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Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

Scientific data 2017年第1期4卷 170179页

作者： Jason Flannick Christian Fuchsberger Anubha Mahajan Tanya M Teslovich Vineeta Agarwala Kyle J Gaulton Lizz Caulkins Ryan Koesterer Clement Ma Loukas Moutsianas Davis J McCarthy Manuel A Rivas John R B Perry Xueling Sim Thomas W Blackwell Neil R Robertson N William Rayner Pablo Cingolani Adam E Locke Juan Fernandez Tajes Heather M Highland Josee Dupuis Peter S Chines Cecilia M Lindgren Christopher Hartl Anne U Jackson Han Chen Jeroen R Huyghe Martijn van de Bunt Richard D Pearson Ashish Kumar Martina Müller-Nurasyid Niels Grarup Heather M Stringham Eric R Gamazon Jaehoon Lee Yuhui Chen Robert A Scott Jennifer E Below Peng Chen Jinyan Huang Min Jin Go Michael L Stitzel Dorota Pasko Stephen C J Parker Tibor V Varga Todd Green Nicola L Beer Aaron G Day-Williams Teresa Ferreira Tasha Fingerlin Momoko Horikoshi Cheng Hu Iksoo Huh Mohammad Kamran Ikram Bong-Jo Kim Yongkang Kim Young Jin Kim Min-Seok Kwon Juyoung Lee Selyeong Lee Keng-Han Lin Taylor J Maxwell Yoshihiko Nagai Xu Wang Ryan P Welch Joon Yoon Weihua Zhang Nir Barzilai Benjamin F Voight Bok-Ghee Han Christopher P Jenkinson Teemu Kuulasmaa Johanna Kuusisto Alisa Manning Maggie C Y Ng Nicholette D Palmer Beverley Balkau Alena Stančáková Hanna E Abboud Heiner Boeing Vilmantas Giedraitis Dorairaj Prabhakaran Omri Gottesman James Scott Jason Carey Phoenix Kwan George Grant Joshua D Smith Benjamin M Neale Shaun Purcell Adam S Butterworth Joanna M M Howson Heung Man Lee Yingchang Lu Soo-Heon Kwak Wei Zhao John Danesh Vincent K L Lam Kyong Soo Park Danish Saleheen Wing Yee So Claudia H T Tam Uzma Afzal David Aguilar Rector Arya Tin Aung Edmund Chan Carmen Navarro Ching-Yu Cheng Domenico Palli Adolfo Correa Joanne E Curran Dennis Rybin Vidya S Farook Sharon P Fowler Barry I Freedman Michael Griswold Daniel Esten Hale Pamela J Hicks Chiea-Chuen Khor Satish Kumar Benjamin Lehne Dorothée Thuillier Wei Yen Lim Jianjun Liu Marie Loh Solomon K Musani Sobha Puppala William R Scott Loïc Yengo Sian-Tsung Tan Herman A Taylor Farook Thameem Gregory Wilson Tien Yin Wong Pål Rasmu Department of Molecular Biology Massachusetts General Hospital Boston Massachusetts USA. Program in Medical and Population Genetics Broad Institute Cambridge Massachusetts USA. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor Michigan USA. Wellcome Trust Centre for Human Genetics Nuffield Department of Medicine University of Oxford Oxford UK. Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology Cambridge Massachusetts USA. Department of Statistics University of Oxford Oxford UK. Genetics of Complex Traits University of Exeter Medical School University of Exeter Exeter UK. MRC Epidemiology Unit Institute of Metabolic Science University of Cambridge Cambridge UK. Department of Twin Research and Genetic Epidemiology King's College London London UK. Oxford Centre for Diabetes Endocrinology and Metabolism Radcliffe Department of Medicine University of Oxford Oxford UK. Department of Human Genetics Wellcome Trust Sanger Institute Hinxton Cambridgeshire UK. School of Computer Science McGill University Montreal Quebec Canada. McGill University and Génome Québec Innovation Centre Montreal Quebec Canada. Human Genetics Center The University of Texas Graduate School of Biomedical Sciences at Houston The University of Texas Health Science Center at Houston Houston Texas USA. Department of Biostatistics Boston University School of Public Health Boston Massachusetts USA. National Heart Lung and Blood Institute's Framingham Heart Study Framingham Massachusetts USA. Medical Genomics and Metabolic Genetics Branch National Human Genome Research Institute National Institutes of Health Bethesda Maryland USA. Department of Biostatistics Harvard School of Public Health Boston Massachusetts USA. Chronic Disease Epidemiology Swiss Tropical and Public Health Institute University of Basel Basel Switzerland. Institute of Genetic Epidemiology Helmholtz Zentrum München German R

