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Chinese Automation Congress (CAC)

作者： Shuling Li Wu Ai Jian Wu College of Science Center for Data analysis and Algorithm Technology Guilin University of Technology Guilin P. R. China College of Science Guilin University of Technology Guangxi Key Laboratory of Spatial Information and Geomatics Guilin P. R. China Perception and Computing of Anhui University Key Laboratory of Intelligent Province Anqing P. R. China

This work is the first to consider the self-triggered distributed optimization problem for multi-agent systems with periodic sampling communication. Each agent computes its next update time instance at the previous time. The self-triggered distributed protocols are proposed to reduce the load of in-network communication. It is proved that these self-triggered protocol achieves optimal consensus exponentially under a undirected and connected network topology.

关键词： Multi-agent systems Cost function Protocols Eigenvalues and eigenfunctions Geomagnetism Network topology

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Biomedical image analysis competitions: The state of current participation practice

arXiv

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arXiv 2022年

作者： Eisenmann, Matthias Reinke, Annika Weru, Vivienn Tizabi, Minu Dietlinde Isensee, Fabian Adler, Tim J. Godau, Patrick Cheplygina, Veronika Kozubek, Michal Maier-Hein, Klaus Jäger, Paul F. Kopp-Schneider, Annette Maier-Hein, Lena Ali, Sharib Gupta, Anubha Kybic, Jan Noble, Alison de Solórzano, Carlos Ortiz Pachade, Samiksha Petitjean, Caroline Sage, Daniel Wei, Donglai Wilden, Elizabeth Alapatt, Deepak Andrearczyk, Vincent Baid, Ujjwal Bakas, Spyridon Balu, Niranjan Bano, Sophia Bawa, Vivek Singh Bernal, Jorge Bodenstedt, Sebastian Casella, Alessandro Choi, Jinwook Commowick, Olivier Daum, Marie Depeursinge, Adrien Dorent, Reuben Egger, Jan Eichhorn, Hannah Engelhardt, Sandy Ganz, Melanie Girard, Gabriel Hansen, Lasse Heinrich, Mattias Heller, Nicholas Hering, Alessa Huaulmé, Arnaud Kim, Hyunjeong Li, Hongwei Bran Landman, Bennett Li, Jianning Ma, Jun Martel, Anne Martín-Isla, Carlos Menze, Bjoern Nwoye, Chinedu Innocent Oreiller, Valentin Padoy, Nicolas Pati, Sarthak Payette, Kelly Sudre, Carole van Wijnen, Kimberlin Vardazaryan, Armine Vercauteren, Tom Wagner, Martin Wang, Chuanbo Yap, Moi Hoon Yu, Zeyun Yuan, Chun Zenk, Maximilian Zia, Aneeq Zimmerer, David Bao, Rina Choi, Chanyeol Cohen, Andrew Dzyubachyk, Oleh Galdran, Adrian Gan, Tianyuan Guo, Tianqi Gupta, Pradyumna Haithami, Mahmood Ho, Edward Jang, Ikbeom Li, Zhili Luo, Zhengbo Lux, Filip Makrogiannis, Sokratis Müller, Dominik Oh, Young-Tack Pang, Subeen Pape, Constantin Polat, Gorkem Reed, Charlotte Rosalie Ryu, Kanghyun Scherr, Tim Thambawita, Vajira Wang, Haoyu Wang, Xinliang Xu, Kele Yeh, Hung Yeo, Doyeob Yuan, Yixuan Zeng, Yan Zhao, Xin Abbing, Julian Adam, Jannes Adluru, Nagesh Agethen, Niklas Ahmed, Salman Al Khalil, Yasmina Alenyà, Mireia Alhoniemi, Esa An, Chengyang Arega, Tewodros Weldebirhan Avisdris, Netanell Aydogan, Dogu Baran Bai, Yingbin Calisto, Maria Baldeon Basaran, Berke Doga Beetz, Marcel Bian, Hao Blansit, Kevin Bloch, Louise Bohnsack, Robert Bosticardo, Sara Breen, Jack Brudfors, Mikael Brüngel, Raphael Cabezas, Mariano Cacciola, Alb Heidelberg Division of Intelligent Medical Systems Germany Heidelberg HI Helmholtz Imaging Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Biostatistics Germany Heidelberg Division of Medical Image Computing Germany Heidelberg HI Applied Vision Lab Germany IT University of Copenhagen Copenhagen Denmark Centre for Biomedical Image Analysis Masaryk University Brno Czech Republic Heidelberg Interactive Machine Learning Group Germany Faculty of Mathematics and Computer Science and Medical Faculty Heidelberg University Heidelberg Germany NCT Heidelberg DKFZ University Hospital Heidelberg Germany School of Computing University of Leeds Leeds United Kingdom SBILab Department of ECE IIIT-Delhi India Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Institute of Biomedical Engineering University of Oxford United Kingdom Center for Applied Medical Research Pamplona Spain Shri Guru Gobind Singhji Institute of Engineering and Technology Maharashtra Nanded India Université de Rouen Normandie France Lausanne Switzerland School of Engineering and Applied Science Harvard University United States ICube University of Strasbourg CNRS France Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Techno-Pôle 3 Sierre3960 Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Rue du Bugnon 46 LausanneCH-1011 Switzerland University of Pennsylvania PhiladelphiaPA United States Department of Radiology University of Washington United States Wellcome EPSRC Centre for Interventional and Surgical Sciences University College London London United Kingdom Visual Artificial Intelligence Lab Oxford Brookes University Oxford United Kingdom Universitat Autònoma de Barcelona & Computer Vision Center Spain Dresden Fetscherstraße 74 PF 64 Dresden01307 Germany

