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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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Tomographic imaging of Central Java, Indonesia: Preliminary result of joint inversion of the MERAMEX and MCGA earthquake data

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AIP Conference Proceedings 2013年第1期1554卷 234-237页

作者： Supriyanto Rohadi Sri Widiyantoro Andri Dian Nugraha Masturyono Study Program of Earth Sciences Faculty of Earth Sciences and Technology Institute of Technology Bandung Jl. Ganesha No.10 Bandung 40132 Indonesia and Meteorological Climatological and Geophysical Agency Jl. Angkasa 1 No.2 Kemayoran Jakarta Indonesia Global Geophysics Research Group Faculty of Mining and Petroleum Engineering Institute of Technology Bandung Jl. Ganesha No.10 Bandung 40132 Indonesia Meteorological Climatological and Geophysical Agency Jl. Angkasa 1 No.2 Kemayoran Jakarta Pusat Indonesia

The realization of local earthquake tomography is usually conducted by removing distant events outside the study region, because these events may increase errors. In this study, tomographic inversion has been conducted using the travel time data of local and regional events in order to improve the structural resolution, especially for deep structures. We used the local MERapi Amphibious EXperiments (MERAMEX) data catalog that consists of 292 events from May to October 2004. The additional new data of regional events in the Java region were taken from the Meteorological, Climatological, and Geophysical Agency (MCGA) of Indonesia, which consist of 882 events, having at least 10 recording phases at each seismographic station from April 2009 to February 2011. We have conducted joint inversions of the combined data sets using double-difference tomography to invert for velocity structures and to conduct hypocenter relocation simultaneously. The checkerboard test results of Vp and Vs structures demonstrate a significantly improved spatial resolution from the shallow crust down to a depth of 165 km. Our tomographic inversions reveal a low velocity anomaly beneath the Lawu - Merapi zone, which is consistent with the results from previous studies. A strong velocity anomaly zone with low Vp, low Vs and low Vp/Vs is also identified between Cilacap and Banyumas. We interpret this anomaly as a fluid content material with large aspect ratio or sediment layer. This anomaly zone is in a good agreement with the existence of a large dome containing sediment in this area as proposed by previous geological studies. A low velocity anomaly zone is also detected in Kebumen, where it may be related to the extensional oceanic basin toward the land.

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Mitigating flood exposure: Reducing disaster risk and trauma signature

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Disaster health 2013年第1期1卷 30-44页

作者： James M Shultz Andrew McLean Holly B Herberman Mash Alexa Rosen Fiona Kelly Helena M Solo-Gabriele Georgia A Youngs Jessica Jensen Oscar Bernal Yuval Neria Center for Disaster & Extreme Event Preparedness (DEEP Center) University of Miami Miller School of Medicine Miami FL USA. School of Medicine and Health Sciences University of North Dakota Fargo ND USA. Department of Psychology Center for the Study of Traumatic Stress Uniformed Services University of the Health Sciences Bethesda MD USA. Clinical & Health Psychology University of Edinburgh Scotland UK. Department of Civil Architectural and Environmental Engineering College of Engineering University of Miami Department of Emergency Management North Dakota State University School of Medicine Universidad de Los Andes Bogota Colombia. Trauma and PTSD Program Department of Psychiatry & The New York State Psychiatric Institute Columbia University New York NY USA.

In 2011, following heavy winter snowfall, two cities bordering two rivers in North Dakota, USA faced major flood threats. Flooding was foreseeable and predictable although the extent of risk was uncertain. One community, Fargo, situated in a shallow river basin, successfully mitigated and prevented flooding. For the other community, Minot, located in a deep river valley, prevention was not possible and downtown businesses and one-quarter of the homes were inundated, in the city's worst flood on record. We aimed at contrasting the respective hazards, vulnerabilities, stressors, psychological risk factors, psychosocial consequences, and disaster risk reduction strategies under conditions where flood prevention was, and was not, possible. . We applied the "trauma signature analysis" (TSIG) approach to compare the hazard profiles, identify salient disaster stressors, document the key components of disaster risk reduction response, and examine indicators of community resilience. . Two demographically-comparable communities, Fargo and Minot, faced challenging river flood threats and exhibited effective coordination across community sectors. We examined the implementation of disaster risk reduction strategies in situations where coordinated citizen action was able to prevent disaster impact (hazard avoidance) compared to the more common scenario when unpreventable disaster strikes, causing destruction, harm, and distress. Across a range of indicators, it is clear that successful mitigation diminishes both physical and psychological impact, thereby reducing the trauma signature of the event. . In contrast to experience of historic flooding in Minot, the city of Fargo succeeded in reducing the trauma signature by way of reducing risk through mitigation.

