检索结果-内蒙古大学图书馆

arXiv 2021年

作者： Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, L.X. Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, H. Cai, J.T. Cao, Zhe Chang, J. Chang, J.F. Chen, B.M. Chen, E.S. Chen, J. Chen, Liang Chen, Liang Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, X.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, S.W. Cui, X.H. Cui, Y.D. D'Ettorre Piazzoli, B. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu Della Volpe, D. Dong, X.J. Duan, K.K. Fan, J.H. Fan, Y.Z. Fan, Z.X. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, Y.L. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Ge, M.M. Geng, L.S. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, J.G. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.C. He, S.L. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, C. Hou, X. Hu, H.B. Hu, S. Hu, S.C. Hu, X.J. Huang, D.H. Huang, Q.L. Huang, W.H. Huang, X.T. Huang, X.Y. Huang, Z.C. Ji, F. Ji, X.L. Jia, H.Y. Jiang, K. Jiang, Z.J. Jin, C. Ke, T. Kuleshov, D. Levochkin, K. Li, B.B. Li, Cheng Li, Cong Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, Jian Li, Jie Li, K. Li, W.L. Li, X.R. Li, Xin Li, Xin Li, Y. Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.S. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Liu, Z.X. Long, W.J. Lu, R. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Masood, A. Min, Z. Mitthumsiri, W. Montaruli, T. Nan, Y.C. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Rulev, V. Sáiz, A. Shao, L. Shchegolev, O. Sheng, X.D. Shi, J.R. Song, H.C. Stenkin, Y.V. Stepanov, V. Su, Y. Sun, Q.N. Sun, X.N. Sun, Z.B. Tam, P.H.T. Tang, Z.B. Tian, W.W. Wang, B.D. Wang, C. Wang, H. Key Laboratory of Particle Astrophyics and Experimental Physics Division and Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China Tianfu Cosmic Ray Research Center Sichuan Chengdu China Dublin Institute for Advanced Studies 31 Fitzwilliam Place Dublin Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China College of Physics Sichuan University Sichuan Chengdu610065 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China School of Physics and Technology Wuhan University Hubei Wuhan430072 China Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Sun Yat-sen University Guangdong Zhuhai519000 China Dipartimento di Fisica Dell'Università di Napoli Federico Ii Complesso Universitario di Monte Sant'Angelo via Cinthia Napoli80126 Italy School of Physics and Astronomy Yunnan University Yunnan Kunming650091 China D'epartement de Physique Nucl'eaire et Corpusculaire Facult'e de Sciences Universit'e de Genève 24 Quai Ernest Ansermet Geneva1211 Switzerland Institute of Frontier and Interdisciplinary Science Shando

Recently the LHAASO Collaboration published the detection of 12 ultra-high-energy gamma-ray sources above 100 TeV, with the highest energy photon reaching 1.4 PeV. The first detection of PeV gamma rays from astrophysical sources may provide a very sensitive probe of the effect of the Lorentz invariance violation (LIV), which results in decay of high-energy gamma rays in the superluminal scenario and hence a sharp cutoff of the energy spectrum. Two highest energy sources are studied in this work. No signature of the existence of LIV is found in their energy spectra, and the lower limits on the LIV energy scale are derived. Our results show that the first-order LIV energy scale should be higher than about 105times the Planck scale Mpland that the second-order LIV scale is > 10-3Mpl. Both limits improve by at least one order of magnitude the previous results. © 2021, CC BY-NC-ND.

关键词： Gamma rays

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Performance of LHAASO-WCDA and Observation of Crab Nebula as a Standard Candle

