检索结果-内蒙古大学图书馆

Corrigendum to "Priorities to inform research on marine plastic pollution in Southeast Asia" [Sci. Total Environ. volume 841 (2022) Article 156704]

引用

The science of the total environment 2023年第PT 3期857卷 159595页

作者： Lucy C M Omeyer Emily M Duncan Kornrawee Aiemsomboon Nicola Beaumont Sujaree Bureekul Bin Cao Luis R Carrasco Suchana Chavanich James R Clark Muhammad R Cordova Fay Couceiro Simon M Cragg Neil Dickson Pierre Failler Gianluca Ferraro Stephen Fletcher Jenny Fong Alex T Ford Tony Gutierrez Fauziah Shahul Hamid Jan G Hiddink Pham T Hoa Sophie I Holland Lowenna Jones Nia H Jones Heather Koldewey Federico M Lauro Charlotte Lee Matt Lewis Danny Marks Sabine Matallana-Surget Claudia G Mayorga-Adame John McGeehan Lauren F Messer Laura Michie Michelle A Miller Zeeda F Mohamad Nur Hazimah Mohamed Nor Moritz Müller Simon P Neill Sarah E Nelms Deo Florence L Onda Joyce J L Ong Agamuthu Pariatamby Sui C Phang Richard Quilliam Peter E Robins Maria Salta Aida Sartimbul Shiori Shakuto Martin W Skov Evelyn B Taboada Peter A Todd Tai Chong Toh Suresh Valiyaveettil Voranop Viyakarn Passorn Wonnapinij Louisa E Wood Clara L X Yong Brendan J Godley Centre for Ecology and Conservation University of Exeter Penryn Campus Penryn Cornwall TR10 9EZ United Kingdom. Electronic address: L.C.M.Omeyer@exeter.ac.uk. Centre for Ecology and Conservation University of Exeter Penryn Campus Penryn Cornwall TR10 9EZ United Kingdom OKEANOS Universidade dos Açores Departamento de Oceanografia e Pescas 9901-862 Horta Portugal. Electronic address: emily.m.duncan@uac.pt. Department of Marine Science Faculty of Science Chulalongkorn University Bangkok 10330 Thailand. Plymouth Marine Laboratory Prospect Place The Hoe Plymouth Devon PL1 3DH United Kingdom. Singapore Centre for Environmental Life Sciences Engineering Nanyang Technological University 637551 Singapore School of Civil and Environmental Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore. Department of Biological Sciences National University of Singapore 14 Science Drive 4 117543 Singapore. Department of Marine Science Faculty of Science Chulalongkorn University Bangkok 10330 Thailand Aquatic Resources Research Institute Chulalongkorn University Bangkok 10330 Thailand. Research Centre for Oceanography Indonesian Institute of Sciences (LIPI) Jalan Pasir Putih 1 Ancol Timur Jakarta 14430 Indonesia Research Centre for Oceanography National Research and Innovation Agency (BRIN) Jalan Pasir Putih 1 Ancol Timur Jakarta 14430 Indonesia. School of Civil Engineering and Surveying Faculty of Technology University of Portsmouth Portsmouth Hampshire PO1 3AH United Kingdom. Institute of Marine Sciences University of Portsmouth Portsmouth Hampshire PO4 9LY United Kingdom Centre for Enzyme Innovation School of Biological Sciences University of Portsmouth Portsmouth Hampshire PO1 2DY United Kingdom. School of Ocean Sciences Bangor University Menai Bridge Anglesey LL59 5AB United Kingdom. Centre for Blue Governance Department of Economics and Finance University of Portsmouth Portsmouth Hampshire PO1 3DE United Kingdom. School of the E

