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CEUR Workshop Proceedings 2022年 3304卷

作者： Jia, Weijia Yin, Jian Hu, Shaolin Peng, Shaoliang Niu, Shaozhang Srinivasa Rao, P.C. Lu, Yao Mirsaeidi, Sohrab Cao, Bin Wu, Yilin Wang, Xingbo Subramaniyam, Kannimuthu Boddu, Raja Sarath Kumar Li, Zhonghua Tao, Qian Zhang, Lei Li, Yi Ding, Deqing Wang, Dahan Zhang, Ziyan AlShawabkeh, Mahmoud Aslam, Muhammad Dib, Omar Sahibuddin, Shamsul Bin Wagh, Sanjeev J. Pardalos, Panos M. Al-Sammarraie, Najeeb Abbas Liu, Linfeng Kong, Jin-Heung Borrego, Carlos Tahir, Sabeen Wu, Zhiheng Li, Jiongcheng Xu, Yong Xie, Zhi Wang, Jiahai Cai, Hongmin Yang, Yuedong Qin, Xiaolin Beijing Normal University Zhuhai China Sun Yat-sen University China Guangdong University of Petrochemical Technology China Hunan University China Beijing University of Posts and Telecommunications China India Beijing Jiaotong University China Hebei University of Technology China Guangdong University of Education China Foshan University China Karpagam College of Engineering India Lenora College of Engineerin India Yat-sen University Guangdong High Performance Computing Society China South China University of Technology China Henan University China Wenzhou University China National University of Defense Technology China Xiamen University of Technology China Hainan Tropical Ocean University China Guangxi Normal University for Nationalities China Wuhan University China Wenzhou-Kean University China School of Software Engineering Universiti Teknologi Malaysia Information Technology Government College of Engineering Karad India Department of Industrial & Systems Engineering University of Florida United States Al-Madinah International University Faculty of Computer and Information Technology Malaysia School of Computer Science and Technology Nanjing University of Posts and Telecommunications China School of Computer and Information Engineering Kwangwoon University Korea Republic of Departament Enginyeria of Information Comunicacions Autonomous University of Barcelona Spain Information Technology Department King AbdulAziz University Jeddah Saudi Arabia Institute of Manufacturing GDAS China Guangdong Planning and Designing Institute of Telecommunications Co. Ltd China Guangzhou Institutes of Biomedicine and Health Chinese Academy of Sciences China Cheng Du Information Technology of Chinese Academy of Sciences Co. Ltd China

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Mining smartphone generated data for user action recognition – Preliminary assessment

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AIP Conference Proceedings 2018年第1期2025卷

作者： J. Fijalkowski M. Ganzha M. Paprzycki S. Fidanova I. Lirkov C. Badica M. Ivanovic 1Faculty of Mathematics and Information Sciences Warsaw University of Technology ul. Koszykowa 75 00-662 Warsaw Poland 7LeanCode sp. z o.o. ul. Mokotowska 46A/25 00-543 Warsaw Poland 2Systems Research Institute Polish Academy of Sciences ul. Newelska 6 01-447 Warsaw Poland 6Warsaw Management Academy ul. Kaweczynska 36 03-772 Warsaw Poland 3Institute of Information and Communication Technologies Bulgarian Academy of Sciences Acad. G. Bonchev bl. 25A 1113 Sofia Bulgaria 4Software Engineering Department Faculty of Automatics Computers and Electronics 107 Decebal Blvd. Craiova RO-200440 Romania 5University of Novi Sad Faculty of Sciences Department of Mathematics and Informatics Trg D. Obradovica 4 Novi Sad Serbia

Smartphones became everyday “companions” of humans. Almost everyone has a smartphone in their pocket, or bag, and use it on daily basis. Modern smartphones are “loaded” with sensors, providing streams of, potentially useful, data. Simultaneously, staying fit, exercising, running, swimming, etc. became fashionable. In this “climate”, employers can try to incentivise their workers, for instance, to use bicycles to come to work. Here, one of interesting questions becomes: are workers actually using bicycles, as declared, or do they try to subvert the system and win prizes, while, for instance, using public transport. One of the ways to check this could be to use data from smartphone sensors to determine the mode of transportation that has been *** paper presents preliminary results of an attempt at using raw sensor data and deep learning techniques for transportation mode detection, in real-time, directly on smartphone. The work tries to balance sensor power consumption and computational requirements with prediction correctness and response time. In this context, results of application of recurrent neural networks, as well as more traditional approaches, to a set of actual mobility data, are presented. Furthermore, approaches that leverage domain knowledge, in order to make classifiers more reliable and requiring less processing power (and less energy), are considered.

