检索结果-内蒙古大学图书馆

Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Scientific data 2021年第1期8卷 72页

作者： Gilberto Pastorello Carlo Trotta Eleonora Canfora Housen Chu Danielle Christianson You-Wei Cheah Cristina Poindexter Jiquan Chen Abdelrahman Elbashandy Marty Humphrey Peter Isaac Diego Polidori Markus Reichstein Alessio Ribeca Catharine van Ingen Nicolas Vuichard Leiming Zhang Brian Amiro Christof Ammann M Altaf Arain Jonas Ardö Timothy Arkebauer Stefan K Arndt Nicola Arriga Marc Aubinet Mika Aurela Dennis Baldocchi Alan Barr Eric Beamesderfer Luca Belelli Marchesini Onil Bergeron Jason Beringer Christian Bernhofer Daniel Berveiller Dave Billesbach Thomas Andrew Black Peter D Blanken Gil Bohrer Julia Boike Paul V Bolstad Damien Bonal Jean-Marc Bonnefond David R Bowling Rosvel Bracho Jason Brodeur Christian Brümmer Nina Buchmann Benoit Burban Sean P Burns Pauline Buysse Peter Cale Mauro Cavagna Pierre Cellier Shiping Chen Isaac Chini Torben R Christensen James Cleverly Alessio Collalti Claudia Consalvo Bruce D Cook David Cook Carole Coursolle Edoardo Cremonese Peter S Curtis Ettore D'Andrea Humberto da Rocha Xiaoqin Dai Kenneth J Davis Bruno De Cinti Agnes de Grandcourt Anne De Ligne Raimundo C De Oliveira Nicolas Delpierre Ankur R Desai Carlos Marcelo Di Bella Paul di Tommasi Han Dolman Francisco Domingo Gang Dong Sabina Dore Pierpaolo Duce Eric Dufrêne Allison Dunn Jiří Dušek Derek Eamus Uwe Eichelmann Hatim Abdalla M ElKhidir Werner Eugster Cacilia M Ewenz Brent Ewers Daniela Famulari Silvano Fares Iris Feigenwinter Andrew Feitz Rasmus Fensholt Gianluca Filippa Marc Fischer John Frank Marta Galvagno Mana Gharun Damiano Gianelle Bert Gielen Beniamino Gioli Anatoly Gitelson Ignacio Goded Mathias Goeckede Allen H Goldstein Christopher M Gough Michael L Goulden Alexander Graf Anne Griebel Carsten Gruening Thomas Grünwald Albin Hammerle Shijie Han Xingguo Han Birger Ulf Hansen Chad Hanson Juha Hatakka Yongtao He Markus Hehn Bernard Heinesch Nina Hinko-Najera Lukas Hörtnagl Lindsay Hutley Andreas Ibrom Hiroki Ikawa Marcin Jackowicz-Korczynski Dalibor Janouš Wilma Jans Rachhpal Jassal Shicheng Jiang Tomomichi Kato Myr Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. gzpastorello@lbl.gov. DIBAF University of Tuscia Viterbo 01100 Italy. Euro-Mediterranean Centre on Climate Change Foundation (CMCC) Lecce 73100 Italy. Climate & Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. Department of Civil Engineering California State University Sacramento CA 95819 USA. Department of Geography Environment and Spatial Sciences Michigan State University East Lansing MI 48823 USA. Department of Computer Science University of Virginia Charlottesville VA 22904 USA. TERN Ecosystem Processes Menzies Creek VIC3159 Australia. Max Planck Institute for Biogeochemistry Jena 07701 Germany. Laboratoire des Sciences du Climat et de l'Environnement (LSCE) CEA CNRS UVSQ UPSACLAY Gif sur Yvette 91190 France. Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China. Department of Soil Science University of Manitoba Winnipeg MB R3T2N2 Canada. Department of Agroecology and Environment Agroscope Research Institute Zürich 8046 Switzerland. School of Geography and Earth Sciences McMaster University L8S4K1 Hamilton ON Canada. Department of Physical Geography and Ecosystem Science Lund University Lund 22362 Sweden. Department of Agronomy and Horticulture University of Nebraska-Lincoln Lincoln NE 68583 USA. School of Ecosystem and Forest Sciences The University of Melbourne Richmond VIC3121 Australia. Department of Biology Research Group PLECO University of Antwerp Antwerp 2610 Belgium. Joint Research Centre European Commission Ispra 21027 Italy. TERRA Teaching and Research Center University of Liege Gembloux B-5030 Belgium. Finnish Meteorological Institute Helsinki 00560 Finland. ES

