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arXiv 2023年

作者： Afach, S. Aybas Tumturk, D. Bekker, H. Buchler, B.C. Budker, D. Cervantes, K. Derevianko, A. Eby, J. Figueroa, N.L. Folman, R. Gavilán Martín, D. Givon, M. Grujić, Z.D. Guo, H. Hamilton, P. Hedges, M.P. Jackson Kimball, D.F. Khamis, S. Kim, D. Klinger, E. Kryemadhi, A. Liu, X. Lukasiewicz, G. Masia-Roig, H. Padniuk, M. Palm, C.A. Park, S.Y. Pearson, H.R. Peng, X. Pospelov, M. Pustelny, S. Rosenzweig, Y. Ruimi, O.M. Scholtes, T. Segura, P.C. Semertzidis, Y.K. Shin, Y.C. Smiga, J.A. Stadnik, Y.V. Stalnaker, J.E. Sulai, I.A. Tandon, D. Vu, K. Weis, A. Wickenbrock, A. Wilson, T.Z. Wu, T. Xiao, W. Yang, Y. Yu, D. Yu, F. Zhang, J. Zhao, Y. Helmholtz-Institut GSI Helmholtzzentrum fur Schwerionenforschung Mainz55128 Germany Johannes Gutenberg University Mainz55128 Germany Department of Physics University of California at Berkeley BerkeleyCA94720-7300 United States Research School of Physics Australian National University CanberraACT2601 Australia Department of Physics California State University - East Bay HaywardCA94542-3084 United States Department of Physics University of Nevada RenoNV89557 United States The University of Tokyo Institutes for Advanced Study The University of Tokyo Chiba Kashiwa277-8583 Japan Department of Physics Ben-Gurion University of the Negev Be'er Sheva84105 Israel Physics Department University of Fribourg FribourgCH-1700 Switzerland Institute of Physics Belgrade Pregrecica 118 Belgrade11080 Serbia State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronics Center for Quantum Information Technology Peking University Beijing100871 China Department of Physics & Astronomy University of California at Los Angeles Los AngelesCA90095-1547 United States Department of Physics KAIST Daejeon34141 Korea Republic of Center for Axion and Precision Physics Research IBS Daejeon34051 Korea Republic of Dept. Computing Math & Physics Messiah University MechanicsburgPA17055 United States Marian Smoluchowski Institute of Physics Jagiellonian University Lojasiewicza 11 Kraków30-348 Poland Department of Physics & Astronomy Oberlin College OberlinOH44074 United States School of Physics and Astronomy University of Minnesota MinneapolisMN55455 United States William I. Fine Theoretical Physics Institute School of Physics and Astronomy University of Minnesota MinneapolisMN55455 United States Racah Institute of Physics Hebrew University of Jerusalem Jerusalem9190401 Israel Leibniz Institute of Photonic Technology Albert-Einstein-Strasse 9 JenaD-07745 Germany School of Physics University of Sydney SydneyNSW20

Numerous observations suggest that there exist undiscovered beyond-the-Standard-Model particles and fields. Because of their unknown nature, these exotic particles and fields could interact with Standard Model particles in many different ways and assume a variety of possible configurations. Here we present an overview of the Global Network of Optical Magnetometers for Exotic physics searches (GNOME), our ongoing experimental program designed to test a wide range of exotic physics scenarios. The GNOME experiment utilizes a worldwide network of shielded atomic magnetometers (and, more recently, comagnetometers) to search for spatially and temporally correlated signals due to torques on atomic spins from exotic fields of astrophysical origin. We survey the temporal characteristics of a variety of possible signals currently under investigation such as those from topological defect dark matter (axion-like particle domain walls), axion-like particle stars, solitons of complex-valued scalar fields (Q-balls), stochastic fluctuations of bosonic dark matter fields, a solar axion-like particle halo, and bursts of ultralight bosonic fields produced by cataclysmic astrophysical events such as binary black hole mergers. © 2023, CC BY.