The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known about the common practice as well as bottlenecks faced by the community in tackling the research questions posed. To shed light on the status quo of algorithm development in the specific field of biomedical imaging analysis, we designed an international survey that was issued to all participants of challenges conducted in conjunction with the IEEE ISBI 2021 and MICCAI 2021 conferences (80 competitions in total). The survey covered participants' expertise and working environments, their chosen strategies, as well as algorithm characteristics. A median of 72% challenge participants took part in the survey. According to our results, knowledge exchange was the primary incentive (70%) for participation, while the reception of prize money played only a minor role (16%). While a median of 80 working hours was spent on method development, a large portion of participants stated that they did not have enough time for method development (32%). 25% perceived the infrastructure to be a bottleneck. Overall, 94% of all solutions were deep learning-based. Of these, 84% were based on standard architectures. 43% of the respondents reported that the data samples (e.g., images) were too large to be processed at once. This was most commonly addressed by patch-based training (69%), downsampling (37%), and solving 3D analysis tasks as a series of 2D tasks. K-fold cross-validation on the training set was performed by only 37% of the participants and only 50% of the participants performed ensembling based on multiple identical models (61%) or heterogeneous models (39%). 48% of the respondents applied postprocessing steps. © 2022, CC BY.

关键词： Benchmarking

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Influential groups for seeding and sustaining nonlinear contagion in heterogeneous hypergraphs

arXiv

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arXiv 2021年

作者： St-Onge, Guillaume Iacopini, Iacopo Latora, Vito Barrat, Alain Petri, Giovanni Allard, Antoine Hébert-Dufresne, Laurent Département de Physique de Génie Physique et d’Optique Université Laval QuébecQCG1V 0A6 Canada Centre Interdisciplinaire en Modélisation Mathématique Université Laval QuébecQCG1V 0A6 Canada Department of Network and Data Science Central European University Vienna1100 Austria Aix Marseille Univ Université de Toulon CNRS CPT Marseille France Centre for Advanced Spatial Analysis University College London LondonW1T 4TJ United Kingdom School of Mathematical Sciences Queen Mary University of London Mile End Road LondonE1 4NS United Kingdom Dipartimento di Fisica ed Astronomia Università di Catania INFN CataniaI-95123 Italy Complexity Science Hub Josefstädter Strasse 39 ViennaA 1080 Austria Tokyo Institute of Technology Tokyo Japan Mathematics and Complex Systems Research Area ISI Foundation Turin Italy ISI Global Science Foundation New York United States Vermont Complex Systems Center University of Vermont BurlingtonVT05401 United States Department of Computer Science University of Vermont BurlingtonVT05401 United States