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

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Haze effect removal from image via haze density estimation in optical model

Haze effect removal from image via haze density estimation i...

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作者： Yeh, Chia-Hung Kang, Li-Wei Lee, Ming-Sui Lin, Cheng-Yang Department of Electrical Engineering National Sun Yat-sen University 804 Taiwan Graduate School of Engineering Science and Technology-Doctoral Program Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin 640 Taiwan Graduate Institute of Networking and Multimedia Department of Computer Science and Information Engineering National Taiwan University Taipei 106 Taiwan

Images/videos captured from optical devices are usually degraded by turbid media such as haze, smoke, fog, rain and snow. Haze is the most common problem in outdoor scenes because of the atmosphere conditions. This paper proposes a novel single image-based dehazing framework to remove haze artifacts from images, where we propose two novel image priors, called the pixel-based dark channel prior and the pixel-based bright channel prior. Based on the two priors with the haze optical model, we propose to estimate atmospheric light via haze density analysis. We can then estimate transmission map, followed by refining it via the bilateral filter. As a result, high-quality haze-free images can be recovered with lower computational complexity compared with the state-of-the-art approach based on patch-based dark channel prior. ©2013 Optical Society of America.

关键词： Pixels

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Self-organization promotes the evolution of cooperation with cultural propagation

Self-organization promotes the evolution of cooperation with...

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7th IFIP TC 6 International Workshop on Self-Organizing Systems, IWSOS 2013

作者： Cortés-Berrueco, Luis Enrique Gershenson, Carlos Stephens, Christopher R. Graduate Program in Computer Science and Engineering Universidad Nacional Autónoma de México Ciudad Universitaria A.P.70-600 México D.F. Mexico Computer Science Department Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas Universidad Nacional Autónoma de México Ciudad Universitaria A.P.20-726 México D.F. Mexico Gravitation Department. Instituto de Ciencias Nucleares Universidad Nacional Autónoma de México Ciudad Universitaria A.P.70-543 México D.F. Mexico Centro de Ciencias de la Complejidad Universidad Nacional Autónoma de México Mexico

ISBN: (纸本)9783642541391

In this paper three computational models for the study of the evolution of cooperation under cultural propagation are studied: Kin Selection, Direct Reciprocity and Indirect Reciprocity. Two analyzes are reported, one comparing their behavior between them and a second one identifying the impact that different parameters have in the model dynamics. The results of these analyzes illustrate how game transitions may occur depending of some parameters within the models and also explain how agents adapt to these transitions by individually choosing their attachment to a cooperative attitude. These parameters regulate how cooperation can self-organize under different circumstances. The emergence of the evolution of cooperation as a result of the agent's adapting processes is also discussed. © IFIP International Federation for Information Processing 2014.

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Cross-camera vehicle tracking via affine invariant object matching for video forensics applications

Cross-camera vehicle tracking via affine invariant object ma...