来源：评论

学校读者我要写书评

暂无评论

KM3NeT sensitivity to a flux of down-going nuclearites 38

KM3NeT sensitivity to a flux of down-going nuclearites

引用

38th International Cosmic Ray Conference, ICRC 2023

作者： Păun, Alice Păvălaş, Gabriela Popa, Vlad Aiello, S. Albert, A. Alves Garre, S. Aly, Z. Ambrosone, A. Ameli, F. Andre, M. Androutsou, E. Anguita, M. Aphecetche, L. Ardid, M. Ardid, S. Atmani, H. Aublin, J. Bailly-Salins, L. Bardačová, Z. Baret, B. Bariego-Quintana, A. Basegmez du Pree, S. Becherini, Y. Bendahman, M. Benfenati, F. Benhassi, M. Benoit, D.M. Berbee, E. Bertin, V. Biagi, S. Boettcher, M. Bonanno, D. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzaş, H. Bretaudeau, F. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Campion, S. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chadolias, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Cocimano, R. Coelho, J.A.B. Coleiro, A. Coniglione, R. Coyle, P. Creusot, A. Cruz, A. Cuttone, G. Dallier, R. Darras, Y. De Benedittis, A. De Martino, B. Decoene, V. Del Burgo, R. Di Cerbo, U.M. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diaz, C. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Dörr, M. Drakopoulou, E. Drouhin, D. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. Enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gabriel, J. Gagliardini, S. Gal, T. García Méndez, J. Garcia Soto, A. Gatius Oliver, C. Geißelbrecht, N. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Goos, I. Goupilliere, D. Gozzini, S.R. Gracia, R. Graf, K. Guidi, C. Guillon, B. Gutiérrez, M. van Haren, H. Heijboer, A. Hekalo, A. Hennig, L. Hernández-Rey, J.J. Huang, F. Idrissi Ibnsalih, W. Illuminati, G. James, C.W. de Jong, M. de Jong, P. Jung, B.J. Kalaczyński, P. Kalekin, O. Katz, U.F. Khan Chowdhury, N.R. Khatun, A. Kistauri, G. Kopper, C. Kouchner, A. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Larosa, G. Lastoria, C. Lazo, A. Le Stum, S. Institute of Space Science Atomiştilor 409 Măgurele Romania University of Bucharest Faculty of Physics Atomiştilor 405 Măgurele Romania INFN Sezione di Catania Via Santa Sofia 64 Catania95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France c/Catedrático José Beltrán 2 Paterna Valencia46980 Spain Aix Marseille Univ CNRS IN2P3 CPPM Marseille France INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain NCSR Demokritos Institute of Nuclear and Particle Physics Ag. Paraskevi Attikis Athens15310 Greece University of Granada Dept. of Computer Architecture and Technology/CITIC Granada18071 Spain Subatech IMT Atlantique IN2P3-CNRS Université de Nantes 4 rue Alfred Kastler - La Chantrerie BP Nantes20722 44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia46730 Spain University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 RabatR.P. 10000 Morocco Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen14050 France Czech Technical University in Prague Institute of Experimental and Applied Physics Husova 240/5 Prague110 00 Czech Republic Comenius University in Bratislava Department of Nuclear Physics and Biophysics Mlynska dolina F1 Bratislava842 48 Slovakia Nikhef National Institute for Subatomic Physics PO Box 41882 Amsterdam1009 DB Netherlands INFN Sezi

Nuclearites are hypothetical, massive particles of Strange Quark Matter (SQM) introduced by E. Witten in 1984. They are composed of approximately equal quantities of up, down, and strange quarks. Due to the third quark flavor component which leads to a total energy lower than in the case of nuclear matter, SQM could represent the ground state of Quantum Chromodynamics (QCD). The detection and characterization of nuclearites could also bring important contributions to the Dark Matter physics. KM3NeT is a network of deep-sea neutrino telescopes placed in the Mediterranean Sea, optimized for the search for high-energy cosmic neutrinos (KM3NeT/ARCA) and the study of neutrino properties with atmospheric neutrinos (KM3NeT/ORCA). Nuclearites above a mass threshold of 1013 GeV/c2 having velocities of approximately 250 km/s could reach the ground and interact in the detector through elastic collisions. A fraction of the energy generated in these collisions is dissipated as visible blackbody radiation. A customized Monte Carlo (MC) program was used to simulate the propagation and the signal of nuclearites inside the KM3NeT detector. The background considered for this study is represented by the 40K decay, which is added during the filtering stage of the MC output, and by the simulated atmospheric muons. The analysis uses selection cuts in order to remove the main background of atmospheric muons and to estimate the sensitivity of the detector. Preliminary results on the sensitivity of the KM3NeT neutrino telescope to a flux of massive down-going nuclearites will be presented. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Ground state