Several biological and social contagion phenomena, such as superspreading events or social reinforcement, are the results of multi-body interactions, for which hypergraphs offer a natural mathematical description. In this paper, we develop a novel mathematical framework based on approximate master equations to study contagions on random hypergraphs with a heterogeneous structure, both in terms of group size (hyperedge cardinality) and of membership of nodes to groups (hyperdegree). The characterization of the inner dynamics of groups provides an accurate description of the contagion process, without losing the analytical tractability. Using a contagion model where multi-body interactions are mapped onto a nonlinear infection rate, our two main results show how large groups are influential, in the sense that they drive both the early spread of a contagion and its endemic state (i.e., its stationary state). First, we provide a detailed characterization of the phase transition, which can be continuous or discontinuous with a bistable regime, and derive analytical expressions for the critical and tricritical points. We find that large values of the third moment of the membership distribution suppress the emergence of a discontinuous phase transition. Furthermore, the combination of heterogeneous group sizes and nonlinear contagion facilitates the onset of a mesoscopic localization phase, where contagion is sustained only by the largest groups, thereby inhibiting bistability as well. Second, we formulate the problem of optimal seeding for hypergraph contagion, and we compare two strategies: tuning the allocation of seeds according to either individual node or group properties. We find that, when the contagion is sufficiently nonlinear, groups are more effective seeds of contagion than individual nodes. Copyright © 2021, The Authors. All rights reserved.

关键词： Graph theory

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High-Performance Thermoelectric α-Ag9Ga1−xTe6Compounds with Ultralow Lattice Thermal Conductivity Originating from Ag9Te2Motifs

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Angewandte Chemie 2022年第36期134卷

作者： Yingfei Tang Yimeng Yu Na Zhao Keke Liu Haijie Chen Constantinos C. Stoumpos Yixuan Shi Shuo Chen Lingxiao Yu Jinsong Wu Qingjie Zhang Xianli Su Xinfeng Tang State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology Wuhan 430070 China International School of Materials Science and Engineering Wuhan University of Technology Wuhan 430070 China Contribution: Conceptualization (equal) Data curation (lead) Formal analysis (lead) Investigation (equal) Methodology (equal) Visualization (equal) Writing - original draft (lead) Nanostructure Research Center Wuhan University of Technology Wuhan 430070 China Contribution: Data curation (equal) Software (equal) Visualization (supporting) Contribution: Investigation (equal) Methodology (equal) Contribution: Investigation (equal) Methodology (equal) Visualization (equal) State Key Laboratory for Modification of Chemical Fibers and Polymer Materials Institute of Functional Materials College of Materials Science and Engineering Donghua University Shanghai 201620 China Contribution: Methodology (equal) Visualization (equal) Writing - review & editing (equal) Department of Materials Science and Technology Voutes Campus University of Crete Iraklio Heraklion 70013 Greece Contribution: Methodology (equal) Visualization (equal) Contribution: Investigation (equal) Visualization (equal) Contribution: Conceptualization (equal) Investigation (equal) Contribution: Methodology (equal) Contribution: Conceptualization (equal) Methodology (equal) Contribution: Conceptualization (equal) Investigation (equal) Methodology (equal) Writing - review & editing (equal) Contribution: Conceptualization (equal) Funding acquisition (lead) Methodology (equal) Supervision (equal) Writing - review & editing (equal)

