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5th International Conference on Variable Neighborhood Search (ICVNS'17)

Electronic Notes in Discrete Mathematics 2018年 66卷 1-5页

作者： Vitor Nazário Coelho Haroldo Gambini Santos Igor Machado Coelho Puca Huachi Vaz Penna Thays A. Oliveira Marcone Jamilson Freitas Souza Angelo Sifaleras Institute of Computer Science Universidade Federal Fluminense Niterói Brazil Grupo da Causa Humana Ouro Preto Brazil Department of Computing Universidade Federal de Ouro Preto Ouro Preto Brazil Institute of Mathematics Statitics Universidade Estadual do Rio de Janeiro Rio de Janeiro Brazil Graduate Program of the Department of Engineering and Information and Communication Technologies Universitat Pompeu Fabra Barcelona Spain Department of Applied Informatics School of Information Sciences University of Macedonia 156 Egnatia Str. Thessaloniki 54636 Greece

This volume presents selected, peer-reviewed, short papers that were accepted for presentation in the 5th International Conference on Variable Neighborhood Search (ICVNS'17) which was held in Ouro Preto, Brazil, d... 详细信息

关键词： Metaheuristics Variable Neighborhood Search Discrete Optimization Nonlinear optimization

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Corrigendum to "Monastrol suppresses invasion and metastasis in human colorectal cancer cells by targeting fascin independent of kinesin-Eg5 pathway" [Biomed. Pharmacother. 175 (2024) 116785]

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Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie 2024年 179卷 117411页

作者： Begoña Alburquerque-González Silvia Montoro-García Ángel Bernabé-García Manuel Bernabé-García Priscila Campioni-Rodrigues Alejandro Rodríguez-Martínez Irene Luque Tuula Salo Alfonso Pérez-Garrido Horacio Pérez-Sánchez María Luisa Cayuela Ginés Luengo-Gil Enrico Luchinat Fatima Postigo-Corrales Tommaso Staderini Francisco José Nicolás Pablo Conesa-Zamora Health Sciences Faculty Universidad Católica de Murcia (UCAM) Guadalupe Spain. Regeneración Oncología Molecular y TGF-ß. IMIB-Arrixaca Carretera Madrid-Cartagena El Palmar 30120 Spain. Research group "Telomerasa Envejecimiento y Cáncer" CIBERER Hospital Clínico Universitario Virgen de la Arrixaca IMIB-Arrixaca Murcia Spain. ECM and Hypoxia research unit Faculty of Biochemistry and Molecular Medicine University of Oulu Aapistie 7C Oulu FI-90014 Finland Microelectronic Research Unit Faculty of Information Technology and Electrical Engineering University of Oulu Oulu FI-90570 Finland. Department of Physical Chemistry Institute of Biotechnology and Excellence Unit in Chemistry Applied to Biomedicine and Environment School of Sciences University of Granada Granada 18071 Spain Structural Bioinformatics and High-Performance Computing (BIO-HPC) Research Group Universidad Católica de Murcia (UCAM) Guadalupe Spain. Department of Physical Chemistry Institute of Biotechnology and Excellence Unit in Chemistry Applied to Biomedicine and Environment School of Sciences University of Granada Granada 18071 Spain. Oral Medicine and Pathology Research Unit of Population Health University of Oulu Finland Medical Research Center and Oulu University Hospital Aapistie 3 Oulu FI-90220 Finland Department of Oral and Maxillofacial Diseases University of Helsinki Haartmaninkatu 8 Helsinki FI-0014 Finland Translational Immunology Research Program (TRIMM) and iCAN Digital Precision Cancer Medicine Flagship University of Helsinki Finland Department of Pathology Helsinki University Hospital Helsinki Finland. Health Sciences Faculty Universidad Católica de Murcia (UCAM) Guadalupe Spain Pathology and Clinical Analysis Department Group of Molecular Pathology and Pharmacogenetics Instituto Murciano de Investigación Biosanitaria (IMIB) Hospital Universitario Santa Lucía Cartagena Spain. CERM - Magnetic Resonance Center and Dipartimento di Chimica Università degli Studi di Firenze Via Luigi