来源：评论

学校读者我要写书评

暂无评论

"So what if ChatGPT wrote it?" Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

引用

International Journal of Information Management 2023年 71卷

作者： Dwivedi, Yogesh K. Kshetri, Nir Hughes, Laurie Slade, Emma Louise Jeyaraj, Anand Kar, Arpan Kumar Baabdullah, Abdullah M. Koohang, Alex Raghavan, Vishnupriya Ahuja, Manju Albanna, Hanaa Albashrawi, Mousa Ahmad Al-Busaidi, Adil S. Balakrishnan, Janarthanan Barlette, Yves Basu, Sriparna Bose, Indranil Brooks, Laurence Buhalis, Dimitrios Carter, Lemuria Chowdhury, Soumyadeb Crick, Tom Cunningham, Scott W. Davies, Gareth H. Davison, Robert M. Dé, Rahul Dennehy, Denis Duan, Yanqing Dubey, Rameshwar Dwivedi, Rohita Edwards, John S. Flavián, Carlos Gauld, Robin Grover, Varun Hu, Mei-Chih Janssen, Marijn Jones, Paul Junglas, Iris Khorana, Sangeeta Kraus, Sascha Larsen, Kai R. Latreille, Paul Laumer, Sven Malik, F. Tegwen Mardani, Abbas Mariani, Marcello Mithas, Sunil Mogaji, Emmanuel Nord, Jeretta Horn O'Connor, Siobhan Okumus, Fevzi Pagani, Margherita Pandey, Neeraj Papagiannidis, Savvas Pappas, Ilias O. Pathak, Nishith Pries-Heje, Jan Raman, Ramakrishnan Rana, Nripendra P. Rehm, Sven-Volker Ribeiro-Navarrete, Samuel Richter, Alexander Rowe, Frantz Sarker, Suprateek Stahl, Bernd Carsten Tiwari, Manoj Kumar van der Aalst, Wil Venkatesh, Viswanath Viglia, Giampaolo Wade, Michael Walton, Paul Wirtz, Jochen Wright, Ryan Digital Futures for Sustainable Business & Society Research Group School of Management Swansea University Bay Campus Fabian Bay Wales Swansea United Kingdom Maharashtra Pune India Bryan School of Business and Economics University of North Carolina at Greensboro United States University of Bristol Business School University of Bristol BS8 1SD United Kingdom Professor of Information Systems Raj Soin College of Business Wright State University 3640 Colonel Glenn Highway DaytonOH45435 United States School of Artificial Intelligence Indian Institute of Technology Delhi Hauz Khas New Delhi India Department of Management Studies Indian Institute of Technology Delhi Hauz Khas New Delhi India Department of Management Information Systems Faculty of Economics and Administration King Abdulaziz University Jeddah Saudi Arabia School of Computing Middle Georgia State University MaconGA United States Client Advisory and Transformation Stackroute NIIT Limited India Department of Information Systems Analytics and Operations College of Business University of Louisville United States Northumbria University London United Kingdom IRC-FDE KFUPM Saudi Arabia ISOM KFUPM Business School KFUPM Saudi Arabia Innovation and Technology Transfer Center Sultan Qaboos University Oman Department of Business Communication Sultan Qaboos University Oman Department of Management Studies National Institute of Technology Tiruchirappalli India Montpellier France FORE School of Management New Delhi India Indian Institute of Management Ahmedabad Vastrapur Ahmedabad380015 India Information School University of Sheffield United Kingdom Bournemouth University Business School Poole United Kingdom School of Information Systems and Technology Management University of New South Wales Sydney Australia Information Operations and Management Sciences Department TBS Business School 1 Place Alphonse Jourdain Toulouse31068 France Department of Education & Childhood Studies Swansea Univers

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT's capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT's use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics;digital transformation of organisations and societies;and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI;examining biases of generative AI attributable to training datasets and processes;exploring business and societal contexts best suited for generative AI implementation;determining optimal combinations of human and generative AI for various tasks;identifying ways to assess accuracy of text produced by generative AI;and uncovering the ethical and legal issues in using generative AI across different contexts. © 2023 The Authors

