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Search for and production in the final state using proton-proton collisions at

The European Physical Journal C 2024年第7期84卷 1-33页

作者： Hayrapetyan, A. Tumasyan, A. Adam, W. Andrejkovic, J. W. Bergauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Hussain, P. S. Jeitler, M. Krammer, N. Li, A. Liko, D. Mikulec, I. Schieck, J. Schöfbeck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenberger, W. Wulz, C.-E. Darwish, M. R. Janssen, T. Van Mechelen, P. Bols, E. S. D’Hondt, J. Dansana, S. De Moor, A. Delcourt, M. Lowette, S. Makarenko, I. Müller, D. Tavernier, S. Tytgat, M. Van Onsem, G. P. Van Putte, S. Vannerom, D. Clerbaux, B. Das, A. K. De Lentdecker, G. Evard, H. Favart, L. Gianneios, P. Hohov, D. Jaramillo, J. Khalilzadeh, A. Khan, F. A. Lee, K. Mahdavikhorrami, M. Malara, A. Paredes, S. Thomas, L. Vanden Bemden, M. Vander Velde, C. Vanlaer, P. De Coen, M. Dobur, D. Hong, Y. Knolle, J. Lambrecht, L. Mestdach, G. Amarilo, K. Mota Rendón, C. Samalan, A. Skovpen, K. Van Den Bossche, N. van der Linden, J. Wezenbeek, L. Benecke, A. Bethani, A. Bruno, G. Caputo, C. Delaere, C. Donertas, I. S. Giammanco, A. Jain, Sa. Lemaitre, V. Lidrych, J. Mastrapasqua, P. Tran, T. T. Wertz, S. Alves, G. A. Coelho, E. Hensel, C. De Oliveira, T. Menezes Moraes, A. Teles, P. Rebello Soeiro, M. Júnior, W. L. Aldá Pereira, M. Alves Gallo Filho, M. Barroso Ferreira Malbouisson, H. Brandao Carvalho, W. Chinellato, J. Da Costa, E. M. Da Silveira, G. G. De Jesus Damiao, D. De Souza, S. Fonseca De Souza, R. Gomes Martins, J. Herrera, C. Mora Mundim, L. Nogima, H. Pinheiro, J. P. Santoro, A. Sznajder, A. Thiel, M. Pereira, A. Vilela Bernardes, C. A. Calligaris, L. Tomei, T. R. Fernandez Perez Gregores, E. M. Mercadante, P. G. Novaes, S. F. Orzari, B. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Shopova, M. Sultanov, G. Dimitrov, A. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Keshri, S. Thakur, S. Cheng, T. Javaid, T. Yuan, L. Hu, Z. Liu, J. Yi, K. Chen, G. M. Chen, H. S. Chen, M. Iemmi, F. Jiang, C. H. Kapoor, A. Liao, H. Liu, Z. -A. Sharma, R. Song, J. N. Tao, J. Wang, C. Wang, J. Wang, Z. Zhang, H. Agapitos, A. Ban, Y. Levin, A Yerevan Physics Institute Yerevan Armenia Yerevan State University Yerevan Armenia Institut für Hochenergiephysik Vienna Austria TU Wien Vienna Austria Universiteit Antwerpen Antwerp Belgium Institute of Basic and Applied Sciences Faculty of Engineering Arab Academy for Science Technology and Maritime Transport Alexandria Egypt Vrije Universiteit Brussel Brussel Belgium Ghent University Ghent Belgium Université Libre de Bruxelles Brussels Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual de Campinas Campinas Brazil Federal University of Rio Grande do Sul Porto Alegre Brazil UFMS Nova Andradina Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Nanjing Normal University Nanjing China The University of Iowa Iowa City USA Institute of High Energy Physics Beijing China University of Chinese Academy of Sciences Beijing China China Center of Advanced Science and Technology Beijing China China Spallation Neutron Source Guangdong China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Henan Normal University Xinxiang China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) Fudan University Shanghai China Zhejiang University Zhejiang China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechan

A search for $${\text {Z}{}{}} {\text {Z}{}{}} $$ and $${\text {Z}{}{}} {\text {H}{}{}} $$ production in the $${\text {b}{}{}} {\bar{{\text {b}{}{}}}{}{}} {\text {b}{}{}} {\bar{{\text {b}{}{}}}{}{}} $$ final state is presented, where H is the standard model (SM) Higgs boson. The search uses an event sample of proton-proton collisions corresponding to an integrated luminosity of 133 $$\,\text {fb}^{-1}$$ collected at a center-of-mass energy of 13 $$\,\text {Te}\hspace{-.08em}\text {V}$$ with the CMS detector at the CERN LHC. The analysis introduces several novel techniques for deriving and validating a multi-dimensional background model based on control samples in data. A multiclass multivariate classifier customized for the $${\text {b}{}{}} {\bar{{\text {b}{}{}}}{}{}} {\text {b}{}{}} {\bar{{\text {b}{}{}}}{}{}} $$ final state is developed to derive the background model and extract the signal. The data are found to be consistent, within uncertainties, with the SM predictions. The observed (expected) upper limits at 95% confidence level are found to be 3.8 (3.8) and 5.0 (2.9) times the SM prediction for the $${\text {Z}{}{}} {\text {Z}{}{}} $$ and $${\text {Z}{}{}} {\text {H}{}{}} $$ production cross sections, respectively.

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When is the immune inspired B-cell algorithm superior to the (1+1) evolutionary algorithm?

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International Journal of High Performance Computing and Networking 2018年第3期12卷 307-313页

作者： Xia, Xiaoyun Tang, Langping Peng, Xue College of Mathematics Physics and Information Engineering Jiaxing University Jiaxing Zhejiang314001 China School of Information Engineering Jiangxi University of Science and Technology Ganzhou China College of Medical Information Engineering Guangdong Pharmaceutical University Guangzhou China Department of Computer Science Guangdong Polytechnic Normal University Guangzhou China

There exist many experimental investigations of artificial immune systems (AIS), and it has been shown that the AIS is useful and efficient for many real-world optimisation problems. However, we know little about that whether the AIS can outperform the traditional evolutionary algorithms on some optimisation problems in theory. This work rigorously proved that a simple AIS called the B-cell algorithm (BCA) with somatic contiguous hypermutations can efficiently optimise two instances of the multiprocessor scheduling problem in expected polynomial runtime, whereas the local search algorithms and the (1+1) evolutionary algorithm ((1+1) EA) using only one individual in the search space and with standard bit mutation are highly inefficient. This work is helpful for gaining insight into the idea there exists no algorithm which is efficient for all specific problems. © 2018 Inderscience Enterprises Ltd.

关键词： Evolutionary algorithms

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Search for the doubly charmed baryon ?cc+

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science China(Physics,Mechanics & Astronomy) 2021年第10期Mechanics & Astronomy) .卷 6-17页