arXiv

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arXiv 2021年

作者： Aharonian, F. An, Q. Axikegu Bai, L.X. Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, H. Cai, J.T. Cao, Z. Cao, Z. Chang, J. Chang, J.F. Chang, X.C. Chen, B.M. Chen, J. Chen, L. Chen, L. Chen, L. Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, X.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu Volpe, D. della Piazzoli, B. D'Ettorre Dong, X.J. Fan, J.H. Fan, Y.Z. Fan, Z.X. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, Y.L. Gao, B. Gao, C.D. Gao, Q. Gao, W. Ge, M.M. Geng, L.S. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, J.G. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.C. He, S.L. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, C. Hou, X. Hu, H.B. Hu, S. Hu, S.C. Hu, X.J. Huang, D.H. Huang, Q.L. Huang, W.H. Huang, X.T. Huang, Z.C. Ji, F. Ji, X.L. Jia, H.Y. Jiang, K. Jiang, Z.J. Jin, C. Kuleshov, D. Levochkin, K. Li, B.B. Li, C. Li, C. Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, K. Li, W.L. Li, X. Li, X. Li, X.R. Li, Y. Li, Y.Z. Li, Z. Li, Z. Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.S. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y.N. Liu, Z.X. Long, W.J. Lu, R. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Masood, A. Mitthumsiri, W. Montaruli, T. Nan, Y.C. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Ruffolo, D. Rulev, V. Sáiz, A. Shao, L. Shchegolev, O. Sheng, X.D. Shi, J.R. Song, H.C. Stenkin, Yu V. Stepanov, V. Sun, Q.N. Sun, X.N. Sun, Z.B. Tam, P.H.T. Tang, Z.B. Tian, W.W. Wang, B.D. Wang, C. Wang, H. Wang, H.G. Wang, J.C. Wang, J.S. Wang, L.P. Wang, L.Y. Wang, R.N. Wang, W. Wang, W. Wang, X.G. Wang, X.J. Wang, X.Y. Key Laboratory of Particle Astrophyics & Experimental Physics Division & Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China TIANFU Cosmic Ray Research Center ChengduSichuan China State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Hefei Anhui230026 China Department of Engineering Physics Tsinghua University Beijing100084 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China National Space Science Center Chinese Academy of Sciences Beijing100190 China School of Physics Peking University Beijing100871 China Center for Astrophysics Guangzhou University GuangzhouGuangdong510006 China Sun Yat-sen University ZhuhaiGuangdong519082 China School of Physical Science and Technology Guangxi University Nanning Guangxi530004 China Hebei Normal University Shijiazhuang Hebei050024 China School of Physics and Microelectronics Zhengzhou University ZhengzhouHenan450001 China School of Astronomy and Space Science Nanjing University NanjingJiangsu210023 China Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences NanjingJiangsu210023 China Institute of Frontier and Interdisciplinary Science Shandong University QingdaoShandong266237 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Tsung-Dao Lee Institute & School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University ChengduSichuan610031 China College of Physics Sichuan University ChengduSichuan610065 China Ministry of Education Lhasa Tibet850000 China School of Physics and Technology Wuhan University Wuhan

The first Water Cherenkov detector of the LHAASO experiment (WCDA-1) has been operating since April, 2019. The first 10 months of data have been analyzed to test its performance by observing the Crab Nebula as a standard candle. The WCDA-1 achieves the sensitivity of 65 mCU per year with a statistical threshold of 5 σ. In order to do so, 97.7% cosmic ray background rejection rate around 1 TeV and 99.8% around 6 TeV with an approximately photon acceptance about 50% by using the compactness of the shower footprints to be greater than 10 as the discriminator between gamma induced showers and the cosmic ray backgrounds. The angular resolution is measured using the Crab Nebula as a point source about 0.45◦ at 1 TeV and better than 0.2◦ above 6 TeV with the pointing accuracy better than 0.05◦. They are all matching the design specifications. The energy resolution is found 33% for gamma rays around 6 TeV. The spectral energy distribution of the Crab Nebula in the range from 500 GeV and 15.8 TeV is measured and in agreement with results of other TeV gamma ray observatories. © 2021, CC BY.

关键词： Spectroscopy

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Metrics Reloaded: Recommendations for image analysis validation