来源：评论

学校读者我要写书评

暂无评论

26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

引用

BMC NEUROscience 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

来源：评论

学校读者我要写书评

暂无评论

Elephant Herding Optimization

Elephant Herding Optimization

引用

International Symposium on Computational and Business Intelligence (ISCBI)

作者： Gai-Ge Wang Suash Deb Leandro dos S. Coelho School of Computer Science and Technology Jiangsu Normal University Xuzhou China Dept. of Computer Science & Engineering Cambridge Institute of Technology Ranchi INDIA Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil

In this paper, a new kind of swarm-based metaheuristic search method, called Elephant Herding Optimization (EHO), is proposed for solving optimization tasks. The EHO method is inspired by the herding behavior of elephant group. In nature, the elephants belonging to different clans live together under the leadership of a matriarch, and the male elephants will leave their family group when they grow up. These two behaviors can be modelled into two following operators: clan updating operator and separating operator. In EHO, the elephants in each clan are updated by its current position and matriarch through clan updating operator. It is followed by the implementation of the separating operator which can enhance the population diversity at the later search phase. To demonstrate its effectiveness, EHO is benchmarked by fifteen test cases comparing with BBO, DE and GA. The results show that EHO can find the better values on most benchmark problems than those three metaheuristic algorithms.

关键词： Optimization Benchmark testing Sociology Statistics Particle swarm optimization Electronic mail Search methods

来源：评论

学校读者我要写书评

暂无评论

Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: the Global Burden of Diseases Study 2019

