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arXiv 2021年

作者： Antonelli, Michela Reinke, Annika Bakas, Spyridon Farahani, Keyvan Kopp-Schneider, Annette Landman, Bennett A. Litjens, Geert Menze, Bjoern Ronneberger, Olaf Summers, Ronald M. van Ginneken, Bram Bilello, Michel Bilic, Patrick Christ, Patrick F. Do, Richard K.G. Gollub, Marc J. Heckers, Stephan H. Huisman, Henkjan Jarnagin, William R. McHugo, Maureen K. Napel, Sandy Golia Pernicka, Jennifer S. Rhode, Kawal Tobon-Gomez, Catalina Vorontsov, Eugene Hulsmon, Hankan Meakin, James A. Ourselin, Sebastien Wiesenfarth, Manuel Arbeláez, Pablo Bae, Byeonguk Chen, Sihong Daza, Laura Feng, Jianjiang He, Baochun Isensee, Fabian Ji, Yuanfeng Jia, Fucang Kim, Namkug Kim, Ildoo Merhof, Dorit Pai, Akshay Park, Beomhee Perslev, Mathias Rezaiifar, Ramin Rippel, Oliver Sarasua, Ignacio Shen, Wei Son, Jaemin Wachinger, Christian Wang, Liansheng Wang, Yan Xia, Yingda Xu, Daguang Xu, Zhanwei Zheng, Yefeng Simpson, Amber L. Maier-Hein, Lena Cardoso, M. Jorge School of Biomedical Engineering & Imaging Sciences King’s College London London United Kingdom Heidelberg Germany Heidelberg Germany Faculty of Mathematics and Computer Science University of Heidelberg Heidelberg Germany University of Pennsylvania PhiladelphiaPA United States BethesdaMD United States Heidelberg Germany Electrical Engineering and Computer Science Vanderbilt University NashvilleTN United States Radboud University Medical Center Radboud Institute for Health Sciences Nijmegen Netherlands Quantitative Biomedicine University of Zurich Zurich Switzerland DeepMind London United Kingdom School of Computing Department of Biomedical and Molecular Sciences Queen’s University KingstonON Canada Department of Surgery Memorial Sloan Kettering Cancer Center New YorkNY United States BethesdaMD United States Department of Informatics Technische Universität München Germany Department of Radiology Memorial Sloan Kettering Cancer Center New YorkNY United States Department of Psychiatry & Behavioral Sciences Vanderbilt University Medical Center NashvilleTN United States Department of Radiology Stanford University StanfordCA United States Department of Computer Science and Software Engineering École Polytechnique de Montréal Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Medical Faculty University of Heidelberg Heidelberg Germany VUNO Inc. Seoul Korea Republic of Universidad de los Andes Colombia Department of Automation Tsinghua University Beijing China Heidelberg Germany Department of Computer Science Xiamen University Xiamen361005 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Kakao Brain Korea Republic of Institute of Imaging & Computer Vision RWTH Aachen University Aachen Germany Cere

International challenges have become the de facto standard for comparative assessment of image analysis algorithms given a specific task. Segmentation is so far the most widely investigated medical image processing task, but the various segmentation challenges have typically been organized in isolation, such that algorithm development was driven by the need to tackle a single specific clinical problem. We hypothesized that a method capable of performing well on multiple tasks will generalize well to a previously unseen task and potentially outperform a custom-designed solution. To investigate the hypothesis, we organized the Medical Segmentation Decathlon (MSD)—a biomedical image analysis challenge, in which algorithms compete in a multitude of both tasks and modalities. The underlying data set was designed to explore the axis of difficulties typically encountered when dealing with medical images, such as small data sets, unbalanced labels, multi-site data and small objects. The MSD challenge confirmed that algorithms with a consistent good performance on a set of tasks preserved their good average performance on a different set of previously unseen tasks. Moreover, by monitoring the MSD winner for two years, we found that this algorithm continued generalizing well to a wide range of other clinical problems, further confirming our hypothesis. Three main conclusions can be drawn from this study: (1) state-of-the-art image segmentation algorithms are mature, accurate, and generalize well when retrained on unseen tasks;(2) consistent algorithmic performance across multiple tasks is a strong surrogate of algorithmic generalizability;(3) the training of accurate AI segmentation models is now commoditized to non AI *** Codes 68T07. © 2021, CC BY-NC-SA.