关键词： community resilience disaster flood mental health mitigation psychological psychosocial resilience trauma trauma signature analysis

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An eddy brakes dynamometer control system design using state space based PID controller

An eddy brakes dynamometer control system design using state...

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IEEE Conference on Control, Systems & Industrial Informatics (ICCSII)

作者： Tirta Nahari Endra Joelianto Suyatman Engineering Physics Study Program Faculty of Industrial Technology Bandung Institute of Technology Bandung Indonesia

Dynamometer is an automotive device that is used to perform engine testing. From this test, engine information such as power, torque, and emition can be obtained for design and analysis purposes. Eddy brakes dynamometer is considered because it is considerably more effective and controllable. In order to design a brakes control system based on state space approach, a state space model is required. ADALINE (Adaptive Linear Network) method is selected to identify state space model of the system from input-output data. The state space based PID controller is then applied by selecting the appropriate parameters using Ackerman pole placement method. Simulation and experimental results show that the closed loop responses satisfiy the design requirements.

关键词： MATLAB Engines Robustness

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Flood Hazard Assessment of the Eastern Region of Bangkok Floodplain,Thailand

Flood Hazard Assessment of the Eastern Region of Bangkok Flo...

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2012 2nd International Conference on Biotechnology and Environment Management

作者： Yuddhana Keokhumcheng Tawatchai Tingsanchali Faculty of Engineering Rajamangala University of Technology Krungthep Program of Civil and Environmental Engineering Nakhon Pathom Rajabhat University

This research aimed to study the uncertainty of flood hazard assessment for the eastern region of Bangkok floodplain in the surrounding area of the new Bangkok International Airport,*** study was focused on the comparison of flood hazard assessment from the hydrodynamic model simulation and the recent flood occurred in November 2011 within the study *** results from the study provide a comparative study of the flood hazard zones from the hydrodynamic model simulation caused by 100 year rainfall in the study area and that from the actual flood caused by the 100-year rainfall over the Chao Phraya River Basin.

关键词： Flood hazard assessment,Bangkok Floodplain,Suvarnabhumi International Airport

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Analysis of Fluconazole in Human Urine Sample by High Performance Liquid Chromatography Method

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Journal of Physics: Conference Series 2013年第1期423卷

作者： D Hermawan N A Md Ali W A Wan Ibrahim M M Sanagi Separation Science and Technology Group Ibnu Sina Institute for Fundamental Sciences Studies Faculty of Science Universiti Teknologi Malaysia 81310 Johor Bahru Malaysia Chemistry Study Program Faculty of Science and Engineering Jenderal Soedirman University Purwokerto Indonesia

A method for determination of fluconazole, antifungal drug in human urine by using reversed-phased high performance liquid chromatography (RP-HPLC) with ultraviolet (UV) detector was developed. Optimization HPLC conditions were carried out by changing the flow rate and composition of mobile phase. The optimum separation conditions at a flow rate 0.85 mL/min with a composition of mobile phase containing methanol:water (70:30, v/v) with UV detection at a wavelength 254 nm was able to analyze fluconazole within 3 min. The excellent linearity was obtained in the range of concentration 1 to 10 μg/mL with r2 = 0.998. The limit of detection (LOD) and limit of quantitation (LOQ) were 0.39 μg/mL and 1.28 μg/mL, respectively. Solid phase extraction (SPE) method using octadecylsilane (C18) as a sorbent was used to clean-up and pre-concentrated of the urine sample prior to HPLC analysis. The average recoveries of fluconazole in spiked urine sample was 72.4% with RSD of 3.21% (n=3).

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Urban flood disaster management

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Procedia engineering 2012年 32卷 25-37页

作者： T. Tingsanchali Program of Civil and Environmental Engineering Faculty of Science and Technology Nakhon Pathom Rajabhat University Nakhon Pathom 73000 Thailand

Flood impact is one of the most significant disasters in the world. More than half of global flood damages occur in Asia. Causes of floods are due to natural factors such as heavy rainfall, high floods and high tides, etc., and human factors such as blocking of channels or aggravation of drainage channels, improper land use, deforestation in headwater regions, etc. Floods result in losses of life and damage properties. Population increase results in more urbanization, more impervious area and less infiltration and greater flood peak and runoff. Problems become more critical due to more severe and frequent flooding likely caused by climate change, socio-economic damage, population affected, public outcry and limited funds. Flood loss prevention and mitigation includes structural flood control measures such as construction of dams or river dikes and non-structural measures such as flood forecasting and warning, flood hazard and risk management, public participation and institutional arrangement, etc. This paper describes concepts, policy, plan and operation on integrated urban flood disaster and risk management. In most developing countries, flood disaster management activities are handled by government. Participation of nongovernmental agencies and private sectors are very limited. Activities are exercised rather independently without proper coordination or integration. Flood disaster management in developing countries is mostly reactive responding to prevailing disaster situations (emergency response and recovery). Reactive response should be changed to proactive response to increase effectiveness of management and reduce losses of life and properties. Proactive disaster management requires more participation from various governments, non-governmental and private agencies and public participation. It involves more effort and time, more budget, equipments, facilities and human resources which leads to integration of flood disaster management for both long term and sh