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The FANTOM5 collection, a data series underpinning mammalian transcriptome atlases in diverse cell types

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Scientific Data 2017年第1期4卷 170113页

作者： Kawaji, Hideya Kasukawa, Takeya Forrest, Alistair Carninci, Piero Hayashizaki, Yoshihide RIKEN Preventive Medicine and Diagnosis Innovation Program Wako Saitama 351-0198 Japan RIKEN Advanced Center for Computing and Communication Preventive Medicine and Applied Genomics Unit Yokohama Kanagawa 230-0045 Japan RIKEN Center for Life Science Technologies Division of Genomic Technologies Yokohama City Kanagawa 230-0045 Japan RIKEN Omics Science Center Yokohama City Kanagawa 230-0045 Japan Harry Perkins Institute of Medical Research Nedlands 6009 WA Australia

The latest project from the FANTOM consortium, an international collaborative effort initiated by RIKEN, generated atlases of transcriptomes, in particular promoters, transcribed enhancers, and long-noncoding RNAs, across a diverse set of mammalian cell types. Here, we introduce the FANTOM5 collection, bringing together data descriptors, articles and analyses of FANTOM5 data published across the Nature Research journals. Associated data are openly available for reuse by all. © 2017 The Author(s).

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Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator

arXiv

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arXiv 2017年

作者： Li, Qianxiao Dietrich, Felix Bollt, Erik M. Kevrekidis, Ioannis G. Institute of High Performance Computing Singapore Singapore Faculty of Mathematics Technical University of Munich Germany Department of Mathematics Clarkson University United States Department of Chemical and Biological Engineering Program in Applied and Computational Mathematics Princeton University United States

Numerical approximation methods for the Koopman operator have advanced considerably in the last few years. In particular, data-driven approaches such as dynamic mode decomposition (DMD) and its generalization, the extended-DMD (EDMD), are becoming increasingly popular in practical applications. The EDMD improves upon the classical DMD by the inclusion of a flexible choice of dictionary of observables that spans a finite dimensional subspace on which the Koopman operator can be approximated. This enhances the accuracy of the solution reconstruction and broadens the applicability of the Koopman formalism. Although the convergence of the EDMD has been established, applying the method in practice requires a careful choice of the observables to improve convergence with just a finite number of terms. This is especially difficult for high dimensional and highly nonlinear systems. In this paper, we employ ideas from machine learning to improve upon the EDMD method. We develop an iterative approximation algorithm which couples the EDMD with a trainable dictionary represented by an artificial neural network. Using the Duffing oscillator and the Kuramoto Sivashinsky PDE as examples, we show that our algorithm can effectively and efficiently adapt the trainable dictionary to the problem at hand to achieve good reconstruction accuracy without the need to choose a fixed dictionary a priori. Furthermore, to obtain a given accuracy we require fewer dictionary terms than EDMD with fixed dictionaries. This alleviates an important shortcoming of the EDMD algorithm and enhances the applicability of the Koopman framework to practical problems. Copyright © 2017, The Authors. All rights reserved.

关键词： Machine learning

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Search for Gamma-Ray Spectral Lines from Dark Matter Annihilation up to 100 TeV toward the Galactic Center with MAGIC

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Physical Review Letters 2023年第6期130卷 061002-061002页