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Varying the Stiffness and Diffusivity of Rod-Shaped Microgels Independently through Their Molecular Building Blocks

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Angewandte Chemie 2023年第44期135卷

作者： Yonca Kittel Luis P. B. Guerzoni Carolina Itzin Dirk Rommel Matthias Mork Céline Bastard Bernhard Häßel Abdolrahman Omidinia-Anarkoli Silvia P. Centeno Tamás Haraszti Kyoohyun Kim Jochen Guck Alexander J. C. Kuehne Laura De Laporte DWI-Leibniz Institute for Interactive Materials e. V. Forckenbeckstraße 50 52074 Aachen Germany Institute of Technical and Macromolecular Chemistry RWTH Aachen University Worringerweg 1–2 52074 Aachen Germany Institute of Organic and Macromolecular Chemistry Ulm University Albert-Einstein Allee 11 89081 Ulm Germany Contribution: Conceptualization (equal) Data curation (lead) Formal analysis (lead) Investigation (lead) Project administration (lead) Visualization (lead) Writing - original draft (lead) Contribution: Conceptualization (equal) Investigation (supporting) Supervision (supporting) Writing - review & editing (supporting) Contribution: Investigation (supporting) Validation (supporting) Visualization (supporting) Writing - review & editing (equal) Contribution: Conceptualization (supporting) Investigation (supporting) Validation (supporting) Writing - review & editing (equal) Contribution: Conceptualization (supporting) Formal analysis (supporting) Investigation (supporting) Visualization (supporting) Writing - review & editing (equal) Center for Biohybrid Medical Systems (CBMS) Advanced Materials for Biomedicine (AMB) Institute of Applied Medical Engineering (AME) Forckenbeckstraße 55 52074 Aachen Germany Contribution: Conceptualization (supporting) Validation (supporting) Visualization (supporting) Writing - original draft (supporting) Writing - review & editing (equal) Contribution: Formal analysis (equal) Software (lead) Validation (supporting) Visualization (supporting) Writing - original draft (supporting) Writing - review & editing (equal) Max Planck Institute for the Science of Light and Max-Planck-Zentrum für Physik und Medizin Staudtstraße 2 91058 Erlangen Germany Contribution: Conceptualization (supporting) Investigation (supporting) Software (supporting) Validation (supporting) Visualization (supporting) Writing - original draft (supporting) Writing - review & editing (equal) Contribution: Conceptualization (supporting) Writing - review

Microgels are water-swollen, crosslinked polymers that are widely used as colloidal building blocks in scaffold materials for tissue engineering and regenerative medicine. Microgels can be controlled in their stiffness, degree of swelling, and mesh size depending on their polymer architecture, crosslink density, and fabrication method—all of which influence their function and interaction with the environment. Currently, there is a lack of understanding of how the polymer composition influences the internal structure of soft microgels and how this morphology affects specific biomedical applications. In this report, we systematically vary the architecture and molar mass of polyethylene glycol-acrylate (PEG-Ac) precursors, as well as their concentration and combination, to gain insight in the different parameters that affect the internal structure of rod-shaped microgels. We characterize the mechanical properties and diffusivity, as well as the conversion of acrylate groups during photopolymerization, in both bulk hydrogels and microgels produced from the PEG-Ac precursors. Furthermore, we investigate cell-microgel interaction, and we observe improved cell spreading on microgels with more accessible RGD peptide and with a stiffness in a range of 20 kPa to 50 kPa lead to better cell growth.