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2013 IEEE International Conference on Multimedia and Expo, ICME 2013

作者： Hsu, Chao-Yung Kang, Li-Wei Mark Liao, Hong-Yuan Institute of Information Science Academia Sinica Taipei Taiwan Graduate School of Engineering Science and Technology-Doctoral Program Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (纸本)9781479900152

The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect and track each vehicle within a large area, which can be applied to video forensics. For example, a suspected vehicle can be automatically identified for mining digital criminal evidences from a large amount of video data. In this paper, we propose an efficient cross-camera vehicle tracking technique via affine invariant object matching. More specifically, we formulate the problem as invariant image feature matching among different viewpoints of cameras. To achieve vehicle matching, we first extract invariant image feature based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, to improve the accuracy of ASIFT feature matching between images from different viewpoints, we propose to efficiently match feature points based on our observed spatially invariant property of ASIFT, as well as the min-hash technique. As a result, cross-camera vehicle tracking can be efficiently and accurately achieved. Experimental results demonstrate the efficacy of the proposed algorithm and the feasibility to video forensics applications. © 2013 IEEE.

关键词： Tracking (position)

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Principles of high–fidelity, high–density 3–d neural recording

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BMC Neuroscience 2014年第1期15卷 1-2页

作者： Caroline Moore-Kochlacs Nancy Kopell Justin P Kinney Ed S Boyden Jorg Scholvin Jacob G Bernstein Scott K Arfin Young Gyu Yoon Graduate Program for Neuroscience Boston University Boston MA 02215 USA McGovern Institute Massachusetts Institute of Technology MA 02139 USA Department of Mathematics and Statistics Boston University Boston MA 02215 USA Media Lab Massachusetts Institute of Technology MA 02139 USA Brain and Cognitive Science Massachusetts Institute of Technology MA 02139 USA Biological Engineering Massachusetts Institute of Technology MA 02139 USA Electrical Engineering and Computer Science Massachusetts Institute of Technology MA 02139 USA

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Development and evaluation of a hospital-wide healthcare-associated surgical site infection detection algorithm

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Journal of Microbiology, Immunology and Infection 2015年第2期48卷 S43-S43页

作者： Yi-Ju Tseng Bo-Chiang Huang Hui-Chi Lin Ming-Yuan Chen Rung-Ji Shang Wang-Huei Sheng Yee-Chun Chen Feipei Lai Shan-Chwen Chang Children's Hospital Informatics Program Boston Children's Hospital Boston MA USA Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taiwan Center for Infection Control National Taiwan University Hospital (NTUH) Taiwan Information Systems Office NTUH Taipei Taiwan Department of Internal Medicine NTUH and College of Medicine Taiwan National Institute of Infectious Diseases and Vaccinology National Health Research Institutes Taiwan Department of Computer Science and Information Engineering National Taiwan University Taiwan

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A heuristic fuzzy algorithm bio-inspired by Evolution Strategies for energy forecasting problems

A heuristic fuzzy algorithm bio-inspired by Evolution Strate...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Vitor N. Coelho Frederico G. Guimarães Agnaldo J. R. Reis Igor M. Coelho Bruno N. Coelho Marcone J. F. Souza Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Departament of Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Department of Control Engineering and Automation Universidade Federal de Ouro Preto Ouro Preto MG Brazil Institute of Computing Universidade Federal Fluminense Niteri RJ Brazil Department of Computer Science Universidade Federal de Ouro Preto Ouro Preto MG Brazil

Improving the use of energy resources has been a great challenge in the last years. A new complex scenario involving a decentralized bidirectional communication between energy suppliers, distribution system and consumption is nowadays becoming reality. Sometimes cited as the largest and most complex machine ever built, Electric Grids (EG) are been transformed into Smart Grids (SG). Hence, the load forecasting problem has become more difficulty and more autonomous load predictors are needed in this new conjecture. In this paper a novel method, so-called MSES, bio-inspired by Evolution Strategies (ES) combined with Multi-Start (MS) procedure is described. This procedure is mainly based on a self-adaptive algorithm to calibrate the parameters of the fuzzy rules. MSES was implemented in C++ via OptFrame framework. Our main goal is to evaluate the performance of this algorithm in a grid environment. Real data from an electric utility have been used in order to test the proposed methodology. The obtained results are fully described and analyzed.