作者： H. Abe S. Abe V. A. Acciari T. Aniello S. Ansoldi L. A. Antonelli A. Arbet Engels C. Arcaro M. Artero K. Asano D. Baack A. Babić A. Baquero U. Barres de Almeida J. A. Barrio I. Batković J. Baxter J. Becerra González W. Bednarek E. Bernardini M. Bernardos A. Berti J. Besenrieder W. Bhattacharyya C. Bigongiari A. Biland O. Blanch G. Bonnoli Ž. Bošnjak I. Burelli G. Busetto R. Carosi M. Carretero-Castrillo G. Ceribella Y. Chai A. Chilingarian S. Cikota E. Colombo J. L. Contreras J. Cortina S. Covino G. D’Amico V. D’Elia P. Da Vela F. Dazzi A. De Angelis B. De Lotto A. Del Popolo M. Delfino J. Delgado C. Delgado Mendez D. Depaoli F. Di Pierro L. Di Venere E. Do Souto Espiñeira D. Dominis Prester A. Donini D. Dorner M. Doro D. Elsaesser G. Emery V. Fallah Ramazani L. Fariña A. Fattorini L. Font C. Fruck S. Fukami Y. Fukazawa R. J. García López M. Garczarczyk S. Gasparyan M. Gaug J. G. Giesbrecht Paiva N. Giglietto F. Giordano P. Gliwny N. Godinović J. G. Green D. Green D. Hadasch A. Hahn T. Hassan L. Heckmann J. Herrera D. Hrupec M. Hütten R. Imazawa T. Inada R. Iotov K. Ishio I. Jiménez Martínez J. Jormanainen D. Kerszberg Y. Kobayashi H. Kubo J. Kushida A. Lamastra D. Lelas F. Leone E. Lindfors L. Linhoff S. Lombardi F. Longo R. López-Coto M. López-Moya A. López-Oramas S. Loporchio A. Lorini E. Lyard B. Machado de Oliveira Fraga P. Majumdar M. Makariev G. Maneva N. Mang M. Manganaro S. Mangano K. Mannheim M. Mariotti M. Martínez A. Mas Aguilar D. Mazin S. Menchiari S. Mender S. Mićanović D. Miceli T. Miener J. M. Miranda R. Mirzoyan E. Molina H. A. Mondal A. Moralejo D. Morcuende V. Moreno T. Nakamori C. Nanci L. Nava V. Neustroev M. Nievas Rosillo C. Nigro K. Nilsson K. Nishijima T. Njoh Ekoume K. Noda S. Nozaki Y. Ohtani T. Oka J. Otero-Santos S. Paiano M. Palatiello D. Paneque R. Paoletti J. M. Paredes L. Pavletić M. Persic M. Pihet F. Podobnik P. G. Prada Moroni E. Prandini G. Principe C. Priyadarshi I. Puljak W. Rhode M. Ribó J. Rico C. Righi A. Rugliancich N. Sahakyan T. Saito S. Sakurai K. Satalecka F. G. Sat Japanese MAGIC Group: Institute for Cosmic Ray Research (ICRR) The University of Tokyo Kashiwa 277-8582 Chiba Japan Instituto de Astrofísica de Canarias and Departamento de Astrofísica Universidad de La Laguna E-38200 La Laguna Tenerife Spain National Institute for Astrophysics (INAF) I-00136 Rome Italy Università di Udine and INFN Trieste I-33100 Udine Italy Max-Planck-Institut für Physik D-80805 München Germany Università di Padova and INFN I-35131 Padova Italy Institut de Física d’Altes Energies (IFAE) The Barcelona Institute of Science and Technology (BIST) E-08193 Bellaterra (Barcelona) Spain Technische Universität Dortmund D-44221 Dortmund Germany Croatian MAGIC Group: University of Zagreb Faculty of Electrical Engineering and Computing (FER) 10000 Zagreb Croatia IPARCOS Institute and EMFTEL Department Universidad Complutense de Madrid E-28040 Madrid Spain Centro Brasileiro de Pesquisas Físicas (CBPF) 22290-180 URCA Rio de Janeiro (RJ) Brazil University of Lodz Faculty of Physics and Applied Informatics Department of Astrophysics 90-236 Lodz Poland Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n 18008 Granada Spain Deutsches Elektronen-Synchrotron (DESY) D-15738 Zeuthen Germany ETH Zürich CH-8093 Zürich Switzerland Università di Pisa and INFN Pisa I-56126 Pisa Italy Universitat de Barcelona ICCUB IEEC-UB E-08028 Barcelona Spain Armenian MAGIC Group: A. Alikhanyan National Science Laboratory 0036 Yerevan Armenia Centro de Investigaciones Energéticas Medioambientales y Tecnológicas E-28040 Madrid Spain Department for Physics and Technology University of Bergen Norway INFN MAGIC Group: INFN Sezione di Catania and Dipartimento di Fisica e Astronomia University of Catania I-95123 Catania Italy INFN MAGIC Group: INFN Sezione di Torino and Università degli Studi di Torino I-10125 Torino Italy INFN MAGIC Group: INFN Sezione di Bari and Dipartimento Interateneo di Fisica dell’Università e del Politecnico di Bari I-70125 Bari Italy