arXiv

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arXiv 2022年

作者： Maier-Hein, Lena Reinke, Annika Godau, Patrick Tizabi, Minu D. Buettner, Florian Christodoulou, Evangelia Glocker, Ben Isensee, Fabian Kleesiek, Jens Kozubek, Michal Reyes, Mauricio Riegler, Michael A. Wiesenfarth, Manuel Emre Kavur, A. Sudre, Carole H. Baumgartner, Michael Eisenmann, Matthias Heckmann-Nötzel, Doreen Rädsch, Tim Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Benis, Arriel Blaschko, Matthew B. Jorge Cardoso, M. Cheplygina, Veronika Cimini, Beth A. Collins, Gary S. Farahani, Keyvan Ferrer, Luciana Galdran, Adrian Ginneken, Bram Van Haase, Robert Hashimoto, Daniel A. Hoffman, Michael M. Huisman, Merel Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kenngott, Hannes Kofler, Florian Kopp-Schneider, Annette Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Petersen, Jens Rajpoot, Nasir Rieke, Nicola Saez-Rodriguez, Julio Sánchez, Clara I. Shetty, Shravya Smeden, Maarten Van Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. Calster, Ben Van Varoquaux, Gaël Jäger, Paul F. Heidelberg Division of Intelligent Medical Systems and HI Helmholtz Imaging Germany Faculty of Mathematics and Computer Science and Medical Faculty Heidelberg University Heidelberg Germany NCT Heidelberg a partnership between DKFZ University Medical Center Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Intelligent Medical Systems Germany partner site Frankfurt/Mainz a partnership between DKFZ and UCT Frankfurt-Marburg Germany Heidelberg Goethe University Frankfurt Germany Department of Medicine Goethe University Frankfurt Germany Department of Informatics Frankfurt Cancer Insititute Germany Department of Computing Imperial College London London United Kingdom Heidelberg Division of Medical Image Computing and HI Applied Computer Vision Lab Germany Institute for AI in Medicine University Medicine Essen Essen Germany Centre for Biomedical Image Analysis Faculty of Informatics Masaryk University Brno Czech Republic ARTORG Center for Biomedical Engineering Research University of Bern Bern Switzerland Department of Radiation Oncology University Hospital Bern University of Bern Bern Switzerland Simula Metropolitan Center for Digital Engineering Oslo Norway UiT The Arctic University of Norway Romsø Norway Heidelberg Division of Biostatistics Germany Heidelberg Division of Intelligent Medical Systems Division of Medical Image Computing HI Applied Computer Vision Lab Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Heidelberg Division of Medical Image Computing Germany Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montréal

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen performance metrics often do not reflect the domain interest, thus failing to adequately measure scientific progress and hindering translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. It was developed by a large international consortium in a multi-stage Delphi process and is based on the novel concept of a problem fingerprint – a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), data set and algorithm output. Based on the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as a classification task at image, object or pixel level, namely image-level classification, object detection, semantic segmentation, and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases. © 2022, CC BY.

关键词： Semantic Segmentation

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Correction: An electronic enzyme-linked immunosorbent assay platform for protein analysis based on magnetic beads and AlGaN/GaN high electron mobility transistors

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The Analyst 2021年第13期146卷 4400页

作者： Jin Wang Zhiqi Gu Xinsheng Liu Lei Zhao Huoxiang Peng Jiadong Li Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou Institute of Nano-Tech and Nano-Bionics Chinese Academy of Sciences Suzhou 215125 People's Republic of China. jdli2009@*** and The College of Materials Science and Engineering Shanghai University Shanghai 200072 People's Republic of China. Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou Institute of Nano-Tech and Nano-Bionics Chinese Academy of Sciences Suzhou 215125 People's Republic of China. jdli2009@*** and School of Nano Technology and Nano Bionics University of Science and Technology of China Hefei 230026 People's Republic of China. Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou Institute of Nano-Tech and Nano-Bionics Chinese Academy of Sciences Suzhou 215125 People's Republic of China. jdli2009@*** and The College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu 610059 People's Republic of China.

Correction for 'An electronic enzyme-linked immunosorbent assay platform for protein analysis based on magnetic beads and AlGaN/GaN high electron mobility transistors' by Jin Wang et al., Analyst, 2020, 145, 2...

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Constraints on Spin-Independent Nucleus Scattering with sub-GeV Weakly Interacting Massive Particle Dark Matter from the CDEX-1B Experiment at the China Jinping Underground Laboratory

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Physical Review Letters 2019年第16期123卷 161301-161301页

作者： Z. Z. Liu Q. Yue L. T. Yang K. J. Kang Y. J. Li H. T. Wong M. Agartioglu H. P. An J. P. Chang J. H. Chen Y. H. Chen J. P. Cheng Z. Deng Q. Du H. Gong X. Y. Guo Q. J. Guo L. He S. M. He J. W. Hu Q. D. Hu H. X. Huang L. P. Jia H. Jiang H. B. Li H. Li J. M. Li J. Li X. Li X. Q. Li Y. L. Li B. Liao F. K. Lin S. T. Lin S. K. Liu Y. D. Liu Y. Y. Liu H. Ma J. L. Ma Y. C. Mao J. H. Ning H. Pan N. C. Qi J. Ren X. C. Ruan V. Sharma Z. She L. Singh M. K. Singh T. X. Sun C. J. Tang W. Y. Tang Y. Tian G. F. Wang L. Wang Q. Wang Y. Wang Y. X. Wang S. Y. Wu Y. C. Wu H. Y. Xing Y. Xu T. Xue N. Yi C. X. Yu H. J. Yu J. F. Yue M. Zeng Z. Zeng F. S. Zhang M. G. Zhao J. F. Zhou Z. Y. Zhou J. J. Zhu Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics Tsinghua University Beijing 100084 Institute of Physics Academia Sinica Taipei 11529 Department of Physics Dokuz Eylül University İzmir 35160 Department of Physics Tsinghua University Beijing 100084 NUCTECH Company Beijing 100084 YaLong River Hydropower Development Company Chengdu 610051 College of Nuclear Science and Technology Beijing Normal University Beijing 100875 College of Physical Science and Technology Sichuan University Chengdu 610065 School of Physics Peking University Beijing 100871 Department of Nuclear Physics China Institute of Atomic Energy Beijing 102413 School of Physics Nankai University Tianjin 300071 Department of Physics Banaras Hindu University Varanasi 221005 Department of Physics Beijing Normal University Beijing 100875

