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The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

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Genomic basis for RNA alterations in cancer (vol 578, pg 129, 2020)

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NATURE 2023年第7948期614卷 E37-E37页

作者： Calabrese, Claudia Davidson, Natalie R. Demircioglu, Deniz Fonseca, Nuno A. He, Yao Lehmann, Kjong-Van Liu, Fenglin Shiraishi, Yuichi Soulette, Cameron M. Urban, Lara Greger, Liliana Li, Siliang Liu, Dongbing Perry, Marc D. Xiang, Qian Zhang, Fan Zhang, Junjun Bailey, Peter Erkek, Serap Hoadley, Katherine A. Hou, Yong Huska, Matthew R. Kilpinen, Helena Korbel, Jan O. Marin, Maximillian G. Markowski, Julia Nandi, Tannistha Pan-Hammarstrom, Qiang Pedamallu, Chandra Sekhar Siebert, Reiner Stark, Stefan G. Su, Hong Tan, Patrick Waszak, Sebastian M. Yung, Christina Zhu, Shida Awadalla, Philip Creighton, Chad J. Meyerson, Matthew Ouellette, B. F. Francis Wu, Kui Yang, Huanming Brazma, Alvis Brooks, Angela N. Goke, Jonathan Ratsch, Gunnar Schwarz, Roland F. Stegle, Oliver Zhang, Zemin European Molecular Biology Laboratory European Bioinformatics Institute Hinxton UK European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany CIBIO/InBIO - Research Center in Biodiversity and Genetic Resources Universidade do Porto Vairão Portugal Berlin Institute for Medical Systems Biology Max Delbruck Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) partner site Berlin Germany German Cancer Research Center (DKFZ) Heidelberg Germany Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) Partner site Berlin Berlin Germany European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Division of Computational Genomics and Systems Genetics German Cancer Research Center (DKFZ) Heidelberg Germany ETH Zurich Zurich Switzerland Memorial Sloan Kettering Cancer Center New York NY USA Weill Cornell Medical College New York NY USA SIB Swiss Institute of Bioinformatics Lausanne Switzerland University Hospital Zurich Zurich Switzerland Computational Biology Center Memorial Sloan Kettering Cancer Center New York NY USA Department of Biology ETH Zurich Zürich Switzerland Department of Computer Science ETH Zurich Zurich Switzerland Korea University Seoul South Korea Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center 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 New York NY USA National University of Singapore Singapore Singapore Genome Institute of Singapore Singapore Singapore Computational and Systems Biology Genome Institute of Singap

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Characterising acute and chronic care needs: insights from the Global Burden of Disease Study 2019

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Nature communications 2025年第1期16卷 4235-4235页