引用

The Lancet HIV 2021年第10期8卷 e633-e651页

作者： Jahagirdar, Deepa Walters, Magdalene K. Novotney, Amanda Brewer, Edmond D. Frank, Tahvi D. Carter, Austin Biehl, Molly H. Abbastabar, Hedayat Abhilash, E.S. Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Adekanmbi, Victor Adeyinka, Daniel Adedayo Adnani, Qorinah Estiningtyas Sakilah Afzal, Saira Aghababaei, Soodabeh Ahinkorah, Bright Opoku Ahmad, Sajjad Ahmadi, Keivan Ahmadi, Sepideh Ahmadpour, Ehsan Ahmed, Muktar Beshir Rashid, Tarik Ahmed Salih, Yusra Ahmed Aklilu, Addis Akram, Tayyaba Akunna, Chisom Joyqueenet Al Hamad, Hanadi Alahdab, Fares Alanezi, Fahad Mashhour Aleksandrova, Ekaterina A. Alene, Kefyalew Addis Ali, Liaqat Alipour, Vahid Almustanyir, Sami Alvis-Guzman, Nelson Ameyaw, Edward Kwabena Amu, Hubert Andrei, Catalina Liliana Andrei, Tudorel Anvari, Davood Arabloo, Jalal Aremu, Olatunde Arulappan, Judie Atnafu, Desta Debalkie Quintanilla, Beatriz Paulina Ayala Ayza, Muluken Altaye Azari, Samad Darshan, B.B. Banach, Maciej Bärnighausen, Till Winfried Barra, Fabio Barrow, Amadou Basu, Sanjay Bazargan-Hejazi, Shahrzad Belay, Habtamu Gebrehana Berheto, Tezera Moshago Bezabhe, Woldesellassie Mequanint Bezabih, Yihienew Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Nikha Bhardwaj, Pankaj Bhattacharyya, Krittika Bibi, Sadia Bijani, Ali Bisignano, Catherine Bolarinwa, Obasanjo Afolabi Boloor, Archith Boltaev, Azizbek A. Briko, Nikolay Ivanovich Buonsenso, Danilo Burkart, Katrin Butt, Zahid A. Cao, Chao Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Choudhari, Sonali Gajanan Chu, Dinh-Toi Couto, Rosa A.S. Cowden, Richard G. Dachew, Berihun Assefa Dadras, Omid Dagnew, Amare Belachew Dahlawi, Saad M.A. Dai, Xiaochen Dandona, Lalit Dandona, Rakhi das Neves, José Degenhardt, Louisa Demeke, Feleke Mekonnen Desta, Abebaw Alemayehu Deuba, Keshab Dhamnetiya, Deepak Dhungana, Govinda Prasad Dianatinasab, Mostafa Diaz, Daniel Djalalinia, Shirin Doan, Linh Phuong Dorostkar, Fariba Edinur, Hisham Atan Effiong, Andem Eftekharzadeh, Sahar El Sayed Zaki, Maysaa Elayedath, Rajesh Elhadi, Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Allergy and Infectious Diseases University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States School of Social Work University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Vagelos College of Physicians and Surgeones Columbia University Medical Center New York NY United States Division of Data Analytics and Delivery for Impact WHO Geneva Switzerland Advanced Diagnostic and Interventional Radiology Research Centre Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Centre Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Paediatric Chronic Kidney Disease Research Centre Tehran University of Medical Sciences Tehran Iran Department of Psychiatry Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Centre Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Centre Tehran University of Medical Sciences Tehran Iran Research Centre for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Centre Tehran University of Medical Sciences Tehran Iran Department of Botany Sree Narayana Guru College Chelannur Kozhikode India Clinical Sciences Department University of Sharjah Sharjah United Arab Emirates Mass Communication Department University of Sharjah Sharjah United Arab Emirates Department of Health-Care Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Department of Population Medicine Ca

Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. Methods: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). Findings: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1–38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78–0·91) per female living with HIV in 2019, 0·99 male infections (0·91–1·10) for every female infection, and 1·02 male deaths (0·95–1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58–35·43, and a 39·66% decrease in deaths, 36·49–42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05–0·06) and the global incidence-to-mortality ratio was

关键词：

来源：评论

学校读者我要写书评

暂无评论

Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis (vol 50, pg 1368, 2020)