关键词： Image segmentation

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Brain modelling as a service: The virtual brain on EBRAINS

arXiv

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arXiv 2021年

作者： Schirner, Michael Domide, Lia Perdikis, Dionysios Triebkorn, Paul Stefanovski, Leon Pai, Roopa Prodan, Paula Valean, Bogdan Palmer, Jessica Langford, Chloê Blickensdörfer, André van der Vlag, Michiel Diaz-Pier, Sandra Peyser, Alexander Klijn, Wouter Pleiter, Dirk Nahm, Anne Schmid, Oliver Woodman, Marmaduke Zehl, Lyuba Fousek, Jan Petkoski, Spase Kusch, Lionel Hashemi, Meysam Marinazzo, Daniele Mangin, Jean-François Flöel, Agnes Akintoye, Simisola Stahl, Bernd Carsten Cepic, Michael Johnson, Emily Deco, Gustavo McIntosh, Anthony R. Hilgetag, Claus C. Morgan, Marc Schuller, Bernd Upton, Alex McMurtrie, Colin Dickscheid, Timo Bjaalie, Jan G. Amunts, Katrin Mersmann, Jochen Jirsa, Viktor Ritter, Petra Berlin Institute of Health Charité - Universitätsmedizin Berlin Charitéplatz 1 Berlin10117 Germany Charité - Universitätsmedizin Berlin Freie Universität Berlin Humboldt Universität zu Berlin Department of Neurology with Experimental Neurology Charitéplatz 1 Berlin10117 Germany Bernstein Focus State Dependencies of Learning Bernstein Center for Computational Neuroscience Berlin Germany Einstein Center for Neuroscience Berlin Charitéplatz 1 Berlin10117 Germany Einstein Center Digital Future Wilhelmstraße 67 Berlin10117 Germany Codemart Str. Petofi Sandor Cluj Napoca Romania Institut de Neurosciences des Systèmes Aix Marseille Université Marseille France Institute for Advanced Simulation JARA Forschungszentrum Jülich GmbH Jülich Germany Jülich Supercomputer Centre Forschungszentrum Jülich Jülich Germany Institut für Theoretische Physik Universität Regensburg Regensburg Germany Campus Biotech Geneva Switzerland Research Centre Jülich Jülich Germany Department of Data-Analysis Faculty of Psychology and Educational Sciences Ghent University Belgium San Camillo IRCSS Venice Italy Université Paris-Saclay CEA CNRS Neurospin Baobab Gif-sur-Yvette France Department of Neurology University Medicine Greifswald Greifswald Germany Standort Greifswald Greifswald Germany Leicester De Montfort Law School De Montfort University Leicester United Kingdom Centre for Computing and Social Responsibility De Montfort University Leicester United Kingdom Department of Innovation and Digitalisation in Law Faculty of Law University of Vienna Austria Center for Brain and Cognition Computational Neuroscience Group Department of Information and Communication Technologies Universitat Pompeu Fabra Barcelona Spain Institució Catalana de la Recerca i Estudis Avançats Barcelona Spain Department of Neuropsychology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany School of Psychological Sciences Turner Institute for Brain and Mental Health

The Virtual Brain (TVB) is now available as open-source cloud ecosystem on EBRAINS, a shared digital research platform for brain science. It offers services for constructing, simulating and analysing brain network models (BNMs) including the TVB network simulator;magnetic resonance imaging (MRI) processing pipelines to extract structural and functional connectomes;multiscale co-simulation of spiking and large-scale networks;a domain specific language for automatic high-performance code generation from user-specified models;simulation-ready BNMs of patients and healthy volunteers;Bayesian inference of epilepsy spread;data and code for mouse brain simulation;and extensive educational material. TVB cloud services facilitate reproducible online collaboration and discovery of data assets, models, and software embedded in scalable and secure workflows, a precondition for research on large cohort data sets, better generalizability and clinical translation. © 2021, CC BY.