We report results on the searches of weakly interacting massive particles (WIMPs) with sub-GeV masses (mχ) via WIMP-nucleus spin-independent scattering with Migdal effect incorporated. Analysis on time-integrated (TI) and annual modulation (AM) effects on CDEX-1B data are performed, with 737.1 kg day exposure and 160 eVee threshold for TI analysis, and 1107.5 kg day exposure and 250 eVee threshold for AM analysis. The sensitive windows in mχ are expanded by an order of magnitude to lower DM masses with Migdal effect incorporated. New limits on σχNSI at 90% confidence level are derived as 2×10−32∼7×10−35 cm2 for TI analysis at mχ∼50–180 MeV/c2, and 3×10−32∼9×10−38 cm2 for AM analysis at mχ∼75 MeV/c2–3.0 GeV/c2.

关键词： Dark matter Particle astrophysics Particle dark matter Weakly interacting massive particles Dark matter detectors

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Transverse Emittance Reduction in Muon Beams by Ionization Cooling

arXiv

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arXiv 2023年

作者： Bogomilov, M. Tsenov, R. Vankova-Kirilova, G. Song, Y.P. Tang, J.Y. Li, Z.H. Bertoni, R. Bonesini, M. Chignoli, F. Mazza, R. de Bari, A. Orestano, D. Tortora, L. Kuno, Y. Sakamoto, H. Sato, A. Ishimoto, S. Chung, M. Sung, C.K. Filthaut, F. Fedorov, M. Jokovic, D. Maletic, D. Savic, M. Jovancevic, N. Nikolov, J. Vretenar, M. Ramberger, S. Asfandiyarov, R. Blondel, A. Drielsma, F. Karadzhov, Y. Boyd, S. Greis, J.R. Lord, T. Pidcott, C. Taylor, I. Charnley, G. Collomb, N. Dumbell, K. Gallagher, A. Grant, A. Griffiths, S. Hartnett, T. Martlew, B. Moss, A. Muir, A. Mullacrane, I. Oates, A. Owens, P. Stokes, G. Warburton, P. White, C. Adams, D. Bayliss, V. Boehm, J. Bradshaw, T.W. Brown, C. Courthold, M. Govans, J. Hayler, T. Hills, M. Lagrange, J.B. Macwaters, C. Nichols, A. Preece, R. Ricciardi, S. Rogers, C. Stanley, T. Tarrant, J. Tucker, M. Watson, S. Wilson, A. Bayes, R. Nugent, J.C. Soler, F.J.P. Chatzitheodoridis, G.T. Dick, A.J. Ronald, K. Whyte, C.G. Young, A.R. Gamet, R. Cooke, P. Blackmore, V.J. Colling, D. Dobbs, A. Dornan, P. Franchini, P. Hunt, C. Jurj, P.B. Kurup, A. Long, K. Martyniak, J. Middleton, S. Pasternak, J. Uchida, M.A. Cobb, J.H. Booth, C.N. Hodgson, P. Langlands, J. Overton, E. Pec, V. Smith, P.J. Wilbur, S. Ellis, M. Gardener, R.B.S. Kyberd, P. Nebrensky, J.J. DeMello, A. Gourlay, S. Lambert, A. Li, D. Luo, T. Prestemon, S. Virostek, S. Palmer, M. Witte, H. Adey, D. Bross, A.D. Bowring, D. Liu, A. Neuffer, D. Popovic, M. Rubinov, P. Freemire, B. Hanlet, P. Kaplan, D.M. Mohayai, T.A. Rajaram, D. Snopok, P. Torun, Y. Cremaldi, L.M. Sanders, D.A. Coney, L.R. Hanson, G.G. Heidt, C. Department of Atomic Physics St. Kliment Ohridski University of Sofia 5 James Bourchier Blvd Sofia Bulgaria Institute of High Energy Physics Chinese Academy of Sciences 19 Yuquan Rd Shijingshan District Beijing China Sichuan University 252 Shuncheng St Chengdu China Sezione INFN Milano Bicocca Dipartimento di Fisica G. Occhialini Piazza della Scienza 3 Milano Italy Sezione INFN Pavia Dipartimento di Fisica Università di Pavia Via Agostino Bassi 6 Pavia Italy INFN Sezione di Roma Tre and Dipartimento di Matematica e Fisica Università Roma Tre Via della Vasca Navale 84 Roma Italy Department of Physics Graduate School of Science Osaka University 1-1 Machikaneyamacho Osaka Toyonaka Japan Institute of Particle and Nuclear Studies Ibaraki Tsukuba Japan Ulsan National Institute of Science & Technology Ulsan Korea Republic of Nikhef Science Park 105 Amsterdam Netherlands Radboud University Houtlaan 4 Nijmegen Netherlands Institute of Physics University of Belgrade Serbia Faculty of Sciences University of Novi Sad Serbia CERN Esplanade des Particules 1 Geneva Switzerland DNPC Section de Physique Université de Genève 24 Quai Ernest-Ansermet Geneva Switzerland Department of Physics University of Warwick Gibbet Hill Road Coventry United Kingdom STFC Daresbury Laboratory Keckwick Ln Cheshire Daresbury United Kingdom STFC Rutherford Appleton Laboratory Harwell Campus Didcot United Kingdom School of Physics and Astronomy Kelvin Building University of Glasgow Glasgow United Kingdom SUPA The Department of Physics University of Strathclyde Rottenrow Glasgow107 United Kingdom Cockcroft Institute Daresbury Laboratory Sci-Tech Daresbury Daresbury Warrington United Kingdom Department of Physics University of Liverpool Oxford St Liverpool United Kingdom Department of Physics Blackett Laboratory Imperial College London London United Kingdom Department of Physics University of Oxford Denys Wilkinson Building Keble Rd Oxford United Kingdom Depa