Linelike features in TeV γ rays constitute a “smoking gun” for TeV-scale particle dark matter and new physics. Probing the Galactic Center region with ground-based Cherenkov telescopes enables the search for TeV spectral features in immediate association with a dense dark matter reservoir at a sensitivity out of reach for satellite γ-ray detectors, and direct detection and collider experiments. We report on 223 hours of observations of the Galactic Center region with the MAGIC stereoscopic telescope system reaching γ-ray energies up to 100 TeV. We improved the sensitivity to spectral lines at high energies using large-zenith-angle observations and a novel background modeling method within a maximum-likelihood analysis in the energy domain. No linelike spectral feature is found in our analysis. Therefore, we constrain the cross section for dark matter annihilation into two photons to ⟨σv⟩≲5×10−28 cm3 s−1 at 1 TeV and ⟨σv⟩≲1×10−25 cm3 s−1 at 100 TeV, achieving the best limits to date for a dark matter mass above 20 TeV and a cuspy dark matter profile at the Galactic Center. Finally, we use the derived limits for both cuspy and cored dark matter profiles to constrain supersymmetric wino models.

关键词： Dark matter Gamma ray astronomy Particle dark matter Milky Way Cosmic ray & astroparticle detectors Cosmic rays & astroparticles Electromagnetic radiation astronomy Telescopes

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Author Correction: The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci

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Nature computational science 2023年第7期3卷 658页

作者： Gengjie Jia Yu Li Xue Zhong Kanix Wang Milton Pividori Rabab Alomairy Aniello Esposito Hatem Ltaief Chikashi Terao Masato Akiyama Koichi Matsuda David E Keyes Hae Kyung Im Takashi Gojobori Yoichiro Kamatani Michiaki Kubo Nancy J Cox James Evans Xin Gao Andrey Rzhetsky Shenzhen Branch Guangdong Laboratory of Lingnan Modern Agriculture Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China. jiagengjie@***. Computational Bioscience Research Center King Abdullah University of Science and Technology Thuwal Saudi Arabia. Computer Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong People's Republic of China. Department of Medicine and Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville TN US. Department of Medicine Institute of Genomics and Systems Biology Committee on Genomics Genetics and Systems Biology University of Chicago Chicago IL US. Department of Operations Business Analytics and Information Systems University of Cincinnati Cincinnati OH US. Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania Philadelphia PA US. Extreme Computing Research Center Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia. HPE HPC/AI EMEA Research Laboratory Bristol UK. RIKEN Center for Integrative Medical Sciences Yokohama Japan. Clinical Research Center Shizuoka General Hospital Shizuoka Japan. Department of Applied Genetics The School of Pharmaceutical Sciences University of Shizuoka Shizuoka Japan. Department of Ophthalmology Graduate School of Medical Sciences Kyushu University Fukuoka Japan. Department of Computational Biology and Medical Sciences Graduate School of Frontier Sciences The University of Tokyo Tokyo Japan. Biological and Environmenta

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Building a quantum engineering undergraduate program