引用

PSYCHOLOGICAL MEDICINE 2020年第16期50卷 2816-2816页

作者： Wu, Yin Levis, Brooke Riehm, Kira E. Saadat, Nazanin Levis, Alexander W. Azar, Marleine Rice, Danielle B. Boruff, Jill Cuijpers, Pim Gilbody, Simon Ioannidis, John P. A. Kloda, Lorie A. McMillan, Dean Patten, Scott B. Shrier, Ian Ziegelstein, Roy C. Akena, Dickens H. Arroll, Bruce Ayalon, Liat Baradaran, Hamid R. Baron, Murray Bombardier, Charles H. Butterworth, Peter Carter, Gregory Chagas, Marcos H. Chan, Juliana C. N. Cholera, Rushina Conwell, Yeates de Manvan Ginkel, Janneke M. Fann, Jesse R. Fischer, Felix H. Fung, Daniel Gelaye, Bizu Goodyear-Smith, Felicity Greeno, Catherine G. Hall, Brian J. Harrison, Patricia A. Harter, Martin Hegerl, Ulrich Hides, Leanne Hobfoll, Stevan E. Hudson, Marie Hyphantis, Thomas Inagaki, Masatoshi Jette, Nathalie Khamseh, Mohammad E. Kiely, Kim M. Kwan, Yunxin Lamers, Femke Liu, Shen-Ing Lotrakul, Manote Loureiro, Sonia R. Lowe, Bernd McGuire, Anthony Mohd-Sidik, Sherina Munhoz, Tiago N. Muramatsu, Kumiko Osorio, Flavia L. Patel, Vikram Pence, Brian W. Persoons, Philippe Picardi, Angelo Reuter, Katrin Rooney, Alasdair G. Santos, Ina S. Shaaban, Juwita Sidebottom, Abbey Simning, Adam Stafford, Lesley Sung, Sharon Tan, Pei Lin Lynnette Turner, Alyna van Weert, Henk C. White, Jennifer Whooley, Mary A. Winkley, Kirsty Yamada, Mitsuhiko Benedetti, Andrea Thombs, Brett D. [a1]Lady Davis Institute for Medical Research Jewish General Hospital Montréal Québec Canada [a2]Department of Psychiatry McGill University Montréal Québec Canada [a3]Department of Epidemiology Biostatistics and Occupational Health McGill University Montréal Québec Canada [a4]Department of Psychology McGill University Montréal Québec Canada [a5]Schulich Library of Physical Sciences Life Sciences and Engineering McGill University Montreal Quebec Canada [a6]Department of Clinical Neuro and Developmental Psychology Amsterdam Public Health Research Institute Vrije Universiteit Amsterdam the Netherlands [a7]Hull York Medical School and the Department of Health Sciences University of York Heslington York UK [a8]Department of Medicine Department of Health Research and Policy Department of Biomedical Data Science Department of Statistics Stanford University Stanford California USA [a9]Library Concordia University Montréal Québec Canada [a10]Department of Community Health Sciences University of Calgary Calgary Alberta Canada [a11]Hotchkiss Brain Institute and O’Brien Institute for Public Health University of Calgary Calgary Alberta Canada [a12]Department of Medicine Johns Hopkins University School of Medicine Baltimore Maryland USA [a13]Department of Psychiatry Makerere University College of Health Sciences Kampala Uganda [a14]Department of General Practice and Primary Health Care University of Auckland Auckland New Zealand [a15]Louis and Gabi Weisfeld School of Social Work Bar Ilan University Ramat Gan Israel [a16]Endocrine Research Center Institute of Endocrinology and Metabolism Iran University of Medical Sciences Tehran Iran [a17]Ageing Clinical & Experimental Research Team Institute of Applied Health Sciences School of Medicine Medical Sciences and Nutrition University of Aberdeen Aberdeen Scotland UK [a18]Department of Medicine McGill University Montréal Québec Canada [a19]Department of Rehabilitation Medicine University of Washington S

BackgroundItem 9 of the Patient Health Questionnaire-9 (PHQ-9) queries about thoughts of death and self-harm, but not suicidality. Although it is sometimes used to assess suicide risk, most positive responses are not associated with suicidality. The PHQ-8, which omits Item 9, is thus increasingly used in research. We assessed equivalency of total score correlations and the diagnostic accuracy to detect major depression of the PHQ-8 and *** conducted an individual patient data meta-analysis. We fit bivariate random-effects models to assess diagnostic ***16 742 participants (2097 major depression cases) from 54 studies were included. The correlation between PHQ-8 and PHQ-9 scores was 0.996 (95% confidence interval 0.996 to 0.996). The standard cutoff score of 10 for the PHQ-9 maximized sensitivity + specificity for the PHQ-8 among studies that used a semi-structured diagnostic interview reference standard (N = 27). At cutoff 10, the PHQ-8 was less sensitive by 0.02 (−0.06 to 0.00) and more specific by 0.01 (0.00 to 0.01) among those studies (N = 27), with similar results for studies that used other types of interviews (N = 27). For all 54 primary studies combined, across all cutoffs, the PHQ-8 was less sensitive than the PHQ-9 by 0.00 to 0.05 (0.03 at cutoff 10), and specificity was within 0.01 for all cutoffs (0.00 to 0.01).ConclusionsPHQ-8 and PHQ-9 total scores were similar. Sensitivity may be minimally reduced with the PHQ-8, but specificity is similar.