We have determined the complex atomic structure of high-temperature α-Ag 9 GaTe 6 phase with a hexagonal lattice ( P 6 3 mc space group, a = b =8.2766 Å, c =13.4349 Å). The structure has outer [GaTe 4 ] 5− tetrahedrons and inner [Ag 9 Te 2 ] 5+ clusters. All of the Ag ions are disorderly distributed in the lattice. Seven types of the Ag atoms constitute the cage-like [Ag 9 Te 2 ] 5+ clusters. The highly disordered Ag ions vibrate in-harmonically, producing strong coupling between low frequency optical phonons and acoustic phonons. This in conjunction with a low sound velocity of 1354 m s −1 leads to an ultralow thermal conductivity of 0.20 W m −1 K −1 at 673 K. Meanwhile, the deficiency of Ga in Ag 9 Ga 1− x Te 6 compounds effectively optimizes the electronic transport properties. Ag 9 Ga 0.91 Te 6 attains a highest power factor of 0.40 mW m −1 K −2 at 673 K. All these contribute to a much-improved ZT value of 1.13 at 623 K for Ag 9 Ga 0.95 Te 6 , which is 41 % higher than that of the pristine Ag 9 GaTe 6 sample.

关键词： α-Ag9GaTe6 Crystal Structure Ga Deficiency Thermoelectrics Ultralow Lattice Thermal Conductivity

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H2O2-Responsive NIR-II AIE Nanobomb for Carbon Monoxide Boosting Low-Temperature Photothermal Therapy

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Angewandte Chemie 2022年第36期134卷

作者： Gongcheng Ma Zhongke Liu Chunguang Zhu Prof. Huajie Chen Prof. Ryan T. K. Kwok Prof. Pengfei Zhang Ben Zhong Tang Prof. Lintao Cai Prof. Ping Gong Guangdong Key Laboratory of Nanomedicine Shenzhen Engineering Laboratory of Nanomedicine and Nanoformulations CAS-HK Joint Lab for Biomaterials Research Laboratory for Biomedical Optics and Molecular Imaging Shenzhen Key Laboratory for Molecular Imaging CAS Key Lab for Health Informatics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China University of Chinese Academy of Sciences Beijing 100049 China Contribution: Data curation (lead) Validation (lead) Writing - original draft (lead) Nano Science and Technology Institute University of Science & Technology of China Suzhou 215123 China Contribution: Data curation (equal) Investigation (equal) Key Laboratory of Environmentally Friendly Chemistry and Application of the Ministry of Education College of Chemistry Xiangtan University Xiangtan 411105 China Contribution: Data curation (supporting) Methodology (supporting) Contribution: Project administration (supporting) Resources (supporting) Supervision (supporting) Writing - review & editing (equal) Department of Chemistry Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction and Institute for Advanced Study The Hong Kong University of Science and Technology (HKUST) Clear Water Bay Kowloon Hong Kong China Contribution: Funding acquisition (equal) Supervision (equal) Writing - review & editing (equal) Contribution: Conceptualization (lead) Formal analysis (lead) Methodology (equal) Project administration (lead) Resources (equal) Supervision (equal) Writing - original draft (equal) Writing - review & editing (lead) School of Science and Engineering Shenzhen Institute of Aggregate Science and Technology The Chinese University of Hong Kong Shenzhen Guangdong 518172 China Contribution: Formal analysis (supporting) Funding acquisition (equal) Writing - review & editing (supporting) Contribution: Funding acquisition (lead) Project administration (lead) Supervision (lead) Writing - revi

Low-temperature photothermal therapy (PTT), which circumvents the limitations of conventional PTT (e.g., thermotolerance and adverse effects), is an emerging therapeutic strategy which shows great potential for future clinical applications. The expression of heat shock proteins (HSPs) can dramatically impair the therapeutic efficacy of PTT. Thus, inhibition of HSPs repair and reducing the damage of nearby normal cells is crucial for improving the efficiency of low-temperature PTT. Herein, we developed a nanobomb based on the self-assembly of NIRII AIE polymer PBPTV and carbon monoxide (CO) carrier polymer mPEG(CO). This smart nanobomb can be exploded in a tumor microenvironment in which hydrogen peroxide is overexpressed and release CO into cancer cells to significantly inhibit the expression of HSPs and hence improve the antitumor efficiency of the low-temperature PTT.

