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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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Estimating Multiple Evoked Emotions from Videos 35

Estimating Multiple Evoked Emotions from Videos

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35th Annual Meeting of the cognitive science Society - Cooperative Minds: Social Interaction and Group Dynamics, CogSci 2013

作者： Choe, Wonhee Chun, Hyo-Sun Noh, Junhyug Lee, Seong-Deok Zhang, Byoung-Tak Cognitive Science Program Seoul National University Seoul151-744 Korea Republic of R&D Center Samsung Electronics Suwon 443-742 Korea Republic of School of Computer Science and Engineering Seoul National University Seoul151-744 Korea Republic of Yongin449-712 Korea Republic of Computer Science and Engineering Cognitive Science and Brain Science Programs Seoul National University Seoul151-744 Korea Republic of

ISBN: (纸本)9780976831891

Video-sharing websites have begun to provide easy access to user-generated video content. How do we find what we want to view among the huge video database? When people search for a video, they may want to know whether the video evokes a certain emotional sensation. The evoked emotion is one of the important factors we consider when we select a video. One of the key concepts of evoked emotions from videos: the evoked emotions are different for each scene and for each viewer. Considering these differences, we obtained human-evoked emotions from 33 videos. We used these emotions to estimate the multiple emotions evoked by each scene of the videos. Using a computational model of emotion estimation based on mid-level visual features, we found that, in individual videos, the same scene evoked multiple emotions. Our results show that a video evoked different emotions from different people. A computational model might deliver probabilistic multiple-evoked emotions from video analyses. © CogSci *** rights reserved.

关键词： Video recording

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Poster abstracts

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Sleep and Biological Rhythms 2016年第1期5卷 A1-A189页

作者： J. Ferrie M. Shipley F. Cappuccio E. Brunner M. Miller M. Kumari M. Marmot A. Coenen J. L. Castillo F. Araya G. Bustamante L. Montecino C. Torres S. Oporto J. Gronli E. Fiske R. Murison B. Bjorvatn E. Sorensen R. Ursin C. M. Portas S. Rajaraman A. Gribok N. Wesensten T. Balkin J. Reifman N. Dursunoglu S. Ozkurt S. Baser O. Delen S. Sarikaya P. Sadler P. Mitchell D. Françon M. Decobert B. Herve A. Richard G. Griebel P. Avenet B. Scatton G. L. Fur D. Eckert A. Jordan A. Wellman S. Smith A. Malhotra D. White D. Bruck I. Thomas A. Kritikos W. Oertel K. Stiasny-Kolster D. Garcia-Borreguero W. Poewe B. Hoegl R. Kohnen E. Schollmayer J. Keffel C. Trenkwalder A. Valle S. Roizenblatt F. Fregni P. Boggio S. Tufik K. Ward L. Robertson L. Palmer P. Eastwood D. Hillman J. Lee S. Mukherjee V. de Padova G. Barbato G. Ficca I. Zilli P. Salzarulo M. Veldi T. Hion V. Vasar M. Kull L. Nowak J. Davis Y. Latzer O. Tzischinsky S. Crowley M. Carskadon M. Anca-Herschkovitsch D. Frey J. Ortega C. Wiseman C. Farley K. Wright A. Campbell A. Neill K. Spiegel R. Leproult E. Tasali N. Scherberg E. van Cauter A. T. Noradina N. A. Karim I. Norlinah A. A. Raymond R. Sahathevan B. Hamidon E. Werth R. Poryazova R. Khatami C. Bassetti R. G. Beran L. Ainley G. Holand J. Duncan H. Kinney B. Davis B. Hood S. Frey C. Schmidt M. Hofstetter P. Peigneux C. Cajochen W.-P. Hu J.-D. Li C. Zhang L. Boehmer J. Siegel Q.-Y. Zhou Y. Sagawa H. Kondo T. Takemura H. Kanayama Y. Kaneko M. Sato T. Kanbayashi Y. Hishikawa T. Shimizu A. Viola L. James L. Schlangen D.-J. Dijk R. Andretic Y.-C. Kim K.-A. Han F. Jones R. Greenspan L. Sanford L. Yang X. Tang K. Dieter E. Uta H. Sven M. Richard N. Oyane S. Pallesen F. Holsten Y. Inoue M. Fujita N. Emura K. Kuroda N. Uchimura A. Johnston J. Astbury G. Kennedy K. Hoedlmoser M. Schabus T. Pecherstorfer S. Moser G. Gruber P. Anderer W. Klimesch N. Naidoo M. Ferber A. Pack D. Neu O. Mairesse G. Hoffmann A. Dris L. Lambrecht P. Linkowski P. Verbanck O. Le Bon N. Matsuura M. Yamao N. Adachi R. Aritomi Y. Komada H. Tanaka S. Shirak University College London London UK University College London London USA Warwick Medical School London UK Warwick Medical School Coventry USA Radboud University Nijmegen Nijmegen Netherlands Department of Neurology University of Chile Santiago Chile Neurology Service Hospital del Salvador Santiago Chile Family Health Center Juan Pablo II Santiago Chile Department of Biomedicine Section on Physiology Univeristy of Bergen Bergen Norway Department of Public Health and Primary Health Care Univeristy of Bergen Bergen Norway Department of Public Health and Primary Health Care University of Bergen Bergen Norway Norwegian Competence Center for Sleep Disorders Haukeland University Hospital Bergen Norway Department of Child and Adolescent Psychiatry Haukeland University Hospital Univeristy of Bergen Bergen Norway Department of Biomedicine University of Bergen Bergen Norway US Army Medical Research and Materiel Command Fort Detrick Frederick USA Walter Reed Army Institute of Research Silver Spring USA Department of Behavioral Biology Walter Reed Army Institute of Research Silver Spring USA Faculty Department of Pulmonology Pamukkale University Medical Denizli Turkey University of Ballarat Ballarat Australia Sanofi-Aventis Recherche et Developpement Paris France Brigham and Women’s Hospital Harvard Medical School Boston USA The University of Queensland Adelaide Australia School of Psychology University of Queensland Brisbane Australia The University of Queensland Brisbane Australia Victoria University Melbourne Australia Department of Psychology Victoria University Melbourne Australia School of Psychology Victoria University Melbourne Australia Philips-Universität Marburg Germany Philips-Universitaet-Marburg Marburg Germany Instituto de Investigaciones del Sueno Madrid Spain Universitätsklinik für Neurologie Innsbruck Austria Universitaetsklinik fuer Neurologie Innsbruck Austria IMEREM GmbH Nuernberg Germany Schwarz Pharma AG Monheim Germany