作者： Cecilia Anza-Ramirez J. Jaime Miranda Benedetta Armocida Jorge César Correia Harriette Gillian Christine Van Spall David Beran Amirali Aali Kalkidan Hassen Abate Semagn Mekonnen Abate Cristiana Abbafati Mohsen Abbasi-Kangevari Zeinab Abbasi-Kangevari Zahra Aryan Sina Azadnajafabad Mohammadreza Azangou-Khyavy Seyyed-Hadi Ghamari Mohammad Keykhaei Javad Khanali Sara Momtazmanesh Fateme Montazeri Shayan Rahmani Mohammad-Mahdi Rashidi Nazila Rezaei Negar Rezaei Sahar Saeedi Moghaddam Hossein Hassanian-Moghaddam Ali-Asghar Kolahi Ali Nikoobar Hedayat Abbastabar Ahmed M. Abdel-Azeem Michael Abdelmasseh Juan Sanabria Sherief Abd-Elsalam Ahmed Abdelwahab Gholamreza Abdoli Mohammad Abdollahi Meriem Abdoun Deldar Morad Abdulah Abu Yousuf Md Abdullah Ame Mehadi Abdurehman Getachew Abebe Aidin Abedi Chirag P. Doshi Vida Abedi Hassan Abidi Richard Gyan Aboagye Hassan Abolhassani Nima Rezaei Lucas Guimarães Abreu Michael R. M. Abrigo Yonas Derso Abtew Hiwa Abubaker Ali Eman Abu-Gharbieh Hiba Jawdat Barqawi Rabih Halwani Maha Mohamed Saber-Ayad Iman M. Talaat Ahmed Abu-Zaid Manfred Mario Kokou Accrombessi Juan Manuel Acuna Denberu Eshetie Adane Tigist Demssew Adane Isaac Yeboah Addo Giovanni Addolorato Oluwafemi Atanda Adeagbo Victor Adekanmbi Miracle Ayomikun Adesina Isaac Iyinoluwa Olufadewa Olatunji O. Adetokunboh Daniel Adedayo Adeyinka Qorinah Estiningtyas Sakilah Adnani Aanuoluwapo Adeyimika Afolabi Olayinka Stephen Ilesanmi Muhammad Sohail Afzal Saira Afzal Gina Agarwal Prerna Agarwal Pradyumna Agasthi Anurag Agrawal Marcela Agudelo-Botero Adolfo Martinez-Valle Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Sohail Ahmad Tauseef Ahmad Ali Ahmadi Siamak Sabour Keivan Ahmadi Sanjay Basu Sepideh Ahmadi Ali Ahmed Shaun Wen Huey Lee Ayman Ahmed Haroon Ahmed Jivan Qasim Ahmed Gahin Abdulraheem Tayib Yahya Yahya Luai A. Ahmed Iffat Elbarazi Syed Mahboob Shah Janardhana P. Aithala Marjan Ajami Budi Aji Hossein Akbarialiabad Yibeltal Akelew Meisam Akhlaghdoust Elham Jamshidi Addis Aklilu Azene Tesfaye Melat Woldemariam Maxwell Ak CRONICAS Center of Excellence in Chronic Diseases Universidad Peruana Cayetano Heredia Lima Peru School of Medicine Universidad Peruana Cayetano Heredia Lima Peru Sydney School of Public Health Faculty of Medicine and Health University of Sydney Sydney NSW Australia Faculty of Epidemiology and Population Health London School of Hygiene & Tropical Medicine London UK Division of Tropical and Humanitarian Medicine University of Geneva Geneva Switzerland Department of Cardiovascular Endocrine-metabolic Diseases and Aging Istituto Superiore di Sanità Rome Italy Division of Endocrinology Diabetology Nutrition and Therapeutic Patient Education Department of Medicine Geneva University Hospitals Geneva Switzerland Department of Medicine and Department of Health Research Evidence and Impact McMaster University Hamilton ON Canada Research Institute of St. Joe’s Hamilton ON Canada Population Health Research Institute Hamilton Canada Geneva University Hospitals Geneva Switzerland Faculty of Medicine Mashhad University of Medical Sciences Mashhad Iran Department of Nutrition and Dietetics Jimma University Jimma Ethiopia Anesthesiology Department Dilla University Addis Ababa Ethiopia Department of Juridical and Economic Studies La Sapienza University Rome Italy Non-Communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Brigham and Women’s Hospital Harvard University Boston MA USA Students’ Scientific Research Center (SSRC) Tehran University of Medical Sciences Tehran Iran School of Medicine Tehran University of Medical Sciences Tehran Iran School of Medicine Shahid Beheshti University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Institute Tehran University of Medical Sciences Tehran Iran Chapter of Addiction Medicine University of Sydney Sydney NSW Australia Advanced Diagnostic and Intervent

Chronic care manages long-term, progressive conditions, while acute care addresses short-term conditions. Chronic conditions increasingly strain health systems, which are often unprepared for these demands. This study examines the burden of conditions requiring acute versus chronic care, including sequelae. Conditions and sequelae from the Global Burden of Diseases Study 2019 were classified into acute or chronic care categories. Data were analysed by age, sex, and socio-demographic index, presenting total numbers and contributions to burden metrics such as Disability-Adjusted Life Years (DALYs), Years Lived with Disability (YLD), and Years of Life Lost (YLL). Approximately 68% of DALYs were attributed to chronic care, while 27% were due to acute care. Chronic care needs increased with age, representing 86% of YLDs and 71% of YLLs, and accounting for 93% of YLDs from sequelae. These findings highlight that chronic care needs far exceed acute care needs globally, necessitating health systems to adapt accordingly. © 2025. The Author(s).