关键词： Aggregation Induced Emission Gas Therapy Heat Shock Protein NIR-II Photothermal Therapy

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Boosting Reactive Oxygen Species Generation Using Inter-Facet Edge Rich WO3Arrays for Photoelectrochemical Conversion

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Angewandte Chemie 2022年第1期135卷

作者： He Li Cheng Lin Yilong Yang Chaoran Dong Prof. Yulin Min Prof. Xiaoqin Shi Prof. Luyang Wang Prof. Siyu Lu Prof. Kan Zhang School of Materials Science and Engineering and School of Chemistry and Chemical Engineering Nanjing University of Science and Technology Nanjing 210094 China Contribution: Data curation (lead) Investigation (equal) Methodology (equal) Writing - original draft (equal) Contribution: Investigation (lead) Methodology (equal) Writing - original draft (equal) Contribution: Formal analysis (equal) Shanghai Key Laboratory of Materials Protection and Advanced Materials in Electric Power Shanghai University of Electric Power Shanghai 200090 P. R. China Contribution: Investigation (supporting) Writing - review & editing (supporting) Contribution: Software (lead) College of New Materials and New Energies Shenzhen Technology University Shenzhen Guangdong 518118 P. R. China Contribution: Methodology (supporting) Supervision (supporting) Writing - review & editing (supporting) Green Catalysis Center and College of Chemistry Zhengzhou University Zhengzhou 450000 P. R. China Contribution: Supervision (equal) Contribution: Supervision (lead) Writing - review & editing (lead)

Water oxidation reaction leaves room to be improved in the development of various solar fuel productions, because of the kinetically sluggish 4-electron transfer process of oxygen evolution reaction. In this work, we realize reactive oxygen species (ROS), H 2 O 2 and OH⋅, formations by water oxidation with total Faraday efficiencies of more than 90 % by using inter-facet edge (IFE) rich WO 3 arrays in an electrolyte containing CO 3 2− . Our results demonstrate that the IFE favors the adsorption of CO 3 2− while reducing the adsorption energy of OH⋅, as well as suppresses surface hole accumulation by direct 1-electron and indirect 2-electron transfer pathways. Finally, we present selective oxidation of benzyl alcohol by in situ using the formed OH⋅, which delivers a benzaldehyde production rate of ≈768 μmol h −1 with near 100 % selectivity. This work offers a promising approach to tune or control the oxidation reaction in an aqueous solar fuel system towards high efficiency and value-added product.

关键词： Charge Transfer Oxygenation Photocatalysis Radicals Water Splitting

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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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The repertoire of mutational signatures in human cancer (vol 578, pg 94, 2020)

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NATURE 2023年第7948期614卷 E41-E41页

作者： Alexandrov, Ludmil B. Kim, Jaegil Haradhvala, Nicholas J. Huang, Mi Ni Ng, Alvin Wei Tian Wu, Yang Boot, Arnoud Covington, Kyle R. Gordenin, Dmitry A. Bergstrom, Erik N. Islam, S. M. Ashiqul Lopez-Bigas, Nuria Klimczak, Leszek J. McPherson, John R. Morganella, Sandro Sabarinathan, Radhakrishnan Wheeler, David A. Mustonen, Ville Getz, Gad Rozen, Steven G. Stratton, Michael R. Department of Cellular and Molecular Medicine Department of Bioengineering Moores Cancer Center University of California San Diego CA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Cellular and Molecular Medicine and Department of Bioengineering University of California San Diego La Jolla CA USA UC San Diego Moores Cancer Center San Diego CA USA University of California San Diego San Diego CA USA Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Massachusetts General Hospital Boston MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama Japan Computational Biology Program Ontario Institute for Cancer Research Toronto ON Canada Programme in Cancer & Stem Cell Biology Duke-NUS Medical School Singapore Singapore Centre for Computational Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Centre for Computational Biology Duke-NUS Medical School Singapore Singapore SingHealth Duke-NUS Institute of Precision Medicine National Heart Centre Singapore Singapore Singapore Cancer Science Institute of Singapore National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Singapore Singapore Laboratory of Cancer Epigenome Division of Medical Science National Cancer Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Dan L. Duncan Cancer Center Baylor College of Medicine Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Genome Integrity and Structural Biology Laboratory National Ins