作者： R. Aaij C. Abellán Beteta T. Ackernley B. Adeva M. Adinolfi H. Afsharnia C. A. Aidala S. Aiola Z. Ajaltouni S. Akar J. Albrecht F. Alessio M. Alexander A. Alfonso Albero Z. Aliouche G. Alkhazov P. Alvarez Cartelle S. Amato Y. Amhis L. An L. Anderlini A. Andreianov M. Andreotti F. Archilli A. Artamonov M. Artuso K. Arzymatov E. Aslanides M. Atzeni B. Audurier S. Bachmann M. Bachmayer J. J. Back P. Baladron Rodriguez V. Balagura W. Baldini J. Baptista Leite R. J. Barlow S. Barsuk W. Barter M. Bartolini F. Baryshnikov J. M. Basels G. Bassi B. Batsukh A. Battig A. Bay M. Becker F. Bedeschi I. Bediaga A. Beiter V. Belavin S. Belin V. Bellee K. Belous I. Belov I. Belyaev G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet D. Berninghoff H. C. Bernstein C. Bertella A. Bertolin C. Betancourt F. Betti I. Bezshyiko S. Bhasin J. Bhom L. Bian M. S. Bieker S. Bifani P. Billoir M. Birch F. C. R. Bishop A. Bitadze A. Bizzeti M. Bj?rn M. P. Blago T. Blake F. Blanc S. Blusk D. Bobulska J. A. Boelhauve O. Boente Garcia T. Boettcher A. Boldyrev A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato J. T. Borsuk S. A. Bouchiba T. J. V. Bowcock A. Boyer C. Bozzi M. J. Bradley S. Braun A. Brea Rodriguez M. Brodski J. Brodzicka A. Brossa Gonzalo D. Brundu A. Buonaura C. Burr A. Bursche A. Butkevich J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese L. Calefice L. Calero Diaz S. Cali R. Calladine M. Calvi M. Calvo Gomez P. Camargo Magalhaes P. Campana A. F. Campoverde Quezada S. Capelli L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini I. Carli P. Carniti L. Carus K. Carvalho Akiba A. Casais Vidal G. Casse M. Cattaneo G. Cavallero S. Celani J. Cerasoli A. J. Chadwick M. G. Chapman M. Charles P. Charpentier G. Chatzikonstantinidis C. A. Chavez Barajas M. Chefdeville C. Chen S. Chen A. Chernov V. Chobanova S. Cholak M. Chrzaszcz A. Chubykin V. Chulikov P. Ciambrone M. F. Cicala X. Cid Vidal G. Ciezarek P. E. L. Clarke M. Clemencic H. V. Clif J. Closier J. L. Cobbledick V. Coco J. A. B. Coelho J. Cogan E. Cogneras L. Nikhef National Institute for Subatomic Physics Physik-Institut Universit?t Zürich Oliver Lodge Laboratory University of Liverpool Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela H.H. Wills Physics Laboratory University of Bristol Université Clermont Auvergne University of Michigan Ann Arbor United States INFN Sezione di Milano University of Cincinnati Fakult?t Physik Technische Universit?t Dortmund European Organization for Nuclear Research (CERN) School of Physics and Astronomy University of Glasgow ICCUB Universitat de Barcelona Department of Physics and Astronomy University of Manchester Petersburg Nuclear Physics Institute NRC Kurchatov Institute (PNPI NRC KI) Cavendish Laboratory University of Cambridge Universidade Federal do Rio de Janeiro (UFRJ) Université Paris-Saclay INFN Sezione di Firenze INFN Sezione di Ferrara Physikalisches Institut Ruprecht-Karls-Universit?t Heidelberg Institute for High Energy Physics NRC Kurchatov Institute (IHEP NRC KI) Syracuse University Yandex School of Data Analysis Aix Marseille Univ Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Department of Physics University of Warwick Centro Brasileiro de Pesquisas Físicas (CBPF) Imperial College London INFN Sezione di Genova National University of Science and Technology “MISIS” I. Physikalisches Institut RWTH Aachen University INFN Sezione di Pisa INFN Sezione di Cagliari Institute of Nuclear Physics Moscow State University (SINP MSU) Institute of Theoretical and Experimental Physics NRC Kurchatov Institute (ITEP NRC KI) INFN Laboratori Nazionali di Frascati LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité Universita degli Studi di Padova Universita e INFN Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences School of Physics and Technology Wuhan University University of Birmingham Università di Modena e Reggio Emilia Department of Physics U

A search for the doubly charmed baryon ?cc+with the decay mode ?cc+→Ξc+K-π+is performed using proton-proton collision data at a centre-of-mass energy of 13 TeV collected by the LHCb experiment from 2016 to 2018, corresponding to an integrated luminosity of 5.4 fb-1. No significant signal is observed within the invariant mass range of 3.6 to 4.0 GeV/c2. Upper limits are set on the ratio R of the production cross-section times the total branching fraction of the ?cc+→Ξc+K-π+decay with respect to the Ξcc++→Λc+K-π+π+decay. Upper limits at 95% credibility level for R in the range 0.005 to 0.11 are obtained for diferent hypotheses on the ?cc+mass and lifetime in the rapidity range from 2.0 to 4.5 and transverse momentum range from 4 to 15 GeV/c.

