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Ductile-to-brittle transition and yielding in soft amorphous materials: perspectives and open questions

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arXiv 2023年

作者： Divoux, Thibaut Agoritsas, Elisabeth Aime, Stefano Barentin, Catherine Barrat, Jean-Louis Benzi, Roberto Berthier, Ludovic Bi, Dapeng Biroli, Giulio Bonn, Daniel Bourrianne, Philippe Bouzid, Mehdi Del Gado, Emanuela Delanoë-Ayari, Hélène Farain, Kasra Fielding, Suzanne Fuchs, Matthias van der Gucht, Jasper Henkes, Silke Jalaal, Maziyar M. Joshi, Yogesh Lemaître, Anaël Leheny, Robert L. Manneville, Sébastien Martens, Kirsten Poon, Wilson C.K. Popović, Marko Procaccia, Itamar Ramos, Laurence Richards, James A. Rogers, Simon Rossi, Saverio Sbragaglia, Mauro Tarjus, Gilles Toschi, Federico Trappe, Véronique Vermant, Jan Wyart, Matthieu Zamponi, Francesco Zare, Davoud Molecular Macromolecular Chemistryand Materials ESPCI Paris Paris France Univ. de Lyon Universite Claude Bernard Lyon 1 CNRS Institut Lumiere Matiere VilleurbanneF-69622 France Soft Matter Group Van der Waals-Zeeman Institute University of Amsterdam Science Park 904 Amsterdam1098XH Netherlands Universite Montpellier CNRS Montpellier France SUPA and the School of Physics and Astronomy The University of Edinburgh Peter Guthrie Tait Road EdinburghEH9 3FD United Kingdom Universite Grenoble Alpes CNRS LIPhy Grenoble38000 France Laboratoire de Physique de l'Ecole Normale Superieure ENS Universite PSL CNRS Sorbonne Universite Universite de Paris ParisF-75005 France LPTMC CNRS-UMR 7600 Sorbonne Universite 4 Pl. Jussieu ParisF-75005 France Department of Physics Durham University South Road DurhamDH1 3LE United Kingdom Navier Ecole des Ponts Univ Gustave Eiffel CNRS Marne-la-Vallee France University of Geneva Quai Ernest-Ansermet 24 GenevaCH-1211 Switzerland Department of Physics and Astronomy Johns Hopkins University BaltimoreMD21218 United States Dipartimento di Fisica INFN Universita di Roma "Tor Vergata" Via della Ricerca Scientifica RomeI-00133 Italy Department of Applied Physics and Science Education Eindhoven University of Technology P.O. Box 513 Eindhoven9 5600 MB Netherlands CNR-IAC Via dei Taurini 19 Rome00185 Italy ENSL CNRS Laboratoire de physique LyonF-69342 France Max Planck Institute for the Physics of Complex Systems Nothnitzer Str.38 Dresden01187 Germany Georgetown University Department of Physics Institute for Soft Matter Synthesis and Metrology WashingtonDC United States Department of Materials ETH Zurich Vladimir Prelog Weg 5 Zurich8032 Switzerland Physical Chemistry and Soft Matter Wageningen University & Research Stippeneng 4 Wageningen6708WE Netherlands Univ. Grenoble Alpes CNRS Grenoble INP 3SR GrenobleF-38000 France PMMH ESPCI Paris France Fachbereich Physik Universitat Konstanz Konst

Soft amorphous materials are viscoelastic solids ubiquitously found around us, from clays and cementitious pastes to emulsions and physical gels encountered in food or biomedical engineering. Under an external deformation, these materials undergo a noteworthy transition from a solid to a liquid state that reshapes the material microstructure. This yielding transition was the main theme of a workshop held from January 9 to 13, 2023 at the Lorentz Center in Leiden. The manuscript presented here offers a critical perspective on the subject, synthesizing insights from the various brainstorming sessions and informal discussions that unfolded during this week of vibrant exchange of ideas. The result of these exchanges takes the form of a series of open questions that represent outstanding experimental, numerical, and theoretical challenges to be tackled in the near future. © 2023, CC BY.