关键词： Diffusion Internal Structure Mechanical Properties Microfluidics PEG Microgels

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Multimodal bioimaging across disciplines and scales: challenges, opportunities and breaking down barriers

npj Imaging

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npj Imaging 2024年第1期2卷 1-6页

作者： Johanna Bischof Antje Keppler Georgina Fletcher Maddy Parsons Paul Verkade Claudia Kuntner Julia Fernandez-Rodriguez Linda Chaabane Leor Ariel Rose Assaf Zaritsky Andreas Walter Michiel Vandenbosch Marc A. M. J. van Zandvoort Euro-BioImaging ERIC Bio-Hub European Molecular Biology Laboratory (EMBL) Heidelberg Meyerhofstraße 1 69117 Heidelberg Germany BioImagingUK and Royal Microscopical Society 37/38 St Clements Oxford Oxford OX4 1AJ UK Randall Centre for Cell and Molecular Biophysics King’s College London Guy’s Campus London SE1 1UL UK School of Biochemistry University of Bristol Bristol BS8 1TD UK Department of Biomedical Imaging and Image-guided Therapy Medical University of Vienna Vienna Austria Centre for Cellular Imaging Sahlgrenska Academy University of Gothenburg SE-405 30 Gothenburg Sweden Euro-BioImaging ERIC Med-Hub Institute of Biostructures and Bioimaging (IBB) Italian National Research Council (CNR) Via Nizza 52 Torino 10126 Italy Department of Software and Information Systems Engineering Ben-Gurion University of the Negev Beer-Sheva 84105 Israel Center of Optical Technologies Aalen University Aalen Germany Department FHML Maastricht University Maastricht Multimodal Molecular imaging institute Maastricht The Netherlands Department of Genetics and Cell Biology Maastricht University Institutes CARIM GROW and MHeNS Maastricht the Netherlands Institute for Molecular Cardiovascular Research (IMCAR) RWTH Aachen University Clinic Aachen Germany

Multimodal bioimaging is a broad term used to describe experimental workflows that employ two or more different imaging modalities. Such approaches have been in use across life science domains for several years but these remain relatively limited in scope, in part due to the complexity of undertaking these types of analysis. Expanding these workflows to encompass diverse, emerging technology holds potential to revolutionize our understanding of spatial biology. In this perspective we reflect on the instrument and workflows in current use, emerging areas to consider and our experience of the barriers to broader adoption and progress. We propose several enabling solutions across the different challenge areas, emerging opportunities for consideration and highlight some of the key community activities to help move the field forward.

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NWChem: Past, present, and future

arXiv

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arXiv 2020年

作者： Aprà, E. Bylaska, E.J. de Jong, W.A. Govind, N. Kowalski, K. Straatsma, T.P. Valiev, M. van Dam, H.J.J. Alexeev, Y. Anchell, J. Anisimov, V. Aquino, F.W. Atta-Fynn, R. Autschbach, J. Bauman, N.P. Becca, J.C. Bernholdt, D.E. Bhaskaran-Nair, K. Bogatko, S. Borowski, P. Boschen, J. Brabec, J. Bruner, A. Cauët, E. Chen, Y. Chuev, G.N. Cramer, C.J. Daily, J. Deegan, M.J.O. Dunning, T.H. Dupuis, M. Dyall, K.G. Fann, G.I. Fischer, S.A. Fonari, A. Früchtl, H. Gagliardi, L. Garza, J. Gawande, N. Ghosh, S. Glaesemann, K. Götz, A.W. Hammond, J. Helms, V. Hermes, E.D. Hirao, K. Hirata, S. Jacquelin, M. Jensen, L. Johnson, B.G. Jónsson, H. Kendall, R.A. Klemm, M. Kobayashi, R. Konkov, V. Krishnamoorthy, S. Krishnan, M. Lin, Z. Lins, R.D. Littlefield, R.J. Logsdail, A.J. Lopata, K. Ma, W. Marenich, A.V. Martin del Campo, J. Mejia-Rodriguez, D. Moore, J.E. Mullin, J.M. Nakajima, T. Nascimento, D.R. Nichols, J.A. Nichols, P.J. Nieplocha, J. Otero-de-la-Roza, A. Palmer, B. Panyala, A. Pirojsirikul, T. Peng, B. Peverati, R. Pittner, J. Pollack, L. Richard, R.M. Sadayappan, P. Schatz, G.C. Shelton, W.A. Silverstein, D.W. Smith, D.M.A. Soares, T.A. Song, D. Swart, M. Taylor, H.L. Thomas, G.S. Tipparaju, V. Truhlar, D.G. Tsemekhman, K. van Voorhis, T. Vázquez-Mayagoitia, Á. Verma, P. Villa, O. Vishnu, A. Vogiatzis, K.D. Wang, D. Weare, J.H. Williamson, M.J. Windus, T.L. Woliński, K. Wong, A.T. Wu, Q. Yang, C. Yu, Q. Zacharias, M. Zhang, Z. Zhao, Y. Harrison, R.J. Pacific Northwest National Laboratory RichlandWA99352 United States Lawrence Berkeley National Laboratory BerkeleyCA94720 United States National Center for Computational Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Brookhaven National Laboratory UptonNY11973 United States Argonne Leadership Computing Facility Argonne National Laboratory ArgonneIL60439 United States Intel Corporation Santa ClaraCA95054 United States QSimulate CambridgeMA02139 United States Department of Physics University of Texas at Arlington ArlingtonTX76019 United States Department of Chemistry University at Buffalo State University of New York BuffaloNY14260 United States Department of Chemistry Pennsylvania State University University ParkPA16802 United States Oak Ridge National Laboratory Oak RidgeTN37831 United States Washington University St. LouisMO63130 United States 4G Clinical WellesleyMA02481 United States Faculty of Chemistry Maria Curie-Sklodowska University in Lublin Lublin20-031 Poland Department of Chemistry Iowa State University AmesIA50011 United States J. Heyrovský Institute of Physical Chemistry Academy of Sciences of the Czech Republic Prague 818223 Czech Republic Department of Chemistry and Physics University of Tennessee at Martin MartinTN38238 United States Université libre de Bruxelles BrusselsB-1050 Belgium Facebook Menlo ParkCA94025 United States Institute of Theoretical and Experimental Biophysics Russian Academy of Science Pushchino Moscow142290 Russia Department of Chemistry Chemical Theory Center Supercomputing Institute University of Minnesota MinneapolisMN55455 United States SKAO Jodrell Bank Observatory MacclesfieldSK11 9DL United Kingdom Department of Chemistry University of Washington SeattleWA98195 United States Dirac Solutions PortlandOR97229 United States Chemistry Division U. S. Naval Research Laboratory WashingtonDC20375 United States School of Chemistry and Biochemis

Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the last few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach and outlook. Copyright © 2020, The Authors. All rights reserved.

关键词： Computational chemistry

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Author Correction: Immunogenicity and efficacy of fourth BNT162b2 and mRNA1273 COVID-19 vaccine doses;three months follow-up

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Nature communications 2023年第1期14卷 1593页

作者： Michal Canetti Noam Barda Mayan Gilboa Victoria Indenbaum Michal Mandelboim Tal Gonen Keren Asraf Yael Weiss-Ottolenghi Sharon Amit Ram Doolman Ella Mendelson Dror Harats Laurence S Freedman Yitshak Kreiss Yaniv Lustig Gili Regev-Yochay The Infection Prevention & Control Unit Sheba Medical Center Tel Hashomer Ramat Gan Israel. Sackler School of Medicine Tel-Aviv University Tel Aviv Israel. ARC Innovation Center Sheba Medical Center Tel Hashomer Ramat Gan Israel. Software and Information Systems Engineering Ben-Gurion University of the Negev Be'er Sheva Israel. Department of Biomedical Informatics Harvard Medical School Boston MA USA. Central Virology Laboratory Public Health Services Ministry of Health Tel-Hashomer Ramat Gan Israel. The Dworman Automated-Mega Laboratory Sheba Medical Center Tel-Hashomer Ramat-Gan Israel. Clinical Microbiology Sheba Medical Center Tel Hashomer Ramat Gan Israel. General Management Sheba Medical Center Tel Hashomer Ramat Gan Israel. Biostatistics and Biomathematics Unit Gertner Institute of Epidemiology and Health Policy Research Sheba Medical Center Tel Hashomer Israel. Vaccine Research Center National Institute of Allergy and Infectious Diseases National Institutes of Health Bethesda MD USA. The Infection Prevention & Control Unit Sheba Medical Center Tel Hashomer Ramat Gan Israel. Gili.Regev@sheba.health.gov.il. Sackler School of Medicine Tel-Aviv University Tel Aviv Israel. Gili.Regev@sheba.health.gov.il.