关键词： Open source software

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Shape staggering of midshell mercury isotopes from in-source laser spectroscopy compared with density-functional-theory and Monte Carlo shell-model calculations

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Physical Review C 2019年第4期99卷 044306-044306页

作者： S. Sels T. Day Goodacre B. A. Marsh A. Pastore W. Ryssens Y. Tsunoda N. Althubiti B. Andel A. N. Andreyev D. Atanasov A. E. Barzakh M. Bender J. Billowes K. Blaum T. E. Cocolios J. G. Cubiss J. Dobaczewski G. J. Farooq-Smith D. V. Fedorov V. N. Fedosseev K. T. Flanagan L. P. Gaffney L. Ghys P.-H. Heenen M. Huyse S. Kreim D. Lunney K. M. Lynch V. Manea Y. Martinez Palenzuela T. M. Medonca P. L. Molkanov T. Otsuka J. P. Ramos R. E. Rossel S. Rothe L. Schweikhard M. D. Seliverstov P. Spagnoletti C. Van Beveren P. Van Duppen M. Veinhard E. Verstraelen A. Welker K. Wendt F. Wienholtz R. N. Wolf A. Zadvornaya KU Leuven Instituut voor Kern-en Stralingsfyisca B-3001 Leuven Belgium School of Physics and Astronomy The University of Manchester Manchester M13 9PL United Kingdom CERN CH-1211 Geneve 23 Switzerland Department of Physics University of York York Y010 5DD United Kingdom IPNL Université de Lyon Université Lyon 1 CNRS/IN2P3 F-69622 Villeurbanne France Department of Physics The University of Tokyo Bunkyo-ku 113-0033 Tokyo Japan Physics Department Faculty of Science Jouf University Aljouf Saudi Arabia Department of Nuclear Physics and Biophysics Comenius University in Bratislava 84248 Bratislava Slovakia Advanced Science Research Center Japan Atomic Energy Agency (JAEA) Tokai-mura Japan Max-Planck-Institut für Kernphysik Saupfercheckweg 1 69117 Heidelberg Germany Petersburg Nuclear Physics Institute NRC Kurchatov Institute Gatchina 188300 Russia Institute of Theoretical Physics Faculty of Physics University of Warsaw ul. Pasteura 5 PL-02-093 Warsaw Poland School of Engineering and Computing University of the West of Scotland Paisley PA1 2BE United Kingdom Belgian Nuclear Research Center SCK•CEN Boeretang 200 B-2400 Mol Belgium PNTPM CP229 Universite Libre de Bruxelles B-1050 Bruxelles Belgium CSNSM-IN2P3-CNRS Université Paris-Sud 91406 Orsay France National Superconducting Cyclotron Laboratory Michigan State University East Lansing MI 48824 USA Laboratory of Powder Technology École polytechnique fédérale de Lausanne (EPFL) CH-1015 Lausanne Switzerland Insitut fürPhysik Johannes Gutenberg-Universität 55122 Mainz Germany Institut für Physik Universität Greifswald 17487 Greifswald Germany Technische Universitat Dresden 01069 Dresden Germany

Neutron-deficient Hg177−185 isotopes were studied using in-source laser resonance-ionization spectroscopy at the CERN-ISOLDE radioactive ion-beam facility in an experiment combining different detection methods tailored to the studied isotopes. These include either α-decay tagging or multireflection time-of-flight gating for isotope identification. The endpoint of the odd-even nuclear shape staggering in mercury was observed directly by measuring for the first time the isotope shifts and hyperfine structures of Hg177−180. Changes in the mean-square charge radii for all mentioned isotopes, magnetic dipole, and electric quadrupole moments of the odd-A isotopes and arguments in favor of I=7/2 spin assignment for Hg177,179 were deduced. Experimental results are compared with density functional theory (DFT) and Monte Carlo shell model (MCSM) calculations. DFT calculations using Skyrme parametrizations predict a jump in the charge radius around the neutron N=104 midshell, with an odd-even staggering pattern related to the coexistence of nearly degenerate oblate and prolate minima. This near-degeneracy is highly sensitive to many aspects of the effective interaction, a fact that renders perfect agreement with experiments out of reach for current functionals. Despite this inherent difficulty, the SLy5s1 and a modified UNEDF1SO parametrization predict a qualitatively correct staggering that is off by two neutron numbers. MCSM calculations of states with the experimental spins and parities show good agreement for both electromagnetic moments and the observed charge radii. A clear mechanism for the origin of shape staggering within this context is identified: a substantial change in occupancy of the proton πh9/2 and neutron νi13/2 orbitals.