arXiv

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arXiv 2021年

作者： Asfaw, Abraham Blais, Alexandre Brown, Kenneth R. Candelaria, Jonathan Cantwell, Christopher Carr, Lincoln D. Combes, Joshua Debroy, Dripto M. Donohue, John M. Economou, Sophia E. Edwards, Emily Fox, Michael F.J. Girvin, Steven M. Ho, Alan Hurst, Hilary M. Jacob, Zubin Johnson, Blake R. Johnston-Halperin, Ezekiel Joynt, Robert Kapit, Eliot Klein-Seetharaman, Judith Laforest, Martin Lewandowski, H.J. Lynn, Theresa W. McRae, Corey Rae H. Merzbacher, Celia Michalakis, Spyridon Narang, Prineha Oliver, William D. Palsberg, Jens Pappas, David P. Raymer, Michael G. Reilly, David J. Saffman, Mark Searles, Thomas A. Shapiro, Jeffrey H. Singh, Chandralekha IBM Quantum IBM T. J. Watson Research Center Yorktown HeightsNY United States Institut Quantique Département de Physique Université de Sherbrooke SherbrookeQCJ1K 2R1 Canada Canadian Institute for Advanced Research TorontoONM5G 1M1 Canada The Duke Quantum Center Department of Physics Department of Electrical and Computer Engineering Department of Chemistry Duke University DurhamNC27708 United States SystemX Program Department of Electrical Engineering Stanford University StanfordCA94305 United States Department of Physics and Astronomy University of Southern California Los AngelesCA90089 United States The Quantum Engineering Program Department of Physics Colorado School of Mines GoldenCO80401 United States The Department of Electrical Computer and Energy Engineering University of Colorado Boulder BoulderCO80309 United States The Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada The Department of Physics Virginia Tech BlacksburgVA24061 United States The IQUIST University of Illinois Urbana-Champaign UrbanaIL61801 United States JILA National Institute of Standards and Technology The University of Colorado BoulderCO80309 United States Department of Physics University of Colorado Boulder BoulderCO80309 United States The Department of Physics Imperial College London Prince Consort Road LondonSW7 2AZ United Kingdom The Yale Quantum Institute Department of Physics Yale University New HavenCT06520 United States Google Research VeniceCA90291 United States The Department of Physics & Astronomy San José State University San JoséCA95192 United States The School of Electrical and Computer Engineering Purdue University Indiana West Lafayatte47907 United States The Department of Physics The Ohio State University ColumbusOH43210 United States The Department of Physics University of Wisconsin-Madison 1150 University Avenue MadisonWI53706 United States The Quantitative Biosciences and Engineering

The rapidly growing quantum information science and engineering (QISE) industry will require both quantum-aware and quantum-proficient engineers at the bachelor's level. We provide a roadmap for building a quantum engineering education program to satisfy this need. For quantum-aware engineers, we describe how to design a first quantum engineering course accessible to all STEM students. For the education and training of quantum-proficient engineers, we detail both a quantum engineering minor accessible to all STEM majors, and a quantum track directly integrated into individual engineering majors. We propose that such programs typically require only three or four newly developed courses that complement existing engineering and science classes available on most larger campuses. We describe a conceptual quantum information science course for implementation at any post-secondary institution, including community colleges and military schools. QISE presents extraordinary opportunities to work towards rectifying issues of inclusivity and equity that continue to be pervasive within engineering. We present a plan to do so and describe how quantum engineering education presents an excellent set of education research opportunities. Finally, we outline a hands-on training plan on quantum hardware, a key component of any quantum engineering program, with a variety of technologies including optics, atoms and ions, cryogenic and solid-state technologies, nanofabrication, and control and readout electronics. Our recommendations provide a flexible framework that can be tailored for academic institutions ranging from teaching and undergraduate-focused two- and four-year colleges to research-intensive universities. © 2021, CC BY.

关键词： Engineering education

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An interactive dashboard to track themes, development maturity, and global equity in clinical artificial intelligence research

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The Lancet. Digital health 2022年第4期4卷 e212-e213页