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Sparse Population Code Models of Word Learning in Concept Drift 34

Sparse Population Code Models of Word Learning in Concept Dr...

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34th Annual Meeting of the cognitive science Society: Building Bridges Across cognitive sciences Around the World, CogSci 2012

作者： Zhang, Byoung-Tak Ha, Jung-Woo Kang, Myunggu School of Computer Science and Engineering Seoul National University Seoul151-744 Korea Republic of Cognitive Science and Brain Science Programs Seoul National University Seoul151-744 Korea Republic of

ISBN: (纸本)9780976831884

Computational modeling has served a powerful tool for studying cross-situational word learning. Previous research has focused on convergence behaviors in a static environment, ignoring dynamic cognitive aspects of concept change. Here we investigate concept drift in word learning in story-telling situations. Informed by findings in cognitive neuroscience, we hypothesize that a large ensemble of sparse codes flexibly represents and robustly traces drifting concepts. We experimentally test the population coding hypothesis on children’s cartoon videos. Our results show that learning the meanings of words over time is hard, especially when the concept evolves slowly, but the sparse population coding can handle the concept drift problem effectively while hypothesis elimination and simplistic parametric models have difficulty. © CogSci *** rights reserved.

关键词： Population statistics

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Subjective Evaluation of Use of Babyloid for Doll Therapy

Subjective Evaluation of Use of Babyloid for Doll Therapy

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IEEE International Conference on Fuzzy Systems

作者： Yoshitaka Furuta Masayoshi Kanoh Taro Shimizu Masaru Shimizu Tsuyoshi Nakamura Graduate School of Computer and Cognitive Sciences Chukyo University School of Information Science and Technology Chukyo University Product Design Office NAGAKUTE-M. Graduate School of Engineering Nagoya Institute of Technology

ISBN: (纸本)9781467315074

In line with the effects of Japan's aging society with fewer children, the number of elderly with dementia who live alone and without care is increasing, therefore at-home care is beginning to be required. Doll therapy is a way of at-home dementia care. Doll therapy can help improve mental status of the elderly, because their logical and rational thinking is activated by imaging the child care experience with feeling and emotion at the times. In this research, we consider using Babyloid, a baby type robot, for doll therapy. As a first step of this research, we investigated whether elderly people in a nursing home for the elderly home accept Babyloid.