关键词： Charge distributions Laser spectroscopy Nuclear structure & decays Nucleon distribution 150 ≤ A ≤ 189 Nuclear density functional theory Shell model

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The Parkes Pulsar Timing Array Third Data Release

arXiv

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arXiv 2023年

作者： Zic, Andrew Reardon, Daniel J. Kapur, Agastya Hobbs, George Mandow, Rami Curylo, Malgorzata Shannon, Ryan M. Askew, Jacob Bailes, Matthew Bhat, N.D. Ramesh Cameron, Andrew Chen, Zu-Cheng Dai, Shi Di Marco, Valentina Feng, Yi Kerr, Matthew Kulkarni, Atharva Lower, Marcus E. Luo, Rui Manchester, Richard N. Miles, Matthew T. Nathan, Rowina S. Oslowski, Stefan Rogers, Axl F. Russell, Christopher J. Sarkissian, John M. Shamohammadi, Mohsen Spiewak, Renée Thyagarajan, Nithyanandan Toomey, Lawrence Wang, Shuangqiang Zhang, Lei Zhang, Songbo Zhu, Xing-Jiang Australia Telescope National Facility CSIRO Space and Astronomy PO Box 76 EppingNSW1710 Australia Department of Physics and Astronomy MQ Research Centre in Astronomy Astrophysics and Astrophotonics Macquarie University NSW2109 Australia Centre for Astrophysics and Supercomputing Swinburne University of Technology P.O. Box 218 HawthornVIC3122 Australia OzGrav The Australian Research Council Centre of Excellence for Gravitational Wave Discovery HawthornVIC3122 Australia Astronomical Observatory University of Warsaw Aleje Ujazdowskie 4 Warsaw00-478 Poland International Centre for Radio Astronomy Research Curtin University BentleyWA6102 Australia Advanced Institute of Natural Sciences Beijing Normal University Zhuhai519087 China Department of Physics Synergistic Innovation Center for Quantum Effects and Applications Hunan Normal University Hunan Changsha410081 China School of Science Western Sydney University Locked Bag 1797 Penrith South DCNSW2751 Australia School of Physics and Astronomy Monash University VIC3800 Australia OzGrav The Australian Research Council Centre of Excellence for Gravitational Wave Discovery ClaytonVIC3800 Australia Research Center for Intelligent Computing Platforms Zhejiang Laboratory Hangzhou311100 China Space Science Division US Naval Research Laboratory 4555 Overlook Ave SW WashingtonDC20375 United States Department of Astronomy School of Physics and Materials Science Guangzhou University Guangzhou510006 China Manly Astrophysics 15/41-42 East Esplanade ManlyNSW2095 Australia Institute for Radio Astronomy & Space Research Auckland University of Technology Private Bag 92006 Auckland1142 New Zealand CSIRO Scientific Computing Australian Technology Park Locked Bag 9013 AlexandriaNSW1435 Australia Australia Telescope National Facility CSIRO Space and Astronomy Parkes Observatory PO Box 276 ParkesNSW2870 Australia Jodrell Bank Centre for Astrophysics Department of Physics and Astronomy Universit

We present the third data release from the Parkes Pulsar Timing Array (PPTA) project. The release contains observations of 32 pulsars obtained using the 64-m Parkes "Murriyang" radio telescope. The data span is up to 18 years with a typical cadence of 3 weeks. This data release is formed by combining an updated version of our second data release with ∼ 3 years of more recent data primarily obtained using an ultra-wide-bandwidth receiver system that operates between 704 and 4032 MHz. We provide calibrated pulse profiles, flux-density dynamic spectra, pulse times of arrival, and initial pulsar timing models. We describe methods for processing such wide-bandwidth observations, and compare this data release with our previous release. Copyright © 2023, The Authors. All rights reserved.

关键词： Pulsars

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Evolution of proton single-particle states in neutron-rich Sb isotopes beyond N=82

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Physical Review C 2020年第3期102卷 034324-034324页