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Author Correction: Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

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Scientific data 2021年第1期8卷 242页

作者： Julien Cohen-Adad Eva Alonso-Ortiz Mihael Abramovic Carina Arneitz Nicole Atcheson Laura Barlow Robert L Barry Markus Barth Marco Battiston Christian Büchel Matthew Budde Virginie Callot Anna J E Combes Benjamin De Leener Maxime Descoteaux Paulo Loureiro de Sousa Marek Dostál Julien Doyon Adam Dvorak Falk Eippert Karla R Epperson Kevin S Epperson Patrick Freund Jürgen Finsterbusch Alexandru Foias Michela Fratini Issei Fukunaga Claudia A M Gandini Wheeler-Kingshott Giancarlo Germani Guillaume Gilbert Federico Giove Charley Gros Francesco Grussu Akifumi Hagiwara Pierre-Gilles Henry Tomáš Horák Masaaki Hori James Joers Kouhei Kamiya Haleh Karbasforoushan Miloš Keřkovský Ali Khatibi Joo-Won Kim Nawal Kinany Hagen H Kitzler Shannon Kolind Yazhuo Kong Petr Kudlička Paul Kuntke Nyoman D Kurniawan Slawomir Kusmia René Labounek Maria Marcella Laganà Cornelia Laule Christine S Law Christophe Lenglet Tobias Leutritz Yaou Liu Sara Llufriu Sean Mackey Eloy Martinez-Heras Loan Mattera Igor Nestrasil Kristin P O'Grady Nico Papinutto Daniel Papp Deborah Pareto Todd B Parrish Anna Pichiecchio Ferran Prados Àlex Rovira Marc J Ruitenberg Rebecca S Samson Giovanni Savini Maryam Seif Alan C Seifert Alex K Smith Seth A Smith Zachary A Smith Elisabeth Solana Y Suzuki George Tackley Alexandra Tinnermann Jan Valošek Dimitri Van De Ville Marios C Yiannakas Kenneth A Weber Ii Nikolaus Weiskopf Richard G Wise Patrik O Wyss Junqian Xu NeuroPoly Lab Institute of Biomedical Engineering Polytechnique Montreal Montreal QC Canada. jcohen@polymtl.ca. Functional Neuroimaging Unit CRIUGM Université de Montréal Montreal QC Canada. jcohen@polymtl.ca. Mila - Quebec AI Institute Montreal QC Canada. jcohen@polymtl.ca. NeuroPoly Lab Institute of Biomedical Engineering Polytechnique Montreal Montreal QC Canada. Department of Radiology Swiss Paraplegic Centre Nottwil Switzerland. Centre for Advanced Imaging The University of Queensland Brisbane Australia. Department of Radiology University of British Columbia Vancouver BC Canada. Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Charlestown MA USA. Department of Radiology Harvard Medical School Boston MA USA. Harvard-Massachusetts Institute of Technology Health Sciences & Technology Cambridge MA USA. School of Information Technology and Electrical Engineering The University of Queensland Brisbane Australia. NMR Research Unit Queen Square MS Centre UCL Queen Square Institute of Neurology Faculty of Brain Sciences University College London London UK. Department of Systems Neuroscience University Medical Center Hamburg-Eppendorf Hamburg Germany. Department of Neurosurgery Medical College of Wisconsin Milwaukee WI USA. Aix-Marseille Univ CNRS CRMBM Marseille France. APHM Hopital Universitaire Timone CEMEREM Marseille France. Vanderbilt University Institute of Imaging Science Vanderbilt University Medical Center Nashville TN USA. Department of Computer and Software Engineering Polytechnique Montreal Montreal Canada. CHU Sainte-Justine Research Centre Montreal QC Canada. Centre de Recherche CHUS CIMS Sherbrooke Canada. Sherbrooke Connectivity Imaging Lab (SCIL) Computer Science department Université de Sherbrooke Sherbrooke Canada. Université de Strasbourg CNRS ICube Strasbourg France. UHB - University Hospital Brno and Masaryk University Department of Radiology and Nuclear

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OC6 Phase I: Investigating the underprediction of low-frequency hydrodynamic loads and responses of a floating wind turbine

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Journal of Physics: Conference Series 2020年第3期1618卷

