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arXiv 2020年

作者： van Viegen, Tara Akrami, Athena Bonnen, Kate DeWitt, Eric Hyafil, Alexandre Ledmyr, Helena Lindsay, Grace W. Mineault, Patrick Murray, John D. Pitkow, Xaq Puce, Aina Sedigh-Sarvestani, Madineh Stringer, Carsen Achakulvisut, Titipat Alikarami, Elnaz Atay, Melvin Selim Batty, Eleanor Erlich, Jeffrey C. Galbraith, Byron V. Guo, Yueqi Juavinett, Ashley L. Krause, Matthew R. Li, Songting Pachitariu, Marius Straley, Elizabeth Valeriani, Davide Vaughan, Emma Vaziri-Pashkam, Maryam Waskom, Michael L. Blohm, Gunnar Kording, Konrad Schrater, Paul Wyble, Brad Escola, Sean Peters, Megan A.K. Princeton Neuroscience Institute Princeton University PrincetonNJ United States Sainsbury Wellcome Centre University College London London United Kingdom Center for Neural Science New York University New York CityNY United States Champalimaud Research Champalimaud Foundation Lisbon Portugal Centre de Recerca Matemàtica Bellaterra Universitat Autònoma de Barcelona Barcelona Spain International Neuroinformatics Coordinating Facility Sweden Gatsby Computational Neuroscience Unit Sainsbury Wellcome Centre University College London London United Kingdom Department of Psychiatry Yale University New HavenCT United States Baylor College of Medicine Dept. of Neuroscience HoustonTX United States Baylor College of Medicine Center for Neuroscience and Artificial Intelligence HoustonTX United States Rice University Dept of Electrical and Computer Engineering HoustonTX United States Psychological & Brain Sciences Indiana University BloomingtonIN United States Max Planck Florida Institute for Neuroscience JupiterFL United States HHMI Janelia Research Campus AshburnVA United States University of Pennsylvania Dept of Neuroscience and Bioengineering PhiladelphiaPA United States Faculty of dentistry McGill University MontrealQB Canada Middle East Technical University Ankara Turkey Department of Neurobiology Harvard University CambridgeMA United States New York University Shanghai Shanghai China Talla Inc BostonMA United States Johns Hopkins University Department of Biomedical Engineering BaltimoreMD United States Division of Biological Sciences UC San Diego San diegoCA United States Montreal Neurological Institute McGill University MontrealQB Canada School of Mathematical Sciences MOE-LSC Institute of Natural Sciences Shanghai Jiao Tong University Shanghai China Department of Otolaryngology - Head & Neck Surgery Massachusetts Eye and Ear BostonMA United States Department of Otolaryngology - Head & Neck Surgery Harvard Medical School BostonM

Neuromatch Academy designed and ran a fully online 3-week computational Neuroscience summer school for 1757 students with 191 teaching assistants working in virtual inverted (or flipped) classrooms and on small group projects. Fourteen languages, active community management, and low cost allowed for an unprecedented level of inclusivity and universal accessibility. © 2020, CC BY.

关键词： Python

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Broadband unidirectional reflectionless aperiodic multilayer structure

Broadband unidirectional reflectionless aperiodic multilayer...

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Frontiers in Optics, FiO 2017

作者： You, Chenglong Matyas, Corey T. Huang, Yin Dowling, Jonathan P. Veronis, Georgios Hearne Institute for Theoretical Physics Department of Physics and Astronomy Louisiana State University Baton RougeLA70803 United States School of Electrical Engineering and Computer Science Louisiana State University Baton RougeLA70803 United States Department of Optoelectrics Information Science and Engineering School of Physics and Electronics Central South University Changsha Hunan410012 China Key Laboratory of Optoelectronic Devices and Systems Ministry of Education Shenzhen University Shenzhen Guangdong Province518060 China Center for Computation and Technology Louisiana State University Baton RougeLA70803 United States

We design non-parity-time-symmetric multilayer structures, one of which consists of alternating silicon and silica layers, while the other one includes a gain material. Our structures can achieve broadband unidirectio... 详细信息

ISBN: (纸本)9781943580330

关键词： Silica

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Joint product numerical range and geometry of reduced density matrices

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science China(Physics,Mechanics & Astronomy) 2017年第2期60卷 9-17页