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An active learning approach for reducing annotation cost in skin lesion analysis

arXiv

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arXiv 2019年

作者： Shi, Xueying Dou, Qi Xue, Cheng Qin, Jing Chen, Hao Heng, Pheng-Ann Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Department of Computing Imperial College London LondonSW7 2AZ United Kingdom Imsight Medical Technology Co. Ltd. Shenzhen China Centre for Smart Health School of Nursing Hong Kong Polytechnic University Hong Kong Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

Automated skin lesion analysis is very crucial in clinical practice, as skin cancer is among the most common human malignancy. Existing approaches with deep learning have achieved remarkable performance on this challenging task, however, heavily relying on large-scale labelled datasets. In this paper, we present a novel active learning framework for cost-effective skin lesion analysis. The goal is to effectively select and utilize much fewer labelled samples, while the network can still achieve state-of-the-art performance. Our sample selection criteria complementarily consider both informativeness and representativeness, derived from decoupled aspects of measuring model certainty and covering sample diversity. To make wise use of the selected samples, we further design a simple yet effective strategy to aggregate intra-class images in pixel space, as a new form of data augmentation. We validate our proposed method on data of ISIC 2017 Skin Lesion Classification Challenge for two tasks. Using only up to 50% of samples, our approach can achieve state-of-the-art performances on both tasks, which are comparable or exceeding the accuracies with full-data training, and outperform other well-known active learning methods by a large margin. Copyright © 2019, The Authors. All rights reserved.

关键词： Cost effectiveness

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The 2021 report of the Lancet Countdown on health and climate change: code red for a healthy future

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The Lancet 2021年第10311期398卷 1619-1662页

作者： Romanello, Marina McGushin, Alice Di Napoli, Claudia Drummond, Paul Hughes, Nick Jamart, Louis Kennard, Harry Lampard, Pete Solano Rodriguez, Baltazar Arnell, Nigel Ayeb-Karlsson, Sonja Belesova, Kristine Cai, Wenjia Campbell-Lendrum, Diarmid Capstick, Stuart Chambers, Jonathan Chu, Lingzhi Ciampi, Luisa Dalin, Carole Dasandi, Niheer Dasgupta, Shouro Davies, Michael Dominguez-Salas, Paula Dubrow, Robert Ebi, Kristie L Eckelman, Matthew Ekins, Paul Escobar, Luis E Georgeson, Lucien Grace, Delia Graham, Hilary Gunther, Samuel H Hartinger, Stella He, Kehan Heaviside, Clare Hess, Jeremy Hsu, Shih-Che Jankin, Slava Jimenez, Marcia P Kelman, Ilan Kiesewetter, Gregor Kinney, Patrick L Kjellstrom, Tord Kniveton, Dominic Lee, Jason K W Lemke, Bruno Liu, Yang Liu, Zhao Lott, Melissa Lowe, Rachel Martinez-Urtaza, Jaime Maslin, Mark McAllister, Lucy McMichael, Celia Mi, Zhifu Milner, James Minor, Kelton Mohajeri, Nahid Moradi-Lakeh, Maziar Morrissey, Karyn Munzert, Simon Murray, Kris A Neville, Tara Nilsson, Maria Obradovich, Nick Sewe, Maquins Odhiambo Oreszczyn, Tadj Otto, Matthias Owfi, Fereidoon Pearman, Olivia Pencheon, David Rabbaniha, Mahnaz Robinson, Elizabeth Rocklöv, Joacim Salas, Renee N Semenza, Jan C Sherman, Jodi Shi, Liuhua Springmann, Marco Tabatabaei, Meisam Taylor, Jonathon Trinanes, Joaquin Shumake-Guillemot, Joy Vu, Bryan Wagner, Fabian Wilkinson, Paul Winning, Matthew Yglesias, Marisol Zhang, Shihui Gong, Peng Montgomery, Hugh Costello, Anthony Hamilton, Ian Institute for Global Health University College London London UK United Kingdom Institute for Sustainable Resources University College London London UK United Kingdom UCL Energy Institute University College London London UK United Kingdom Institute for Environmental Design and Engineering University College London London UK United Kingdom Department of Geography University College London London UK United Kingdom The Bartlett School of Sustainable Construction University College London London UK United Kingdom Centre for Human Health and Performance University College London London UK United Kingdom School of Agriculture Policy and Development University of Reading Reading United Kingdom Department of Meteorology University of Reading Reading United Kingdom The Walker Institute University of Reading Reading United Kingdom Department of Health Sciences University of York York United Kingdom Institute for Environment and Human Security United Nations University Bonn Germany Centre on Climate Change and Planetary Health London School of Hygiene & Tropical Medicine London UK United Kingdom Centre for Mathematical Modelling of Infectious Diseases London School of Hygiene & Tropical Medicine London UK United Kingdom Department of Public Health Environments and Society London School of Hygiene & Tropical Medicine London UK United Kingdom Department of Earth System Science Tsinghua University Beijing China Department of Environment Climate Change and Health World Health Organization Geneva Switzerland Institute for Environmental Sciences World Health Organization Geneva Switzerland Centre for Climate Change and Social Transformations School of Psychology Cardiff University Cardiff United Kingdom Yale Center on Climate Change and Health Yale University New Haven CT United States School of Government University of Birmingham Birmingham United Kingdom Economic analysis of Climate Impacts and Policy Centro Euro-Mediterraneo sui Cambiamenti Climatic

