tirado, A.J. Ceribella, G. Chai, Y. Chilingarian, A. Cifuentes, A. Cikota, S. Colombo, E. Contreras, J.L. Cortina, J. Covino, S. D’Amico, G. D’Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. De Lotto, B. Del Popolo, A. Delfino, M. Delgado, J. Delgado Mendez, C. Depaoli, D. Di Pierro, F. Di Venere, L. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsaesser, D. Emery, G. Escudero, J. Fariña, L. Fattorini, A. Foffano, L. Font, L. Fröse, S. Fukami, S. Fukazawa, Y. García López, R.J. Garczarczyk, M. Gasparyan, S. Gaug, M. Giesbrecht Paiva, J.G. Giglietto, N. Giordano, F. Gliwny, P. Godinović, N. Grau, R. Green, D. Green, J.G. Hadasch, D. Hahn, A. Hassan, T. Heckmann, L. Herrera, J. Hrupec, D. Hütten, M. Imazawa, R. Inada, T. Iotov, R. Ishio, K. Jiménez Martínez, I. Jormanainen, J. Kerszberg, D. Kluge, G.W. Kobayashi, Y. Kouch, P.M. Kubo, H. Kushida, J. Láinez Lezáun, M. Lamastra, A. Lelas, D. Leone, F. Lindfors, E. Linhoff, L. Lombardi, S. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Loporchio, S. Lorini, A. Lyard, E. Machado de Oliveira Fraga, B. Majumdar, P. Makariev, M. Maneva, G. Mang, N. Manganaro, M. Mangano, S. Mannheim, K. Mariotti, M. Martínez, M. Martínez-Chicharro, M. Mas-Aguilar, A. Mazin, D. Menchiari, S. Mender, S. Mićanović, S. Miceli, D. Miener, T. Miranda, J.M. Mirzoyan, R. Molero González, M. Molina, E. Mondal, H.A. Moralejo, A. Morcuende, D. Nakamori, T. Nanci, C. Nava, L. Max-Planck-Institut für Physik Föhringer Ring 6 München80805 Germany Wydzial Fizyki Astronomii i Informatyki Stosowanej Institut Astronomii Uniwersytet Mikolaja Kopernika w Toruniu Piwnice k. Torunia Lysomice87-148 Poland Institut de Física d’Altes Energies Edifici Cn Campus UAB Barcelona Bellaterra08193 Spain Centro de Investigaciones Energéticas Medioambientales y Tecnológicas Avda. Complutense 40 Madrid28.040 Spain The University of Tokyo Kashiwa Chiba277-8582 Japan ETH Zürich ZürichCH-8093 Switzerland Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna Tenerife La LagunaE-38200 Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain RomeI-00136 Italy Università di Udine INFN Trieste UdineI-33100 Italy Università di Padova INFN PadovaI-35131 Italy Barcelona BellaterraE-08193 Spain Technische Universität Dortmund DortmundD-44221 Germany Zagreb10000 Croatia IPARCOS Institute EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain URCA RJ Rio de Janeiro22290-180 Brazil University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics Lodz90-236 Poland Centro de Investigaciones Energéticas Medioambientales y Tecnológicas MadridE-28040 Spain Departament de Física CERES-IEEC Universitat Autònoma de Barcelona BellaterraE-08193 Spain Università di Pisa INFN Pisa PisaI-56126 Italy Universitat de Barcelona ICCUB IEEC-UB BarcelonaE-08028 Spain Armenian MAGIC Group A. Alikhanyan National Science Laboratory Yerevan0036 Armenia Department for Physics and Technology University of Bergen Norway INFN MAGIC Group INFN Sezione di Catania Dipartimento di Fisica e Astronomia University of Catania CataniaI-95123 Italy INFN MAGIC Group INFN Sezione di Torino Università degli Studi di Torino TorinoI-10125 Italy INFN MAGIC Group INFN Sezione di Bari Dipartimento Interateneo di Fisica Università e del Politecn

Cosmic-ray electrons and positrons (CREs) of TeV energies suffer severe energy loss during propagation due to inverse Compton scattering and synchrotron radiation process, they are therefore very useful to constrain the local cosmic-ray sources in the Galaxy. The ability to measure CREs by ground-based imaging atmospheric Cherenkov telescopes (IACTs) has been demonstrated in the past. In this proceeding, we will present two methods – a template fit method and a tight cut method based on a two-steps-trained Random Forest (RF) – optimized for the detection and study of CREs and will report on the measurement of the CREs energy spectrum from 300 GeV to 6 TeV with the MAGIC telescopes. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Positrons

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：