作者： Jianxin Chen Cheng Guo Zhengfeng Ji Yiu-Tung Poon Nengkun YU Bei Zeng Jie Zhou Joint Center for Quantum Information and Computer Science University of Maryland College Park 20740 USA Institute for Advanced Study Tsinghua University Beijing 100084 China Centre for Quantum Computation ＆ Intelligent Systems School of Software Faculty of Engineering and Information Technology University of Technology Sydney Sydney 2007 Australia State Key Laboratory of Computer Science.Institute of Software Chinese Academy of Sciences Beijing 100084 China Department of Mathematics Iowa State University Ames 50011-2140 USA Institute for Quantum Computing University of Waterloo Waterloo N2L 3G1 Canada Department of Mathematics ＆ Statistics University of Guelph Guelph N1G 2 W1 Canada Perimeter Institute for Theoretical Physics Waterloo N2L 2Y5 Canada

The reduced density matrices of a many-body quantum system form a convex set, whose three-dimensional projection is convex in R3. The boundary of may exhibit nontrivial geometry, in particular ruled surfaces. Two physical mechanisms are known for the origins of ruled surfaces： symmetry breaking and gapless. In this work, we study the emergence of ruled surfaces for systems with local Hamiltonians in infinite spatial dimension, where the reduced density matrices are known to be separable as a consequence of the quantum de Finetti＇s theorem. This allows us to identify the reduced density matrix geometry with joint product numerical range II of the Hamiltonian interaction terms. We focus on the case where the interaction terms have certain structures, such that a ruled surface emerges naturally when taking a convex hull of ∏. We show that, a ruled surface on sitting in ∏ has a gapless origin, otherwise it has a symmetry breaking origin. As an example, we demonstrate that a famous ruled surface, known as the oloid, is a possible shape of , with two boundary pieces of symmetry breaking origin separated by two gapless lines.

关键词： reduced density matrices quantum tomography numerical range quantum information oloid ruled surface

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Microsphere Embedded in Cantilever Opens the AFM to High Resolution Optical Microscopy

Microsphere Embedded in Cantilever Opens the AFM to High Res...

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Conference on Lasers and Electro-Optics Europe

作者： Francesco Tantussi Marti Duocastella Ali Haddadapour Remo Proietti Zaccaria Andrea Jacassi Georgios Veronis Alberto Diaspro Francesco De Angelis Istituto Italiano di Tecnologia Via Morego 30 16063 Genoa Italy School of Electrical Engineering and Computer Science Center for Computation and Technology (CCT) Louisiana State University Baton Rouge LA 70803 USA Center for Computation and Technology Louisiana State University Baton Rouge Louisiana 70803 USA.

ISBN: (纸本)9781509067374

The combination of the AFM technique and the sphere-mediated microscopy (SMM) [1] opens a new opportunity to the Atomic Force Microscopy (AFM). With the help of a tipless AFM cantilever is possible to place and scan a microspheres (MS) close to the surface. From the optical point of view, when a MS is close to a surface act as high NA nanolenses whose optical characteristics define the maximum attainable resolution.

关键词： Atomic force microscopy Diffraction limit Modulation transfer function Optical microscopy Spatial frequency Spatial resolution

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Personalization of learning paths in online communities of creators 9

Personalization of learning paths in online communities of c...

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9th International Conference on Educational Data Mining, EDM 2016

作者： Sun, Mingxuan Yang, Seungwon Division of Computer Science and Engineering Louisiana State University United States School of Library and Information Science Center for Computation and Technology Louisiana State University United States

In massive online communities of creators (OCOCs), one of the core challenges is to encourage users to learn to create original contents using basic components. Recommending the right learning components at the right time is critical for improving user engagement and has not been fully studied due to the unstructured nature of online communities. To address the problem, we propose in this paper a novel recommendation model which integrates Cox’s survival analysis and collaborative filtering. Our model can incorporate factors such as user learning history and social engagements, which provides us insights in improving the personalized service. We apply our method to the user data from Scratch online platform and demonstrate the performance of the model. © 2016 International Educational Data Mining Society. All rights reserved.

关键词： Collaborative filtering

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Author Correction: National identity predicts public health support during a global pandemic

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Nature communications 2022年第1期13卷 1949页

