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Magnetic-free nonreciprocal photonic platform based on time-modulated graphene capacitors

Physical Review B 2018年第16期98卷 165428-165428页

作者： D. Correas-Serrano A. Alù J. S. Gomez-Diaz Department of Electrical and Computer Engineering University of California Davis One Shields Avenue Kemper Hall 2039 Davis California 95616 USA Photonics Initiative Advanced Science Research Center City University of New York 85 St. Nicholas Terrace New York City New York 10031 USA Physics Program Graduate Center City University of New York New York New York 10016 USA and Department of Electrical Engineering City College of the City University of New York New York New York 10031 USA

We propose a paradigm for the realization of nonreciprocal photonic devices based on time-modulated graphene capacitors coupled to photonic waveguides, without relying on magneto-optic effects. The resulting hybrid graphene-dielectric platform is low loss, silicon compatible, robust against graphene imperfections, scalable from terahertz to near-infrared frequencies, and it exhibits large nonreciprocal responses using realistic biasing schemes. We introduce an analytical framework based on solving the eigenstates of the modulated structure and on spatial coupled mode theory, unveiling the physical mechanisms that enable nonreciprocity and enabling a quick analysis and design of optimal isolator geometries based on synthetic linear and angular momentum bias. Our results, validated through harmonic-balance full-wave simulations, confirm the feasibility of the introduced low-loss (<3 dB) platform to realize large photonic isolation through various mechanisms, such as narrow-band asymmetric band gaps and interband photonic transitions that allow multiple isolation frequencies and large bandwidths. We envision that this technology may pave the wave to magnetic-free, fully integrated, and CMOS–compatible nonreciprocal components with wide applications in photonic networks and thermal management.

关键词： Photonics Plasmonics Graphene Waveguides Lorentz symmetry

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Coherently Enhanced Wireless Power Transfer

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Physical Review Letters 2018年第14期120卷 143901-143901页

作者： Alex Krasnok Denis G. Baranov Andrey Generalov Sergey Li Andrea Alù Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Department of Physics Chalmers University of Technology 412 96 Gothenburg Sweden Moscow Institute of Physics and Technology Dolgoprudny 141700 Russia Department of Electronics and Nanoengineering Aalto University 02150 Espoo Finland ITMO University St. Petersburg 197101 Russia Photonics Initiative Advanced Science Research Center City University of New York New York 10031 USA Physics Program Graduate Center City University of New York New York 10016 USA Department of Electrical Engineering City College of The City University of New York New York 10031 USA

Extraction of electromagnetic energy by an antenna from impinging external radiation is at the basis of wireless communications and wireless power transfer (WPT). The maximum of transferred energy is ensured when the antenna is conjugately matched, i.e., when it is resonant and it has an equal coupling with free space and its load. This condition, however, can be easily affected by changes in the environment, preventing optimal operation of a WPT system. Here, we introduce the concept of coherently enhanced WPT that allows us to bypass this difficulty and achieve dynamic control of power transfer. The approach relies on coherent excitation of the waveguide connected to the antenna load with a backward propagating signal of specific amplitude and phase. This signal creates a suitable interference pattern at the load resulting in a modification of the local wave impedance, which in turn enables conjugate matching and a largely increased amount of extracted energy. We develop a simple theoretical model describing this concept, demonstrate it with full-wave numerical simulations for the canonical example of a dipole antenna, and verify experimentally in both near-field and far-field regimes.