Accelerated muon beams have been considered for next-generation studies of high-energy lepton-antilepton collisions and neutrino oscillations. However, high-brightness muon beams have not yet been produced. The main challenge for muon acceleration and storage stems from the large phase-space volume occupied by the beam, derived from the muon production mechanism through the decay of pions from proton collisions. Ionization cooling is the technique proposed to decrease the muon beam phase-space volume. Here we demonstrate a clear signal of ionization cooling through the observation of transverse emittance reduction in beams that traverse lithium hydride or liquid hydrogen absorbers in the Muon Ionization Cooling Experiment (MICE). The measurement is well reproduced by the simulation of the experiment and the theoretical model. The results shown here represent a substantial advance towards the realization of muon-based facilities that could operate at the energy and intensity frontiers. © 2023, CC BY.

关键词： Liquefied gases

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Search for Light Weakly-Interacting-Massive-Particle Dark Matter by Annual Modulation Analysis with a Point-Contact Germanium Detector at the China Jinping Underground Laboratory

引用

Physical Review Letters 2019年第22期123卷 221301-221301页

作者： L. T. Yang H. B. Li Q. Yue H. Ma K. J. Kang Y. J. Li H. T. Wong M. Agartioglu H. P. An J. P. Chang J. H. Chen Y. H. Chen J. P. Cheng Z. Deng Q. Du H. Gong Q. J. Guo L. He J. W. Hu Q. D. Hu H. X. Huang L. P. Jia H. Jiang H. Li J. M. Li J. Li X. Li X. Q. Li Y. L. Li B. Liao F. K. Lin S. T. Lin S. K. Liu Y. D. Liu Y. Y. Liu Z. Z. Liu J. L. Ma Y. C. Mao H. Pan J. Ren X. C. Ruan V. Sharma Z. She M. B. Shen L. Singh M. K. Singh T. X. Sun C. J. Tang W. Y. Tang Y. Tian G. F. Wang J. M. Wang L. Wang Q. Wang Y. Wang Y. X. Wang S. Y. Wu Y. C. Wu H. Y. Xing Y. Xu T. Xue N. Yi C. X. Yu H. J. Yu J. F. Yue X. H. Zeng M. Zeng Z. Zeng F. S. Zhang Y. H. Zhang M. G. Zhao J. F. Zhou Z. Y. Zhou J. J. Zhu Z. H. Zhu Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics Tsinghua University Beijing 100084 Institute of Physics Academia Sinica Taipei 11529 Department of Physics Dokuz Eylül University İzmir 35160 Department of Physics Tsinghua University Beijing 100084 NUCTECH Company Beijing 100084 YaLong River Hydropower Development Company Chengdu 610051 College of Nuclear Science and Technology Beijing Normal University Beijing 100875 College of Physical Science and Technology Sichuan University Chengdu 610064 School of Physics Peking University Beijing 100871 Department of Nuclear Physics China Institute of Atomic Energy Beijing 102413 School of Physics Nankai University Tianjin 300071 Department of Physics Banaras Hindu University Varanasi 221005 Department of Physics Beijing Normal University Beijing 100875

