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Publisher Correction: Ozone pollution mitigation strategy informed by long-term trends of atmospheric oxidation capacity

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Nature Geoscience 2024年 172页

作者： Wenjie Wang Xin Li Ying Liu Sihua Lu Yusheng Wu Shiyi Chen Keding Lu Min Hu Limin Zeng Min Shao Yuanhang Zhang Hang Su Yafang Cheng Ruijing Ni Ulrich Pöschl Zhaofeng Tan Franz Rohrer Andreas Wahner David D. Parrish Cheng Huang Xudong Tian K. M. Leung Liangfu Chen Meng Fan Qiang Zhang State Key Joint Laboratory of Environmental Simulation and Pollution Control College of Environmental Sciences and Engineering Peking University Beijing China State Key Laboratory of Atmospheric Environment and Extreme Meteorology Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China Max Planck Institute for Chemistry Mainz Germany International Joint Laboratory for Regional Pollution Control Ministry of Education Beijing China Collaborative Innovation Centre of Atmospheric Environment and Equipment Technology Nanjing University of Information Science & Technology Nanjing China Institute of Carbon Neutrality Peking University Beijing China Institute for Environmental and Climate Research Jinan University Guangzhou China State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex Shanghai Academy of Environmental Sciences Shanghai China Institut für Energie-und Klimaforschung: Troposphäre (IEK-8) Forschungszentrum Jülich Jülich Germany Key Laboratory of Ecological and Environmental Monitoring Forewarning and Quality Control of Zhejiang Zhejiang Ecological and Environmental Monitoring Center Hangzhou China Environmental Protection Department The Government of the Hong Kong Special Administrative Region Hong Kong China State Key Laboratory of Remote Sensing Science The Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Department of Earth System Science Tsinghua University Beijing China

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A ring-like accretion structure in M87 connecting its black hole and jet

arXiv

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arXiv 2023年

作者： Lu, Ru-Sen Asada, Keiichi Krichbaum, Thomas P. Park, Jongho Tazaki, Fumie Pu, Hung-Yi Nakamura, Masanori Lobanov, Andrei Hada, Kazuhiro Akiyama, Kazunori Kim, Jae-Young Marti-Vidal, Ivan Gómez, José L. Kawashima, Tomohisa Yuan, Feng Ros, Eduardo Alef, Walter Britzen, Silke Bremer, Michael Broderick, Avery E. Doi, Akihiro Giovannini, Gabriele Giroletti, Marcello Ho, Paul T.P. Honma, Mareki Hughes, David H. Inoue, Makoto Jiang, Wu Kino, Motoki Koyama, Shoko Lindqvist, Michael Liu, Jun Marscher, Alan P. Matsushita, Satoki Nagai, Hiroshi Rottmann, Helge Savolainen, Tuomas Schuster, Karl-Friedrich Shen, Zhi-Qiang de Vicente, Pablo Walker, R. Craig Yang, Hai Zensus, J. Anton Algaba, Juan Carlos Allardi, Alexander Bach, Uwe Berthold, Ryan Bintley, Dan Byun, Do-Young Casadio, Carolina Chang, Shu-Hao Chang, Chih-Cheng Chang, Song-Chu Chen, Chung-Chen Chen, Ming-Tang Chilson, Ryan Chuter, Tim C. Conway, John Crew, Geoffrey B. Dempsey, Jessica T. Dornbusch, Sven Faber, Aaron Friberg, Per García, Javier González Garrido, Miguel Gómez Han, Chih-Chiang Han, Kuo-Chang Hasegawa, Yutaka Herrero-Illana, Ruben Huang, Yau-De Huang, Chih-Wei L. Impellizzeri, Violette Jiang, Homin Jinchi, Hao Jung, Taehyun Kallunki, Juha Kirves, Petri Kimura, Kimihiro Koay, Jun Yi Koch, Patrick M. Kramer, Carsten Kraus, Alex Kubo, Derek Kuo, Cheng-Yu Li, Chao-Te Lin, Lupin Chun-Che Liu, Ching-Tang Liu, Kuan-Yu Lo, Wen-Ping Lu, Li-Ming MacDonald, Nicholas Martin-Cocher, Pierre Messias, Hugo Meyer-Zhao, Zheng Minter, Anthony Nair, Dhanya G. Nishioka, Hiroaki Norton, Timothy J. Nystrom, George Ogawa, Hideo Oshiro, Peter Patel, Nimesh A. Pen, Ue-Li Pidopryhora, Yurii Pradel, Nicolas Raffin, Philippe A. Rao, Ramprasad Ruiz, Ignacio Sanchez, Salvador Shaw, Paul Snow, William Sridharan, T.K. Srinivasan, Ranjani Tercero, Belén Torne, Pablo Traianou, Efthalia Wagner, Jan Walther, Craig Wei, Ta-Shun Yang, Jun Yu, Chen-Yu Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai China Key Laboratory of Radio Astronomy Chinese Academy of Sciences Nanjing China Max-Planck-Institut für Radioastronomie Bonn Germany Institute of Astronomy and Astrophysics Academia Sinica Taipei Taiwan Korea Astronomy and Space Science Institute Daejeon Korea Republic of Simulation Technology Development Department Tokyo Electron Technology Solutions Oshu Japan Mizusawa VLBI Observatory National Astronomical Observatory of Japan Oshu Japan Department of Physics National Taiwan Normal University Taipei Taiwan Center of Astronomy and Gravitation National Taiwan Normal University Taipei Taiwan Department of General Science and Education National Institute of Technology Hachinohe College Hachinohe City Japan Department of Astronomical Science The Graduate University for Advanced Studies SOKENDAI Mitaka Japan Black Hole Initiative Harvard University CambridgeMA United States Massachusetts Institute of Technology Haystack Observatory WestfordMA United States National Astronomical Observatory of Japan Mitaka Japan Department of Astronomy and Atmospheric Sciences Kyungpook National University Daegu Korea Republic of Departament d’Astronomia i Astrofísica Universitat de València Valencia Spain Observatori Astronòmic Universitat de València Valencia Spain Instituto de Astrofísica de Andalucía-CSIC Granada Spain Institute for Cosmic Ray Research The University of Tokyo Chiba Japan Key Laboratory for Research in Galaxies and Cosmology Chinese Academy of Sciences Shanghai China School of Astronomy and Space Sciences University of Chinese Academy of Sciences Beijing China Institut de Radioastronomie Millimétrique Saint Martin d’Hères France Department of Physics and Astronomy University of Waterloo WaterlooON Canada Waterloo Centre for Astrophysics University of Waterloo WaterlooON Canada Perimeter Institute for Theoretical Physics WaterlooON Canada Institute of Space and Astron