关键词： Electromagnetism engineering Light propagation, transmission & absorption Photonics

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The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

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NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

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Total variation superiorized conjugate gradient method for image reconstruction

arXiv

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arXiv 2017年

作者： Zibetti, Marcelo V. W. Lin, Chuan Herman, Gabor T. Graduate Program in Electrical Engineering and Computer Science Federal University of Technology - Paraná Curitiba80230-901 Brazil School of Electrical Engineering Southwest Jiaotong University Chengdu Sichuan610031 China Department of Computer Science Graduate Center City University of New York New YorkNY10016 United States

The conjugate gradient (CG) method is commonly used for the relatively-rapid solution of least squares problems. In image reconstruction, the problem can be ill-posed and also contaminated by noise;due to this, approaches such as regularization should be utilized. Total variation (TV) is a useful regularization penalty, frequently utilized in image reconstruction for generating images with sharp edges. When a non-quadratic norm is selected for regularization, as is the case for TV, then it is no longer possible to use CG. Nonlinear CG is an alternative, but it does not share the efficiency that CG shows with least squares and methods such as fast iterative shrinkage-thresholding algorithms (FISTA) are preferred for problems with TV norm. A different approach to including prior information is superiorization. In this paper it is shown that the conjugate gradient method can be superiorized. Five different CG variants are proposed, including preconditioned CG. The CG methods superiorized by the total variation norm are presented and their performance in image reconstruction is demonstrated. It is illustrated that some of the proposed variants of the superiorized CG method can produce reconstructions of superior quality to those produced by FISTA and in less computational time, due to the speed of the original CG for least squares problems. In the Appendix we examine the behavior of one of the superiorized CG methods (we call it S-CG);one of its input parameters is a positive number ". It is proved that, for any given " that is greater than the half-squared-residual for the least squares solution, S-CG terminates in a finite number of steps with an output for which the half-squared-residual is less than or equal to ". Importantly, it is also the case that the output will have a lower value of TV than what would be provided by unsuperiorized CG for the same value " of the half-squared residual. Copyright © 2017, The Authors. All rights reserved.

关键词： Conjugate gradient method

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Applying the MVC EA-IRPM to reporting-guidelines in medicine: A strategy that is a web system 4

Applying the MVC EA-IRPM to reporting-guidelines in medicine...

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4th IEEE EMBS international Conference on Biomedical and Health Informatics, BHI 2017

作者： Letouze, Patrick De Souza, J.I.M. Silva, Valeria Martins Climaco, Glaubos Chagas, F.B. Ishihara, Joao Y. Graduate Program of Computational Modeling of Systems Universidade Federal Do Tocantins Quadra 109 Norte Avenida NS-15 Palmas77001-090 Brazil Graduate Program of Systems' Engineering and Computation - PESC Universidade Federal Do Rio de Janeiro Rio de Janeiro Brazil Department of Informatics at the Universidade Federal Do Maranh/ Ao - UFMA Brazil Faculty of Computer Science Faculdade Pitagoras Imperatriz Imperatriz Brazil Faculty of Electrical Engineering Universidade de Brasília Brasília Brazil

ISBN: (纸本)9781509041794

Reporting-Guidelines in Medicine play an important role in promoting the quality of reports in health-related research. For instance, a poorly reported research may induce misinterpretation and inappropriate clinical settings. Basically, three major issues regarding Reporting-Guidelines in Medicine has to be addressed: (1) the existence of lots of reporting guidelines covering a broad spectrum of medical research increases the difficulties when reporting a medical research because it may not be clear which guidelines are applicable, or if all related guidelines are considered;(2) most guideline developers have not described how their guidance was developed, consequently tracking guidelines and features for evaluation, or even for correcting, may be not possible;(3) few guideline developers have evaluated the effectiveness of their guidance, then the real value that the guideline brings to reporting the research is not assured. Hence, we propose a solution to these three issues based on the Model-View-Controller Evolutionary Acquisition Interdisciplinary Research Project Management (MVC EA-IRPM) that is simultaneously a strategy and a web system for the development and management of reporting guidelines. © 2017 IEEE.