关键词： Software testing

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A multi-messenger search for exotic field emission with a global magnetometer network

arXiv

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arXiv 2024年

作者： Khamis, Sami S. Sulai, Ibrahim A. Hamilton, Paul Afach, S. Buchler, B.C. Budker, D. Figueroa, N.L. Folman, R. Gavilán-Martín, D. Givon, M. Grujić, Z.D. Guo, H. Hedges, M.P. Kimball, D.F. Jackson Kim, D. Klinger, E. Kornack, T. Kryemadhi, A. Kukowski, N. Lukasiewicz, G. Masia-Roig, H. Padniuk, M. Palm, C.A. Park, S.Y. Peng, X. Pospelov, M. Pustelny, S. Rosenzweig, Y. Ruimi, O.M. Segura, P.C. Scholtes, T. Semertzidis, Y.K. Shin, Y.C. Stalnaker, J.E. Tandon, D. Weis, A. Wickenbrock, A. Wilson, T. Wu, T. Zhang, J. Zhao, Y. Department of Physics and Astronomy University of California Los AngelesCA90095 United States Department of Physics and Astronomy Bucknell University LewisburgPA17837 United States Helmholtz Institute Mainz Mainz55099 Germany GSI Helmholtzzentrum für Schwerionenforschung GmbH Darmstadt64291 Germany Johannes Gutenberg-Universität Mainz Mainz55128 Germany Research School of Physics Australian National University CanberraACT2601 Australia Department of Physics University of California BerkeleyCA94720 United States Department of Physics Ben-Gurion University of the Negev Be’er Sheva84105 Israel Institute of Physic Belgrade University of Belgrade Belgrade11080 Serbia State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronics Center for Quantum Information Technology Peking University Beijing100871 China Centre for Quantum Computation and Communication Technology Research School of Physics The Australian National University Acton2601 Australia Department of Physics California State University – East Bay HaywardCA94542-3084 United States Center for Axion and Precision Physics Research IBS Daejeon34051 Korea Republic of Department of Physics KAIST Daejeon34141 Korea Republic of Institut FEMTO-ST UMR 6174 CNRS SupMicroTech-ENSMM Université de Franche-Comté Besançon25030 France Twinleaf LLC 300 Deer Creek Drive PlainsboroNJ08536 United States Department of Computing Math & Physics Messiah University MechanicsburgPA17055 United States Friedrich Schiller University Jena Institute of Geosciences Burgweg 11 JenaD-07749 Germany Institute of Physics Jagiellonian University in Krakow prof. Stanislawa Lojasiewicza 11 Kraków30-348 Poland Jagiellonian University Doctoral School of Exact and Natural Sciences Lojasiewicza 11 Kraków30-348 Poland Department of Physics and Astronomy Oberlin College OberlinOH44074 United States School of Physics and Astronomy University of Minnesota Minneapolis

We present an analysis method to search for exotic low-mass field (ELF) bursts generated during large energy astrophysical events such as supernovae, binary black hole or binary neutron star mergers, and fast radio bursts using the Global Network of Optical Magnetometers for Exotic physics searches (GNOME). In our model, the associated gravitational waves or electromagnetic signals herald the arrival of the ELF burst that interacts via coupling to the spin of fermions in the magnetometers. This enables GNOME to serve as a tool for multi-messenger astronomy. The algorithm employs a model-agnostic excess-power method to identify network-wide candidate events to be subjected to a model-dependent generalized likelihood-ratio test to determine their statistical significance. We perform the first search with this technique on GNOME data coincident with the binary black hole merger S200311bg detected by LIGO/Virgo on the 11th of March 2020 and find no significant events. We place the first lab-based limits on combinations of ELF production and coupling parameters. Copyright © 2024, The Authors. All rights reserved.

关键词： Magnetometers

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Author Correction: The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci

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Nature computational science 2023年第7期3卷 658页