The nearby radio galaxy M87 is a prime target for studying black hole accretion and jet formation1,2. Event Horizon Telescope observations of M87 in 2017, at a wavelength of 1.3 mm, revealed a ring-like structure, which was interpreted as gravitationally lensed emission around a central black hole3. Here we report images of M87 obtained in 2018, at a wavelength of 3.5 mm, showing that the compact radio core is spatially resolved. High-resolution imaging shows a ring-like structure of 8. 4!1.1$0.5 Schwarzschild radii in diameter, approximately 50% larger than that seen at 1.3 mm. The outer edge at 3.5 mm is also larger than that at 1.3 mm. This larger and thicker ring indicates a substantial contribution from the accretion flow with absorption effects in addition to the gravitationally lensed ring-like emission. The images show that the edge–brightened jet connects to the accretion flow of the black hole. Close to the black hole, the emission profile of the jet-launching region is wider than the expected profile of a black -hole-driven jet, suggesting the possible presence of a wind associated with the accretion flow. © 2023, CC BY.

关键词： Galaxies

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A ring-like accretion structure in M87 connecting its black hole and jet

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Nature 2023年第7958期616卷 686-690页

作者： Ru-Sen Lu Keiichi Asada Thomas P Krichbaum Jongho Park Fumie Tazaki Hung-Yi Pu Masanori Nakamura Andrei Lobanov Kazuhiro Hada Kazunori Akiyama Jae-Young Kim Ivan Marti-Vidal José L Gómez Tomohisa Kawashima Feng Yuan Eduardo Ros Walter Alef Silke Britzen Michael Bremer Avery E Broderick Akihiro Doi Gabriele Giovannini Marcello Giroletti Paul T P Ho Mareki Honma David H Hughes Makoto Inoue Wu Jiang Motoki Kino Shoko Koyama Michael Lindqvist Jun Liu Alan P Marscher Satoki Matsushita Hiroshi Nagai Helge Rottmann Tuomas Savolainen Karl-Friedrich Schuster Zhi-Qiang Shen Pablo de Vicente R Craig Walker Hai Yang J Anton Zensus Juan Carlos Algaba Alexander Allardi Uwe Bach Ryan Berthold Dan Bintley Do-Young Byun Carolina Casadio Shu-Hao Chang Chih-Cheng Chang Song-Chu Chang Chung-Chen Chen Ming-Tang Chen Ryan Chilson Tim C Chuter John Conway Geoffrey B Crew Jessica T Dempsey Sven Dornbusch Aaron Faber Per Friberg Javier González García Miguel Gómez Garrido Chih-Chiang Han Kuo-Chang Han Yutaka Hasegawa Ruben Herrero-Illana Yau-De Huang Chih-Wei L Huang Violette Impellizzeri Homin Jiang Hao Jinchi Taehyun Jung Juha Kallunki Petri Kirves Kimihiro Kimura Jun Yi Koay Patrick M Koch Carsten Kramer Alex Kraus Derek Kubo Cheng-Yu Kuo Chao-Te Li Lupin Chun-Che Lin Ching-Tang Liu Kuan-Yu Liu Wen-Ping Lo Li-Ming Lu Nicholas MacDonald Pierre Martin-Cocher Hugo Messias Zheng Meyer-Zhao Anthony Minter Dhanya G Nair Hiroaki Nishioka Timothy J Norton George Nystrom Hideo Ogawa Peter Oshiro Nimesh A Patel Ue-Li Pen Yurii Pidopryhora Nicolas Pradel Philippe A Raffin Ramprasad Rao Ignacio Ruiz Salvador Sanchez Paul Shaw William Snow T K Sridharan Ranjani Srinivasan Belén Tercero Pablo Torne Efthalia Traianou Jan Wagner Craig Walther Ta-Shun Wei Jun Yang Chen-Yu Yu Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai People's Republic of China. rslu@***. Key Laboratory of