关键词： Clinical research

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College 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 Ne

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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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A task-oriented and parameterized (semi) autonomous navigation framework for the development of simulation systems

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Procedia computer science 2017年 112卷 534-543页

作者： Juliana R. Brondani Edison P. de Freitas Luis A.L. Silva Graduate Program in Electrical Engineering Federal University of Rio Grande do Sul Av. Paulo Gama 110 Porto Alegre 90040-060 Brazil Graduate Program in Computer Science Federal University of Santa Maria“ Av. Roraima 1000 Santa Maria 97105-900 Brazil

Agent behaviors in simulation systems are related to fundamental capabilities of realistically developing (semi) autonomous navigation actions. This is particularly important when dealing with the implementation of computer Generated Forces (CGFs) for simulation systems in tactical military training applications. Moreover, these systems take into consideration the particularities of the domain-specific simulation tasks and the numerous heterogeneous CGFs inserted on them in order to generate better knowledge and learning experience to simulation system users. Based on these reasons, this paper reviews recurrent navigation problems as to propose a task-oriented and parameterized (semi) autonomous navigation framework to deal with CGF navigation needs in military simulation. Combining global and local navigation techniques, and controlled transition between alternative degrees of navigation autonomy, the framework aims to overcome the challenges of implementing customizable CGF navigation behaviors and, at the same time, to allow interaction with both users and other simulation systems in distributed simulation settings. A case study is presented in which the proposed techniques are analyzed in a domain-specific simulation problem providing evidence of their suitability to address the studied military simulation problems.

关键词： Navigation problems task-oriented navigation semi-autonomous algorithms simulation systems

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Streaming k-means clustering with fast queries

arXiv

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arXiv 2017年

作者： Zhang, Yu Tangwongsan, Kanat Tirthapura, Srikanta Department of Electrical and Computer Engineering Iowa State University AmesIA50011 United States Compute Science Program Mahidol University International College Thailand Department of Electrical and Computer Engineering Iowa State University AmesIA50011 United States

We present methods for k-means clustering on a stream with a focus on providing fast responses to clustering queries. Compared to the current state-of-the-art, our methods provide substantial improvement in the query time for cluster centers while retaining the desirable properties of provably small approximation error and low space usage. Our algorithms rely on a novel idea of "coreset caching" that systematically reuses coresets (summaries of data) computed for recent queries in answering the current clustering query. We present both theoretical analysis and detailed experiments demonstrating their correctness and efficiency. Copyright © 2017, The Authors. All rights reserved.

关键词： Machine learning

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A Hyper-Heuristic in MOEA/D-DRA Using the Upper Confidence Bound Technique

A Hyper-Heuristic in MOEA/D-DRA Using the Upper Confidence B...

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Brazilian Conference on Intelligent Systems (BRACIS)

作者： Lucas Prestes Myriam Regattieri de Biase da Silva Delgado Richard Aderbal Goncalves Carolina Paula de Almeida Aurora Trinidad Pozo Universidade Tecnologica Federal do Parana Curitiba PR BR Graduate Program in Electrical and Computer Engineering UTFPR Universidade Estadual do Centro-Oeste Guarapuava PR BR Computer Science Department UNICENTRO Computer Science Department UFPR

The Multi-Objective Evolutionary Algorithm based on Decomposition with Dynamical Resource Allocation (MOEA/D-DRA) has obtained very good results on various multi-objective optimization problems in the past few years. This paper focuses on an attempt to improve even more its performance by introducing a hyper-heuristic mechanism to select the best set of its operators and parameters. In this paper we use Upper Confidence Bound (UCB) as the basis of the hyper-heuristic, and test three versions of the proposed approach. Four well known benchmarks (CEC 2009, WFG, DTLZ and ZDT) and a quality indicator (hypervolume) are used to analyze the performance of the three variants. The proposed approach is compared with the original MOEA/D-DRA and the results show that tuning the parameters via UCB is an interesting alternative for a hyper-heuristic based version of MOEA/D-DRA on the addressed problems.

关键词： Optimization Sociology Statistics Evolutionary computation Benchmark testing Resource management Approximation algorithms

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