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Author Correction: Deep learning and genome-wide association meta-analyses of bone marrow adiposity in the UK Biobank

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Nature communications 2025年第1期16卷 4331页

作者： Wei Xu Ines Mesa-Eguiagaray David M Morris Chengjia Wang Calum D Gray Samuel Sjöström Giorgos Papanastasiou Sammy Badr Julien Paccou Xue Li Paul R H J Timmers Maria Timofeeva Susan M Farrington Malcolm G Dunlop Scott I Semple Tom MacGillivray Evropi Theodoratou William P Cawthorn Centre for Global Health and Molecular Epidemiology Usher Institute University of Edinburgh Edinburgh UK. University/BHF Centre for Cardiovascular Science University of Edinburgh The Queen's Medical Research Institute Edinburgh BioQuarter 47 Little France Crescent Edinburgh UK. Edinburgh Imaging University of Edinburgh The Queen's Medical Research Institute Edinburgh BioQuarter 47 Little France Crescent Edinburgh UK. School of Mathematics and Computer Sciences Heriot-Watt University Edinburgh UK. Archimedes Unit Athena Research Centre Marousi Greece. Univ. Lille CHU Lille Marrow Adiposity and Bone Laboratory (MABlab) ULR 4490 Department of Rheumatology Lille France. Department of Big Data in Health Science School of Public Health and The Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou China. Medical Research Council Human Genetics Unit Medical Research Council Institute of Genetics & Molecular Medicine University of Edinburgh Edinburgh UK. Danish Institute for Advanced Study (DIAS) Epidemiology Biostatistics and Biodemography Department of Public Health University of Southern Denmark Odense Denmark. Cancer Research UK Edinburgh Centre Medical Research Council Institute of Genetics and Cancer University of Edinburgh Edinburgh UK. Colon Cancer Genetics Group Institute of Genetics and Cancer University of Edinburgh Edinburgh UK. Centre for Clinical Brain Sciences University of Edinburgh The Queen's Medical Research Institute Edinburgh BioQuarter 47 Little France Crescent Edinburgh UK. Centre for Global Health and Molecular Epidemiology Usher Institute University of Edinburgh Edinburgh UK. E.Theodoratou@ed.ac.uk. Edinburgh Cancer Research Centre Institute of Genetics and Molecular Medicine University of Edinburgh Edinburgh UK. E.Theodoratou@ed.ac.uk. University/BHF Centre for Cardiovascular Science University of Edinburgh The Queen's Medical Research Institute Edinburgh BioQuarter 47 Little France Crescent Edinburgh UK. W.

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Exploring interaction modalities and task allocation for household robotic arms

Exploring interaction modalities and task allocation for hou...

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34th Annual CHI Conference on human Factors in Computing Systems, CHI EA 2016

作者： Herr, Sascha Gross, Tom Gradmann, Michael Henrich, Dominik Human-Computer Interaction Group University of Bamberg Germany Department for Applied Computer Science III University of Bayreuth Germany

ISBN: (纸本)9781450340823

human-robot interaction in private households demands easy and natural interfaces, as well as an understanding of areas of application. Two fundamental issues are multimodal interaction (i.e., multifarious ways of communication with the robot) and task allocation (i.e., division of labour between the user and the robot). We report on an explorative interview study that gathered users' requirements for multimodal interaction and gained understanding for task allocation in private households. © 2016 Authors.

关键词： human robot interaction

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Personal fabrication

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Communications of the ACM 2017年第10期60卷 48-49页

作者： Mueller, Stephanie Baudisch, Patrick MIT's Electrical Engineering and Computer Science Department United States MIT CSAIL United States Hasso Plattner Institute Potsdam University Germany Human Computer Interaction Lab United States

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The sea lamprey germline genome provides insights into programmed genome rearrangement and vertebrate evolution (vol 50, pg 270, 2018)

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NATURE GENETICS 2018年第11期50卷 1617-1617页