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Search for the doubly charmed baryon Ω_(cc)^(+)

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science China(Physics,Mechanics & Astronomy) 2021年第10期64卷 2-13页

作者： LHCb Collaboration Centro Brasileiro de Pesquisas Físicas (CBPF) Rio de Janeiro Brazil Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Center for High Energy Physics Tsinghua University Beijing 100084 China Institute Of High Energy Physics (IHEP) Beijing 100039 China School of Physics State Key Laboratory of Nuclear Physics and Technology Peking University Beijing 100091 China University of Chinese Academy of Sciences Beijing 100086 China Institute of Particle Physics Central China Normal University Wuhan 430079 China CNRS IN2P3-LAPP Univ. Savoie Mont Blanc Annecy France CNRS/IN2P3 LPC Université Clermont Auvergne Clermont-Ferrand France CNRS/IN2P3 CPPM Aix Marseille Univ Marseille France CNRS/IN2P3 IJCLab Université Paris-Saclay Orsay France Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS/IN2P3 Paris France I. Physikalisches Institut RWTH Aachen University Aachen Germany Fakultät Physik Technische Universität Dortmund Dortmund Germany Max-Planck-Institut für Kernphysik (MPIK) Heidelberg Germany Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany School of Physics University College Dublin Dublin Ireland INFN Sezione di Bari Bari Italy INFN Sezione di Bologna Bologna Italy INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Firenze Firenze Italy INFN Laboratori Nazionali di Frascati Frascati Italy INFN Sezione di Genova Genova Italy INFN Sezione di Milano Milano Italy INFN Sezione di Milano-Bicocca Milano Italy INFN Sezione di Cagliari Monserrato Italy Universita degli Studi di Padova Universita e INFN Padova Padova Italy INFN Sezione di Pisa Pisa Italy INFN Sezione di Roma La Sapienza Roma Italy INFN Sezione di Roma Tor Vergata Roma Italy Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Nikhef National Institute for Subatomic Physics and VU Unive

A search for the doubly charmed baryon ?cc+ with the decay mode c Ω_(cc)^(+)→ Ξc+K-π+ is performed using proton-proton collision data at a centre-of-mass energy of 13 TeV collected by the LHCb experiment from 2016 to 2018, corresponding to an integrated luminosity of 5.4 fb-1. No significant signal is observed within the invariant mass range of 3.6 to 4.0 GeV/c2. Upper limits are set on the ratio R of the production cross-section times the total branching fraction of the Ω_(cc)^(+)→ Ξc+K-π+ decay with respect to the Ξcc++→ Λc+K-π+π+ decay. Upper limits at 95% credibility level for R in the range 0.005 to 0.11 are obtained for diferent hypotheses on the ?cc+ mass and lifetime in the rapidity range from 2.0 to 4.5 and transverse momentum range from 4 to 15 GeV/c.