关键词： Depression diagnostic accuracy individual participant data meta-analysis meta-analysis PHQ-8 PHQ-9 screening systematic review

来源：评论

学校读者我要写书评

暂无评论

25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

引用

BMC NEUROscience 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

关键词：

来源：评论

学校读者我要写书评

暂无评论

Subnational mapping of HIV incidence and mortality among individuals aged 15–49 years in sub-Saharan Africa, 2000–18: a modelling study

引用

The Lancet HIV 2021年第6期8卷 e363-e375页

作者： Sartorius, Benn VanderHeide, John D. Yang, Mingyou Goosmann, Erik A. Hon, Julia Haeuser, Emily Cork, Michael A. Perkins, Samantha Jahagirdar, Deepa Schaeffer, Lauren E. Serfes, Audrey L. LeGrand, Kate E. Abbastabar, Hedayat Abebo, Zeleke Hailemariam Abosetugn, Akine Eshete Abu-Gharbieh, Eman Accrombessi, Manfred Mario Kokou Adebayo, Oladimeji M. Adegbosin, Adeyinka Emmanuel Adekanmbi, Victor Adetokunboh, Olatunji O. Adeyinka, Daniel Adedayo Ahinkorah, Bright Opoku Ahmadi, Keivan Ahmed, Muktar Beshir Akalu, Yonas Akinyemi, Oluwaseun Oladapo Akinyemi, Rufus Olusola Aklilu, Addis Akunna, Chisom Joyqueenet Alahdab, Fares Al-Aly, Ziyad Alam, Noore Alamneh, Alehegn Aderaw Alanzi, Turki M. Alemu, Biresaw Wassihun Alhassan, Robert Kaba Ali, Tilahun Alipour, Vahid Amini, Saeed Ancuceanu, Robert Ansari, Fereshteh Anteneh, Zelalem Alamrew Anvari, Davood Anwer, Razique Appiah, Seth Christopher Yaw Arabloo, Jalal Asemahagn, Mulusew A. Asghari Jafarabadi, Mohammad Asmare, Wondwossen Niguse Atnafu, Desta Debalkie Atout, Maha Moh'd Wahbi Atreya, Alok Ausloos, Marcel Awedew, Atalel Fentahun Ayala Quintanilla, Beatriz Paulina Ayanore, Martin Amogre Aynalem, Yared Asmare Ayza, Muluken Altaye Azari, Samad Azene, Zelalem Nigussie Babar, Zaheer-Ud-Din Baig, Atif Amin Balakrishnan, Senthilkumar Banach, Maciej Bärnighausen, Till Winfried Basu, Sanjay Bayati, Mohsen Bedi, Neeraj Bekuma, Tariku Tesfaye Bezabhe, Woldesellassie M. Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Pankaj Bhattacharyya, Krittika Bhutta, Zulfiqar A. Bibi, Sadia Bikbov, Boris Birhan, Tsegaye Adane Bitew, Zebenay Workneh Bockarie, Moses John Boloor, Archith Brady, Oliver J. Bragazzi, Nicola Luigi Briko, Andrey Nikolaevich Briko, Nikolay Ivanovich Burugina Nagaraja, Sharath Butt, Zahid A. Cárdenas, Rosario Carvalho, Felix Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Chowdhury, Mohiuddin Ahsanul Kabir Chu, Dinh-Toi Cook, Aubrey J. Cormier, Natalie Maria Cowden, Richard G. Culquichicon, Carlos Dagnew, Baye Dahlawi, Saad M.A. D Centre for Tropical Medicine and Global Health Nuffield Department of Medicine University of Oxford Oxford United Kingdom Malaria Atlas Project University of Oxford Oxford United Kingdom The George Institute for Global Health University of Oxford Oxford United Kingdom Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Insights Program Bill and Melinda Gates Foundation Seattle WA United States Global Programs Medical Teams International Seattle WA United States Department of Pediatric Newborn Medicine Brigham and Women's Hospital Boston MA United States Advanced Diagnostic and Interventional Radiology Research Center Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Pediatric Chronic Kidney Disease Research Center Tehran University of Medical Sciences Tehran Iran Department of Environmental Health Engineering Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Public Health Arba Minch University Arba Minch Ethiopia Department of Medical Laboratory Sciences Arba Minch University Arba Minch Ethiopia College of Medicine and Health Science Arba Minch University Arba Minch Ethiopia Department of Nursing Arba Minch University Arba Minch Ethiopia Department of Biomedical Sciences Arba Minch University Arba Minch Ethiopia Department of Public Health Debre Berhan University Debre Brehan