作者： Smith, Jeramiah J. Timoshevskaya, Nataliya Ye, Chengxi Holt, Carson Keinath, Melissa C. Parker, Hugo J. Cook, Malcolm E. Hess, Jon E. Narum, Shawn R. Lamanna, Francesco Kaessmann, Henrik Timoshevskiy, Vladimir A. Waterbury, Courtney K. M. Saraceno, Cody Wiedemann, Leanne M. Robb, Sofia M. C. Baker, Carl Eichler, Evan E. Hockman, Dorit Sauka-Spengler, Tatjana Yandell, Mark Krumlauf, Robb Elgar, Greg Amemiya, Chris T. Department of Biology University of Kentucky Lexington KY USA Department of Computer Science University of Maryland College Park MD USA Department of Human Genetics University of Utah Salt Lake City UT USA Stowers Institute for Medical Research Kansas City MO USA Columbia River Inter-Tribal Fish Commission Portland OR USA Center for Molecular Biology of Heidelberg University (ZMBH) DKFZ-ZMBH Alliance Heidelberg Germany Department of Pathology and Laboratory Medicine University of Kansas School of Medicine Kansas City KS USA Department of Anatomy & Cell Biology The University of Kansas School of Medicine Kansas City KS USA Department of Genome Sciences University of Washington School of Medicine Seattle WA USA Howard Hughes Medical Institute University of Washington Seattle WA USA Radcliffe Department of Medicine University of Oxford Oxford England The Francis Crick Institute London England Benaroya Research Institute Seattle WA USA Division of Cell Biology Department of Anatomy Faculty of Health Sciences University of Cape Town Cape Town South Africa

The sea lamprey (Petromyzon marinus) serves as a comparative model for reconstructing vertebrate evolution. To enable more informed analyses, we developed a new assembly of the lamprey germline genome that integrates several complementary data sets. Analysis of this highly contiguous (chromosome-scale) assembly shows that both chromosomal and whole-genome duplications have played significant roles in the evolution of ancestral vertebrate and lamprey genomes, including chromosomes that carry the six lamprey HOX clusters. The assembly also contains several hundred genes that are reproducibly eliminated from somatic cells during early development in lamprey. Comparative analyses show that gnathostome (mouse) homologs of these genes are frequently marked by polycomb repressive complexes (PRCs) in embryonic stem cells, suggesting overlaps in the regulatory logic of somatic DNA elimination and bivalent states that are regulated by early embryonic PRCs. This new assembly will enhance diverse studies that are informed by lampreys’ unique biology and evolutionary/comparative perspective.

关键词： Developmental biology Epigenomics Genomics Sequencing

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Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

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The Lancet 2020年第10258期396卷 1204-1222页

