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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

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FANTOM5 CAGE profiles of human and mouse samples

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Scientific Data 2017年第1期4卷 1-10页

作者： Noguchi, Shuhei Arakawa, Takahiro Fukuda, Shiro Furuno, Masaaki Hasegawa, Akira Hori, Fumi Ishikawa-Kato, Sachi Kaida, Kaoru Kaiho, Ai Kanamori-Katayama, Mutsumi Kawashima, Tsugumi Kojima, Miki Kubosaki, Atsutaka Manabe, Ri-Ichiroh Murata, Mitsuyoshi Nagao-Sato, Sayaka Nakazato, Kenichi Ninomiya, Noriko Nishiyori-Sueki, Hiromi Noma, Shohei Saijyo, Eri Saka, Akiko Sakai, Mizuho Simon, Christophe Suzuki, Naoko Tagami, Michihira Watanabe, Shoko Yoshida, Shigehiro Arner, Peter Axton, Richard A. Babina, Magda Kenneth Baillie, J. Barnett, Timothy C. Beckhouse, Anthony G. Blumenthal, Antje Bodega, Beatrice Bonetti, Alessandro Briggs, James Brombacher, Frank Carlisle, Ailsa J. Clevers, Hans C. Davis, Carrie A. Detmar, Michael Dohi, Taeko Edge, B. Albert S. Edinger, Matthias Ehrlund, Anna Ekwall, Karl Endoh, Mitsuhiro Enomoto, Hideki Eslami, Afsaneh Fagiolini, Michela Fairbairn, Lynsey Farach-Carson, Mary C. Faulkner, Geoffrey J. Ferrai, Carmelo Fisher, Malcolm E. Forrester, Lesley M. Fujita, Rie Furusawa, Jun-Ichi Geijtenbeek, Teunis B. Gingeras, Thomas Goldowitz, Daniel Guhl, Sven Guler, Reto Gustincich, Stefano Ha, Thomas J. Hamaguchi, Masahide Hara, Mitsuko Hasegawa, Yuki Herlyn, Meenhard Heutink, Peter Hitchens, Kelly J. Hume, David A. Ikawa, Tomokatsu Ishizu, Yuri Kai, Chieko Kawamoto, Hiroshi Kawamura, Yuki I. Kempfle, Judith S. Kenna, Tony J. Kere, Juha Khachigian, Levon M. Kitamura, Toshio Klein, Sarah Peter Klinken, S. Knox, Alan J. Kojima, Soichi Koseki, Haruhiko Koyasu, Shigeo Lee, Weonju Lennartsson, Andreas MacKay-Sim, Alan Mejhert, Niklas Mizuno, Yosuke Morikawa, Hiromasa Morimoto, Mitsuru Moro, Kazuyo Morris, Kelly J. Motohashi, Hozumi Mummery, Christine L. Nakachi, Yutaka Nakahara, Fumio Nakamura, Toshiyuki Nakamura, Yukio Nozaki, Tadasuke Ogishima, Soichi Ohkura, Naganari Ohno, Hiroshi Ohshima, Mitsuhiro Okada-Hatakeyama, Mariko Okazaki, Yasushi Orlando, Valerio Ovchinnikov, Dmitry A. Passier, Robert Patrikakis, Margaret Pombo, Ana Pradhan-Bhatt, Swati Qin, Xian-Yang Rehli, Michael Rizzu, Patrizia Roy, S Division of Genomic Technologies RIKEN Center for Life Science Technologies Yokohama Kanagawa 230-0045 Japan RIKEN Omics Science Center Yokohama Kanagawa 230-0045 Japan Department of Medicine Karolinska Institutet Stockholm 14186 Sweden Karolinska University Hospital Center for Metabolism and Endocrinology Stockholm 14186 Sweden Scottish Centre for Regenerative Medicine University of Edinburgh 5 Little France Drive Edinburgh EH164UU United Kingdom Department of Dermatology and Allergy Charite University Medicine Berlin Charitéplatz 1 Berlin 10117 Germany Roslin Institute and Royal School of Veterinary Studies University of Edinburgh Edinburgh EH259RG United Kingdom Australian Infectious Diseases Research Centre University of Queensland St Lucia 4072 QLD Australia School of Chemistry and Molecular Biosciences University of Queensland St Lucia 4072 QLD Australia Bio-Rad Laboratories Pty Ltd Hercules 94547 CA United States University of Queensland Diamantina Institute University of Queensland Woolloongabba 4102 QLD Australia IRCCS Fondazione Santa Lucia Via del Fosso di Fiorano 64 Rome 00143 Italy Australian Institute for Bioengineering and Nanotechnology University of Queensland Brisbane St Lucia 4072 QLD Australia Division of Immunology Institute of Infectious Diseases and Molecular Medicine University of Cape Town Anzio Road Observatory 7925 South Africa Immunology of Infectious Diseases Faculty of Health Sciences South African Medical Research Council University of Cape Town Anzio Road 7925 South Africa International Centre for Genetic Engineering and Biotechnology Cape Town Component Anzio Road 7925 South Africa Hubrecht Institute Royal Netherlands Academy of Arts and Sciences Uppsalalaan 8 3584 Netherlands University Medical Centre Utrecht Postbus 85500 Utrecht 3508 Netherlands Genomics Cold Spring Harbor Laboratory Cold Spring Harbor New York 11797 NY United States Institute of Pharmaceutical Sciences ETH Zurich Vladi