Background: High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. Methods: In this modelling study, we developed a framework that used the geographically specific HIV prevalence data collected in seroprevalence surveys and antenatal care clinics to train a model that estimates HIV incidence and mortality among individuals aged 15–49 years. We used a model-based geostatistical framework to estimate HIV prevalence at the second administrative level in 44 countries in sub-Saharan Africa for 2000–18 and sought data on the number of individuals on antiretroviral therapy (ART) by second-level administrative unit. We then modified the Estimation and Projection Package (EPP) to use these HIV prevalence and treatment estimates to estimate HIV incidence and mortality by second-level administrative unit. Findings: The estimates suggest substantial variation in HIV incidence and mortality rates both between and within countries in sub-Saharan Africa, with 15 countries having a ten-times or greater difference in estimated HIV incidence between the second-level administrative units with the lowest and highest estimated incidence levels. Across all 44 countries in 2018, HIV incidence ranged from 2·8 (95% uncertainty interval 2·1–3·8) in Mauritania to 1585·9 (1369·4–1824·8) cases per 100 000 people in Lesotho and HIV mortality ranged from 0·8 (0·7–0·9) in Mauritania to 676·5 (513·6–888·0) deaths per 100 000 people in Lesotho. Variation in both incidence and mortality was substantially greater at the subnational level than at the national level and the highest estimated rates were accordingly higher. Among second-level administrative units, Guijá District, Gaza Province, Mozambique,

关键词：

来源：评论

学校读者我要写书评

暂无评论

Gene expression imputation across multiple brain regions provides insights into schizophrenia risk (vol 51, pg 659, 2019)

引用

NATURE GENETICS 2019年第6期51卷 1068-1068页

作者： Huckins, Laura M. Dobbyn, Amanda Ruderfer, Douglas M. Hoffman, Gabriel Wang, Weiqing Pardinas, Antonio F. Rajagopal, Veera M. Als, Thomas D. Nguyen, Hoang T. Girdhar, Kiran Boocock, James Roussos, Panos Fromer, Menachem Kramer, Robin Domenici, Enrico Gamazon, Eric R. Purcell, Shaun Demontis, Ditte Borglum, Anders D. Walters, James T. R. O'Donovan, Michael C. Sullivan, Patrick Owen, Michael J. Devlin, Bernie Sieberts, Solveig K. Cox, Nancy J. Im, Hae Kyung Sklar, Pamela Stahl, Eli A. Pamela Sklar Division of Psychiatric Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics and Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Psychiatry Icahn School of Medicine at Mount Sinai New York NY USA Icahn Institute for Genomics and Multiscale Biology Icahn School of Medicine at Mount Sinai New York NY USA Vanderbilt University Medical Center Nashville TN USA MRC Centre for Neuropsychiatric Genetics and Genomics Cardiff University Cardiff UK Department of Biomedicine Aarhus University Aarhus Denmark The Lundbeck Foundation Initiative for Integrative Psychiatric Research iPSYCH Denmark Center for Integrative Sequencing Aarhus University Aarhus Denmark Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA Human Brain Collection Core National Institute of Mental Health Bethesda MD USA Laboratory of Neurogenomic Biomarkers Centre for Integrative Biology (CIBIO) University of Trento Trento Italy Clare Hall University of Cambridge Cambridge UK University of North Carolina at Chapel Hill Chapel Hill NC USA Karolinska Institutet Stockholm Sweden Department of Psychiatry University of Pittsburgh Pittsburgh PA USA Systems Biology Sage Bionetworks Seattle WA USA Section of Genetic Medicine Department of Medicine University of Chicago Chicago IL USA Integrated Technology Research Laboratories Pharmaceutical Research Division Takeda Pharmaceutical Company Limited Fujisawa Japan Neuropsychiatry Section Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Neuropsychiatric Signaling Program Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Psychiatry JJ Peters Virginia Medical Center Bronx NY USA Department of Neuroscience Icahn School of Medicine at Mount Sinai New York New York NY USA Friedman Brain Institute