关键词： charmed baryons limits on production of particles charmed quarks experimental tests

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Strong pseudospin-lattice coupling in Sr3Ir2O7: Coherent phonon anomaly and negative thermal expansion

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Physical Review B 2019年第9期99卷 094307-094307页

作者： L. L. Hu M. Yang Y. L. Wu Q. Wu H. Zhao F. Sun W. Wang Rui He S. L. He H. Zhang R. J. Huang L. F. Li Y. G. Shi Jimin Zhao Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing 100190 China School of Physical Sciences University of Chinese Academy of Sciences Beijing 100049 China Technical Institute of Physics and Chemistry Chinese Academy of Sciences Beijing 100190 China Department of Electrical and Computer Engineering Texas Tech University Lubbock Texas 79409 USA Ningbo Institute of Material Technology & Engineering Chinese Academy of Sciences Ningbo 315201 China College of Physical Science and Technology Sichuan University Chengdu 610065 China Songshan Lake Materials Laboratory Dongguan Guangdong 523808 China

The similarities to cuprates make iridates an interesting potential platform for investigating superconductivity. Equally attractive are their puzzling complex intrinsic interactions. Here, we report an ultrafast optical spectroscopy investigation of a coherent phonon mode in Sr3Ir2O7, a bilayer Ruddlesden-Popper perovskite iridate. An anomaly in the A1g optical phonon (ν=4.4THz) is unambiguously observed below the Néel temperature (TN), which we attribute to pseudospin-lattice coupling (PLC). Significantly, we find that PLC is the dominant interaction at low temperature, and we directly measure the PLC coefficient to be λ=150±20cm−1, which is two orders of magnitude higher than that in manganites (<2.4cm−1) and comparable to that in CuO (50cm−1, the strongest PLC or spin-lattice coupling (SLC) previously known). Moreover, we find that the strong PLC induces an anisotropic negative thermal expansion. Our findings highlight the key role of PLC in iridates and uncovers another intriguing similarity to cuprates.

关键词： Lattice dynamics Phonons Ultrafast phenomena Strongly correlated systems

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GAN-based semi-supervised for imbalanced data classification

GAN-based semi-supervised for imbalanced data classification

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International Conference on Information Management (ICIM)

作者： Tingting Zhou Wei Liu Congyu Zhou Leiting Chen School of Computer Science and Engineering Dongguan Data Science software Technology Co. Ltd Dongguan China Chengdu Vocational and Technical College of Industry Dongguan Data Science software Technology Co. Ltd Dongguan China School of Computer Science and Engineering Institute of Electronic and Information Engineering UESTC in Guangdong Dongguan China

Most of the traditional classification algorithms are based on the premise that the datasets are uniformly distributed or roughly equivalent. Once the sample dataset is not balanced , the classification performance drops sharply. To efficiently deal with the imbalance of data, an improved generative adversarial network (GAN) algorithm is proposed in this work . Firstly, we construct artificial samples so that more minority-class's data can be obtained via optimizing GAN loss function. Secondly, we build a fully-connected network for structured data classification. Finally, experimental evaluations are conducted on two open structured-datasets and the results of the proposed algorithm demonstrate a good applicability for the classification of structured data.

关键词： Gallium nitride Generators Classification algorithms Training Data models Feature extraction Radio frequency

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Search for the doubly heavy baryons Ω^(0)_(bc) and E^(0)_(bc) decaying to Λ^(+)_(c)π^(-) and E^(+)_(c)π^(-)

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Chinese Physics C 2021年第9期45卷 10-21页