关键词： Marketing

来源：评论

学校读者我要写书评

暂无评论

Discrimination of quantum states under locality constraints in the many-copy setting

arXiv

引用

arXiv 2020年

作者： Cheng, Hao-Chung Winter, Andreas Yu, Nengkun Department of Electrical Engineering Graduate Institute of Communication Engineering Department of Mathematics National Taiwan University Tapei106 Taiwan Center for Quantum Science and Engineering National Taiwan University Tapei106 Taiwan Physics Division National Center for Theoretical Sciences Taipei10617 Taiwan Quantum Computing Center New Taipei City236 Taiwan ICREA-Institució Catalana de Recerca i Estudis Avançats Barcelona08010 Spain Física Teòrica: Informaciò i Fenòmens Quàntics Departament de Física Universitat Autònoma de Barcelona Barcelona08193 Spain Computer Science Department Stony Brook University NY United States Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology Sydney UltimoNSW2007 Australia

We study quantum hypothesis testing between orthogonal states under restricted local measurements in the many-copy scenario. For testing arbitrary multipartite entangled pure state against its orthogonal complement state via the local operation and classical communication (LOCC) operation, we prove that the optimal average error probability always decays exponentially in the number of copies. Second, we provide a sufficient condition for the LOCC operations to achieve the same performance as the positive-partial-transpose (PPT) operations. We further show that testing a maximally entangled state against its orthogonal complement and testing extremal Werner states both fulfill the above-mentioned condition. Hence, we determine the explicit expressions for the optimal average error probability, the optimal trade-off between the type-I and type-II errors, and the associated Chernoff, Stein, Hoeffding, and strong converse exponents. Then, we show an infinite asymptotic separation between the separable (SEP) and PPT operations by providing a pair of states constructed from an unextendible product basis (UPB). The quantum states can be distinguished perfectly by PPT operations, while the optimal error probability, with SEP operations, admits an exponential lower bound. On the technical side, we prove this result by providing a quantitative version of the well-known statement that the tensor product of UPBs is a UPB. Copyright © 2020, The Authors. All rights reserved.

关键词： Quantum entanglement

来源：评论

学校读者我要写书评

暂无评论

Realising the potential impact of artificial intelligence for rare diseases – A framework

Rare. Open Research in Rare Diseases

引用

Rare. Open Research in Rare Diseases 2025年 3卷 100057-100057页

作者： Groza, Tudor Chan, Chun-Hung Pearce, David A. Baynam, Gareth Rare Care Centre Perth Children’s Hospital Nedlands WA 6009 Australia Bioinformatics Institute Agency for Science Technology and Research (A⁎STAR) 30 Biopolis Street #07-01 Matrix Singapore 138671 Singapore Telethon Kids Institute 15 Hospital Avenue Nedlands WA 6009 Australia SingHealth Duke-NUS Institute of Precision Medicine 5 Hospital Drive Level 9 Singapore 169609 Singapore School of Electrical Engineering Computing and Mathematical Sciences Curtin University Kent St Bentley WA 6102 Australia Sanford Research Sioux Falls SD 57104 USA Sanford School of Medicine University of South Dakota Sioux Falls South Dakota 57105 USA Western Australian Register of Developmental Anomalies King Edward Memorial Hospital 374 Bagot Road Subiaco WA 6008 Australia Faculty of Health and Medical Sciences University of Western Australia 35 Stirling Hwy Crawley WA 6009 Australia

AbstractRare diseases (RD) are conditions affecting fewer than 1 in 2000 persons, with over 7000 largely genetic RDs affecting 3.5 %-5.9 % of the global population, or approximately 262.9–446.2 million people. The substantial healthcare burden and costs, such as the $1 trillion annual expense in the USA, highlight the urgent need for improved RD management. The International Rare Diseases Research Consortium (IRDiRC) addresses this need through global collaboration, aiming for timely and accurate diagnosis, development of 1000 new therapies, and methodologies to measure impact by 2027. IRDiRC's initiatives include biannual meetings and workshops, like the AI-focused workshop in October 2023. This identified AI as crucial for advancing RD research and proposed a Framework for AI to enhance the RD patient journey by addressing efficiency and quality of life through modular solutions mapped to critical stages. The Framework integrates diverse data sources to improve diagnosis, treatment, and impact assessment, reflecting a holistic, cross-sector approach. By guiding multi-stakeholder efforts, the Framework aims to harness AI’s potential to significantly improve rare disease care.