In the FANTOM5 project, transcription initiation events across the human and mouse genomes were mapped at a single base-pair resolution and their frequencies were monitored by CAGE (Cap Analysis of Gene Expression) coupled with single-molecule sequencing. Approximately three thousands of samples, consisting of a variety of primary cells, tissues, cell lines, and time series samples during cell activation and development, were subjected to a uniform pipeline of CAGE data production. The analysis pipeline started by measuring RNA extracts to assess their quality, and continued to CAGE library production by using a robotic or a manual workflow, single molecule sequencing, and computational processing to generate frequencies of transcription initiation. Resulting data represents the consequence of transcriptional regulation in each analyzed state of mammalian cells. Non-overlapping peaks over the CAGE profiles, approximately 200,000 and 150,000 peaks for the human and mouse genomes, were identified and annotated to provide precise location of known promoters as well as novel ones, and to quantify their activities.

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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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GUGA: A tool for participatory cities

GUGA: A tool for participatory cities

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IEEE Symposium on Computers and Communications (ISCC)

作者： Luana Carine Schünke Luiz Paulo Luna de Oliveira Marta Becker Villamil Applied Computing Graduate Program University of Vale do Rio dos Sinos - Unisinos São Leopoldo RS Brazil Applied Computing Graduate Program University of Vale do Rio dos Sinos - Unisinos São Leopoldo Brazil

Participatory cities are those that allow the participation of citizens in the construction and improvement of their common daily life. In this work we present a tool for that participation, allowing the citizens to register the occurrences as well as take knowledge about the global geographic status of their city in on a variety of contexts (security, transit, etc.). However, a tool like that, fed by the people, certainly will deal with a large amount of information, distributed geographically. To accomplish that, a precise criterion for visualizing the resultant density distribution of occurrences must be used. In this paper, we also propose an automatic method for that visualization based on Voronoi Diagrams. The Voronoi polygons divide the region according to the concentration of occurrences. In this scheme, the area of each Voronoi polygon defines the density of the occurrences of the specific categories which are shown in the city map in color and transparency intensities for visualization. This can easily reveal the space distribution of important issues, in a variety of contexts such as criminality, commercial and industrial activities, drugs traffic, illumination concerns, and others.

关键词： Cities and towns Data visualization Registers Government Social network services Visualization Color

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Expert user discovery in a spontaneous social network an approach using knowledge retrieval

Expert user discovery in a spontaneous social network an app...

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International Conference on Computational Aspects of Social Networks, CASON

作者： Gustavo Freitas Cristiano da Costa Jorge Barbosa Rodrigo Righi Adenauer Yamin Applied Computing Graduate Program-PlPCA University of Vale do Rio dos Sinos Sao Leopoldo Brazil Graduate Program in Computer Science-PPGC Federal University of Pelotas Pelotas Brazil

Nowadays, we can observe that finding answers on social networks is a hard and time-consuming task. The main contribution of this article is the creation of a model and algorithm that allows users to find answers to their questions using a spontaneous social network called Mingle. This algorithm uses the Mingle ontology-based knowledge base to find expert users. To achieve this, two important steps are taken: Mingle ontology is updated to support user-oriented expertise and a detailed model is created for the given algorithm. This model was created considering other three similar applications and algorithms. Moreover, we used a semantic web framework. In the end, an evaluation using real-life scenarios is applied to evaluate if the created algorithm meets the initial goals.