作者： Jay J Van Bavel Aleksandra Cichocka Valerio Capraro Hallgeir Sjåstad John B Nezlek Tomislav Pavlović Mark Alfano Michele J Gelfand Flavio Azevedo Michèle D Birtel Aleksandra Cislak Patricia L Lockwood Robert Malcolm Ross Koen Abts Elena Agadullina John Jamir Benzon Aruta Sahba Nomvula Besharati Alexander Bor Becky L Choma Charles David Crabtree William A Cunningham Koustav De Waqas Ejaz Christian T Elbaek Andrej Findor Daniel Flichtentrei Renata Franc Biljana Gjoneska June Gruber Estrella Gualda Yusaku Horiuchi Toan Luu Duc Huynh Agustin Ibanez Mostak Ahamed Imran Jacob Israelashvili Katarzyna Jasko Jaroslaw Kantorowicz Elena Kantorowicz-Reznichenko André Krouwel Michael Laakasuo Claus Lamm Caroline Leygue Ming-Jen Lin Mohammad Sabbir Mansoor Antoine Marie Lewend Mayiwar Honorata Mazepus Cillian McHugh John Paul Minda Panagiotis Mitkidis Andreas Olsson Tobias Otterbring Dominic J Packer Anat Perry Michael Bang Petersen Arathy Puthillam Julián C Riaño-Moreno Tobias Rothmund Hernando Santamaría-García Petra C Schmid Drozdstoy Stoyanov Shruti Tewari Bojan Todosijević Manos Tsakiris Hans H Tung Radu G Umbreș Edmunds Vanags Madalina Vlasceanu Andrew Vonasch Meltem Yucel Yucheng Zhang Mohcine Abad Eli Adler Narin Akrawi Hamza Alaoui Mdarhri Hanane Amara David M Amodio Benedict G Antazo Matthew Apps F Ceren Ay Mouhamadou Hady Ba Sergio Barbosa Brock Bastian Anton Berg Maria P Bernal-Zárate Michael Bernstein Michał Białek Ennio Bilancini Natalia Bogatyreva Leonardo Boncinelli Jonathan E Booth Sylvie Borau Ondrej Buchel C Daryl Cameron Chrissie F Carvalho Tatiana Celadin Chiara Cerami Hom Nath Chalise Xiaojun Cheng Luca Cian Kate Cockcroft Jane Conway Mateo Andres Córdoba-Delgado Chiara Crespi Marie Crouzevialle Jo Cutler Marzena Cypryańska Justyna Dabrowska Michael A Daniels Victoria H Davis Pamala N Dayley Sylvain Delouvee Ognjan Denkovski Guillaume Dezecache Nathan A Dhaliwal Alelie B Diato Roberto Di Paolo Marianna Drosinou Uwe Dulleck Jānis Ekmanis Arhan S Ertan Tom W Etienne Hapsa Hossain Farhana Fahima Farkhari Har Department of Psychology and Neural Science New York University New York NY USA. jay.vanbavel@nyu.edu. School of Psychology University of Kent Canterbury England. Department of Economics Middlesex University London London England. Department of Strategy and Management Norwegian School of Economics Bergen Norway. SWPS University of Social Sciences and Humanities Poznań Poland. Department of Psychological Sciences College of William and Mary Williamsburg VA USA. Institute of Social Sciences Ivo Pilar Zagreb Croatia. Department of Philosophy Macquarie University Sydney NSW Australia. Stanford Graduate School of Business Stanford University Stanford CA USA. Institute of Communication Science Friedrich-Schiller University Jena Jena Germany. flavio.azevedo@uni-jena.de. School of Human Sciences Institute for Lifecourse Development University of Greenwich London England. Department of Experimental Psychology University of Oxford Oxford England. Center for Human Brain Health School of Psychology University of Birmingham Birmingham England. Department of Psychology Macquarie University Sydney NSW Australia. KU Leuven Leuven Belgium. National Research University Higher School of Economics (HSE) Moscow Russia. De La Salle University Manila Philippines. Department of Psychology University of the Witwatersrand Johannesburg South Africa. Department of Political Science Aarhus University Aarhus Denmark. X University Toronto ON Canada. Department of Government Dartmouth College Hanover NH USA. Department of Psychology University of Toronto Toronto ON Canada. Gatton College of Business and Economics University of Kentucky Lexington KY USA. Department of Mass Communication National University of Science and Technology (NUST) Islamabad Pakistan. Department of Management Aarhus University Aarhus Denmark. Faculty of Social and Economic Sciences Comenius University Bratislava Slovakia. IntraMed Buenos Aires Argentina. Macedonian Academy of Sciences and

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Correction: Improving Nutrition and Activity Behaviors Using Digital Technology and Tailored Feedback: Protocol for the Tailored Diet and Activity (ToDAy) Randomized Controlled Trial

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JMIR research protocols 2020年第12期9卷 e25940页