Radio Astronomy Chinese Academy of Sciences Nanjing People's Republic of China. rslu@***. Max-Planck-Institut für Radioastronomie Bonn Germany. rslu@***. Institute of Astronomy and Astrophysics Academia Sinica Taipei Taiwan ROC. asada@asiaa.sinica.edu.tw. Max-Planck-Institut für Radioastronomie Bonn Germany. tkrichbaum@mpifr-bonn.mpg.de. Institute of Astronomy and Astrophysics Academia Sinica Taipei Taiwan ROC. Korea Astronomy and Space Science Institute Daejeon Republic of Korea. Simulation Technology Development Department Tokyo Electron Technology Solutions Oshu Japan. Mizusawa VLBI Observatory National Astronomical Observatory of Japan Oshu Japan. Department of Physics National Taiwan Normal University Taipei Taiwan ROC. Center of Astronomy and Gravitation National Taiwan Normal University Taipei Taiwan ROC. Department of General Science and Education National Institute of Technology Hachinohe College Hachinohe City Japan. Max-Planck-Institut für Radioastronomie Bonn Germany. Mizusawa VLBI Observatory National Astronomical Observatory of Japan Oshu Japan. kazuhiro.hada@nao.ac.jp. Department of Astronomical Science The Graduate University for Advanced Studies SOKENDAI Mitaka Japan. kazuhiro.hada@nao.ac.jp. Black Hole Initiative Harvard University Cambridge MA USA. Massachusetts Institute of Technology Haystack Observatory Westford MA USA. National Astronomical Observatory of Japan Mitaka Japan. Department of Astronomy and Atmospheric Sciences Kyungpook National University Daegu Republic of Korea. Departament d'Astronomia i Astrofísica Universitat de València Valencia Spain. Observatori Astronòmic Universitat de València Valencia Spain. Instituto de Astrofísica de Andalucía-CSIC Granada Spain. Institute for Cosmic Ray Research The University of Tokyo Chiba Japan. Shanghai Astronomical Observatory Chinese Academy of S

The nearby radio galaxy M87 is a prime target for studying black hole accretion and jet formation. Event Horizon Telescope observations of M87 in 2017, at a wavelength of 1.3 mm, revealed a ring-like structure, which was interpreted as gravitationally lensed emission around a central black hole. Here we report images of M87 obtained in 2018, at a wavelength of 3.5 mm, showing that the compact radio core is spatially resolved. High-resolution imaging shows a ring-like structure of [Formula: see text] Schwarzschild radii in diameter, approximately 50% larger than that seen at 1.3 mm. The outer edge at 3.5 mm is also larger than that at 1.3 mm. This larger and thicker ring indicates a substantial contribution from the accretion flow with absorption effects, in addition to the gravitationally lensed ring-like emission. The images show that the edge-brightened jet connects to the accretion flow of the black hole. Close to the black hole, the emission profile of the jet-launching region is wider than the expected profile of a black-hole-driven jet, suggesting the possible presence of a wind associated with the accretion flow.

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROscience 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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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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