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REGIONAL CLIMATES

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Bulletin of the American Meteorological Society 2024年第8期105卷 S371-S484页

作者： Agyakwah, W. Ahmadpour, Somayeh Aldeco, Laura S. Alfaro, Eric J. Alves, Lincoln M. Amador, Jorge A. Andrade, B. Arguez, Anthony Avalos, Grinia Bardin, M.Yu. Beauchemin, Marc Bekele, E. Berne, Christine Bissolli, Peter Bochníček, Oliver Bukunt, Brandon Calderón, Blanca Campbell, Jayaka Chandler, Elise Charlton, Candice S. Chen, Jack Cheng, Vincent Y.S. Chisholm, Lucy Clarke, Leonardo Correa, Kris Costa, Felipe Cunha, Ana P. Dindyal, S. Dulamsuren, Dashkhuu Echeverría Garcés, Paola Ekici, Mithat ElKharrim, M. Espinoza, Jhan-Carlo Fenimore, Chris Fu, Shanshan Ganter, Catherine Gevorgyan, Artur Gleason, Karin Gómez Camacho, Julio González Hernández, Yolanda Hakmi, S. Heim, Richard R. Hicks, J. Hidalgo, Hugo G. Huang, Hongjie Jadra, Gerardo Jain, Piyush Jumaux, G. Kabidi, K. Kazemi, Amin Fazl Kendon, Michael Kennedy, John Khalatyan, Yelena Khan, Valentina Khiem, Mai Van Kirchmeier-Young, Megan Korshunova, Natalia N. Kruger, A.C. Lakatos, Mónika Lam, Hoang Phuc Lavado-Casimiro, Waldo Lee, Tsz-Cheung Lu, Rui Mamen, Jostein Marengo, Jose A. Marjan, Mohammadi Martinez, Rodney McBride, C. Mekonnen, Ademe Meyers, Tristan Minney, Caitlin Moise, Aurel Molina-Carpio, Jorge Moody, Ronald Mora, Natali Mostafa, A.E. Muharsyah, Robi Okunaka, Yuka Orlik, Alexander Pascual Ramírez, Reynaldo Porat, Amos Quispe, Willy R. Ramos, Andrea M. Ressl, Hans Rivera, Patricia P. Robjhon, M. Rodriguez Guisado, Esteban Roebeling, Maarit Ronchail, Josyane Rösner, Benjamin Sabeerali, C.T. Salinas, Roberto Sayouri, A. Segele, Z.T. Sensoy, Serhat Seong, Ji-In Serna Cuenca, Julieta Shukla, R. Smith, Adam Spence-Hemmings, Jacqueline Sreejith, O.P. Srivastava, A.K. Stella, Jose L. Stephenson, Tannecia S. Stevens, Laura Takahashi, Kiyotoshi Takemura, Kazuto Taylor, Michael A. Thiaw, W.M. Trachte, Katja Trotman, Adrian van der Linden, Roderick van der Schrier, Gerard Van Meerbeeck, Cédric J. Vazife, Ahad Virasami, R. Wu, Francis Zhang, Peiqun Zhu, Zhiwei NOAA NWS National Centers for Environmental Prediction Climate Prediction Center College ParkMD United States Senftenberg Cottbus Germany Servicio Meteorológico Nacional Buenos Aires Argentina Center for Geophysical Research School of Physics University of Costa Rica San José Costa Rica Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN São Paulo Brazil Seychelles Meteorological Authority Mahe Seychelles NOAA/NESDIS National Centers for Environmental Information AshevilleNC United States Servicio Nacional de Meteorología e Hidrología del Perú Lima Peru Yu. A. Izrael Institute of Global Climate and Ecology Institute of Geography Russian Academy of Sciences Moscow Russia Environment and Climate Change Canada Montreal Canada Météo France Toulouse France Deutscher Wetterdienst WMO RA VI Regional Climate Centre Network Offenbach Germany Slovak Hydrometeorological Institute Bratislava Slovakia NOAA/NWS Weather Forecast Office Guam Tiyan United States Center for Geophysical Research University of Costa Rica San José Costa Rica Department of Physics The University of the West Indies Kingston Jamaica Bureau of Meteorology Melbourne Australia Environment and Climate Change Canada Ottawa Canada Environment and Climate Change Canada Toronto Canada Environment and Climate Change Canada Halifax Canada Guayaquil Ecuador Mauritius Meteorological Service Vacoas Mauritius Institute of Meteorology Hydrology and Environment National Agency for Meteorology Ulaanbaatar Mongolia Quito Ecuador Turkish State Meteorological Service Ankara Turkey General Directorate of Meteorology Rabat Morocco Université Grenoble Alpes Institut des Géosciences de l’Environnement IRD CNRS Grenoble INP Grenoble France Nanjing University of Information Science and Technology Nanjing China Hydrometeorology and Monitoring Center Yerevan Armenia National Meteorological Service of Mexico Mexico City Mexico NOAA NWS National Centers for Environmental Prediction