关键词： Biomedical engineering

Roadmap on Deep Learning for Microscopy

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arXiv 2023年

作者： Volpe, Giovanni Wählby, Carolina Tian, Lei Hecht, Michael Yakimovich, Artur Monakhova, Kristina Waller, Laura Sbalzarini, Ivo F. Metzler, Christopher A. Xie, Mingyang Zhang, Kevin Lenton, Isaac C.D. Rubinsztein-Dunlop, Halina Brunner, Daniel Bai, Bijie Ozcan, Aydogan Midtvedt, Daniel Wang, Hao Sladoje, Nataša Lindblad, Joakim Smith, Jason T. Ochoa, Marien Barroso, Margarida Intes, Xavier Qiu, Tong Yu, Li-Yu You, Sixian Liu, Yongtao Ziatdinov, Maxim A. Kalinin, Sergei V. Sheridan, Arlo Manor, Uri Nehme, Elias Goldenberg, Ofri Shechtman, Yoav Moberg, Henrik K. Langhammer, Christoph Špačková, Barbora Helgadottir, Saga Midtvedt, Benjamin Argun, Aykut Thalheim, Tobias Cichos, Frank Bo, Stefano Hubatsch, Lars Pineda, Jesus Manzo, Carlo Bachimanchi, Harshith Selander, Erik Homs-Corbera, Antoni Fränzl, Martin de Haan, Kevin Rivenson, Yair Korczak, Zofia Adiels, Caroline Beck Mijalkov, Mite Veréb, Dániel Chang, Yu-Wei Pereira, Joana B. Matuszewski, Damian Kylberg, Gustaf Sintorn, Ida-Maria Caicedo, Juan C. Cimini, Beth A. Bell, Muyinatu Lediju A. Saraiva, Bruno M. Jacquemet, Guillaume Henriques, Ricardo Ouyang, Wei Le, Trang Gómez-De-Mariscal, Estibaliz Sage, Daniel Muñoz-Barrutia, Arrate Lindqvist, Ebba Josefson Bergman, Johanna Department of Physics University of Gothenburg Gothenburg41296 Sweden Dept. IT and SciLifeLab Uppsala University Sweden Department of Electrical and Computer Engineering Boston University BostonMA02215 United States Department of Biomedical Engineering Boston University BostonMA02215 United States Görlitz Germany Department of Renal Medicine Division of Medicine University College London Royal Free Hospital Campus London United Kingdom Artificial Intelligence for Life Sciences CIC Dorset United Kingdom Roche Pharma International Informatics Roche Diagnostics GmbH Mannheim Germany Department of Electrical Engineering and Computer Sciences UC Berkeley United States Technische Universität Dresden Faculty of Computer Science Dresden Germany Max Planck Institute of Molecular Cell Biology and Genetics Center for Systems Biology Dresden Dresden Germany University of Maryland College Park United States Klosterneuburg3400 Austria School of Mathematics and Physics The University of Queensland Brisbane4072 Australia Australian Research Council Centre of Excellence for Engineered Quantum Systems The University of Queensland Brisbane4072 Australia Département d’Optique P. M. Duffieux Institut FEMTO-ST Université Franche-Comté CNRS UMR 6174 Besançon France Department of Electrical and Computer Engineering University of California Los Angeles Los AngelesCA United States Department of Information Technology Uppsala University Sweden Department of Biomedical Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Elephas 1 Erdman Pl. Madison53705 United States University of Wisconsin–Madison Department of Medical Physics MadisonWI53705 United States Department of Molecular and Cellular Physiology Albany Medical College AlbanyNY12208 United States Research Laboratory of Electronics Electrical Engineering and Computer Science Massachusetts Institute of Technology BostonMA United States Center for Nanophase Materials Sciences Oak R

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of machine learning for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences. Copyright © 2023, The Authors. All rights reserved.

关键词： Image enhancement

Personalized radiotherapy design for glioblastoma: Integrating mathematical tumor models, multimodal scans and Bayesian inference

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arXiv 2018年

作者： Lipková, Jana Angelikopoulos, Panagiotis Wu, Stephen Alberts, Esther Wiestler, Benedikt Diehl, Christian Preibisch, Christine Pyka, Thomas Combs, Stephanie Hadjidoukas, Panagiotis van Leemput, Koen Koumoutsakos, Petros Lowengrub, John Menze, Bjoern Germany Dept. of Neuroradiolog Klinikum Rechts der Isar TUM Germany D.E. Shaw Research L.L.C United States Institute of Statistical Mathematics Tokyo Japan Dept. of Diagnostic and Interventional Neuroradiology & Neuroimaging Center & Clinic for Neurology Klinikum Rechts der Isar TUM Germany Dept. of Nuclear Medicine Klinikum Rechts der Isar TUM Germany Dept. of Radiation Oncology Klinikum Rechts der Isar TUM Institute of Innovative Radiotherapy Helmholtz Zentrum Munich & Deutsches Konsortium für Translationale Krebsforschung Germany IBM Research - Zurich Switzerland Harvard Medical School Boston United States Dept. of Applied Mathematics and Computer Science TU Denmark Denmark Computational Science and Engineering Lab ETH Zürich Switzerland Dept. of Mathematics Biomedical Engineering Chemical Engineering and Materials Science Center for Complex Biological Systems Chao Family Comprehensive Cancer Center UC Irvine United States Institute for Advanced Study TUM Germany