作者： Gengjie Jia Yu Li Xue Zhong Kanix Wang Milton Pividori Rabab Alomairy Aniello Esposito Hatem Ltaief Chikashi Terao Masato Akiyama Koichi Matsuda David E Keyes Hae Kyung Im Takashi Gojobori Yoichiro Kamatani Michiaki Kubo Nancy J Cox James Evans Xin Gao Andrey Rzhetsky Shenzhen Branch Guangdong Laboratory of Lingnan Modern Agriculture Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China. jiagengjie@***. Computational Bioscience Research Center King Abdullah University of Science and Technology Thuwal Saudi Arabia. Computer Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong People's Republic of China. Department of Medicine and Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville TN US. Department of Medicine Institute of Genomics and Systems Biology Committee on Genomics Genetics and Systems Biology University of Chicago Chicago IL US. Department of Operations Business Analytics and Information Systems University of Cincinnati Cincinnati OH US. Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania Philadelphia PA US. Extreme Computing Research Center Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia. HPE HPC/AI EMEA Research Laboratory Bristol UK. RIKEN Center for Integrative Medical Sciences Yokohama Japan. Clinical Research Center Shizuoka General Hospital Shizuoka Japan. Department of Applied Genetics The School of Pharmaceutical Sciences University of Shizuoka Shizuoka Japan. Department of Ophthalmology Graduate School of Medical Sciences Kyushu University Fukuoka Japan. Department of Computational Biology and Medical Sciences Graduate School of Frontier Sciences The University of Tokyo Tokyo Japan. Biological and Environmenta

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Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning

arXiv

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arXiv 2021年

作者： Hering, Alessa Hansen, Lasse Mok, Tony C.W. Chung, Albert C.S. Siebert, Hanna Häger, Stephanie Lange, Annkristin Kuckertz, Sven Heldmann, Stefan Shao, Wei Vesal, Sulaiman Rusu, Mirabela Sonn, Geoffrey Estienne, Théo Vakalopoulou, Maria Han, Luyi Huang, Yunzhi Yap, Pew-Thian Brudfors, Mikael Balbastre, Yaël Joutard, Samuel Modat, Marc Lifshitz, Gal Raviv, Dan Lv, Jinxin Li, Qiang Jaouen, Vincent Visvikis, Dimitris Fourcade, Constance Rubeaux, Mathieu Pan, Wentao Xu, Zhe Jian, Bailiang De Benetti, Francesca Wodzinski, Marek Gunnarsson, Niklas Sjölund, Jens Grzech, Daniel Qiu, Huaqi Li, Zeju Thorley, Alexander Duan, Jinming Großbröhmer, Christoph Hoopes, Andrew Reinertsen, Ingerid Xiao, Yiming Landman, Bennett Huo, Yuankai Murphy, Keelin Lessmann, Nikolas van Ginneken, Bram Dalca, Adrian V. Heinrich, Mattias P. Institute of Medical Informatics Universität zu Lübeck Ratzeburger Allee 160 Lübeck23562 Germany Fraunhofer MEVIS Institute for Digital Medicine Lübeck23562 Germany Department of Radiology and Nuclear Medicine Radboud University Medical Center GA Nijmegen6525 Netherlands The Institute of Medical Informatics Universität zu Lübeck Lübeck23562 Germany The Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong The Fraunhofer MEVIS Institute for Digital Medicine Lübeck23562 Germany The Department of Radiology Stanford University StanfordCA94305 United States The Department of Urology Stanford University StanfordCA94305 United States The Université Paris-Saclay CentraleSupélec Mathématiques et Informatique pour la Complexité et les Systèmes Inria Saclay Gif-sur-Yvette 91190 France Université Paris-Saclay Institut Gustave Roussy Inserm Radiothérapie Moléculaire et Innovation Thérapeutique Villejuif94800 France The Université Paris-Saclay CentraleSupélec Mathématiques et Informatique pour la Complexité et les Systèmes Inria Saclay Gif-sur-Yvette91190 France The Department of Radiology and Nuclear Medicine Radboud University Medical Center Nijmegen6525 GA Netherlands The School of Automation Nanjing University of Information Science and Technology Nanjing210044 China The School of Biomedical Engineering and Imaging Sciences King’s College London London United Kingdom The Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital United States Harvard Medical School Boston United States The King’s College London United Kingdom The Tel Aviv University The Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology Hubei Wuhan430074 China MoE Key Laboratory for Biomedical Photonics Collaborative Innovation Center for Biomedical Engineering School of Engineering Sciences Huazhong University of Sci

Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed. However, only a few studies have comprehensively compared medical image registration approaches on a wide range of clinically relevant tasks. This limits the development of registration methods, the adoption of research advances into practice, and a fair benchmark across competing approaches. The Learn2Reg challenge addresses these limitations by providing a multi-task medical image registration data set for comprehensive characterisation of deformable registration algorithms. A continuous evaluation will be possible at https://***. Learn2Reg covers a wide range of anatomies (brain, abdomen, and thorax), modalities (ultrasound, CT, MR), availability of annotations, as well as intra- and inter-patient registration evaluation. We established an easily accessible framework for training and validation of 3D registration methods, which enabled the compilation of results of over 65 individual method submissions from more than 20 unique teams. We used a complementary set of metrics, including robustness, accuracy, plausibility, and runtime, enabling unique insight into the current state-of-the-art of medical image registration. This paper describes datasets, tasks, evaluation methods and results of the challenge, as well as results of further analysis of transferability to new datasets, the importance of label supervision, and resulting bias. While no single approach worked best across all tasks, many methodological aspects could be identified that push the performance of medical image registration to new state-of-the-art performance. Furthermore, we demystified the common belief that conventional registration methods have to be much slower than deep-learning-based methods. © 2021, CC BY.

关键词： Image registration

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The Liver Tumor Segmentation Benchmark (LiTS)

arXiv

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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

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GLOBAL CLIMATE

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Bulletin of the American Meteorological Society 2024年第8期105卷 S12-S155页

作者： Dunn, R.J.H. Blannin, J. Gobron, N. Miller, J.B. Willett, K.M. Met Office Hadley Centre Exeter United Kingdom European Commission Joint Research Centre Ispra Italy NOAA Global Monitoring Laboratory Boulder Colorado European Centre for Medium-Range Weather Forecasts Reading United Kingdom University of Maryland College Park Maryland European Centre for Medium-Range Weather Forecasts Bonn Germany Department of Meteorology and National Centre for Earth Observation University of Reading Reading United Kingdom Hampton University Hampton Virginia National Research Institute for Agriculture Food and Environment (INRAE) CARRTEL Université Savoie Mont Blanc Thonon les Bains France Graduate School of Agriculture Osaka Metropolitan University Sakai Japan NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Science Faculty Universidad Nacional de Colombia Bogotá Colombia University of Bremen Bremen Germany Centro de Investigaciones sobre Desertificación – Spanish National Research Council (CSIC-UV-GVA) Valencia Spain Hydro-Climate Extremes Lab (H-CEL) Ghent University Ghent Belgium Laboratoire des Sciences du Climat et de l’Environnement (LSCE) LSCE/IPSL CEA-CNRS-UVSQ Gif-sur-Yvette France Instituto de Geografía Pontificia Universidad Católica de Valparaíso Valparaíso Chile Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia University of Reading Reading United Kingdom Institute Pierre Simon Laplace (IPSL) Guyancourt France School of Engineering Newcastle University Newcastle-upon-Tyne United Kingdom Université Paris Cité Institut de physique du globe de Paris CNRS IGN F-75005 Paris France Univ Gustave Eiffel ENSG IGN F-77455 Marne-la-Vallée France Laboratoire EDYTEM CNRS/Université Savoie Mont-Blanc Le Bourget-du-Lac France Global Modeling and Assimilation Office NASA Goddard Space Flight Center Greenbelt Maryland Universität Hamburg Hamburg Germany Climate Dynamics Lab University of St Andrews St Andrews United Kingdom Ea

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The global spectrum of tree crown architecture

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Nature communications 2025年第1期16卷 4876页