关键词： Dolls aged person Homes for the Aged Home Care Services subjective evaluation Mental status Medicine Dementia Feelings logical Emotions Reasoning

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An operation plane using a neural network for intuitive generation of robot motion

An operation plane using a neural network for intuitive gene...

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International Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Junki Ito Masayoshi Kanoh Reona Arisawa Tsuyoshi Nakamura Takanori Komatsu Graduate School of Computer and Cognitive Sciences Chukyo University Toyota Japan School of Information Science and Technology Chukyo University Toyota Japan Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan Faculty of Textile Science and Technology Shinshu University Ueda Japan

An operation plane is developed that greatly simplifies the task of editing motion of humanoid robots. The plane uses onomatopoeias, which are words that mimic the appearance or sound of things to produce richly realistic expressions. To create the plane, first, features of known motions for which there are onomatopoeias are extracted by P-type Fourier descriptors. Second, the similarity relationship between the features is learned by using a five-layer auto-associative neural network. Finally, the network's third layer, which has two units, is used as an operation plane. Using this plane, even people who are unfamiliar with robotics can edit motion of humanoid robots intuitively.

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Evaluation of measured and estimated dynamic moduli for selected asphalt mixes

Journal of ASTM International

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Journal of ASTM International 2011年第9期8卷

作者： Singh, Dharamveer Zaman, Musharraf Commuri, Sesh School of Civil Engineering and Environmental Science Univ. of Oklahoma 202 W. Boyd St. Norman OK 73019 United States Research and Graduate Programs College of Engineering Univ. of Oklahoma Norman OK 73019 United States School of Electrical and Computer Engineering Univ. of Oklahoma Norman OK 73019 United States

An accurate measurement or estimation of dynamic modulus (|E*|) of a hot mix asphalt (HMA) mix is important to understand stress-strain behavior of flexible pavements under loading and unloading conditions. The Mechanistic Empirical Pavement Design Guide (MEPDG) (Transportation Research Board, Washington, D.C., 2004) recommends that |E*| be used in all three levels of design (i.e., Level 1, Level 2, and Level 3). For Level 1, |E*| is measured in the laboratory, while it is estimated using the Witczak models for Level 2 and Level 3 designs. The measurement of |E*| in the laboratory is not always feasible because it requires costly equipment and skilled personnel. Consequently, use of empirical models seems to be a reasonable approach to estimate |E*|. Several researchers have reported that the accuracy of the Witczak models varies with local materials and volumetric properties. The present study was undertaken to compare the measured and the estimated |E*| for some commonly used mixes in Oklahoma. Specifically, |E*| of five different HMA mixes, comprised of aggregates from several sources and sizes, binder grades, and air voids, were measured in the laboratory. The Witczak 1999 model (Andrei et al., 1999) was used to estimate |E*| for each of these mixes. A comparison was made between the measured and the estimated |E*| at four different levels of air voids, namely, 6%, 8%, 10%, and 12%. It was observed that the Witczak 1999 model overestimates |E*| at all four levels of air voids. To address these overestimates, the Witczak 1999 model was calibrated. The calibrated model was similar in form to the Witczak 1999 model but having different numerical coefficients. Verification of this model was done using a mix that was not used in the calibration process. Furthermore, two full depth field cores were obtained to further verify the accuracy of the calibrated model. Three different criteria, namely, goodness-of-fit statistics, matching the measured and the estimated |E*|,

关键词： Stress analysis

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Learning to grasp with parental scaffolding

Learning to grasp with parental scaffolding

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2011 11th IEEE-RAS International Conference on Humanoid Robots, HUMANOIDS 2011

作者： Ugur, Emre Celikkanat, Hande Şahin, Erol Nagai, Yukie Oztop, Erhan Advanced ICT National Institute of Information and Communication Technology Kyoto Japan Cognitive Mechanisms Labs. Advanced Telecommunications Institute International Kyoto Japan KOVAN Research Lab. Department of Computer Engineering Middle East Technical University Ankara Turkey Graduate School of Engineering Osaka University Osaka Japan School of Engineering Science Osaka University Osaka Japan Computer Science Dept. Ozyegin University Istanbul Turkey