关键词： Forecasting Vectors Prediction algorithms Predictive models Training Standards Adaptation models

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Measurement of capacitance and electrical potential of plural points for estimation of permittivity distribution

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IEEJ Transactions on Fundamentals and Materials 2013年第4期133卷 173-179+5页

作者： Okada, Shota Ohchi, Masashi Furukawa, Tatsuya Itoh, Hideaki Fukumoto, Hisao Master's Program in Electrical Graduate School of Engineering Chiba Institute of Technology 2-17-1 Tudanuma Narashino 275-0016 Japan Department of Electrical Electronics and Computer Engineering Faculty of Engineering Chiba Institute of Technology 2-17-1 Tudanuma Narashino 275-0016 Japan Graduate School of Science and Engineering Saga University 1 Honjo-machi Saga 840-8502 Japan

Recently, a method for estimating permittivity distributions was reported. The method combined a numerical technique (Finite Element Method) with Genetic Algorithm (GA). However, methods for estimating the distribution of permittivity have not yet been established. The purpose of this study is to obtain experimental data in order to improve the estimation method. We measured capacitance and electrical potential of plural points when an acrylic rod is placed in various positions within a measurement system. © 2013 The Institute of Electrical Engineers of Japan.

关键词： Capacitance

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Error analysis for RADAR neighbor matching localization in linear logarithmic strength varying Wi-Fi environment

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The Scientific World Journal 2014年第1期2014卷 647370页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Yu, Xiang Wu, Haibo Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong Graduate Telecommunications and Networking Program University of Pittsburgh Pittsburgh PA 15260 United States China Internet Research Lab Computer Network Information Center Chinese Academy of Sciences Beijing 100190 China

This paper studies the statistical errors for the fingerprint-based RADAR neighbor matching localization with the linearly calibrated reference points (RPs) in logarithmic received signal strength (RSS) varying Wi-Fi environment. To the best of our knowledge, little comprehensive analysis work has appeared on the error performance of neighbor matching localization with respect to the deployment of RPs. However, in order to achieve the efficient and reliable location-based services (LBSs) as well as the ubiquitous context-awareness in Wi-Fi environment, much attention has to be paid to the highly accurate and cost-efficient localization systems. To this end, the statistical errors by the widely used neighbor matching localization are significantly discussed in this paper to examine the inherent mathematical relations between the localization errors and the locations of RPs by using a basic linear logarithmic strength varying model. Furthermore, based on the mathematical demonstrations and some testing results, the closed-form solutions to the statistical errors by RADAR neighbor matching localization can be an effective tool to explore alternative deployment of fingerprint-based neighbor matching localization systems in the future. © 2014 Mu Zhou et al.

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Hardware-based parallel firefly algorithm for embedded applications

Hardware-based parallel firefly algorithm for embedded appli...

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2013 NASA/ESA Conference on Adaptive Hardware and Systems, AHS 2013

作者： Muñoz, Daniel M. Llanos, Carlos H. Dos Santos Coelho, Leandro Ayala-Rincón, Mauricio Electronics Engineering Graduate Program Faculty of Gama University of Brasilia Brasilia DF Brazil Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia DF Brazil Industrial and Systems Engineering Graduate Program LAS/PPGEPS Pontifical Catholic University of Parana Curitiba Parana Brazil Departments of Computer Science and Mathematics University of Brasilia Brasilia DF Brazil

ISBN: (纸本)9781467363839

The firefly algorithm (FA) is a new population-based metaheuristic bioinspired on the behavior of the flashing characteristics of fireflies. As a population-based algorithm, the FA suffers from large execution times specifically for embedded optimization problems with computational limitations. For reducing execution times we propose a hardware parallel architecture of the FA algorithm that facilitates the implementation in Field programmable Gate Arrays (FPGAs). In addition, this work proposes the application of the opposition-based learning (OBL) approach to the FA algorithm. The respective hardware implementation (HPOFA) was mapped into a Virtex5 FPGA device and numerical experiments using four well-known benchmark problems demonstrate that the opposition-based approach allows the FA algorithm to improve its functionality, preserving the swarm diversity and avoiding the premature convergence problem. Synthesis results point out that the HPOFA architecture is effectively mapped in hardware and is suitable for embedded applications. © 2013 IEEE.

关键词： Parallel architectures

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