作者： A N Robertson S Gueydon E Bachynski L Wang J Jonkman D Alarcón E Amet A Beardsell P Bonnet B Boudet C Brun Z Chen M Féron D Forbush C Galinos J Galvan P Gilbert J Gómez V Harnois F Haudin Z Hu J Le Dreff M Leimeister F Lemmer H Li G Mckinnon I Mendikoa A Moghtadaei S Netzband S Oh A Pegalajar-Jurado M Q Nguyen K Ruehl P Schünemann W Shi H Shin Y Si F Surmont P Trubat J Qwist S Wohlfahrt-Laymann National Renewable Energy Laboratory 15013 Denver W Pkwy Golden CO USA 80401 Maritime Research Institute Netherlands Haagsteeg 2 6708 PM Wageningen Netherlands Norwegian University of Science and Technology 7491 Trondheim Norway Bureau Veritas 60 avenue du Général de Gaulle 92046 Paris - La Défense DNV GL One Linear Park Avon St. Temple Quay Bristol BS2 0PS UK Siemens Digital Industries Software C/Lluis Muntadas 5 Cornellà Spain 08940 Bureau Veritas 8 avenue Jacques Cartier Atlantis - 44807 Saint-Herblain Cdx - France Ocean College Zhejiang University Zhoushan 316021 China DORIS Engineering 58a rue du Dessous des Berges 75013 Paris France Sandia National Laboratories 1515 Eubank Blvd SE Albuquerque NM 87123 DTU Wind Energy Nils Koppels Allé 403 Kgs. Lyngby DK-2800 Denmark Tecnalia Research & Innovation Parque Tecnologico Bizkaia Ed.700 48160 Derio Spain IFPEN 4 avenue de Bois Préau 92852 Rueil-Malmaison Cedex France PRINCIPIA ZAC Athelia I - 215 Voie Ariane 13705 La CIOTAT Cedex France Vulcain Ingénierie 5 rue Beffroy 92200 Neuilly-sur-Seine France School of Engineering Newcastle University Newcastle upon Tyne NE1 7RU UK EDF R&D 7 boulevard Gaspard Monge 91120 Palaiseau France Fraunhofer Inst. for Wind Energy Systems Am Luneort 100 27572 Bremerhaven Germany University of Stuttgart 70569 Stuttgart Germany Orcina Ltd. Daltongate Ulverston Cumbria LA12 7AJ UK Queen's University Belfast Belfast BT9 5AG Northern Ireland United Kingdom Hamburg University of Technology 21071 Hamburg Germany ClassNK 4-7 Kioicho Chiyodaku Tokyo Japan Universität Rostock Albert-Einstein-Str. 2 18059 Rostock Germany Dalian University of Technology No.2 Linggong Road Dalian Liaoning China 116024 University of Ulsan 93 Daehakro Namgu Ulsan 44610 South Korea Universitat Politècnica de Catalunya Jordi Girona 1-3 08034 Barcelona Spain 4Subsea Hagaløkkveien 26 1383 Asker Norway

Phase I of the OC6 project is focused on examining why offshore wind design tools underpredict the response (loads/motion) of the OC5-DeepCwind semisubmersible at its surge and pitch natural frequencies. Previous investigations showed that the underprediction was primarily related to nonlinear hydrodynamic loading, so two new validation campaigns were performed to separately examine the different hydrodynamic load components. In this paper, we validate a variety of tools against this new test data, focusing on the ability to accurately model the low-frequency loads on a semisubmersible floater when held fixed under wave excitation and when forced to oscillate in the surge direction. However, it is observed that models providing better load predictions in these two scenarios do not necessarily produce a more accurate motion response in a moored configuration.

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Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

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Human genomics 2016年第1期10 Suppl 1卷 12页