关键词： Social network services

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Analyzing Performance of the Parallel-based Fractal Image Compression Problem on Multicore Systems

Analyzing Performance of the Parallel-based Fractal Image Co...

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The 2013 AASRI Conference on Parallel and Distributed computing and Systems(DCS 2013)

作者： Roberto de Quadros Gomes Vladimir Guerreiro Rodrigo da Rosa Righi Luiz Gonzaga da Silveira Jr. JinyoungYang Applied Computing Graduate Program-PIPCA-UNISINOS-Unisinos Avenue 950 Korean Advanced Institute of Science and Technology-KAIST-291 Daehak-ro

Both the size and the resolution of images always were key topics in the graphical computing ***,they become more and more relevant in the big data *** can observe that often a huge amount of data is exchanged by medium/low bandwidth networks or yet,they need to be stored on devices with limited space of *** this context,the present paper shows the use of the Fractal method for image *** is a lossy method known by providing higher indexes of file reduction through a highly time consuming *** this way,we developed a model of parallel application for exploiting the power of multiprocessor architectures in order to get the Fractal method advantages in a feasible *** evaluation was done with different-sized images as well as by using two types of machines,one with two and another with four *** results demonstrated that both the speedup and efficiency are highly dependent of the number of *** emphasized that a large number of threads does not always represent a better performance.

关键词： Parallel programing Fractal Coding Multicore architectures Parallel modeling Threads Performance analysis

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Abstracts from the Food Allergy and Anaphylaxis Meeting 2016 Abstracts

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CLINICAL AND TRANSLATIONAL ALLERGY 2017年第SUPPL 1期7卷 10-10页

作者： [Anonymous] Department of Pediatrics Children’s Hospital Roubaix France Division of Pulmonology and Allergology Department of Pediatrics Faculty of Medicine and Children’s Hospital Lille France Allergy Vigilance Network Vandoeuvre les Nancy France Université Lille 2 CHU Lille EA 2694 - Santé Publique: épidémiologie et qualité des soins Lille France Biostatistics Unit Maison Régionale de la Recherche Clinique CHRU Lille Lille France Department of Allergology Emile Durkheim Hospital Epinal France Centre d’Epidémiologie sur les Causes Médicales de Décès INSERM CHU de Bicêtre Le Kremlin-Bicêtre France The Allergy Vigilance Network University Hospital Nancy Nancy France Pediatric Pulmonology and Allergy Department Hôpital Jeanne de Flandre CHU Lille Lille France Charité - Universitätsmedizin Berlin Berlin Germany Institute for Social Medicine Epidemiology and Health Economics Charité - Universitätsmedizin Berlin Berlin Germany Institute of Social Medicine Epidemiology and Health Economics Charité Universitätsmedizin Berlin Berlin Germany Department of Dermatology and Allergology Comprehensive Allergy Center Charité Charité – Universitätsmedizin Berlin Berlin Germany Department of Dermatology and Allergy Allergie-Centrum-Charité Charité-Universiätsmedizin Berlin Berlin Germany Department of Dermatology and Allergology Comprehensive Allergy Center Charité Charité Universitätsmedizin Berlin Berlin Germany University Hospital Basel Basel Switzerland Allergy Unit Department of Dermatology University Hospital Basel Switzerland Universitätsklinikum Salzburg Salzburg Austria Department of Dermatology and Allergy Centre Odense Research Center for Anaphylaxis (ORCA) Odense University Hospital Odense Denmark Odense University Hospital Odense Denmark Serviço de ImunoalergologiaCentro Hospitalar de São João E.P.E. Porto Portugal GRIAC Research Institute University of Groningen University Medical Center Groningen Groningen The Netherlands Serviço de Imunoalergologia Centr

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Analyzing Performance of the Parallel-based Fractal Image Compression Problem on Multicore Systems

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AASRI Procedia 2013年 5卷 140-146页

作者： Roberto de Quadros Gomes Vladimir Guerreiro Rodrigo da Rosa Righi Luiz Gonzaga da Silveira Jinyoung Yang Applied Computing Graduate Program –PIPCA - UNISINOS–Unisinos Avenue 950 São Leopoldo RS Brazil Korean Advanced Institute of Science and Technology –KAIST – 291 Daehak-ro Yuseong-gu Daejeon 305-701South Korea