作者： R.Aaij C.Abelian Beteta T.Ackernley B.Adeva M.Adinolfi H.Afshamia C.A.Aidala S.Aiola Z.Ajaltouni S.Aka J.Albrecht F.Alessio M.Alexander A.Alfonso Albero Z.Aliouche G.Alkhazov P.Alvarez Cartelie S.Amato Y.Amhis L.An L.Anderlini A.Andreianov M.Andreotti F.Archilli A.Artamonov M.Artuso K.Arzymatov E.Aslanides M.Atzeni B.Audurier S.Bachmann M.Bachmayer J.J.Back P.Baladron Rodriguez V.Balagura W.Baldini J.Baptista Leite R.J.Barlow S.Barsuk W.Barter M.Bartolini F.Baryshnikov J.M.Basels G.Bassi B.Batsukh A.Battig A.Bay M.Becker F.Bedeschi I.Bediaga A.Beiter V.Belavin S.Belin V.Bellee K.Belous I.Belov I.Belyaev G.Bencivenni E.Ben-Haim A.Berezhnoy *** D.Beminghoff H.C.Bernstein C.Bertella A.Bertolin C.Betancourt F.Betti Ia.Bezshyiko S.Bhasin J.Bhom L.Bian M.S.Bieker S.Bifani P.Billoir M.Birch F.C.R.Bishop A.Bitadze A.Bizzeti M.Bjorn M.P.Blago T.Blake F.Blanc S.Blusk D.Bobulska J.A.Boelhauve O.Boente Garcia T.Boettcher A.Boldyrev A.Bondar N.Bondar S.Borghi M.Borisyak M.Borsato J.T.Borsuk S.A.Bouchiba T.J.V.Bowcock A.Boyer C.Bozzi M J.Bradley S.Braun A.Brea Rodriguez M.Brodski J.Brodzicka A.Brossa Gonzalo D.Brundu A.Buonaura C.Burr A.Bursche A.Butkevich J.S.Butter J.Buytaert W.Byczynski S.Cadeddu H.Cai R.Calabrese L.Calefice L.Calero Diaz S.Cali R.Calladine M.Calvi M.Calvo Gomez P.Camargo Magalhaes A.Camboni P.Campana A.F.Campoverde Quezada S.Capelli L.Capriotti A.Carbone G.Carboni R.Cardinale A.Cardini I.Carli P.Camiti L.Carus K.Carvalho Akiba A.Casais Vidal G.Casse M.Cattaneo G.Cavallero S.Celani J.Cerasoli A.J.Chadwick M.G.Chapman M.Charles Ph.Charpentier G.Chatzikonstantinidis C.A.Chavez Barajas M.Chefdeville C.Chen S.Chen A.Chernov V.Chobanova S.Cholak M.Chrzaszcz A.Chubykin V.Chulikov P.Ciambrone M.F.Cicala X.Cid Vidal G.Ciezarek P.E.L.Clarke M.Clemencic H.V.Cliff J.Closier J.L.Cobbledick V.Coco J.A.B.Coelho J.Cogan E.Cogneras L.Cojocariu P.Collins T.Colombo L.Congedo A.Contu N.Cooke G.Coombs G.Corti C.M.Costa Sobral B.Couturier D.C.Craik J.Crkovska M.Cruz Torres R.Currie C.L.Da Silva E.Dall'Occo J.Dalseno C.D'Ambrosi Centro Brasileiro de Pesquisas Fisicas(CBPF) Rio de JaneiroBrazil Universidade Federal do Rio de Janeiro(UFRJ) Rio de JaneiroBrazil Center for High Energy Physics Tsinghua UniversityBeijingChina Institute of High Energy Physics(IHEP) BeijingChina School of Physics State Key Laboratory of Nuclear Physics and Technology Peking UniversityBeijingChina University ofChinese Academy of Sciences BeijingChina Institute of Particle Physics Central China Normal UniversityWuhanHubeiChina Univ.Savoie Mont Blanc CNRSIN2P3-LAPPAnnecyFrance Universite Clermont Auvergne CNRS/IN2P3LPCClermont-FerrandFrance Aix Marseille Univ CNRS/IN2P3CPPMMarseilleFrance Universite Paris-Saclay CNRS/IN2P3IJCLabOrsayFrance Laboratoire Leprince-Ringuet CNRS/IN2P3Ecole PolytechniqueInstitut Polytechnique de ParisPalaiseauFrance LPNHE Sorbonne UniversiteParis Diderot Sorbonne Paris CiteCNRS/FN2P3ParisFrance I.Physikalisches Institut RWTH Aachen UniversityAachenGermany Fakultat Physik Technische Universitat DortmundDortmundGermany Max-Planck-Institut für Kemphysik(MPIK) HeidelbergGermany Physikalisches Institut Ruprecht-Karls-Universitat HeidelbergHeidelbergGermany School of Physics University College DublinDublinIreland INFN Sezione di Bari BariItaly INFN Sezione di Bologna BolognaItaly INFN Sezione di Ferrara FerraraItaly INFN Sezione di Firenze FirenzeItaly INFN Laboratori Nazionali di Frascati FrascatiItaly INFN Sezione di Genova GenovaItaly INFN Sezione di Milano MilanoItaly INFN Sezione di Milano-Bicocca MilanoItaly INFN Sezione di Cagliari MonserratoItaly Universita degli Studi di Padova Universita e INFNPadovaPadovaItaly INFN Sezione di Pisa PisaItaly INFN Sezione di Roma La Sapienza RomaItaly INFN Sezione di Roma Tor Vergata RomaItaly Nikhef National Institute for Subatomic Physics AmsterdamNetherlands Nikhef National Institute for Subatomic Physics and VU University Amsterdam AmsterdamNetherlands AGH-University of Science and Technology Faculty of Physics and Applied Computer ScienceKr