关键词： Rare diseases Patient journey Generative artificial intelligence Diagnosis Care coordination

来源：评论

学校读者我要写书评

暂无评论

Correction: On the usage of average Hausdorff distance for segmentation performance assessment: hidden error when used for ranking

引用

European radiology experimental 2022年第1期6卷 56页

作者： Orhun Utku Aydin Abdel Aziz Taha Adam Hilbert Ahmed A Khalil Ivana Galinovic Jochen B Fiebach Dietmar Frey Vince Istvan Madai CLAIM - Charité Lab for Artificial Intelligence in Medicine Charité Universitätsmedizin Berlin Berlin Germany. orhun-utku.aydin@charite.de. Research Studio Data Science Research Studios Austria Salzburg Austria. CLAIM - Charité Lab for Artificial Intelligence in Medicine Charité Universitätsmedizin Berlin Berlin Germany. Centre for Stroke Research Berlin Charité Universitätsmedizin Berlin Berlin Germany. Department of Neurology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany. Mind Brain Body Institute Berlin School of Mind and Brain Humboldt-Universität Berlin Berlin Germany. School of Computing and Digital Technology Faculty of Computing Engineering and the Built Environment Birmingham City University Birmingham UK.

来源：评论

学校读者我要写书评

暂无评论

Multiwavelength study of GRB 201216C using the sub-TeV emission detected by MAGIC 38

Multiwavelength study of GRB 201216C using the sub-TeV emiss...

引用

38th International Cosmic Ray Conference, ICRC 2023

作者： Fukami, Satoshi Berti, Alessio Loporchio, Serena Nava, Lara Suda, Yusuke Noda, Koji Asano, Katsuaki Bošnjak, Željka Longo, Francesco Jordana-Mitjans, Nuria Melandri, Andrea Mundell, Carole Shrestha, Manisha Steele, Iain 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. Institute for Particle Physics and Astrophysics ETH Zürich Otto-Stern-Weg 5 Zürich8093 Switzerland Institute for Cosmic Ray Research The University of Tokyo Kashiwanoha 5-1-5 Kashiwa Japan Max Planck Institut for Physics Föhringer Ring 6 Munich Germany INFN MAGIC Group INFN Sezione di Bari Dipartimento Interateneo di Fisica Università e del Politecnico di Bari BariI-70125 Italy RomeI-00136 Italy Physics Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima739-8526 Japan Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia INFN Sezione di Trieste via Valerio 2 Trieste Italy Department of Physics University of Bath Claverton Down BathBA2 7AY United Kingdom INAF-Osservatorio Astronomico di Brera Via E. Bianchi 46 LC MerateI-23807 Italy European Space Agency European Space Astronomy Centre Villanueva de la Canñada Madrid28692 Spain Astrophysics Research Institute Liverpool John Moores University Liverpool Science Park IC2 146 Brownlow HillL3 5RF United Kingdom Steward Observatory University of Arizona 933 North Cherry Avenue TucsonAZ85721-0065 United States The University of Tokyo Chiba Kashiwa277-8582 Japan ETH Zürich ZürichCH-8093 Switzerland Instituto de Astrofísica de Canarias Dpto. de Astrofísica Universidad de La Laguna Tenerife La LagunaE-38200 Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 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 Pola

Recently, several gamma-ray bursts (GRBs) have been detected in the very-high-energy (VHE) gamma-ray energy range by ground-based gamma-ray experiments such as MAGIC, H.E.S.S., and LHASSO. For some GRBs, the VHE emission is consistent with synchrotron self-Compton (SSC) emission from high-energy electrons accelerated in the forward shock of the relativistic jet. However, more statistics are needed to further constrain the emission models. GRB 201216C is a long bright GRB detected in a broad energy range from radio to VHE. The redshift is estimated to be 1.1, making the GRB the most distant source detected in the VHE energy range. MAGIC started the observation 56 seconds after the GRB was triggered by the Swift-BAT telescope. We performed a detailed analysis and detected the signal with about 6 sigma in the first 20 minutes. MAGIC continued the observation for 2.2 hours on the same night and 4 hours on the next night. No signal was detected later than 40 minutes after the GRB trigger. We have performed modelling of the multi-wavelength emission using the MAGIC data. We analysed simultaneous optical data from Liverpool Telescope with MAGIC and included the results in the modelling. The sub-TeV emission is consistent with the single-zone SSC model in the forward shock. In this presentation, we show the final results of the MAGIC data analysis of GRB 201216C and discuss the emission mechanism of the multi-wavelength data. © 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