作者： A. K. Srivastava Y. Wang R. Huang C. Skinner T. Thompson L. Pollard T. Wood F. Luo R. Stevenson R. Polimanti J. Gelernter X. Lin I. Y. Lim Y. Wu A. L. Teh L. Chen I. M. Aris S. E. Soh M. T. Tint J. L. MacIsaac F. Yap K. Kwek S. M. Saw M. S. Kobor M. J. Meaney K. M. Godfrey Y. S. Chong J. D. Holbrook Y. S. Lee P. D. Gluckman N. Karnani A. Kapoor D. Lee A. Chakravarti C. Maercker F. Graf M. Boutros G. Stamoulis F. Santoni P. Makrythanasis A. Letourneau M. Guipponi N. Panousis M. Garieri P. Ribaux E. Falconnet C. Borel S. E. Antonarakis S. Kumar J. Curran J. Blangero S. Chatterjee J. Akiyama D. Auer C. Berrios L. Pennacchio T. R. Donti G. Cappuccio M. Miller P. Atwal A. Kennedy A. Cardon C. Bacino L. Emrick J. Hertecant F. Baumer B. Porter M. Bainbridge P. Bonnen B. Graham R. Sutton Q. Sun S. Elsea Z. Hu P. Wang Y. Zhu J. Zhao M. Xiong David A. Bennett A. Hidalgo-Miranda S. Romero-Cordoba S. Rodriguez-Cuevas R. Rebollar-Vega E. Tagliabue M. Iorio E. D’Ippolito S. Baroni B. Kaczkowski Y. Tanaka H. Kawaji A. Sandelin R. Andersson M. Itoh T. Lassmann Y. Hayashizaki P. Carninci A. R. R. Forrest C. A. Semple E. A. Rosenthal B. Shirts L. Amendola C. Gallego M. Horike-Pyne A. Burt P. Robertson P. Beyers C. Nefcy D. Veenstra F. Hisama R. Bennett M. Dorschner D. Nickerson J. Smith K. Patterson D. Crosslin R. Nassir N. Zubair T. Harrison U. Peters G. Jarvik F. Menghi K. Inaki X. Woo P. Kumar K. Grzeda A. Malhotra H. Kim D. Ucar P. Shreckengast K. Karuturi J. Keck J. Chuang E. T. Liu B. Ji A. Tyler G. Ananda G. Carter H. Nikbakht M. Montagne M. Zeinieh A. Harutyunyan M. Mcconechy N. Jabado P. Lavigne J. Majewski J. B. Goldstein M. Overman G. Varadhachary R. Shroff R. Wolff M. Javle A. Futreal D. Fogelman L. Bravo W. Fajardo H. Gomez C. Castaneda C. Rolfo J. A. Pinto K. C. Akdemir L. Chin S. Patterson C. Statz S. Mockus S. N. Nikolaev X. I. Bonilla L. Parmentier B. King F. Bezrukov G. Kaya V. Zoete V. Seplyarskiy H. Sharpe T. McKee K. Popadin N. Basset-Seguin R. Ben Chaabene M. Andrianova C. Verdan K. Grosdemange O. Sumara M. E JCSRI Greenwood Genetic Center Greenwood USA School of Computing Clemson University Clemson USA Biochemical Genetics Laboratory Greenwood Genetic Center Greenwood USA Department Psychiatry Yale Sch Med and VA CT Healthcare Center West Haven USA Department Genetics Yale Sch Med and VA CT Healthcare Center West Haven USA Department Neurobiology Yale Sch Med and VA CT Healthcare Center West Haven USA Singapore Institute for Clinical Sciences Singapore Singapore National University of Singapore Singapore Singapore University of British Columbia Vancouver Canada KK Women’s and Children’s Hospital Singapore Singapore University of Southampton and University Hospital Southampton NHS Foundation Trust Southampton UK University of Auckland Auckland New Zealand McKusick-Nathans Institute of Genetic Medicine Johns Hopkins University School of Medicine Baltimore USA Esslingen University of Applied Sciences Esslingen Germany German Cancer Research Center Heidelberg Germany Department of Genetic Medicine and Development University of Geneva Medical School Geneva Switzerland Geneva University Hospitals-HUG Service of Genetic Medicine Geneva Switzerland GE3 Institute of Genetics and Genomics of Geneva University of Geneva Medical School Geneva Switzerland South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Edinburg USA South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Brownsville USA Institute of Genetic Medicine Johns Hopkins University Baltimore USA Genomics Division Lawrence Berkeley National Laboratory Berkeley USA Molecular and Human Genetics Baylor College of Medicine Houston USA Department of Translational Medical Sciences Federico II University Naples Italy Metabolon Inc Durham USA Section of Pediatric Neurology and Neuroscience Baylor College of Medicine Houston USA Tawam Hospital Abu Dhabi United Arab Emirates Stanford Medical School Stanford USA Sch

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s

关键词： Pulmonary Arterial Hypertension Oral Squamous Cell Carcinoma Deep Neural Network Autosomal Recessive Polycystic Kidney Disease Whole Genome Bisulfite Sequencing

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