作者： A. Jungclaus J. M. Keatings G. S. Simpson H. Naïdja A. Gargano S. Nishimura P. Doornenbal G. Gey G. Lorusso P.-A. Söderström T. Sumikama J. Taprogge Z. Y. Xu H. Baba F. Browne N. Fukuda N. Inabe T. Isobe H. S. Jung D. Kameda G. D. Kim Y.-K. Kim I. Kojouharov T. Kubo N. Kurz Y. K. Kwon Z. Li H. Sakurai H. Schaffner Y. Shimizu H. Suzuki H. Takeda Z. Vajta H. Watanabe J. Wu A. Yagi K. Yoshinaga S. Bönig J.-M. Daugas R. Gernhäuser S. Ilieva T. Kröll A. Montaner-Piza K. Moschner D. Mücher H. Nishibata A. Odahara R. Orlandi M. Scheck K. Steiger A. Wendt Instituto de Estructura de la Materia CSIC E-28006 Madrid Spain School of Computing Engineering and Physical Sciences University of the West of Scotland Paisley PA1 2BE United Kingdom LPSC Université Joseph Fourier Grenoble 1 CNRS/IN2P3 Institut National Polytechnique de Grenoble F-38026 Grenoble Cedex France Laboratoire de Physique Mathematique et Subatomique Constantine 1 University Constantine 25000 Algeria Istituto Nazionale di Fisica Nucleare Complesso Universitario di Monte S. Angelo I-80126 Napoli Italy RIKEN Nishina Center RIKEN 2-1 Hirosawa Wako-shi Saitama 351-0198 Japan Institut Laue-Langevin B.P. 156 F-38042 Grenoble Cedex 9 France Department of Physics Tohoku University Aoba Sendai Miyagi 980-8578 Japan Departamento de Física Teórica Universidad Autónoma de Madrid E-28049 Madrid Spain School of Computing Engineering and Mathematics University of Brighton Brighton BN2 4GJ United Kingdom Department of Physics Chung-Ang University Seoul 156-756 Republic of Korea Rare Isotope Science Project Institute for Basic Science Daejeon 305-811 Republic of Korea Department of Nuclear Engineering Hanyang University Seoul 133-791 Republic of Korea GSI Helmholtzzentrum für Schwerionenforschung GmbH 64291 Darmstadt Germany School of Physics and State Key Laboratory of Nuclear Physics and Technology Peking University Beijing 100871 China Department of Physics University of Tokyo Hongo 7-3-1 Bunkyo-ku 113-0033 Tokyo Japan Atomki P.O. Box 51 Debrecen H-4001 Hungary Department of Physics Osaka University Machikaneyama-machi 1-1 Osaka 560-0043 Toyonaka Japan Department of Physics Faculty of Science and Technology Tokyo University of Science 2641 Yamazaki Noda Chiba Japan Institut für Kernphysik Technische Universität Darmstadt D-64289 Darmstadt Germany CEA DAM DIF 91297 Arpajon cedex France Physik Department E12 Technische Universität München D-85748 Garching Germany Instituto de Fsica Corpuscular CSIC-Univ. of Valencia E-46980 Paterna Spai

The β decay of the semimagic Sn isotopes Sn136,137,138 has been studied at the Radioactive Isotope Beam Factory at the RIKEN Nishina center. The first experimental information on excited states was obtained for Sb137 while, in the case of Sb136, the established excitation scheme could be extended by ten previously unidentified levels. In the decay of the most-neutron-rich isotope Sn138, two γ rays were observed for the first time. The new experimental results, in combination with state-of-the-art shell-model calculations, provide the first information with respect to the evolution of the 0g7/2 and 1d5/2 proton single-particle states with increasing neutron number beyond N=84.

关键词： Beta decay Energy levels & level densities Nuclear structure & decays Shell model 90 ≤ A ≤ 149

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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Simulating nearby disc galaxies on the main star formation sequence I. Bar formation and the building of the central gas reservoir