关键词： Urban floods Flood disaster management Flood control measures Risk management Thailand

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Prediction of Leachate Generation in a Landfill Using Artificial Neural Networks

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Journal of Environmental Science and engineering(B) 2012年第11期1卷 1233-1238页

作者： Samin Tohru Furuichi Kiasei Ishhi Enri Damanhuri Suprihanto Notodarmodjo Kuntjoro Adji Sidarta Department of Civil Engineering University of Muhammadiyah Malang East Java 062-65144 Indonesia School of Engineering Hokkaido University Sapporo 060-8628 Japan Study Program of Environmental Engineering lnstitut Teknologi Bandung West Java 062-40116 Indonesia Study Program of Mathematic Institut Teknologi Bandung West Java 062-40116 Indonesia

One of the problems encountered in the operation of a leachate treatment in a landfill is the quantity of the fluctuating leachate. Therefore, information on the precise prediction about the quantity of leachate produced in a landfill is required. This information can be obtained by using an ANN （artificial neural networks） model. In this study, a prediction on a leachate generation for a period of 15 days was made. The input for the ANN model consists of data such as rainfall, temperature, humidity, duration of solar radiation, and the landfill characteristics, while the output is the leachate landfills production in Minamiashigara, Japan. The ANN algorithm uses a BP （back propagation） with LM （Levenberg-Marquadrt） training type. By using the input-output data pairs, the training of ANN model was conducted in order to obtain the values of the weights that describe the relationship between the input-output data. Furthermore, with the trained ANN model, the prediction of leachate generation for a period of 15 days was made. The study result shows that the prediction accuracy ofleachate generation of ANN-C model, with a correlation coefficient （r） of 0.924, is quite good. Thus, the prediction of leachate generation using artificial neural network model can be recommended for predicting leachate generation in the future. In this study, a prediction on a leachate generation for a period of 15 days was made. The quantity of leachate generation in a landfill can be obtained by using ANN for future periods. By entering data for future periods （t ＋1） in ANN models, the leachate generation for the period （t ＋1） can be predicted.

关键词： Artificial neural network back-propagation leachate neurons landfills.

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Development Model for Knowledge Management System (KMS) to Improve University's Performance (Case Studies in Indonesia University of Education)

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International Journal of Computer Science Issues 2012年第1 1-1期9卷 1-6页

作者： Munir Rohendi, Dedi Study Program of Computer Science Faculty of Mathematics and Sciences Education Indonesia University of Education Bandung Indonesia Mechanical Engineering Education Department Faculty of Technology and Vocational Education Indonesia University of Education Bandung Indonesia

Knowledge Management System (KMS) is one way to organize and documented the knowledge of institution. The purpose of this study is to develop a prototype KMS in organizing and documenting the knowledge in the university and to do a document aggregation based on the total number, subjects and writers (lecturers). The development method of KMS prototype is using sharepoints which are able to collect, store and publish all digital data available at the university which can be accessed online. Aggregation is using the percentage between the number of documents, subjects, and writers (lecturers). The aggregation's result between the number of digital files compared to the number of courses and the number of lecturers are each below 10%. In the future, the university still needs to encourage all lecturers or academic community to increase the collection of digital files that can indirectly improve the quality and educational services. © 2012 International Journal of Computer Science Issues.

关键词： Knowledge based systems

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ESICM LIVES 2016: part three

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Intensive Care Medicine Experimental 2016年第1期4卷 405-607页