Glioblastoma is a highly invasive brain tumor, whose cells infiltrate surrounding normal brain tissue beyond the lesion outlines visible in the current medical scans. These infiltrative cells are treated mainly by radiotherapy. Existing radiotherapy plans for brain tumors derive from population studies and scarcely account for patient-specific conditions. Here we provide a Bayesian machine learning framework for the rational design of improved, personalized radiotherapy plans using mathematical modeling and patient multimodal medical scans. Our method, for the first time, integrates complementary information from high resolution MRI scans and highly specific FET-PET metabolic maps to infer tumor cell density in glioblastoma patients. The Bayesian framework quantifies imaging and modeling uncertainties and predicts patient-specific tumor cell density with credible intervals. The proposed methodology relies only on data acquired at a single time point and thus is applicable to standard clinical settings. An initial clinical population study shows that the radiotherapy plans generated from the inferred tumor cell infiltration maps spare more healthy tissue thereby reducing radiation toxicity while yielding comparable accuracy with standard radiotherapy protocols. Moreover, the inferred regions of high tumor cell densities coincide with the tumor radioresistant areas, providing guidance for personalized dose-escalation. The proposed integration of multimodal scans and mathematical modeling provides a robust, non-invasive tool to assist personalized radiotherapy design. Copyright © 2018, The Authors. All rights reserved.

关键词： Radiotherapy

Optimal-MDPREF: Novel approach for distributive association rules mining 11

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Optimal-MDPREF: Novel approach for distributive association ...

11th International Conference on Intelligent systems: Theories and Applications, SITA 2016

作者： Mohammed, Mouhir Youssef, Balouki Taoufiq, Gadi Laboratory Informatics Imaging and Modeling of Complex Systems - IIMCS Laboratory Dept. of Mathematics and Computer Sciences FSTS University of Hassan 1 Settat Morocco

ISBN: (纸本)9781509057818

Association Rules is applied on databases - small or big - as a technique to discover useful knowledge with regard to predefined conditions, it is in the core of Data mining and is also used in several fields of business such as insurance, medicine, education.... The algorithms which are used to mine Association Rules, usually generate a huge number of rules. this fact makes them beyond the user's ability to interpret. Prior to this is that the generation process may not in most cases be fast enough to save time and effort. The objective of this contribution empowered by MDPref algorithm is to lessen the number of rules and to make the generation process relatively faster via scaling-distributive approach to make its efficiency better and the runtime shorter. © 2016 IEEE.

关键词： Association rules

Diagonal stability of a class of discrete-time positive switched systems with delay

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arXiv 2017年

作者： Aleksandrov, Alexander Mason, Oliver Faculty of Applied Mathematics and Control Processes Saint Petersburg State University Saint Petersburg199034 Russia Department of Control of Complex Systems ITMO University Saint Petersburg197101 Russia Dept. of Mathematics and Statistics Hamilton Institute Maynooth University Maynooth Co. Kildare Ireland Irish Software Research Centre

A class of discrete-time nonlinear positive time-delay switched systems with sector-type nonlinearities is studied. Sufficient conditions for the existence of common and switched diagonal Lyapunov–Krasovskii functionals for this system class are derived;these are expressed as feasibility conditions for systems of linear algebraic inequalities. Corresponding spectral conditions for the existence of common L–K functionals are also described. Furthermore, it is shown that the proposed approaches can be applied to discrete-time models of digital filters and neural networks. Finally, a numerical example is given to illustrate the effectiveness of theoretical results. Copyright © 2017, The Authors. All rights reserved.