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Verification benchmarks for single-phase flow in three-dimensional fractured porous media

arXiv

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arXiv 2020年

作者： Berre, Inga Boon, Wietse M. Flemisch, Bernd Fumagalli, Alessio Gläser, Dennis Keilegavlen, Eirik Scotti, Anna Stefansson, Ivar Tatomir, Alexandru Brenner, Konstantin Burbulla, Samuel Devloo, Philippe Duran, Omar Favino, Marco Hennicker, Julian Lee, I-Hsien Lipnikov, Konstantin Masson, Roland Mosthaf, Klaus Chiara Nestola, Maria Giuseppina Ni, Chuen-Fa Nikitin, Kirill Schädle, Philipp Svyatskiy, Daniil Yanbarisov, Ruslan Zulianp, Patrick Department of Mathematics University of Bergen Allégaten 41 Bergen5007 Norway Department of Mathematics KTH Royal Institute of Technology Lindstedtsvägen 25 Stockholm11428 Sweden Department of Hydromechanics and Modelling of Hydrosystems University of Stuttgart Pfaffenwaldring 61 Stuttgart70569 Germany Laboratory for Modeling and Scientific Computing MOX Politecnico di Milano p.za Leonardo da Vinci 32 Milano20133 Italy Department of Applied Geology Geosciences Center University of Göttingen Goldschmidtstrasse 3 Göttingen37077 Germany Department of Earth Sciences Uppsala University Villavägen 16 UppsalaS-75236 Sweden University of Côte d’Azur CNRS INRIA LJAD Nice France Institute of Applied Analysis and Numerical Simulation University of Stuttgart Pfaffenwaldring 57 Stuttgart70569 Germany FEC Universidade Estadual de Campinas Cidade Universitária R. Josiah Willard Gibbs 85 Campinas-SPCEP 13083-839 Brazil Institute of Earth Sciences University of Lausanne Building Geopolis UNIL-Mouline Lausanne1015 Switzerland Section de Mathématiques Université de Genève 2-4 rue du Lièvre CP 64 Genève1211 Switzerland Graduate Institute of Applied Geology National Central University Taiwan Center for Environmental Studies National Central University Taiwan Los Alamos National Laboratory New Mexico United States Department of Environmental Engineering Technical University of Denmark Bygningstorvet Building 115 Kgs. Lyngby2800 Denmark Numerical Simulation in Science Medicine and Engineering Group Institute of Computational Science Università della Svizzera italiana. Via G. Buffi 13 Lugano Ticino6900 Switzerland Marchuk Institute of Numerical Mathematics of Russian Academy of Sciences Moscow Russia ETH Zürich Geothermal Energy and Geofluids Group Institute of Geophysics Zürich8092 Switzerland

Flow in fractured porous media occurs in the earth’s subsurface, in biological tissues, and in man-made materials. Fractures have a dominating influence on flow processes, and the last decade has seen an extensive development of models and numerical methods that explicitly account for their presence. To support these developments, we present a portfolio of four benchmark cases for single-phase flow in three-dimensional fractured porous media. The cases are specifically designed to test the methods’ capabilities in handling various complexities common to the geometrical structures of fracture networks. Based on an open call for participation, results obtained with 17 numerical methods were collected. This paper presents the underlying mathematical model, an overview of the features of the participating numerical methods, and their performance in solving the benchmark cases. Copyright © 2020, The Authors. All rights reserved.

关键词： numerical methods

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REGIONAL CLIMATES

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BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 2023年第9期104卷 S366-S473页

作者： Bissolli, P. Ganter, C. Mekonnen, A. Sanchez-Lugo, A. Zhu, Z. Deutscher Wetterdienst WMO RA VI Regional Climate Centre Network Offenbach Germany Tobin Bureau of Meteorology Melbourne Australia North Carolina A&T University Greensboro North Carolina NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Nanjing University of Information Science and Technology Nanjing China Agence Nationale de l’Aviation Civile et de la Météorologie Moroni Union of the Comoros NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland Servicio Meteorológico Nacional Buenos Aires Argentina Center for Geophysical Research and School of Physics University of Costa Rica San José Costa Rica Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN São Paulo Brazil Seychelles Meteorological Authority Mahe Seychelles Servicio Nacional de Meteorología e Hidrología del Perú Lima Perú Federal Office of Meteorology and Climatology MeteoSwiss Switzerland Universidad Católica Nuestra Señora de la Asunción Asunción Paraguay Yu. A. Izrael Institute of Global Climate and Ecology Institute of Geography Russian Academy of Sciences Moscow Russia Govern d’Andorra Andorra la Vella Andorra Meteo France Toulouse France NOAA/NWS Climate Prediction Center Silver Spring Maryland Slovak Hydrometeorological Institute Bratislava Slovakia NOAA/NWS Weather Forecast Office Tiyan Guam Center for Geophysical Research University of Costa Rica San José Costa Rica Department of Physics The University of the West Indies Kingston Jamaica Environment and Climate Change Canada Toronto Ontario Canada Czech Hydrometeorological Institute Prague Czech Republic Royal Meteorological Institute of Belgium (KMI) Brussels Belgium Turkish State Meteorological Service Igdir Türkiye Portuguese Sea and Atmosphere Institute Lisbon Portugal Mauritius Meteorological Service Vacoas Mauritius Namibia Meteorological Service Windhoek Namibia Institute of Meteorology Hydrology and Environment National