作者： Rhiannon E Halse Charlene L Shoneye Christina M Pollard Jonine Jancey Jane A Scott Iain S Pratt Satvinder S Dhaliwal Richard Norman Leon M Straker Carol J Boushey Edward J Delp Fengqing Zhu Amelia J Harray Maria A Szybiak Anne Finch Joanne A McVeigh Barbara Mullan Clare E Collins Syed Aqif Mukhtar Kieran N Edwards Janelle D Healy Deborah A Kerr School of Public Health Curtin University Perth Western Australia Australia. East Metropolitan Health Service Perth Western Australia Australia. Cancer Council WA Perth Western Australia Australia. Health Psychology & Behavioural Medicine Research Group School of Psychology Curtin University Perth Western Australia Australia. School of Physiotherapy and Exercise Science Curtin University Perth Western Australia Australia. Cancer Epidemiology Program University of Hawaii Cancer Center Honolulu HI United States. Department of Nutrition Purdue University West Lafayette IN United States. School of Electrical and Computer Engineering Purdue University West Lafayette IN United States. School of Occupational Therapy Speech Therapy & Social Work Curtin University Perth Western Australia Australia. Movement Physiology Laboratory University of Witwatersrand Johannesburg South Africa. School of Health Sciences Faculty of Health and Medicine University of Newcastle Callaghan New South Wales Australia. Priority Research Centre in Physical Activity and Nutrition University of Newcastle Callaghan New South Wales Australia. Curtin Institute of Computation Curtin University Perth Western Australia Australia.

[This corrects the article DOI: 10.2196/12782.].

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Enhanced photothermal cooling of nanowires

arXiv

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arXiv 2017年

作者： Guccione, G. Hosseini, M. Mirzaei, A. Slatyer, H.J. Buchler, B.C. Lam, P.K. Centre for Quantum Computation and Communication Technology Department of Quantum Science Research School of Physics and Engineering Australian National University CanberraACT2601 Australia Birck Nanotechnology Center School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States Nonlinear Physics Centre Research School of Physics and Engineering Australian National University CanberraACT2601 Australia

We investigate the optomechanical interaction between light and metallic nanowires through the action of bolometric forces. We show that the response time of the photothermal forces induced on the nanowire is fast and the strength of the interaction can overcome the radiation pressure force. Furthermore, we suggest the photothermal forces can be enhanced by surface plasmon excitation to cool the sub-megahertz vibrational modes of the nanowires close to its quantum limit. Copyright © 2017, The Authors. All rights reserved.

关键词： Nanowires

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An efficient npn boolean matching algorithm based on structural signature and shannon expansion

arXiv

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arXiv 2017年

作者： Zhang, Juling Yang, Guowu Hung, William N.N. Zhang, Yan Wu, Jinzhao Big Data Research Center School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Synopsys Inc. Mountain ViewCA United States Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis Guangxi University for Nationalities Nanning530006 China

An efficient pairwise Boolean matching algorithm for solving the problem of matching single-output specified Boolean functions under input negation and/or input permutation and/or output negation (NPN) is proposed in this paper. We present the structural signature (SS) vector, which comprises a first-order signature value, two symmetry marks, and a group mark. As a necessary condition for NPN Boolean matching, the SS is more effective than the traditional signature. Two Boolean functions, f and g, may be equivalent when they have the same SS vector. A symmetry mark can distinguish symmetric variables and asymmetric variables and be used to search for multiple variable mappings in a single variable-mapping search operation, which reduces the search space significantly. Updating the SS vector via Shannon decomposition provides benefits in distinguishing unidentified variables, and the group mark and phase collision check can be used to discover incorrect variable mappings quickly, which also speeds up the NPN Boolean matching process. Using the algorithm proposed in this paper, we test both equivalent and non-equivalent matching speeds on the MCNC benchmark circuit sets and random circuit sets. In the experiment, our algorithm is shown to be 4.2 times faster than competitors when testing equivalent circuits and 172 times faster, on average, when testing non-equivalent circuits. The experimental results show that our approach is highly effective at solving the NPN Boolean matching problem. Copyright © 2017, The Authors. All rights reserved.

关键词： Mapping

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A canonical-based NPN boolean matching algorithm utilizing boolean difference and cofactor signature

arXiv

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arXiv 2017年

作者： Zhang, Juling Yang, Guowu Hung, W.N.N. Wu, Jinzhao Big Data Research Center School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Synopsys Inc. Mountain ViewCA United States Guangxi Key Laboratory of Hybrid Computation IC Design Analysis Guangxi University for Nationalities Nanning530006 China

This paper presents a new compact canonical-based algorithm to solve the problem of single-output completely specified NPN Boolean matching. We propose a new signature vector Boolean difference and cofactor (DC) signature vector. Our algorithm utilizes the Boolean difference, cofactor signature and symmetry properties to search for canonical transformations. The use of symmetry and Boolean difference notably reduces the search space and speeds up the Boolean matching process compared to the algorithm proposed in [1]. We tested our algorithm on a large number of circuits. The experimental results showed that the average runtime of our algorithm 37% higher and its average search space 67% smaller compared to [1] when tested on general circuits. Copyright © 2017, The Authors. All rights reserved.

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