We present results on light weakly interacting massive particle (WIMP) searches with annual modulation (AM) analysis on data from a 1-kg mass p-type point-contact germanium detector of the CDEX-1B experiment at the China Jinping Underground Laboratory. Datasets with a total live time of 3.2 yr within a 4.2-yr span are analyzed with analysis threshold of 250 eVee. Limits on WIMP-nucleus (χ−N) spin-independent cross sections as function of WIMP mass (mχ) at 90% confidence level (C.L.) are derived using the dark matter halo model. Within the context of the standard halo model, the 90% C.L. allowed regions implied by the DAMA/LIBRA and CoGeNT AM-based analysis are excluded at >99.99% and 98% C.L., respectively. These results correspond to the best sensitivity at mχ<6 GeV/c2 among WIMP AM measurements to date.

关键词： Particle astrophysics Particle dark matter Weakly interacting massive particles Solid-state detectors Dark matter detectors

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Corrigendum to “Performance test of the electromagnetic particle detectors for the LHAASO experiment” [Nucl. Instrum. Methods Phys. Res. A 1001 (2021) 165193]

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nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 2022年 1022卷

作者： F. Aharonian Q. An Axikegu L.X. Bai Y.X. Bai Y.W. Bao D. Bastieri X.J. Bi Y.J. Bi H. Cai J.T. Cai Z. Cao J. Chang J.F. Chang X.C. Chang B.M. Chen J. Chen X. Zuo University of Chinese Academy of Sciences 100049 Beijing China Department of Engineering Physics Tsinghua University 100084 Beijing China Dublin Institute for Advanced Studies 31 Fitzwilliam Place 2 Dublin Ireland National Astronomical Observatories Chinese Academy of Sciences 100101 Beijing China Max–Planck-Institut for Nuclear Physics P.O. Box 103980 69029 Heidelberg Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China 230026 Hefei Anhui China School of Physical Science and Technology & School of Information Science and Technology Southwest Jiaotong University 610031 Chengdu Sichuan China Key Laboratory of Particle Astrophysics & Experimental Physics Division & Computing Center Institute of High Energy Physics Chinese Academy of Sciences 100049 Beijing China College of Physics Sichuan University 610065 Chengdu Sichuan China TIANFU Cosmic Ray Research Center Chengdu Sichuan China School of Astronomy and Space Science Nanjing University 210023 Nanjing Jiangsu China Center for Astrophysics Guangzhou University 510006 Guangzhou Guangdong China School of Physics and Technology Wuhan University 430072 Wuhan Hubei China Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences 210023 Nanjing Jiangsu China Hebei Normal University 050024 Shijiazhuang Hebei China

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Self‐Driven Photodetectors: GaSe/MoS2Heterostructure with Ohmic‐Contact Electrodes for Fast, Broadband Photoresponse, and Self‐Driven Photodetectors (Adv. Mater. Interfaces 9/2020)

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Advanced Materials Interfaces 2020年第9期7卷

作者： Zhenbei He Junxiong Guo Shangdong Li Zhicheng Lei Lin Lin Yizhen Ke Wenjing Jie Tianxun Gong Yuan Lin Tiedong Cheng Wen Huang Xiaosheng Zhang State Key Laboratory of Electronic Thin Films and Integrated Devices School of Electronic Science and Engineering (National Exemplary School of Microelectronics) University of Electronic Science and Technology of China Chengdu 610054 China College of Chemistry and Materials Science Sichuan Normal University Chengdu 610066 China School of Electrical Engineering and Automation Jiangxi University of Science and Technology Ganzhou 341000 China

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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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