关键词： Digital filters

The sounds of science – A symphony for many instruments and voices

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arXiv 2019年

作者： Alexander, Gerianne Allen, Roland E. Atala, Anthony Bowen, Warwick P. Coley, Alan A. Goodenough, John Katsnelson, Mikhail I. Koonin, Eugene V. Krenn, Mario Madsen, Lars S. Månsson, Martin Mauranyapin, Nicolas P. Melvin, Art I. Rasel, Ernst Reichl, Linda E. Yampolskiy, Roman Yasskin, Philip B. Zeilinger, Anton Lidström, Suzy Department of Psychological and Brain Sciences Texas A&M University College StationTX United States Department of Physics and Astronomy Texas A&M University College StationTX United States Wake Forest Institute for Regenerative Medicine 391 Technology Way Winston-SalemNC27157 United States School of Mathematics and Physics University of Queensland St. Lucia4072 Australia Australian Centre for Engineered Quantum Systems University of Queensland St. Lucia4072 Australia Department of Mathematics and Statistics Dalhousie University HalifaxNSB3H 4R2 Canada Walker Department of Mechanical Engineering Cockrell Institute University of Texas at Austin AustinTX United States Institute for Molecules and Materials Radboud University Nijmegen6525AJ Netherlands National Library of Medicine National Center for Biotechnology Information BethesdaMD20894 United States Austrian Academy of Sciences Boltzmanngasse 3 Vienna1090 Austria Department of Chemistry University of Toronto Toronto Canada Dept. of Applied Physics KTH Royal Institute of Technology Stockholm KistaSE-164 40 Sweden Faculty of Physics University of Vienna Boltzmanngasse 5 Vienna1090 Austria Institut für Quantenoptik Welfengarten 1 Hannover30167 Germany Center for Complex Quantum Systems Department of Physics University of Texas at Austin AustinTX United States Department of Computer Engineering and Computer Science Duthie Center for Engineering University of Louisville LouisvilleKY40292 United States Department of Mathematics Texas A&M University College StationTX United States Department of Physics and Astronomy Texas A&M University College StationTX United States

Sounds of Science is the first movement of a symphony for many (scientific) instruments and voices, united in celebration of the frontiers of science. John Goodenough, the maestro who transformed energy usage and technology through the invention of the lithium-ion battery, opens the programme, reflecting on the ultimate limits of battery technology. This applied theme continues through the subsequent pieces on energy related topics – the sodium-ion battery and artificial fuels, by Martin Månsson – and the ultimate challenge for 3D printing, the eventual production of life, by Anthony Atala. A passage by Gerianne Alexander follows, reflecting on a related issue: How might an artificially produced human being behave? Next comes a consideration of consiousness and free will by Roland Allen and Suzy Lidström. Further voices and new instruments enter as Warwick Bowen, Nicolas Mauranyapin and Lars Madsen discuss whether dynamical processes of single molecules might be observed in their native state. The exploitation of chaos in science and technology, applications of Bose-Einstein condensates and a consideration of the significance of entropy follow in pieces by Linda Reichl, Ernst Rasel and Roland Allen, respectively. Mikhail Katsnelson and Eugene Koonin then discuss the potential generalisation of thermodynamic concepts in the context of biological evolution. Entering with the music of the cosmos, Philip Yasskin discusses whether we might be able to observe torsion in the geometry of the universe. The crescendo comes with the crisis of singularities, their nature and whether they can be resolved through quantum effects, in the composition of Alan Coley. The climax is Mario Krenn, Art Melvin and Anton Zeilinger’s consideration of how computer code can be autonomously surprising and creative. In a harmonious counterpoint – his ‘Guidelines for considering AIs as coauthors’ – Roman Yampolskiy concludes that such code is not yet able to take responsibility for coauthoring a

关键词： Metal ions

26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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On the interplay between social and topical structure

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On the interplay between social and topical structure

7th International AAAI Conference on Weblogs and Social Media, ICWSM 2013

作者： Romero, Daniel M. Tan, Chenhao Ugander, Johan Northwestern Institute on Complex Systems Northwestern University Evanston IL United States Dept. of Computer Science Cornell University Ithaca NY United States Center for Applied Mathematics Cornell University Ithaca NY United States

ISBN: (纸本)9781577356103

People's interests and people's social relationships are intuitively connected, but understanding their interplay and whether they can help predict each other has remained an open question. We examine the interface of two decisive structures forming the backbone of online social media: the graph structure of social networks - who connects with whom - and the set structure of topical affiliations - who is interested in what. In studying this interface, we identify key relationships whereby each of these structures can be understood in terms of the other. The context for our analysis is Twitter, a complex social network of both follower relationships and communication relationships. On Twitter, "hash-tags" are used to label conversation topics, and we examine hashtag usage alongside these social structures. We find that the hashtags that users adopt can predict their social relationships, and also that the social relationships between the initial adopters of a hashtag can predict the future popularity of that hashtag. By studying weighted social relationships, we observe that while strong reciprocated ties are the easiest to predict from hashtag structure, they are also much less useful than weak directed ties for predicting hash-tag popularity. Importantly, we show that computationally simple structural determinants can provide remarkable performance in both tasks. While our analyses focus on Twitter, we view our findings as broadly applicable to topical affiliations and social relationships in a host of diverse contexts, including the movies people watch, the brands people like, or the locations people frequent. Copyright © 2013, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Social networking (online)