作者： Velasquez, T. Mackey, G. Lusk, J. Kyle, U. G. Fontenot, T. Marshall, P. Shekerdemian, L. S. Coss-Bu, J. A. Nishigaki, A. Yatabe, T. Tamura, T. Yamashita, K. Yokoyama, M. Ruiz-Rodriguez, J. C. Encina, B. Belmonte, R. Troncoso, I. Tormos, P. Riveiro, M. Baena, J. Sanchez, A. Bañeras, J. Cordón, J. Duran, N. Ruiz, A. Caballero, J. Nuvials, X. Riera, J. Serra, J. Rutten, A. M. F. van Ieperen, S. N. M. Der Kinderen, E. P. H. M. Van Logten, T. Kovacikova, L. Skrak, P. Zahorec, M. Akcan-Arikan, A. Silva, J. C. Goldsworthy, M. Wood, D. Harrison, D. Parslow, R. Davis, P. Pappachan, J. Goodwin, S. Ramnarayan, P. Chernyshuk, S. Yemets, H. Zhovnir, V. Pulitano’, S. M. De Rosa, S. Mancino, A. Villa, G. Tosi, F. Franchi, P. Conti, G. Patel, B. Khine, H. Shah, A. Sung, D. Singer, L. Haghbin, S. Inaloo, S. Serati, Z. Idei, M. Nomura, T. Yamamoto, N. Sakai, Y. Yoshida, T. Matsuda, Y. Yamaguchi, Y. Takaki, S. Yamaguchi, O. Goto, T. Longani, N. Medar, S. Abdel-Aal, I. R. El Adawy, A. S. Mohammed, H. M. E. H. Mohamed, A. N. Parry, S. M. Knight, L. D. Denehy, L. De Morton, N. Baldwin, C. E. Sani, D. Kayambu, G. da Silva, V. Z. M. Phongpagdi, P. Puthucheary, Z. A. Granger, C. L. Rydingsward, J. E. Horkan, C. M. Christopher, K. B. McWilliams, D. Jones, C. Reeves, E. Atkins, G. Snelson, C. Aitken, L. M. Rattray, J. Kenardy, J. Hull, A. M. Ullman, A. Le Brocque, R. Mitchell, M. Davis, C. Macfarlane, B. Azevedo, J. C. Rocha, L. L. De Freitas, F. F. M. Cavalheiro, A. M. Lucinio, N. M. Lobato, M. S. Ebeling, G. Kraegpoeth, A. Laerkner, E. De Brito-Ashurst, I. White, C. Gregory, S. Forni, L. G. Flowers, E. Curtis, A. Wood, C. A. Siu, K. Venkatesan, K. Muhammad, J. B. H. Ng, L. Seet, E. Baptista, N. Escoval, A. Tomas, E. Agrawal, R. Mathew, R. Varma, A. Dima, E. Charitidou, E. Perivolioti, E. Pratikaki, M. Vrettou, C. Giannopoulos, A. Zakynthinos, S. Routsi, C. Atchade, E. Houzé, S. Jean-Baptiste, S. Thabut, G. Genève, C. Tanaka, S. Lortat-Jacob, B. Augustin, P. Desmard, M. Montravers, P. de Molina, F. J. González Barbadillo, S. Alejandro, R. Texas Children’s Hospital Clinical Nutriiton Houston USA Texas Children’s Hospital Intensive Care Houston USA Baylor College of Medicine Pediatrics Houston USA Kochi Medical School Department of Anesthesiology and Intensive Care Medicine Nankoku Japan Vall d’ Hebron University Hospital Critical Care Department Barcelona Spain Vall d’ Hebron University Hospital Anesthesia & Reanimation Department Barcelona Spain Vall d’ Hebron University Hospital Neurocritical Care Department Barcelona Spain Vall d’ Hebron University Hospital Coronary Care Unit Barcelona Spain Sagrat Cor University Hospital Critical Care Department Barcelona Spain St Elisabeth Twee Steden Hospital ICU Tilburg Netherlands National Institute of Cardiovascular Diseases PCICU Bratislava Slovakia National Institute of Cardiovascular Diseases Bratislava Slovakia National Institute of Cardiovascular Diseases Pediatric Cardiac Intensive Care Unit Bratislava Slovakia Texas Children’s Hospital Renal Service Houston USA Bristol Royal Hospital for Children Paediatric Intensive Care Unit Bristol UK Intensive Care National Audit & Research Centre (ICNARC) London UK University of Leeds Leeds UK Southampton University Hospitals NHS Trust Southampton UK Great Ormond Street Hospital London UK UCCC ICU Kyiv Ukraine Catholic University Department of Anesthesia and Intensive Care Rome Italy International Renal Research Institute of Vicenza (IRRIV) Department of Nephrology Dialysis and Transplantation Vicenza Italy University of Florence Department of Health Science Section of Anaesthesiology and Intensive Care Florence Italy The Children’s Hospital at Montefiore Pediatric Critical Care Bronx USA The Children’s Hospital at Montefiore Bronx USA Shiraz University of Medical Sciences Pediatric intensive Care Shiraz Islamic Republic of Iran Shiraz University of Medical Sciences Shiraz Islamic Republic of Iran Yokohama City University Hospital Intensive Care Unit Yokohama Japan Yokohama City Univ

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