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A genomic catalog of Earth's microbiomes (November, 10.1038/s41587-020-0718-6, 2020)

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NATURE BIOtechnology 2021年第4期39卷 520-520页

作者： Nayfach, Stephen Roux, Simon Seshadri, Rekha Udwary, Daniel Varghese, Neha Schulz, Frederik Wu, Dongying Paez-Espino, David Chen, I-Min Huntemann, Marcel Palaniappan, Krishna Ladau, Joshua Mukherjee, Supratim Reddy, T. B. K. Nielsen, Torben Kirton, Edward Faria, Jose P. Edirisinghe, Janaka N. Henry, Christopher S. Jungbluth, Sean P. Chivian, Dylan Dehal, Paramvir Wood-Charlson, Elisha M. Arkin, Adam P. Tringe, Susannah G. Visel, Axel Woyke, Tanja Mouncey, Nigel J. Ivanova, Natalia N. Kyrpides, Nikos C. Eloe-Fadrosh, Emiley A. DOE Joint Genome Institute Berkeley CA USA Argonne National Laboratory Argonne IL USA Lawrence Berkeley National Laboratory Berkeley CA USA Travessa Alexandre da Conceicao ALGAplus Ilhavo Portugal Department of Marine Biology and Oceanography Institute of Marine Sciences-CSIC Barcelona Spain Scripps Institution of Oceanography University of California San Diego La Jolla CA USA School of Biotechnology and Biomolecular Sciences UNSW Sydney Sydney New South Wales Australia Centre for Microbiology and Environmental Systems Science University of Vienna Vienna Austria Department of Environmental Science Aarhus University Roskilde Denmark Rumen Microbiology Animal Science AgResearch Grasslands Research Centre Palmerston North New Zealand Department of Biology Pennsylvania State University University Park Pennsylvania PA USA Scottish Association for Marine Science Oban UK Department of Earth and Environmental Sciences University of Minnesota Minneapolis MN USA Department of Marine Science University of Texas Austin Austin TX USA Institute of Microbiology of the Czech Academy of Sciences Praha 4 Czech Republic Department of Biology University of Akron Akron OH USA Department of Chemical Engineering & eScience Institute University of Washington Seattle WA USA Department of Biology University of North Alabama Florence AL USA Life and Environmental Sciences and Sierra Nevada Research Institute University of California Merced Merced CA USA Ecole Polytechnique Federale de Lausanne Lausanne Switzerland Department of Soil Science University of Wisconsin-Madison Madison WI USA School of Biological Sciences Georgia Institute of Technology Atlanta GA USA Department of Aquatic Sciences and Assessment Swedish University of Agricultural Sciences Uppsala Sweden Department of Biology Boston University Boston MA USA University of Arkansas for Medical Sciences Little Rock AR USA Biology Department University of Massachusetts Amherst Amherst MA USA

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

关键词： Computational biology and bioinformatics Microbiology

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Laplacian preconditioning of elliptic pdes: Localization of the eigenvalues of the discretized operator

arXiv

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arXiv 2018年

作者： Gergelits, Tomáš Mardal, Kent-André Nielsen, Bjørn Fredrik Strakoš, Zdeněk Institute of Computer Sciences Czech Academy of Science Prague Czech Republic Faculty of Mathematics and Physics Charles University Prague Czech Republic Department of Mathematics University of Oslo Oslo0316 Norway Department of Numerical Analysis and Scientific Computing Simula Research Laboratory Lysaker1325 Norway Faculty of Science and Technology Norwegian University of Life Sciences ÅsNO-1432 Norway