作者： Tommaso Jucker Fabian Jörg Fischer Jérôme Chave David A Coomes John Caspersen Arshad Ali Grace Jopaul Loubota Panzou Ted R Feldpausch Daniel Falster Vladimir A Usoltsev Toby D Jackson Stephen Adu-Bredu Luciana F Alves Mohammad Aminpour Bhely Angoboy Ilondea Niels P R Anten Cécile Antin Yousef Askari Narayanan Ayyappan Lindsay F Banin Nicolas Barbier John J Battles Hans Beeckman Yannick E Bocko Ben Bond-Lamberty Frans Bongers Samuel Bowers Michiel van Breugel Arthur Chantrain Rajeev Chaudhary Jingyu Dai Michele Dalponte Kangbéni Dimobe Jean-Christophe Domec Jean-Louis Doucet Juan Manuel Dupuy Rada Remko A Duursma Moisés Enríquez Karin Y van Ewijk William Farfán-Rios Adeline Fayolle Marco Ferretti Eric Forni David I Forrester Hammad Gilani John L Godlee Matthias Haeni Jefferson S Hall Jie-Kun He Andreas Hemp José L Hernández-Stefanoni Steven I Higgins Robert J Holdaway Kiramat Hussain Lindsay B Hutley Tomoaki Ichie Yoshiko Iida Hai-Sheng Jiang Puspa Raj Joshi Hasan Kaboli Maryam Kazempour Larsary Tanaka Kenzo Brian D Kloeppel Takashi S Kohyama Suwash Kunwar Shem Kuyah Jakub Kvasnica Siliang Lin Emily R Lines Hongyan Liu Craig Lorimer Jean-Joël Loumeto Yadvinder Malhi Peter L Marshall Eskil Mattsson Radim Matula Jorge A Meave Sylvanus Mensah Xiangcheng Mi Stéphane T Momo Glenn R Moncrieff Francisco Mora Rodrigo Muñoz Sarath P Nissanka Zamah Shari Nur Hajar Kevin L O'Hara Steven Pearce Raphaël Pelissier Pablo L Peri Pierre Ploton Lourens Poorter Mohsen Javanmiri Pour Hassan Pourbabaei Sabina C Ribeiro Casey Ryan Anvar Sanaei Jennifer Sanger Michael Schlund Giacomo Sellan Alexander Shenkin Bonaventure Sonké Frank J Sterck Martin Svátek Kentaro Takagi Anna T Trugman Matthew A Vadeboncoeur Ahmad Valipour Mark C Vanderwel Alejandra G Vovides Peter Waldner Weiwei Wang Li-Qiu Wang Christian Wirth Murray Woods Wenhua Xiang Fabiano de Aquino Ximenes Yaozhan Xu Toshihiro Yamada Miguel A Zavala Niklaus E Zimmermann School of Biological Sciences University of Bristol Bristol BS8 1TQ UK. t.jucker@bristol.ac.uk. School of Biological Sciences University of Bristol Bristol BS8 1TQ UK. UMR5300 Centre de Recherche sur la Biodiversité et l'Environnement CNRS INPT IRD Université de Toulouse Bât 4R1 118 route de Narbonne 31062 Toulouse France. Conservation Research Institute University of Cambridge Cambridge CB2 3EA UK. Institute of Forestry and Conservation University of Toronto 33 Willcocks Street Toronto ON M5S 3B3 Canada. Forest Ecology Research Group College of Life Sciences Hebei University Baoding 071002 Hebei China. Institut Supérieur des Sciences Géographiques Environnementales et de l'Aménagement (ISSGEA) Université DENIS SASSOU-N'GUESSO Kintélé République du Congo. Laboratoire de Biodiversité de Gestion des Ecosystèmes et de l'Environnement (LBGE) Faculté des Sciences et Techniques Université Marien NGOUABI BP 69 Brazzaville Brazzaville République du Congo. Faculty of Environment Science and Economy University of Exeter Exeter EX4 4QE UK. Evolution & Ecology Research Centre University of New South Wales Sydney NSW Sydney Australia. Department of Forest Mensuration and Management Ural State Forest Engineering and Economic University Yekaterinburg Russia. Forestry Research Institute of Ghana Council for Scientific and Industrial Research University Kumasi Ghana. Center for Tropical Research Institute of the Environment and Sustainability University of California Los Angeles Los Angeles CA USA. Natural Recourses and Watershed Management Office West Azerbaijan Province Urmia Iran. Institut National pour l'Etude et la Recherche Agronomiques BP 2037 Kinshasa Democratic Republic of the Congo. Université Pédagogique Nationale BP 8815 Kinshasa-Ngaliema Democratic Republic of the Congo. Center for Crop Systems Analysis Wageningen University & Research Wageningen Netherlands. AMAP lab Montpellier University IRD CIRAD CNRS INRAE Montpellier France. Rese