作者： Abbafati, Cristiana Abbas, Kaja M. Abbasi, Mohammad Abbasifard, Mitra Abbasi-Kangevari, Mohsen Abbastabar, Hedayat Abd-Allah, Foad Abdelalim, Ahmed Abdollahi, Mohammad Abdollahpour, Ibrahim Abedi, Aidin Abedi, Parisa Abegaz, Kedir Hussein Abolhassani, Hassan Abosetugn, Akine Eshete Aboyans, Victor Abrams, Elissa M. Abreu, Lucas Guimarães Abrigo, Michael R.M. Abu Haimed, Abdulaziz Khalid Abualhasan, Ahmed Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Abushouk, Abdelrahman I. Acebedo, Alyssa Ackerman, Ilana N. Adabi, Maryam Adair, Tim Adamu, Abdu A. Adebayo, Oladimeji M. Adedeji, Isaac Akinkunmi Adekanmbi, Victor Adelson, Jaimie D. Adeoye, Abiodun Moshood Adetokunboh, Olatunji O. Adham, Davoud Advani, Shailesh M. Afarideh, Mohsen Afshari, Mahdi Afshin, Ashkan Agardh, Emilie E. Agarwal, Gina Agasthi, Pradyumna Agesa, Kareha M. Aghaali, Mohammad Aghamir, Seyed Mohammad Kazem Agrawal, Anurag Ahmad, Tauseef Ahmadi, Alireza Ahmadi, Keivan Ahmadi, Mehdi Ahmadieh, Hamid Ahmadpour, Ehsan Ahmed, Muktar Beshir Aji, Budi Akalu, Temesgen Yihunie Akinyemi, Rufus Olusola Akinyemiju, Tomi Akombi, Blessing Akunna, Chisom Joyqueenet Alahdab, Fares Al-Aly, Ziyad Alam, Khurshid Alam, Noore Alam, Samiah Alam, Tahiya Alanezi, Fahad Mashhour Alanzi, Turki M. Albertson, Samuel B. Alcalde-Rabanal, Jacqueline Elizabeth Alema, Niguse Meles Alemu, Biresaw Wassihun Alemu, Yihun Mulugeta Alhabib, Khalid F. Alhassan, Robert Kaba Ali, Muhammad Ali, Saqib Alicandro, Gianfranco Alijanzadeh, Mehran Alinia, Cyrus Alipour, Vahid Alizade, Hesam Aljunid, Syed Mohamed Alla, François Allebeck, Peter Almadi, Majid Abdulrahman Hamad Almasi, Ali Almasi-Hashiani, Amir Almasri, Nihad A. Al-Mekhlafi, Hesham M. Almulhim, Abdulaziz M. Alonso, Jordi Al-Raddadi, Rajaa M. Altirkawi, Khalid A. Alumran, Arwa Khalid Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Amare, Bekalu Amini, Saeed Amini-Rarani, Mostafa Aminorroaya, Arya Amiri, Fatemeh Amit, Arianna Maever L. Amugsi, Dickson A. Amul, Gianna Gayle Herrera Anbesu, Etsay Woldu Ancuceanu, Robert Anderl Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Infectious Disease Epidemiology London School of Hygiene and Tropical Medicine London United Kingdom Social Determinants of Health Research Center Tehran Iran Department of Neurology Cairo University Cairo Egypt School of Pharmacy Tehran Iran The Institute of Pharmaceutical Sciences (TIPS) Tehran Iran Neuroscience Research Center Isfahan University of Medical Sciences Isfahan Iran Biostatistics Department Near East University Nicosia Cyprus Biostatistics and Health Informatics Madda Walabu University Bale Robe Ethiopia Research Center for Immunodeficiencies Tehran Iran Karolinska University Hospital Huddinge Sweden Department of Cardiology Dupuytren University Hospital Limoges France University of Limoges Limoges France Department of Pediatric Dentistry Federal University of Minas Gerais Belo Horizonte Brazil Department of Research Philippine Institute for Development Studies Quezon City Philippines Department of Healthcare Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Harvard Medical School Boston MA United States Department of Medicine Ain Shams University Cairo Egypt Hamadan University of Medical Sciences Hamadan Iran School of Medicine Cardiff University Cardiff United Kingdom School of Laboratory Medicine and Science University College Hospital Ibadan Ibadan Nigeria Institute of Cardiovascular Diseases University of Ibadan Ibadan Nigeria Centre of Excellence for Epidemiological Modelling and Analysis Stellenbosch University Cape Town South Africa Department of Global Health Stellenbosch University Cape Town South Africa School of Health Ardabil University of Medical Science Ardabil Iran Social Behavioral Research Branch National Institute of Health Bethesda MD United States Department of Oncology Georgetown University Washington DC DC United States Department of Health Metrics Sciences School of Medicine Seattle WA

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw value

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LifeTime and improving European healthcare through cell-based interceptive medicine (vol 587, pg 377, 2020)

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NATURE 2021年第7852期592卷 E8-E8页