In the paper Preconditioning by inverting the Laplacian;an analysis of the eigenvalues. IMA Journal of numerical analysis 29, 1 (2009), 24-42, Nielsen, Hackbusch and Tveito study the operator generated by using the inverse of the Laplacian as preconditioner for second order elliptic PDEs ∇ · (k(x)∇u) = f. They prove that the range of k(x) is contained in the spectrum of the preconditioned operator, provided that k is continuous. Their rigorous analysis only addresses mappings defined on infinite dimensional spaces, but the numerical experiments in the paper suggest that a similar property holds in the discrete case. Motivated by this investigation, we analyze the eigenvalues of the matrix L−1A, where L and A are the stiffness matrices associated with the Laplace operator and general second order elliptic operators, respectively. Without any assumption about the continuity of k(x), we prove the existence of a one-to-one pairing between the eigenvalues of L−1A and the intervals determined by the images under k(x) of the supports of the FE nodal basis functions. As a consequence, we can show that the nodal values of k(x) yield accurate approximations of the eigenvalues of L−1A. Our theoretical results are illuminated by several numerical experiments.65F08, 65F15, 65N12, 35J99 Copyright © 2018, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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Odor Recognition in an Attractor Network Model of the Mammalian Olfactory Cortex

Odor Recognition in an Attractor Network Model of the Mammal...

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International Joint Conference on Neural Networks

作者： Pawel Andrzej Herman Simon Benjaminsson Anders Lansner Department of Computational Science and Technology KTH Royal Institute of Technology Stockholm Sweden Stockholm Sweden Department of Numerical Analysis and Computer Science Stockholm University Sweden

ISBN: (纸本)9781509061839

Odor recognition constitutes a key functional aspect of olfaction and in real-world scenarios it requires that odorants occurring in complex chemical mixtures are identified irrespective of their concentrations. We investigate this challenging pattern recognition problem in the framework of a three-stage computational model of the mammalian olfactory system. To this end, we first synthesize odor stimuli with the primary representations in the olfactory receptor neuron (ORN) layer and the secondary representations in the output of the olfactory bulb (OB) in the model. Next, sparse olfactory codes are extracted and fed into the recurrent network model, where as a result of Hebbian-like associative learning an attractor memory storage is produced. We demonstrate the capability of the resultant olfactory cortex (OC) model to perform robust odor recognition tasks and offer computational insights into the underlying network mechanisms.

关键词： Olfactory Brain modeling Encoding Computational modeling Integrated circuit modeling Sensitivity Chemicals

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State of the climate in 2020 7. Regional climates

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Bulletin of the American Meteorological Society 2021年第8期102卷 S357-S463页