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Genomic basis for RNA alterations in cancer (vol 578, pg 129, 2020)

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NATURE 2023年第7948期614卷 E37-E37页

作者： Calabrese, Claudia Davidson, Natalie R. Demircioglu, Deniz Fonseca, Nuno A. He, Yao Lehmann, Kjong-Van Liu, Fenglin Shiraishi, Yuichi Soulette, Cameron M. Urban, Lara Greger, Liliana Li, Siliang Liu, Dongbing Perry, Marc D. Xiang, Qian Zhang, Fan Zhang, Junjun Bailey, Peter Erkek, Serap Hoadley, Katherine A. Hou, Yong Huska, Matthew R. Kilpinen, Helena Korbel, Jan O. Marin, Maximillian G. Markowski, Julia Nandi, Tannistha Pan-Hammarstrom, Qiang Pedamallu, Chandra Sekhar Siebert, Reiner Stark, Stefan G. Su, Hong Tan, Patrick Waszak, Sebastian M. Yung, Christina Zhu, Shida Awadalla, Philip Creighton, Chad J. Meyerson, Matthew Ouellette, B. F. Francis Wu, Kui Yang, Huanming Brazma, Alvis Brooks, Angela N. Goke, Jonathan Ratsch, Gunnar Schwarz, Roland F. Stegle, Oliver Zhang, Zemin European Molecular Biology Laboratory European Bioinformatics Institute Hinxton UK European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany CIBIO/InBIO - Research Center in Biodiversity and Genetic Resources Universidade do Porto Vairão Portugal Berlin Institute for Medical Systems Biology Max Delbruck Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) partner site Berlin Germany German Cancer Research Center (DKFZ) Heidelberg Germany Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) Partner site Berlin Berlin Germany European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Division of Computational Genomics and Systems Genetics German Cancer Research Center (DKFZ) Heidelberg Germany ETH Zurich Zurich Switzerland Memorial Sloan Kettering Cancer Center New York NY USA Weill Cornell Medical College New York NY USA SIB Swiss Institute of Bioinformatics Lausanne Switzerland University Hospital Zurich Zurich Switzerland Computational Biology Center Memorial Sloan Kettering Cancer Center New York NY USA Department of Biology ETH Zurich Zürich Switzerland Department of Computer Science ETH Zurich Zurich Switzerland Korea University Seoul South Korea Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine New York NY USA National University of Singapore Singapore Singapore Genome Institute of Singapore Singapore Singapore Computational and Systems Biology Genome Institute of Singap

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