作者： Rajewsky, Nikolaus Almouzni, Genevieve Gorski, Stanislaw A. Aerts, Stein Amit, Ido Bertero, Michela G. Bock, Christoph Bredenoord, Annelien L. Cavalli, Giacomo Chiocca, Susanna Clevers, Hans De Strooper, Bart Eggert, Angelika Ellenberg, Jan Fernandez, Xose M. Figlerowicz, Marek Gasser, Susan M. Hubner, Norbert Kjems, Jorgen Knoblich, Jurgen A. Krabbe, Grietje Lichter, Peter Linnarsson, Sten Marine, Jean-Christophe Marioni, John C. Marti-Renom, Marc A. Netea, Mihai G. Nickel, Dorthe Nollmann, Marcelo Novak, Halina R. Parkinson, Helen Piccolo, Stefano Pinheiro, Ines Pombo, Ana Popp, Christian Reik, Wolf Roman-Roman, Sergio Rosenstiel, Philip Schultze, Joachim L. Stegle, Oliver Tanay, Amos Testa, Giuseppe Thanos, Dimitris Theis, Fabian J. Torres-Padilla, Maria-Elena Valencia, Alfonso Vallot, Celine van Oudenaarden, Alexander Vidal, Marie Voet, Thierry Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine in the Helmholtz Association Berlin Germany Charité-Universitätsmedizin Berlin Germany Berlin Institute of Health (BIH) Berlin Germany German Center for Cardiovascular Research (DZHK) Partner Site Berlin Berlin Germany Institute for Biology Humboldt University of Berlin Berlin Germany Cardiovascular and Metabolic Sciences Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) Berlin Germany Department of Pediatric Oncology/Hematology Charité-Universitätsmedizin Berlin Berlin Germany Institut Curie CNRS PSL Research University Sorbonne Université Nuclear Dynamics Unit Equipe Labellisée Ligue contre le cancer Paris France VIB Center for Brain and Disease Research Leuven Belgium Department of Human Genetics KU Leuven Leuven Belgium Department of Neurosciences KU Leuven Leuven Belgium UK Dementia Research Institute at UCL University College London London UK Wellcome Sanger Institute Wellcome Genome Campus Cambridge UK Department of Immunology Weizmann Institute of Science Rehovot Israel Centre for Genomic Regulation (CRG) Barcelona Institute of Science and Technology Barcelona Spain CNAG-CRG Centre for Genomic Regulation Barcelona Institute of Science and Technology Barcelona Spain Universitat Pompeu Fabra Barcelona Spain ICREA Barcelona Spain CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences Vienna Austria Department of Laboratory Medicine Medical University of Vienna Vienna Austria Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases Vienna Austria Department of Medical Humanities Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht The Netherlands Institute of Human Genetics UMR 9002 CNRS and University of Montpellier Montpellier France Department of Experimental Oncology IEO European Institute of Oncology IRCCS Milan Italy Department of Oncology and Hemato

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Author Correction: Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative

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Genome medicine 2022年第1期14卷 128页

作者： Ruth Johnson Yi Ding Vidhya Venkateswaran Arjun Bhattacharya Kristin Boulier Alec Chiu Sergey Knyazev Tommer Schwarz Malika Freund Lingyu Zhan Kathryn S Burch Christa Caggiano Brian Hill Nadav Rakocz Brunilda Balliu Christopher T Denny Jae Hoon Sul Noah Zaitlen Valerie A Arboleda Eran Halperin Sriram Sankararaman Manish J Butte Clara Lajonchere Daniel H Geschwind Bogdan Pasaniuc Department of Computer Science University of California Los Angeles Los Angeles CA 90095 USA. ruthjohnson@g.ucla.edu. Department of Pathology and Laboratory Medicine David Geffen School of Medicine University of California Los Angeles Los Angeles CA 90095 USA. ruthjohnson@g.ucla.edu. Department of Pathology and Laboratory Medicine David Geffen School of Medicine University of California Los Angeles Los Angeles CA 90095 USA. Bioinformatics Interdepartmental Program University of California Los Angeles Los Angeles CA 90095 USA. Department of Oral Biology School of Dentistry University of California Los Angeles Los Angeles CA 90095 USA. Institute for Quantitative and Computational Biosciences David Geffen School of Medicine University of California Los Angeles Los Angeles CA 90095 USA. Department of Medicine Division of Cardiology University of California Los Angeles Los Angeles CA 90095 USA. Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA 90095 USA. Department of Genetics Stanford School of Medicine Stanford CA 94305 USA. Molecular Biology Institute David Geffen School of Medicine University of California Los Angeles Los Angeles CA 90095 USA. Program in Neurogenetics Department of Neurology David Geffen School of Medicine University of California Los Angeles Los Angeles CA 90095 USA. Department of Computer Science University of California Los Angeles Los Angeles CA 90095 USA. Department of Computational Medicine David Geffen School of Medicine University of California Los Angeles Los Angeles CA 90095 USA. Division of Hematology/Oncology Department of Pediatrics Gwynne Hazen Cherry Memorial Laboratories University of California Los Angeles Los Angeles CA 90095 USA. Molecular Biology Institute University of California Los Angeles Los Angeles CA 90095 USA. Jonsson Comprehensive Cancer Center University of California Los Angeles Los Angeles CA 90095