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

关键词： Gene expression Genome-wide association studies Schizophrenia Transcriptomics

来源：评论

学校读者我要写书评

暂无评论

Performance Evaluation of Hypervisors for HPC Applications

Performance Evaluation of Hypervisors for HPC Applications

引用

IEEE International Conference on systems, Man and Cybernetics

作者： David Beserra Felipe Oliveira Jean Araujo Felipe Fernandes Alberto Araújo Patrícia Endo Paulo Maciel Edward David Moreno Graduate Program in Computer Science University of Sergipe Aracaju Brazil Academic Unit of Garanhuns Federal Rural University of Pernambuco Garanhuns Brazil Informatics Center Federal University of Pernambuco Recife Brazil Graduate in Systems and Computing Military Institute of Engineering Rio de Janeiro Brazil University of Pernambuco Caruaru Brazil

ISBN: (纸本)9781479986989

High Performance Computing (HPC) aggregates computing power in order to solve large and complex problems in different knowledge areas. Nowadays, HPC users can utilize virtualized infrastructures as a low-cost alternative to deploy their applications. However, virtualization brings some challenges for HPC, specially in regard to overhead caused by hyper visors. In this work, our main goal is to analyze the performance of two hyper visors (KVM and Virtual Box) under HPC activities, considering full virtualization, and Para virtualization approaches. We used the HPC Challenge Benchmark (HPCC) to evaluate processor, RAM, inter-process communication and network communication performance. Our results show KVM in Para virtualization mode has a similar performance of a native cluster.

关键词： Virtualization Virtual machine monitors Bandwidth Benchmark testing Random access memory Performance evaluation Kernel

来源：评论

学校读者我要写书评

暂无评论

Calibrationless parallel imaging reconstruction based on structured low-rank matrix completion

Calibrationless parallel imaging reconstruction based on str...

引用

作者： Shin, Peter J. Larson, Peder E. Z. Ohliger, Michael A. Elad, Michael Pauly, John M. Vigneron, Daniel B. Lustig, Michael Department of Radiology and Biomedical Imaging University of California at San Francisco San FranciscoCA United States UC Berkeley-UCSF Graduate Program in Bioengineering CA United States Department of Electrical Engineering and Computer Science University of California at Berkeley BerkeleyCA United States Department of Computer Science Technion'Israel Institute of Technology Haifa Israel Magnetic Resonance Systems Research Laboratory Department of Electrical Engineering Stanford University StanfordCA United States

Purpose: A calibrationless parallel imaging reconstruction method, termed simultaneous autocalibrating and k-space estimation (SAKE), is presented. It is a data-driven, coil-by-coil reconstruction method that does not require a separate calibration step for estimating coil sensitivity information. Methods: In SAKE, an undersampled, multichannel dataset is structured into a single data matrix. The reconstruction is then formulated as a structured low-rank matrix completion problem. An iterative solution that implements a projection-ontosets algorithm with singular value thresholding is described. Results: Reconstruction results are demonstrated for retrospectively and prospectively undersampled, multichannel Cartesian data having no calibration signals. Additionally, non-Cartesian data reconstruction is presented. Finally, improved image quality is demonstrated by combining SAKE with wavelet-based compressed sensing. Conclusion: Because estimation of coil sensitivity information is not needed, the proposed method could potentially benefit MR applications where acquiring accurate calibration data is limiting or not possible at all. © 2013 Wiley Periodicals, Inc.

关键词： Compressed sensing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：