arXiv

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arXiv 2024年

作者： Verwilghen, Pierrick Emsellem, Eric Renaud, Florent Valentini, Milena Sun, Jiayi Jeffreson, Sarah Klessen, Ralf S. Sormani, Mattia C. Barnes, Ashley T. Dolag, Klaus Grasha, Kathryn Liang, Fu-Heng Meidt, Sharon Neumann, Justus Querejeta, Miguel Schinnerer, Eva Williams, Thomas G. Excellence Cluster ORIGINS Boltzmannstraße 2 Garching85748 Germany European Southern Observatory Karl-Schwarzschild-Straße 2 Garching85748 Germany Univ Lyon Univ Lyon1 ENS de Lyon CNRS Centre de Recherche Astrophysique de Lyon UMR5574 Saint-Genis-LavalF-69230 France Observatoire Astronomique de Strasbourg Université de Strasbourg CNRS UMR 7550 StrasbourgF-67000 France University of Strasbourg Institute for Advanced Study 5 allée du Général Rouvillois StrasbourgF-67083 France Astronomy Unit Department of Physics University of Trieste via Tiepolo 11 TriesteI-34131 Italy INAF – Osservatorio Astronomico di Trieste via Tiepolo 11 TriesteI-34131 Italy ICSC - Italian Research Center on High Performance Computing Big Data and Quantum Computing Italy Department of Astrophysical Sciences Princeton University 4 Ivy Lane PrincetonNJ08544 United States Center for Astrophysics Harvard & Smithsonian 60 Garden Street CambridgeMA United States Universität Heidelberg Zentrum für Astronomie Institut für Theoretische Astrophysik Albert-Ueberle-Str. 2 HeidelbergD-69120 Germany Universität Heidelberg Interdisziplinäres Zentrum für Wissenschaftliches Rechnen Im Neuenheimer Feld 205 HeidelbergD-69120 Germany Università dell’Insubria via Valleggio 11 Como22100 Italy Department of Physics University of Surrey GuildfordGU2 7XH United Kingdom Universitäts-Sternwarte Fakultät für Physik Ludwig-Maximilians-Universität München Scheinerstr. 1 München81679 Germany Max-Planck-Institut für Astrophysik Karl-Schwarzschild-Straße 1 Garching85741 Germany Research School of Astronomy and Astrophysics Australian National University CanberraACT2611 Australia Australia Sub-Department of Astrophysics Department of Physics University of Oxford Keble Road OxfordOX1 3RH United Kingdom Sterrenkundig Observatorium Universiteit Gent Krijgslaan 281 S9 GentB-9000 Belgium Max Planck Institut für Astronomie Königstuhl 17 Heidelberg69117 Germany C/Alfonso XII 3 Madri

Past studies have long emphasised the key role played by galactic stellar bars in the context of disc secular evolution, via the redistribution of gas and stars, the triggering of star formation, and the formation of prominent structures such as rings and central mass concentrations. However, the exact physical processes acting on those structures, as well as the timescales associated with the building and consumption of central gas reservoirs are still not well understood. We are building a suite of hydro-dynamical RAMSES simulations of isolated, low-redshift galaxies that mimic the properties of the PHANGS sample. The initial conditions of the models reproduce the observed stellar mass, disc scale length, or gas fraction, and this paper presents a first subset of these models. Most of our simulated galaxies develop a prominent bar structure, which itself triggers central gas fuelling and the building of an over-density with a typical scale of 100-1000 pc. We confirm that if the host galaxy features an ellipsoidal component, the formation of the bar and gas fuelling are delayed. We show that most of our simulations follow a common time evolution, when accounting for mass scaling and the bar formation time. In our simulations, the stellar mass of 1010 M☉ seems to mark a change in the phases describing the time evolution of the bar and its impact on the interstellar medium. In massive discs (M★ ≥ 1010 M☉), we observe the formation of a central gas reservoir with star formation mostly occurring within a restricted starburst region, leading to a gas depletion phase. Lower-mass systems (M★ 10 M☉) do not exhibit such a depletion phase, and show a more homogeneous spread of star-forming regions along the bar structure, and do not appear to host inner bar-driven discs or rings. Our results seem to be supported by observations, and we briefly discuss how this new suite of simulations can help our understanding of the secular evolution of main sequence disc galaxies. © 2024,

关键词： Gases

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Sulfurized Composite Interphase Enables a Highly Reversible Zn Anode

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Angewandte Chemie 2024年第7期137卷

作者： Lu Wu Dr. Hao Yuan Yongkang An Dr. Jianguo Sun Yu Liu Dr. Han Tang Wei Yang Lianmeng Cui Jinghao Li Prof. Qinyou An Prof. Yong-Wei Zhang Prof. Lin Xu Prof. Liqiang Mai State Key Laboratory of Advanced Technology for Materials Synthesis and Processing School of Materials Science and Engineering Wuhan University of Technology Wuhan 430070 China Institute of High Performance Computing (IHPC) Agency for Science Technology and Research (A*STAR) 1 Fusionopolis Way #16-16 Connexis Singapore 138632 Singapore Department of Materials Science and Engineering National University of Singapore Singapore 117574 Singapore Hubei Provincial Key Laboratory of Green Materials for Light Industry School of Materials and Chemical Engineering Hubei University of Technology Wuhan 430068 China Hubei Longzhong Laboratory Wuhan University of Technology (Xiangyang Demonstration Zone) Xiangyang 441000 China Zhongyu Feima New Material Technology Innovation Center (Zhengzhou) Co. Ltd. Zhengzhou 450001 China