Trees can differ enormously in their crown architectural traits, such as the scaling relationships between tree height, crown width and stem diameter. Yet despite the importance of crown architecture in shaping the structure and function of terrestrial ecosystems, we lack a complete picture of what drives this incredible diversity in crown shapes. Using data from 374,888 globally distributed trees, we explore how climate, disturbance, competition, functional traits, and evolutionary history constrain the height and crown width scaling relationships of 1914 tree species. We find that variation in height-diameter scaling relationships is primarily controlled by water availability and light competition. Conversely, crown width is predominantly shaped by exposure to wind and fire, while also covarying with functional traits related to mechanical stability and photosynthesis. Additionally, we identify several plant lineages with highly distinctive stem and crown forms, such as the exceedingly slender dipterocarps of Southeast Asia, or the extremely wide crowns of legume trees in African savannas. Our study charts the global spectrum of tree crown architecture and pinpoints the processes that shape the 3D structure of woody ecosystems.

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Deep learning for multi-messenger astrophysics a gateway for discovery in the big data era

arXiv

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arXiv 2019年

作者： Allen, Gabrielle Andreoni, Igor Bachelet, Etienne Bruce Berriman, G. Bianco, Federica B. Biswas, Rahul Kind, Matias Carrasco Chard, Kyle Cho, Minsik Cowperthwaite, Philip S. Etienne, Zachariah B. George, Daniel Gibbs, Tom Graham, Matthew Gropp, William Gupta, Anushri Haas, Roland Huerta, E.A. Jennings, Elise Katz, Daniel S. Khan, Asad Kindratenko, Volodymyr Kramer, William T.C. Liu, Xin Mahabal, Ashish McHenry, Kenton Miller, J.M. Neubauer, M.S. Oberlin, Steve Olivas, Alexander R. Rosofsky, Shawn Ruiz, Milton Saxton, Aaron Schutz, Bernard Schwing, Alex Seidel, Ed Shapiro, Stuart L. Shen, Hongyu Shen, Yue Sipocz, Brigitta M. Sun, Lunan Towns, John Tsokaros, Antonios Wei, Wei Wells, Jack Williams, Timothy J. Xiong, Jinjun Zhao, Zhizhen NCSA University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Astronomy University of Illinois at Urbana-Champaign UrbanaIL61801 United States California Institute of Technology 1200 E California Blvd PasadenaCA91125 United States Las Cumbres Observatory 6740 Cortona Drive Suite 102 GoletaCA93117 United States Caltech/IPAC-NExScI 1200 E California Blvd PasadenaCA91125 United States Department of Physics and Astronomy University of Delaware NewarkDE19716 United States Joseph R. Biden Jr . School of Public Policy and Administration University of Delaware NewarkDE19716 United States Data Science Institute University of Delaware NewarkDE19716 United States Center for Urban Science and Progress New York University 370 Jay St BrooklynNY11201 United States The Oskar Klein Centre for Cosmoparticle Physics Stockholm University AlbaNova StockholmSE-106 91 Sweden University of Chicago ChicagoIL60605 United States IBM Systems AustinTX78717 United States Observatories of the Carnegie Institution for Science 813 Santa Barbara St. PasadenaCA91101 United States Department of Mathematics West Virginia University MorgantownWV26506 United States Center for Gravitational Waves and Cosmology West Virginia University Chestnut Ridge Research Building MorgantownWV26505 United States NVIDIA 2788 San Tomas Expressway Santa ClaraCA95050 United States Center for Data Driven Discovery Caltech PasadenaCA91125 United States Department of Computer Science University of Illinois at Urbana-Champaign UrbanaIL61801 United States Argonne National Laboratory Leadership Computing Facility LemontIL60439 United States Department of Electrical & Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States School of Information Sciences University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Physics University of Illinois at Urbana-Champaign UrbanaIL61801 Unit