An Online Treatment Decision Aid for Men with Low-risk Prostate Cancer Eligible for Active Surveillance and Their Partners Increases the Uptake of Active Surveillance: The Navigate Randomised Controlled Trial

引用

European urology oncology 2025年

作者： Penelope Schofield Stephen Quinn Natalie Richards Alan White Fiona White Mark Frydenberg Suzanne Chambers Louisa G Gordon Robert Alexander 'Frank' Gardiner Declan G Murphy Matthew J Roberts John Yaxley Nathan Lawrentschuk Kevin Chu Jeremy Millar Jeremy Grummet Ilona Juraskova School of Computing Engineering and Mathematical Sciences La Trobe University Melbourne Victoria Australia Sir Peter MacCallum Department of Oncology The University of Melbourne Parkville Victoria Australia Department of Psychological Sciences Swinburne University of Technology Melbourne Victoria Australia. Electronic address: p.schofield@latrobe.edu.au. Department of Health Science and Biostatistics Swinburne University of Technology Melbourne Victoria Australia. Department of Health Sciences Research Peter MacCallum Cancer Centre Melbourne Victoria Australia. Department of Urology Cabrini Institute Cabrini Health Melbourne Victoria Australia Department of Surgery Monash University Melbourne Victoria Australia. Faculty of Health Sciences Australian Catholic University Brisbane Queensland Australia Health and Wellness Institute Edith Cowan University Perth Australia Menzies Health Institute Queensland Griffith University Southport Australia. Population Health Program Health Economics QIMR Berghofer Medical Research Institute Brisbane Queensland Australia School of Nursing Queensland University of Technology (QUT) Brisbane Queensland Australia School of Public Health The University of Queensland Brisbane Queensland Australia. The University of Queensland Brisbane Queensland Australia The University of Queensland Centre for Clinical Research Brisbane Queensland Australia The Royal Brisbane & Women's Hospital Herston Queensland Australia Edith Cowan University Perth Western Australia Griffith University Queensland Australia. Division of Cancer Surgery Peter MacCallum Cancer Centre Melbourne Victoria Australia. Department of Urology Royal Brisbane and Women's Hospital Herston Queensland Australia Department of Urology Redcliffe Hospital Redcliffe Queensland Australia. The University of Queensland Brisbane Queensland Australia. Department of Surgery The University of Melbourne Melbourne Victoria Australia Department of Urology The Ro

BACKGROUND AND OBJECTIVE:Evidence suggests that curative treatment for low-risk prostate cancer (LRPC) has no survival benefits over active surveillance (AS); thus, treatment choice becomes a value-sensitive decision. Decision aids (DAs) have the potential to facilitate this process, yet no DA has been tailored to the Australian health care system or population. This study aims to evaluate the impact of an online DA (Navigate) on the uptake of AS, quality of life, and decision-making in Australia. METHODS:This parallel-group, prospective, randomised controlled trial recruited men (from May 2017 to May 2021) from participating cancer centres, via self-referral, or via clinician referral. The inclusion criteria were the following: a recent LRPC diagnosis, no decision on treatment, and clinical suitability for AS. Partners could also enrol. Assessments were undertaken at baseline (before decision) and after baseline (1, 2, and 6 mo). Participants were randomised 1:1 to Navigate (online DA, intervention) or a national prostate cancer website (usual care), stratified by the site/recruitment method. Partners were allocated to the group matching their respective partners. The primary outcome was self-reported uptake of AS for first-line treatment at 1 mo. The secondary outcomes included decision-making preparedness; decisional conflict, regret, and satisfaction; illness communication; and prostate cancer-specific quality of life. Intention-to-treat analyses were conducted. KEY FINDINGS AND LIMITATIONS:Of the 619 patients referred, those eligible (n = 302) were randomised to either Navigate (n = 153) or usual care (n = 149), with no significant between-group differences at baseline. The proportion of men self-reporting AS versus another treatment was 90.6% (Navigate) versus 79.0% (usual care; p = 0.008). Navigate participants also reported greater decision-making preparedness (p < 0.001). Partners were allocated to Navigate (n = 70) or usual care (n = 49); no significant be