作者： Joe Zhang Stephen Whebell Jack Gallifant Sanjay Budhdeo Heather Mattie Piyawat Lertvittayakumjorn Maria Del Pilar Arias Lopez Beatrice J Tiangco Judy W Gichoya Hutan Ashrafian Leo A Celi James T Teo Institute of Global Health Innovation Imperial College London London UK Department of Critical Care King's College Hospital NHS Foundation Trust London UK. Electronic address: joe.zhang@imperial.ac.uk. Department of Critical Care Townsville University Hospital Queensland Health Townsville QLD Australia. Department of Surgery Imperial College Healthcare NHS Foundation Trust London UK Centre for Human and Applied Physiological Sciences King's College London London UK. Department of Neurology National Hospital for Neurology and Neurosurgery London UK Department of Clinical and Movement Neurosciences University College London London UK. Department of Biostatistics Harvard T H Chan School of Public Health Harvard University Cambridge MA USA. Department of Computing Imperial College London London UK. SATI-Q Program Argentine Society of Intensive Care Buenos Aires Argentina. National Institute of Health College of Medicine University of the Philippines Metro Manila Philippines Division of Medicine The Medical City Pasig City Philippines. Department of Radiology Emory University School of Medicine Atlanta Georgia USA. Preemptive Medicine and Health Security Initiative Flagship Pioneering Cambridge MA USA. Department of Biostatistics Harvard T H Chan School of Public Health Harvard University Cambridge MA USA Institute for Medical Engineering & Science Massachusetts Institute of Technology Cambridge MA USA Department of Medicine Beth Israel Deaconess Medical Centre Boston MA USA. Department of Neurology King's College Hospital NHS Foundation Trust London UK London Medical Imaging & AI Centre Guy's and St Thomas' Hospital London UK.

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5th Anniversary Article: A Lesson from Plants: High-Speed Soft Robotic Actuators (Adv. Sci. 5/2020)

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Advanced Science 2020年第5期7卷 2070024-2070024页

作者： Richard Baumgartner Alexander Kogler Josef M. Stadlbauer Choon Chiang Foo Rainer Kaltseis Melanie Baumgartner Guoyong Mao Christoph Keplinger Soo Jin Adrian Koh Nikita Arnold Zhigang Suo Martin Kaltenbrunner Siegfried Bauer Soft Matter Physics Institute of Experimental Physics Johannes Kepler University Linz Altenberger Straße 69 Linz 4040 Austria Soft Materials Lab Linz Institute of Technology LIT Johannes Kepler University Linz Altenberger Straße 69 Linz 4040 Austria Institute of High Performance Computing A*STAR 1 Fusionopolis Way #16-16 Connexis Singapore 138632 Singapore Institute of Polymer Science Johannes Kepler University Linz Altenberger Straße 69 Linz 4040 Austria Department of Mechanical Engineering University of Colorado Boulder Boulder CO 80309 USA Materials Science and Engineering Program University of Colorado Boulder Boulder CO 80303 USA Department of Mechanical Engineering National University of Singapore Singapore 117575 Singapore John A Paulson School of Engineering and Applied Sciences Harvard University 29 Oxford Street Cambridge MA 02138 USA

Explosion of ping‐pong balls that is caused by the rapid inflation of an elastomer membrane. The illustrated ultrafast actuation is based on a plant‐inspired mechanical instability that occurs in natural rubber and can be remotely triggered, presented in article number https://***/10.1002/advs.201903391 by Martin Kaltenbrunner and co‐workers. These new types of high‐speed soft actuators have potential applications in object sorting or grasping.

关键词： bioinspired dielectric elastomer actuators coupled dielectric elastomer balloons snap-buckling snap-through instabilities soft robotics for high-speed actuation

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Fourier phase retrieval: Uniqueness and algorithms

arXiv

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arXiv 2017年

作者： Bendory, Tamir Beinerty, Robert Eldarz, Yonina C. Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Institute of Mathematics and Scientific Computing University of Graz Heinrichstraße 36 Graz8010 Austria Andrew and Erna Viterbi Faculty of Electrical Engineering Technion - Israel Institute of Technology Haifa Israel

The problem of recovering a signal from its phaseless Fourier transform measurements, called Fourier phase retrieval, arises in many applications in engineering and science. Fourier phase retrieval poses fundamental theoretical and algorithmic challenges. In general, there is no unique mapping between a one-dimensional signal and its Fourier magnitude and therefore the problem is ill-posed. Additionally, while almost all multidimensional signals are uniquely mapped to their Fourier magnitude, the performance of existing algorithms is generally not well-understood. In this chapter we survey methods to guarantee uniqueness in Fourier phase retrieval. We then present different algorithmic approaches to retrieve the signal in practice. We conclude by outlining some of the main open questions in this field. Copyright © 2017, The Authors. All rights reserved.

关键词： Fourier transforms

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