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End-to-end spoofing detection with raw waveform CLDNNS

End-to-end spoofing detection with raw waveform CLDNNS

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Heinrich Dinkel Nanxin Chen Yanmin Qian Kai Yu Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering SpeechLab Department of Computer Science and Engineering Shanghai Jiao Tong University China

ISBN: (纸本)9781509041183

Albeit recent progress in speaker verification generates powerful models, malicious attacks in the form of spoofed speech, are generally not coped with. Recent results in ASVSpoof2015 and BTAS2016 challenges indicate that spoof-aware features are a possible solution to this problem. Most successful methods in both challenges focus on spoof-aware features, rather than focusing on a powerful classifier. In this paper we present a novel raw waveform based deep model for spoofing detection, which jointly acts as a feature extractor and classifier, thus allowing it to directly classify speech signals. This approach can be considered as an end-to-end classifier, which removes the need for any pre- or post-processing on the data, making training and evaluation a streamlined process, consuming less time than other neural-network based approaches. The experiments on the BTAS2016 dataset show that the system performance is significantly improved by the proposed raw waveform convolutional long short term neural network (CLDNN), from the previous best published 1.26% half total error rate (HTER) to the current 0.82% HTER. Moreover it shows that the proposed system also performs well under the unknown (RE-PH2-PH3,RE-LPPH2-PH3) conditions.

关键词： CLDNN End-to-End BTAS2016 Spoofing detection end-to-end computer information security Spoofing Classifiers waveforms speaker recognition System performance immatures Speech

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Sequence matters, but how exactly? A method for evaluating activity sequences from data 9

Sequence matters, but how exactly? A method for evaluating a...

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9th International Conference on Educational Data Mining, EDM 2016

作者： Doroudi, Shayan Holstein, Kenneth Aleven, Vincent Brunskill, Emma Computer Science Department Carnegie Mellon University United States Human-Computer Interaction Institute Carnegie Mellon University United States

How should a wide variety of educational activities be sequenced to maximize student learning? Although some experimental studies have addressed this question, educational data mining methods may be able to evaluate a wider range of possibilities and better handle many simultaneous sequencing constraints. We introduce Sequencing Constraint Violation Analysis (SCOVA): a general method for evaluating alternative activity sequences using existing data. SCOVA can be used to explore many complex sequencing constraints, such as prerequisite relationships, blocking, interleaving, and spiraling. We demonstrate SCOVA on data collected from a fractions intelligent tutoring system (ITS). Some of our findings challenge our initial hypotheses regarding sequencing, illustrating the utility and versatility of the method. The method can also be applied to other learning environments, as long as the available data has substantial variability in students’ activity sequences. © 2016 International Educational Data Mining Society. All rights reserved.

关键词： Students

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Sequence matters, but how do I discover how? Towards a workflow for evaluating activity sequences from data

Sequence matters, but how do I discover how? Towards a workf...

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2016 EDM Workshops and Tutorials, WT-EDM 2016

How should a wide variety of educational activities be sequenced in order to maximize student learning? We recently proposed the Sequencing Constraint Violation Analysis (SCOVA) method to help address this question. In this paper, we propose how SCOVA could be transformed into a workflow in LearnSphere so that other researchers and practitioners can find answers to the aforementioned question in their own datasets. We hope that such a workflow will lead to more and better research into this important question, as well as interesting new findings for both the educational data mining and learning sciences communities. © 2016, CEUR-WS. All rights reserved.

关键词： Data mining

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