This report provides an overview of recent work that harnesses the Big Data Revolution and Large Scale computing to address grand computational challenges in Multi-Messenger Astrophysics, with a particular emphasis on real-time discovery campaigns. Acknowledging the transdisciplinary nature of Multi-Messenger Astrophysics, this document has been prepared by members of the physics, astronomy, computer science, data science, software and cyberinfrastructure communities who attended the NSF-, DOE- and NVIDIA-funded "Deep Learning for Multi-Messenger Astrophysics: Real-time Discovery at Scale" workshop, hosted at the National Center for Supercomputing Applications, October 17-19, 2018. Highlights of this report include unanimous agreement that it is critical to accelerate the development and deployment of novel, signal-processing algorithms that use the synergy between artificial intelligence (AI) and high performance computing to maximize the potential for scientific discovery with Multi-Messenger Astrophysics. We discuss key aspects to realize this endeavor, namely (i) the design and exploitation of scalable and computationally efficient AI algorithms for Multi-Messenger Astrophysics;(ii) cyberinfrastructure requirements to numerically simulate astrophysical sources, and to process and interpret Multi-Messenger Astrophysics data;(iii) management of gravitational wave detections and triggers to enable electromagnetic and astro-particle follow-ups;(iv) a vision to harness future developments of machine and deep learning and cyberinfrastructure resources to cope with the scale of discovery in the Big Data Era;(v) and the need to build a community that brings domain experts together with data scientists on equal footing to maximize and accelerate discovery in the nascent field of Multi-Messenger Astrophysics. Copyright © 2019, The Authors. All rights reserved.

关键词： Big data

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Highlights from the 11th ISCB Student Council Symposium 2015. Dublin, Ireland. 10 July 2015

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BMC bioinformatics 2016年第3期17 Suppl 3卷 95页

作者： Katie Wilkins Mehedi Hassan Margherita Francescatto Jakob Jespersen R. Gonzalo Parra Bart Cuypers Dan DeBlasio Alexander Junge Anupama Jigisha Farzana Rahman Griet Laenen Sander Willems Lieven Thorrez Yves Moreau Nagarajan Raju Sonia Pankaj Chothani C. Ramakrishnan Masakazu Sekijima M. Michael Gromiha Paddy J Slator Nigel J Burroughs Przemysław Szałaj Zhonghui Tang Paul Michalski Oskar Luo Xingwang Li Yijun Ruan Dariusz Plewczynski Giulia Fiscon Emanuel Weitschek Massimo Ciccozzi Paola Bertolazzi Giovanni Felici Pieter Meysman Manu Vanaerschot Maya Berg Hideo Imamura Jean-Claude Dujardin Kris Laukens Westa Domanova James R. Krycer Rima Chaudhuri Pengyi Yang Fatemeh Vafaee Daniel J. Fazakerley Sean J. Humphrey David E. James Zdenka Kuncic Plant Pathology and Plant-Microbe Biology Section School of Integrative Plant Science Cornell University Ithaca USA Graduate Field of Computational Biology Cornell University Ithaca USA School of Computing & Mathematics University of South Wales Cardiff UK Department of Genome Biology for Neurodegenerative Diseases German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association ᅟ Germany Department of Surgery Massachusetts General Hospital The Broad Institute of MIT and Harvard Boston USA Department of Systems Biology Technical University of Denmark Kemitorvet Denmark Protein Physiology Lab Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Buenos Aires Argentina Molecular Parasitology Unit (MPU) Institute of Tropical Medicine Antwerp Belgium Advanced Database Research and Modeling (ADReM) research group University of Antwerp Antwerpen Belgium Department of Computer Science University of Arizona Tucson USA Department of Veterinary Clinical and Animal Sciences Center for non-coding RNA in Technology and Health University of Copenhagen Copenhagen Denmark University College Dublin Dublin Ireland Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Minds Medical IT Department Leuven Belgium Scientific Institute of Public Health (WIV-ISP) Platform of Biotechnology and Molecular Biology (PBB) Brussels Belgium Department of Development and Regeneration @ Kulak KU Leuven Kortrijk Belgium Department of Biotechnology Bhupat and Jyoti Metha School of Biosciences Indian Institute of Technology Madras Chennai India Philips Research North America Briarcliff Manor USA Global Scientific Information and Computing Center (GSIC) Tokyo Institute of Technology Tokyo Japan Systems Biology Centre University of Warwick Senate House Coventry UK Systems Biology Doctoral Training Centre University of Warwick Senate House Coventry UK Center for B

A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laenen, Sander Willems, Lieven Thorrez, Yves Moreau O2 Organism specific protein-RNA recognition: A computational analysis of protein-RNA complex structures from different organisms Nagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael Gromiha O3 Detection of Heterogeneity in Single Particle Tracking Trajectories Paddy J Slator, Nigel J Burroughs O4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecture Przemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz Plewczynski O5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classification Giulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni Felici O6 A systems Biology Compendium for Leishmania donovani Bart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris Laukens O7 Unravelling signal coordination from large scale phosphorylation kinetic data Westa Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic

关键词： Visceral Leishmaniasis Feature Selection Method Frequent Itemset Mining Leishmania Donovani Student Council

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Launching the VASCO Citizen Science Project

arXiv

引用

arXiv 2020年

作者： Villarroel, Beatriz Pelckmans, Kristiaan Solano, Enrique Laaksoharju, Mikael Souza, Abel Dom, Onyeuwaoma Nnaemeka Laggoune, Khaoula Mimouni, Jamal Guergouri, Hichem Mattsson, Lars García, Aurora Lago Soodla, Johan Castillo, Diego Shultz, Matthew E. Aworka, Rubby Comerón, Sébastien Geier, Stefan Marcy, Geoffrey W. Gupta, Alok C. Bergstedt, Josefine Bär, Rudolf E. Buelens, Bart Enriquez, Emilio Mellon, Christopher K. Prieto, Almudena Wamalwa, Dismas Simiyu de Souza, Rafael S. Ward, Martin J. Nordita KTH Royal Institute of Technology Stockholm University Roslagstullsbacken 23 StockholmSE-106 91 Sweden Instituto de Astrofísica de Canarias Avda Vía Láctea s/n Tenerife La LagunaE-38205 Spain Department of Information Technology Uppsala University Box 337 UppsalaSE-751 05 Sweden P.O. Box 78 Villanueva de la CañadaE-28691 Spain Autonomous Distributed Systems Lab Department of Computing Science Umeå Universitet Umeå901 87 Sweden Center for Basic Space Science National Space Research and Development Agency P.O. Box 2022 Nsukka Enugu410002 Nigeria Sirius Astronomy Association Sirius Astronomy Association BP 18 Cité du 20 Aout Constantine25000 Algeria Department of Physics University of Constantine 1 LPMPS CERIST Constantine25000 Algeria Science of Matter Division Research Unit in Scientific Mediation CERIST Constantine25016 Algeria IES Tartessos Barriada Hiconsa s/n Camas Sevilla41900 Spain Department of Physics & Astronomy University of Delaware 217 Sharp Lab NewarkDE19716 United States Ghana Space Science and Technology Institute Atomic-Haatso Road Kwabenya Box LG 80 Accra233 Ghana University of Ghana Summerhill Estates Ltd Rd Santeo P.O. Box LG 25 Legon Accra Ghana Departamento de Astrofísica Universidad de La Laguna Tenerife La LagunaE-38206 Spain Cuesta de San José s/n La Palma Breña Baja38712 Spain Space Laser Awareness 3883 Petaluma Hill Rd Santa RosaCA95404 United States Manora Peak Nainital263 001 India Freelance Uppsala752 17 Sweden Institute for Particle Physics and Astrophysics ETH Zürich Wolfgang-Pauli-Strasse 27 ZürichCH-8093 Switzerland Mol2400 Belgium Department of Astrophysics IMAPP Radboud University Nijmegen Nijmegen6525 AJ Netherlands Galileo project affiliate Meru Physics Department University of Science and Technology Meru P.O. Box Kenya972-60200 Kenya Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences 80

The Vanishing & Appearing Sources during a Century of Observations (VASCO) project investigates astronomical surveys spanning a time interval of 70 years, searching for unusual and exotic transients. We present herein the VASCO Citizen Science Project, which can identify unusual candidates driven by three different approaches: hypothesis, exploratory, and machine learning, which is particularly useful for SETI searches. To address the big data challenge, VASCO combines three methods: the Virtual Observatory, user-aided machine learning, and visual inspection through citizen science. Here we demonstrate the citizen science project and its improved candidate selection process, and we give a progress report. We also present the VASCO citizen science network led by amateur astronomy associations mainly located in Algeria, Cameroon, and Nigeria. At the moment of writing, the citizen science project has carefully examined 15,593 candidate image pairs in the data (ca. 10% of the candidates), and has so far identified 798 objects classified as "vanished". The most interesting candidates will be followed up with optical and infrared imaging, together with the observations by the most potent radio telescopes. Copyright © 2020, The Authors. All rights reserved.

关键词： Machine learning

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