Both the size and the resolution of images always were key topics in the graphical computing area. Especially, they become more and more relevant in the big data era. We can observe that often a huge amount of data is exchanged by medium/low bandwidth networks or yet, they need to be stored on devices with limited space of memory. In this context, the present paper shows the use of the Fractal method for image compression. It is a lossy method known by providing higher indexes of file reduction through a highly time consuming phase. In this way, we developed a model of parallel application for exploiting the power of multiprocessor architectures in order to get the Fractal method advantages in a feasible time. The evaluation was done with different-sized images as well as by using two types of machines, one with two and another with four cores. The results demonstrated that both the speedup and efficiency are highly dependent of the number of cores. They emphasized that a large number of threads does not always represent a better performance.

关键词： Parallel programing Fractal Coding Multicore architectures Parallel modeling Threads Performance analysis

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Methodology for Acquisition of Intensity Data in Forest Targets Using Terrestrial Laser Scanner

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IERI Procedia 2013年 5卷 238-244页

作者： Fabiane Bordin Elba Calesso Teixeira Sílvia Beatriz Alves Rolim Francisco Manoel Wohnrath Tognoli Maurício Roberto Veronez Luiz Gonzaga da Silveira Junior Camila Fernandes Natus de Souza Graduate Program in Remote Sensing Federal University of Rio Grande do Sul (UFRGS) Porto Alegre - RS Brazil Remote Sensing and Digital Cartography Laboratory (LASERCA) University of Vale do Rio dos Sinos (UNISINOS) São Leopoldo-RS Brazil State Foundation of Environmental Protection Luiz Henrique Roessler (FEPAM) Porto Alegre - RS Brazil Graduate Program in Geology University of Vale do Rio dos Sinos (UNISINOS) São Leopoldo-RS Brazil Graduate Program in Applied Computing University of Vale do Rio dos Sinos (UNISINOS) São Leopoldo-RS Brazil

The advance of technology and the availability of high-resolution and accurate systems have permitted the development of new methods for studies in forests. Terrestrial laser scanners have been consolidated as one of the most effective technologies for geospatial data acquisition since the last decade. They have offered the possibility of mapping tridimensionally with high positional accuracy a great number of targets, including forests. However, it is quite difficult to find methodological approaches for acquisition of forest data involving these type of systems. Thus, based on a mid and long range laser scanner with an electromagnetic spectrum ranging into the mid-infrared, 1535 nm, different distances and radiometric resolutions were tested in order to establish a method of acquisition of intensity data in forest targets. After processing, data were analyzed with a clustering algorithm to test the possibility of identifying different elements. Trunk, branches and leaves as well as an edge effect were satisfactorily grouped. Besides defining a method for acquisition of intensity, it opens good perspectives in terms of integrating the classification obtained by the clustering technique with the point cloud. Future studies can contribute to develop a method for quantifying the volume of forest elements and, consequently, estimate biomass.

关键词： Remote sensing Radiometric resolution Distance K-means algorithm LIDAR Mid-infrared Edge effect

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U'Ductor: A model for supporting ubiquitous chronic disease care management

U'Ductor: A model for supporting ubiquitous chronic disease ...

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13th Symposium on computing Systems, WSCAD-SSC 2012

作者： Vianna, Henrique Barbosa, Jorge Costa, Cristiano Yamin, Adenauer C. Applied Computing Graduate Program - PIPCA UNISINOS São Leopoldo Brazil Computer Science - Polytechnic Center UCPEL Pelotas Brazil

ISBN: (纸本)9780769548470

Accordingly with the World Health Organization, heart disease, chronic respiratory diseases, cancer and diabetes are the most common chronic diseases and one of the leading causes of the mortality in the world. In such cases we need more than patient engagement to help to control of the disease, community and health organizations support is also desirable. These roles must support the patients' self-management activities, making them feel confident and motivated. This support can be accomplished by ubiquitous computing. The ubiquitous computing gives conditions to help chronic diseases patients in the management of their activities, offering support to them anytime, anywhere. In this context, this article presents U'Ductor, a model for supporting ubiquitous chronic care management, whose goal is to help the integration between patient and community resources. The U'Ductor gives a step forward in relation to the studied related works by integrating patients, community resources and community members. Those features were not completely explored in the studied works in the way we employ in U'Ductor. An implementation of the model was evaluated by a chronic patient, which gave a positive feedback about it. © 2012 IEEE.

关键词： Ubiquitous computing

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