The first search for the doubly heavyΩ^(0)_(bc)baryon and a search for the E^(0)_(bc)baryon are performed using pp collision data collected via the LHCb experiment from 2016 to 2018 at a centre-of-mass energy of 13 TeV,corresponding to an integrated luminosity of 5.2 fb^(-1).The baryons are reconstructed via their decays to Λ^(+)_(c)π^(-)and E^(+)_(c)π^(-).No significant excess is fbund for invariant masses between 6700 and 7300 MeV/c^(2),in a rapidity range from 2.0 to 4.5 and a transverse momentum range from 2 to 20 MeV/*** limits are set on the ratio of the Ω^(0)_(bc)and E^(0)_(bc)production cross-section times the branching fraction to Λ^(+)_(c)π^(-)(E^(+)_(c)π^(-))relative to that of the Λ^(0)_(b)(E^(0)_(b))baryon,for different lifetime hypotheses,at 95%confidence *** upper limits range from 0.5 x 10^(-4)to 2.5 x 10^(-4)for theΩ^(0)_(bc)→Λ^(+)_(c)π^(-)(E^(0)_(bc)→Λ^(+)_(c)π^(-))decay,and from 1.4x 10^(-3)to 6.9 x 10^(-3)for theΩ^(0)_(bc)→E^(+)_(c)π^(-)(E^(0)_(bc)→E^(+)_(c)π^(-))decay,depending on the considered mass and lifetime of theΩ^(0)_(bc)(E^(0)_(bc))baryon.

关键词： B physics quarkonium spectroscopy heavy quark production

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Author Correction: Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study

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NPJ digital medicine 2022年第1期5卷 56页

作者： Qi Dou Tiffany Y So Meirui Jiang Quande Liu Varut Vardhanabhuti Georgios Kaissis Zeju Li Weixin Si Heather H C Lee Kevin Yu Zuxin Feng Li Dong Egon Burian Friederike Jungmann Rickmer Braren Marcus Makowski Bernhard Kainz Daniel Rueckert Ben Glocker Simon C H Yu Pheng Ann Heng Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong SAR China. qdou@cse.cuhk.edu.hk. Department of Imaging and Interventional Radiology The Chinese University of Hong Kong Hong Kong SAR China. Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong SAR China. Department of Diagnostic Radiology Li Ka Shing Faculty of Medicine The University of Hong Kong Hong Kong SAR China. Biomedical Image Analysis Group Imperial College London London UK. Institute for Diagnostic and Interventional Radiology Technical University of Munich School of Medicine Munich Germany. OpenMined Oxford UK. Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen Guangdong China. Department of Diagnostic Radiology Princess Margaret Hospital Hong Kong SAR China. Department of Radiology Tuen Muen Hospital Hong Kong SAR China. Department of Emergency Medicine Peking University ShenZhen Hospital Shenzhen Guangdong China. Department of Radiology Zhijiang People's Hospital Zhijiang Hubei China. German Cancer Research Center (DKFZ) Heidelberg Germany. AI in Medicine and Healthcare Technical University of Munich School of Informatics and Medicine Munich Germany. Biomedical Image Analysis Group Imperial College London London UK. b.glocker@imperial.ac.uk. Department of Imaging and Interventional Radiology The Chinese University of Hong Kong Hong Kong SAR China. simonyu@cuhk.edu.hk. Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong SAR China. pheng@cse.cuhk.edu.hk.

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