ISBN: (纸本)9781612848679

Parental scaffolding is an important mechanism utilized by infants during their development. Infants, for example, pay stronger attention to the features of objects highlighted by parents and learn the way of manipulating an object while being supported by parents. In this paper, a robot with the basic ability of reaching for an object, closing fingers and lifting its hand lacks knowledge of which parts of the object affords grasping, and in which hand orientation should the object be grasped. During reach and grasp attempts, the movement of the robot hand is modified by the human caregiver's physical interaction to enable successful grasping. The object regions that the robot fingers contact first are detected and stored as potential graspable object regions along with the trajectory of the hand. In the experiments, we showed that although the human caregiver did not directly show the graspable regions, the robot was able to find regions such as handles of the mugs after its action execution was partially guided by the human. Later, this experience was used to find graspable regions of never seen objects. At the end, the robot was able to grasp objects based on the position of the graspable part and stored action execution trajectories. © 2011 IEEE.

关键词： Scaffolds

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Feature extraction based on common spatial analysis for time domain parameters

Feature extraction based on common spatial analysis for time...

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2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2011

作者： Li, Xinyang Sam Ge, Shuzhi Pan, Yaozhang Hong, Keum-Shik Zhang, Zhengchen Hu, Xiaosu Social Robotics Laboratory Interactive Digital Media Institute National University of Singapore Singapore 119077 Singapore NUS Graduate School for Integrative Sciences and Engineering National University of Singapore Singapore 119613 Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore Singapore 138632 Singapore Cognitive Science Laboratory Department of Cogno-Mechatronics Engineering Pusan National University Busan 609735 Korea Republic of

ISBN: (纸本)9781457707223

In this paper, an approach of feature extraction by designing common spatial filters specifically for time domain parameters (TDP) is proposed. This approach is aiming at motor imagery detection in electroencephalogram (EEG). Particularly, this method calculates the derivatives of the original signals and then applies common spatial analysis (CSP) to each order of derivatives. Variances of the spatially filtered signal after taking logarithm are used as features. Quadratic discriminant analysis (QDA) is applied to the feature vectors and classifies the vectors into different categories. We evaluate our approach using data consisting of two classes: left-hand and right-hand movement imageries from three subjects, and comparison between the proposed method and applying CSP analysis to the whole set of EEG signal directly is presented. Our results show that the proposed method generates more discriminant features in this motor imagery classification issue. © 2011 IEEE.

关键词： Feature extraction

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WORKSHOP: The role of expectations in intuitive human-robot interaction

WORKSHOP: The role of expectations in intuitive human-robot ...

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ACM/IEEE International Conference on Human-Robot Interaction (HRI)

作者： Verena Hafner Manja Lohse Joachim Meyer Yukie Nagai Britta Wrede Department of Computer Science Cognitive Robotics Berlin Germany CoR-Laboratory and Applied Informatics Technical Faculty Bielefeld University Germany Department of Industrial Engineering and Management University of Negev Israel Department of Adaptive Machine Systems Graduate School of Engineering Osaka University Japan Head of CoR-Laboratory research group Hybrid Society Technical Faculty Bielefeld University Germany

Human interaction is highly intuitive: we infer reactions of our opponents mainly from what we have learned in years of experience and often assume that other people have the same knowledge about certain situations, abilities, and expectations as we do. In human-robot interaction (HRI) we cannot take for granted that this is equally true since HRI is asymmetrical. In other words, robots have different abilities, knowledge, and expectations than humans. They need to react appropriately to human expectations and behaviour. With this respect, scientific advances have been made to date for applications in entertainment and service robotics that largely depend on intuitive interaction. However, HRI today is often still unnatural, slow, and unsatisfactory for the human interlocutor. Both the sensorimotor interaction with environment and interlocutor, and the social aspects of the interaction still need to be researched and improved. Therefore, this full-day workshop aims to bring together researchers from different scientific fields to discuss these crosscutting issues and to exchange views on what are the preconditions and principles of intuitive interaction.

关键词： Educational institutions computer science Robot sensing systems Electronic mail Humans Industrial engineering

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