The stability and reversibility of Zn anode can be greatly improved by in situ construction of solid electrolyte interphase (SEI) on Zn surface via a low-cost design strategy of ZnSO 4 electrolyte. However, the role of hydrogen bond acceptor -SO 3 accompanying ZnS formation during SEI reconstruction is overlooked. In this work, we have explored and revealed the new role of -SO 3 and ZnS in the in situ formed sulfide composite SEI (SCSEI) on Zn anode electrochemistry in ZnSO 4 aqueous electrolytes. Structure characterization and DFT demonstrate that the introduction of -SO 3 can not only reduce the dehydration energy of [Zn(H 2 O) 6 ] 2+ , but also enhance the stability of the ZnS/Zn interface and homogenize the ZnS/Zn interface electric field, thereby significantly improving the dynamic kinetics and uniform deposition of Zn 2+ . Owing to the synergistic effect of ZnS and -SO 3 , a high cycling stability of 1500 h with a cumulative-plated capacity of 7.5 Ah cm −2 at 10 mA cm −2 has been achieved within the symmetrical cell. Furthermore, the full cell with NH 4 V 4 O 10 cathode exhibits outstanding cyclic stability, exceeding 2000 cycles at 5 A g −1 and maintaining a Coulombic efficiency of 100 %. These new insights into anionic synergistic strategy could significantly enhance the practical application of zinc-ion batteries.

关键词： electrolyte in situ sulfurized SEI anionic synergistic zinc ion batteries

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Cover Picture

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Chemistry – A European Journal 2001年第12期7卷 2493-2493页

作者： Marek Hytha Dr. Ivan Štich Prof. Julian D. Gale Dr. Kiyoyuki Terakura Prof. Michael C. Payne Prof. National Center for High Performance Computing P. O. Box 19-136 Hsinchu (Taiwan) CCMS Department of Physics Slovak Technical University (FEI STU) Ilkovičova 3 812 19 Bratislava (Slovakia) Fax: (+421) 7-654-11-483 Department of Chemistry Imperial College of Science Technology and Medicine South Kensington London SW7 2AY (UK) JRCAT Angstrom Technology Partnership (ATP) 1-1-4 Higashi Tsukuba Ibaraki 305-0046 Japan National Institute for Advanced Interdisciplinary Research 1-1-4 Higashi Ibaraki 305-8562 (Japan) Cavendish Laboratory Madingley Road Cambridge CB3 0HE (UK)

The cover picture shows methanol molecules (ball and stick models in gray, white, and red) in the eight-ring channel of zeolite ferrierite (framework in orange, red, and blue) in the process of dehydration to dimethyl ether. The valence-electronic charge densities are superimposed in green. A theorectical study on the formation of the first intermediate (dimethyl ether) in the methanol-to-gasoline conversion is presented in full detail by I. Štich et al. on p. 2521 ff.

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Chemical Electron Tomography at Lower Dose and Higher Resolution

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Microscopy and Microanalysis 2024年第SUPPLEMENT_1期30卷

作者： Hovden, Robert Schwartz, Jonathan Sung, Suk Hyun Di, Zichao Wendy Jiang, Yi Manassa, Jason Pietryga, Jacob Qian, Yiwen Cho, Min Gee Rowell, Jonathan L Zheng, Huihuo Robinson, Richard D Gu, Junsi Kirilin, Alexey Rozeveld, Steve Ercius, Peter Scott, Mary Department of Materials Science and Engineering University of Michigan Ann Arbor MI Applied Physics Program University of Michigan Ann Arbor MI Chan Zuckerberg Initiative Redwood City CA Rowland Institute at Harvard Cambridge MA. Mathematics and Computer Science Division Argonne National Laboratory Lemont IL Advanced Photon Source Facility Argonne National Laboratory Lemont IL Department of Materials Science and Engineering U.C. Berkeley Berkeley CA National Center for Electron Microscopy Molecular Foundry Berkeley CA Department of Chemistry and Chemical Biology Cornell University Ithaca NY Argonne Leadership Computing Facility Argonne National Laboratory Lemont IL Dow Chemical Co. Terneuzen Netherlands Dow Chemical Co. Midland MI

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