作者： Alfaro, Eric J. Alves, Lincoln M. Amador, Jorge A. Andrade, B. Argeñalso, Francisco Asgarzadeh, P. Baez, Julian Barakiza, Reuben Bardin, M.Yu. Bardin, Mikhail Bissolli, Peter Bochníček, Oliver Bukunt, Brandon Calderón, Blanca Campbell, Jayaka D. Chandler, Elise Chang'a, Ladislaus Cheng, Vincent Y.S. Clarke, Leonardo A. Correa, Kris Cortés, Catalina Costa, Felipe Cunha, A.P.M.A. Demircan, Mesut Dhurmea, K.R. Diawara, A. Diouf, Sarah Dulamsuren, Dashkhuu ElKharrim, M. Espinoza, Jhan-Carlo Fazl-Kazem, A. Fenimore, Chris Fuhrman, Steven Ganter, Catherine Gleason, Karin Guard, Charles P. Hagos, Samson Hanafusa, Mizuki Hasannezhad, H.R. Heim, Richard R. Hidalgo, Hugo G. Ijampy, J.A. Im, Gyo Soon Joseph, Annie C. Jumaux, G. Kabidi, K.R. Kamsu-Tamo, P.-H. Kennedy, John Khan, Valentina Khiem, Mai Van King'uza, Philemon Korshunova, Natalia N. Kruger, A.C. Lakatos, Mónika Lam, Hoang Phuc Lander, Mark A. Lavado-Casimiro, Waldo Lee, Tsz-Cheung Leung, Kinson H.Y. Li, Tim Macara, Gregor Mamen, Jostein Marengo, José A. McBride, Charlotte Mekonnen, Ademe Misevicius, Noelia Moise, Aurel Molina-Carpio, Jorge Mora, Natali Mostafa, Awatif E. Mtongori, Habiba Mutai, Charles Ndiaye, O. Nieto, Juan José Nyembo, Latifa Nying'uro, Patricia Pan, Xiao Pascual Ramírez, Reynaldo Phillips, David Pugh, Brad Rajeevan, Madhavan Rakotonirina, M.L. Ramos, Andrea M. Robjhon, M. Camino, Rodriguez Guisado, Rodriguez Ronchail, Josyane Rösner, Benjamin Salinas, Roberto Sánchez-Lugo, Ahira Sato, Hirotaka Sato, Hitoshi Sayouri, Amal Sebaziga, Joseph Sensoy, Serhat Spillane, Sandra Trachte, Katja van der Schrier, Gerard Sima, F. Smith, Adam Spence, Jacqueline M. Sreejith, O.P. Srivastava, A.K. Stella, José L. Stephenson, Kimberly A. Stephenson, Tannecia S. Supari, S. Tajbakhsh-Mosalman, Sahar Tamar, Gerard Taylor, Michael A. Teshome, Asaminew Thiaw, Wassila M. Tobin, Skie Trotman, Adrian R. Van Meerbeeck, Cedric J. Vazifeh, A. Wakamatsu, Shunya Wang, Wei Xin, Fei Zeng, F. Zhang, Peiqun Zhu, Zhiwei Allen, Jessicca Andersen, Andrea Hammer, Gregory Love-Brota Center for Geophysical Research School of Physics University of Costa Rica San José Costa Rica Centro de Ciencia do Sistema Terrestre Instituto Nacional de Pesquisas Espaciais Sao Paulo Brazil Seychelles Meteorological Authority Mahe Seychelles Centro Nacional de Estudios Atmosféricos Oceanográficos y Sísmicos Tegucigalpa Honduras National Center for Climate and Drought Crisis Management Islamic Republic of Iranian Meteorological Organization Iran Universidad Católica Nuestra Senora de la Asunción Asunción Paraguay Burundi Hydrometeorological Department Bujumbura Burundi Yu. A. Izrael Institute of Global Climate and Ecology Institute of Geography Russian Academy of Sciences Russia Institute of Global Climate and Ecology Moscow Russia Deutscher Wetterdienst WMO RA VI Regional Climate Centre Network Offenbach Germany Slovak Hydrometeorological Institute Slovakia NOAA/NWS Weather Forecast Office Guam Center for Geophysical Research University of Costa Rica San José Costa Rica Department of Physics The University of the West Indies Jamaica Bureau of Meteorology MelbourneVIC Australia Tanzania Meteorological Authority Dar es Salaam Tanzania United Republic of Environment and Climate Change Canada TorontoON Canada Servicio Nacional de Meteorología e Hidrología del Perú Lima Peru Dirección de Meteorológica de Chile Santiago de Chile Chile International Centre for Research on El Niño Guayaqui Ecuador Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN Sao Paulo Brazil Turkish State Meteorological Service Ankara Turkey Mauritius Meteorological Service Vacoas Mauritius NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College ParkMD United States Climate Change and Resource Research Section Information and Research Institute of Meteorology Hydrology and Environment National Agency for Meteorology Hydrology and Environmental Monitoring Ulaanbaatar Mongolia Direction de la Météorologie Nationale Maroc Rabat

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Convergence of finite difference methods for the wave equation in two space dimensions

arXiv

引用

arXiv 2017年

作者： Wang, Siyang Nissen, Anna Kreiss, Gunilla Division of Scientific Computing Department of Information Technology Uppsala University UppsalaSE-751 05 Sweden Division of Numerical Analysis Department of Mathematics Royal Institute of Technology StockholmSE-100 44 Sweden Division of Scientific Computing Department of Information Technology Uppsala University UppsalaSE-751 05 Sweden

When using a finite difference method to solve an initial–boundary–value problem, the truncation error is often of lower order at a few grid points near boundaries than in the interior. Normal mode analysis is a powerful tool to analyze the effect of the large truncation error near boundaries on the overall convergence rate, and has been used in many previous literatures for different equations. However, existing work only concerns problems in one space dimension. In this paper, we extend the analysis to problems in two space dimensions. The two dimensional analysis is based on a diagonalization procedure that decomposes a two dimensional problem to many one dimensional problems of the same type. We present a general framework of analyzing convergence for such one dimensional problems, and explain how to obtain the result for the corresponding two dimensional problem. In particular, we consider two kinds of truncation errors in two space dimensions: the truncation error along an entire boundary, and the truncation error localized at a few grid points close to a corner of the computational domain. The accuracy analysis is in a general framework, here applied to the second order wave equation. numerical experiments corroborate our accuracy analysis.65M12, 65M06 Copyright © 2017, The Authors. All rights reserved.

关键词： Finite difference method

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