关键词： Active surveillance Decision support techniques Domestic partners Internet-based intervention Prostate cancer Randomised controlled trial

来源：评论

学校读者我要写书评

暂无评论

Comparison of the atmospheric muon flux measured by the KM3NeT detectors with the CORSIKA simulation using the Global Spline Fit model

Comparison of the atmospheric muon flux measured by the KM3N...

引用

38th International Cosmic Ray Conference, ICRC 2023

作者： Romanov, Andrey Kalaczynski, Piotr Aiello, S. Albert, A. Alves Garre, S. Aly, Z. Ambrosone, A. Ameli, F. Andre, M. Androutsou, E. Anguita, M. Aphecetche, L. Ardid, M. Ardid, S. Atmani, H. Aublin, J. Bailly-Salins, L. Bardačová, Z. Baret, B. Bariego-Quintana, A. Basegmez du Pree, S. Becherini, Y. Bendahman, M. Benfenati, F. Benhassi, M. Benoit, D.M. Berbee, E. Bertin, V. Biagi, S. Boettcher, M. Bonanno, D. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzaş, H. Bretaudeau, F. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Campion, S. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chadolias, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Cocimano, R. Coelho, J.A.B. Coleiro, A. Coniglione, R. Coyle, P. Creusot, A. Cruz, A. Cuttone, G. Dallier, R. Darras, Y. De Benedittis, A. De Martino, B. Decoene, V. Del Burgo, R. Di Cerbo, U.M. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diaz, C. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Dörr, M. Drakopoulou, E. Drouhin, D. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. Enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gabriel, J. Gagliardini, S. Gal, T. García Méndez, J. Garcia Soto, A. Gatius Oliver, C. Geißelbrecht, N. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Goos, I. Goupilliere, D. Gozzini, S.R. Gracia, R. Graf, K. Guidi, C. Guillon, B. Gutiérrez, M. van Haren, H. Heijboer, A. Hekalo, A. Hennig, L. Hernández-Rey, J.J. Huang, F. Idrissi Ibnsalih, W. Illuminati, G. James, C.W. de Jong, M. de Jong, P. Jung, B.J. Kalaczyński, P. Kalekin, O. Katz, U.F. Khan Chowdhury, N.R. Khatun, A. Kistauri, G. Kopper, C. Kouchner, A. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Larosa, G. Lastoria, C. Lazo, A. Le Stum, S. Lehaut, G. Dipartimento di Fisica dell’Università di Genova Via Dodecaneso 33 Genova16146 Italy INFN - Sezione di Genova Via Dodecaneso 33 Genova16146 Italy National Centre for Nuclear Research Warsaw02-093 Poland Nicolaus Copernicus Astronomical Center Polish Academy of Sciences Particle Astrophysics Science and Technology Centre Rektorska 4 Warsaw00-614 Poland INFN Sezione di Catania Via Santa Sofia 64 Catania95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France IFIC - Instituto de Física Corpuscular CSIC Universitat de València c/Catedrático José Beltrán 2 Paterna Valencia46980 Spain Aix Marseille Univ CNRS IN2P3 CPPM Marseille France INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain NCSR Demokritos Institute of Nuclear and Particle Physics Ag. Paraskevi Attikis Athens15310 Greece University of Granada Dept. of Computer Architecture and Technology CITIC Granada18071 Spain Subatech IMT Atlantique IN2P3-CNRS Université de Nantes 4 rue Alfred Kastler - La Chantrerie BP 20722 Nantes44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia46730 Spain University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 RabatR.P. 10000 Morocco Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen14050 France Czech Technical University in Prague Institute of Experimental a

Atmospheric muons are the dominant component of the down-going events for the KM3NeT neutrino telescopes. Deep underwater measurements of muons provide important information about the cosmic ray properties. The KM3NeT research infrastructure includes two telescopes currently in operation while still being under construction in the Mediterranean Sea. The KM3NeT/ORCA detector is deployed at 2450 m depth near Toulon, France. The KM3NeT/ARCA telescope is located at 3500 m depth off-shore Capo Passero, Italy. In this work, the measured atmospheric muon flux is compared to the Monte Carlo simulation using the CORSIKA package with the Sibyll 2.3d model for high-energy hadronic interactions and the GSF model for mass composition. The data from both KM3NeT/ORCA and KM3NeT/ARCA telescopes are considered for this analysis. In the current configuration, KM3NeT/ORCA covers cosmic ray energy range from several TeV up to hundreds of TeV per nucleon, while for KM3NeT/ARCA the range is from several TeV up to PeV per nucleon. Systematic uncertainties considered for the analysis include that on the cosmic ray flux normalization and its composition, water properties, detector response, and high-energy hadronic interaction models. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Hadrons

来源：评论

学校读者我要写书评

暂无评论

Anonymization of labeled TOF-MRA images for brain vessel segmentation using generative adversarial networks

arXiv

引用

arXiv 2020年

作者： Kossen, Tabea Subramaniam, Pooja Madai, Vince I. Hennemuth, Anja Hildebrand, Kristian Hilbert, Adam Sobesky, Jan Livne, Michelle Galinovic, Ivana Khalil, Ahmed A. Fiebach, Jochen B. Frey, Dietmar CLAIM - Charité Lab for AI in Medicine Charité Universitätsmedizin Berlin Germany Department of Computer Engineering and Microelectronics Computer Vision & Remote Sensing Technical University Berlin Berlin Germany Department of Electrical Engineering and Computer Science Technical University of Berlin Berlin Germany School of Computing and Digital Technology Faculty of Computing Engineering and the Built Environment Birmingham City University Birmingham United Kingdom Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine Charité Universitätsmedizin Berlin Berlin Germany Fraunhofer MEVIS Bremen Germany Department VI Computer Science and Media Beuth University of Applied Sciences Berlin Germany Johanna-Etienne-Hospital Neuss Germany Centre for Stroke Research Berlin Charité Universitätsmedizin Berlin Berlin Germany Department of Neurology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany Mind Brain Body Institute Berlin School of Mind and Brain Humboldt University Berlin Berlin Germany Berlin Institute of Health Berlin Germany

Anonymization and data sharing are crucial for privacy protection and acquisition of large datasets for robust medical image analysis. This represents a major challenge, especially for brain imaging research. Here, the unique structure of brain images allows for potential re-identification and thus requires anonymization beyond conventional methods. Generative adversarial networks (GANs) have the potential to provide anonymous images while maintaining their predictive properties. Analyzing brain vessel segmentation as a use case, we trained 3 GAN architectures on time-of-flight (TOF) magnetic resonance angiography (MRA) patches of patients with cerebrovascular disease for image-label pair generation: 1) Deep convolutional GAN, 2) Wasserstein-GAN with gradient penalty (WGAN-GP) and 3) WGAN-GP with spectral normalization (WGAN-GP-SN). First, the synthesized image-labels from each GAN architecture were used to train a U-net for vessel segmentation. The U-nets were then tested on real patient data. In total, 66 patients were used for this analysis. In a second step, we simulated the application of our synthetic patches in a transfer learning approach using a second, independent dataset. Here, for an increasing number of up to 15 patients we evaluated vessel segmentation model performance on real data with and without pre-training on generated patches. Finally, performance for all models was assessed by the Dice Similarity Coefficient (DSC) and the 95th percentile of the Hausdorff Distance (95HD). Comparing the 3 GAN architectures, the U-net model trained on synthetic data generated by the WGAN-GP-SN showed the highest performance to predict brain vessels (DSC/95HD 0.82/28.97) benchmarked by the U-net trained on real data (0.89/26.61). The transfer learning approach showed superior performance for the same GAN architecture compared to no pre-training, especially for one labeled patient only (DSC/95HD 0.91/25.68 compared to DSC/95HD 0.85/27.36). In a brain imaging segment

关键词： Image segmentation

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：