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NECESSARY AND SUFFICIENT CONDITIONS FOR DEADLOCKS IN FLEXIBLE MANUFACTURING systemS BASED ON A DIGRAPH MODEL

Asian Journal of Control 2008年第2期6卷

作者： Wenle Zhang Robert P. Judd Paul Deering School of Electrical Engineering and Computer Science Ohio University Athens OH 45701. Dr. Judd has over twenty years of experience as an educator researcher and consultant in system simulation discrete event controls and systems integration. Dr. Judd has received over thirty research grants totaling over $3500000. His funding has come from both industrial and governmental sources. He is the author or co-author of over a hundred published papers in journals and conferences. He also wrote a book chapter devoted to integrating manufacturing design tools and edited a special issue of the International Journal of Computer Integrated Manufacturing dedicated to intelligent manufacturing systems. Dr. Judd holds a patent on simulation software integration. Russ College of Engineering and Technology Ohio University Athens OH 45701.

As typical discrete event systems, flexible manufacturing systems have been extensively studied in such aspects as modeling, control and performance analysis. One important topic in the study of such systems is the deadlock detection, prevention and avoidance. In the past decade, two major modeling formalisms, i.e., Petri nets and digraphs, have been adopted for developing deadlock control policies for flexible manufacturing systems. In this paper, the concepts of slack, knot, order and effective free space of circuits in the digraph are established and used to concisely and precisely quantify the sufficient conditions for a system state to be live. Necessary conditions for this liveness is quantified for a special class of system states - called evaluation states. The significance of the result is that the conditions are true for avoiding both primary deadlocks and impending deadlocks that are arbitrary steps away from a primary one, whereas only second level deadlocks have been studied in the literature. Examples are provided to illustrate the method.

关键词： Flexible manufacturing systems deadlock avoidance deadlock prevention petri net digraph

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Correction: Improving Pelvic Floor Muscle Training Adherence Among Pregnant Women: Validation Study

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JMIR human factors 2022年第2期9卷 e38175页

作者： Aida Jaffar Sherina Mohd-Sidik Chai Nien Foo Novia Admodisastro Sobihatun Nur Abdul Salam Noor Diana Ismail Department of Psychiatry Faculty of Medicine and Health Sciences Universiti Putra Malaysia Selangor Malaysia. Primary Care Unit Faculty of Medicine and Defence Health Universiti Pertahanan Nasional Malaysia Wilayah Persekutuan Malaysia. Department of Population Medicine Universiti Tunku Abdul Rahman Selangor Malaysia. Software Engineering & Information System Department Faculty of Computer Science & Information Technology Universiti Putra Malaysia Selangor Malaysia. School of Multimedia Technology and Communication College of Arts and Sciences Universiti Utara Malaysia Kedah Malaysia. Klinik Kesihatan Bt 9 Cheras Ministry of Health Selangor Malaysia.

[This corrects the article DOI: 10.2196/30989.].

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FAIR Data Pipeline: provenance-driven data management for traceable scientific workflows

arXiv

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arXiv 2021年

作者： Mitchell, Sonia Natalie Lahiff, Andrew Cummings, Nathan Hollocombe, Jonathan Boskamp, Bram Field, Ryan Reddyhoff, Dennis Zarebski, Kristian Wilson, Antony Viola, Bruno Burke, Martin Archibald, Blair Bessell, Paul Blackwell, Richard Boden, Lisa A. Brett, Alys Brett, Sam Dundas, Ruth Enright, Jessica Gonzalez-Beltran, Alejandra N. Harris, Claire Hinder, Ian Hughes, Christopher David Knight, Martin Mano, Vino McMonagle, Ciaran Mellor, Dominic Mohr, Sibylle Marion, Glenn Matthews, Louise McKendrick, Iain J. Pooley, Christopher Mark Porphyre, Thibaud Reeves, Aaron Townsend, Edward Turner, Robert Walton, Jeremy Reeve, Richard Institute of Biodiversity Animal Health and Comparative Medicine College of Medical Veterinary and Life Sciences University of Glasgow GlasgowG12 8QQ United Kingdom Boyd Orr Centre for Population and Ecosystem Health University of Glasgow Glasgow United Kingdom United Kingdom Atomic Energy Authority Didcot OX14 3DB United Kingdom James Clerk Maxwell Building Peter Guthrie Tait Road The King’s Buildings EdinburghEH9 3FD United Kingdom MRC/CSO Social and Public Health Sciences Unit Institute of Health and Wellbeing College of Medical Veterinary and Life Sciences University of Glasgow GlasgowG12 8QQ United Kingdom Department of Computer Science University of Sheffield Regent Court SheffieldS1 4DP United Kingdom Science and Technology Facilities Council Harwell Campus United Kingdom School of Computing Science College of Science and Engineering University of Glasgow GlasgowG12 8QQ United Kingdom Roslin Institute University of Edinburgh Edinburgh United Kingdom Man Group plc Riverbank House 2 Swan Lane LondonEC4R 3AD United Kingdom The University of Manchester Research IT ManchesterM1 3BU United Kingdom School of Veterinary Medicine College of Medical Veterinary and Life Sciences University of Glasgow GlasgowG61 1QH United Kingdom VetAgro Sup UMR5558 Laboratoire de Biométrie et Biologie Évolutive Campus Vétérinaire de Lyon Marcy-l’Etoile 69280 France Peter Wilson Building The King’s Buildings West Mains Road EdinburghEH9 3JG United Kingdom UK Earth System Model Core Group Met Office ExeterEX1 3PB United Kingdom

Modern epidemiological analyses to understand and combat the spread of disease depend critically on access to, and use of, data. Rapidly evolving data, such as data streams changing during a disease outbreak, are particularly challenging. Data management is further complicated by data being imprecisely identified when used. Public trust in policy decisions resulting from such analyses is easily damaged and is often low, with cynicism arising where claims of "following the science" are made without accompanying evidence. Tracing the provenance of such decisions back through open software to primary data would clarify this evidence, enhancing the transparency of the decision-making process. Here, we demonstrate a Findable, Accessible, Interoperable and Reusable (FAIR) data pipeline. Although developed during the COVID-19 pandemic, it allows easy annotation of any data as they are consumed by analyses, or conversely traces the provenance of scientific outputs back through the analytical or modelling source code to primary data. Such a tool provides a mechanism for the public, and fellow scientists, to better assess scientific evidence by inspecting its provenance, while allowing scientists to support policy-makers in openly justifying their decisions. We believe that such tools should be promoted for use across all areas of policy-facing research. Copyright © 2021, The Authors. All rights reserved.

关键词： Information management

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Three-dimensional Atmospheric Dynamics of Jupiter from Ground-based Doppler Imaging Spectroscopy in the Visible

arXiv

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arXiv 2023年

作者： Schmider, Francois-Xavier Gaulme, Patrick Morales-Juberías, Raúl Jackiewicz, Jason Gonçalves, Ivan Guillot, Tristan Simon, Amy A. Wong, Michael H. Underwood, Thomas Voelz, David Sanchez, Cristo DeColibus, Riley Kovac, Sarah A. Sellers, Sean Gilliam, Doug Boumier, Patrick Appourchaux, Thierry Dejonghe, Julien Rivet, Jean Pierre Markham, Steve Howard, Saburo Abe, Lyu Mekarnia, Djamel Ikoma, Masahiro Ama, Hidekazu Hana Sato, Bunei Kunitomo, Masanobu Izumiura, Hideyuki Université Côte d’Azur Observatoire de la Côte d’Azur Laboratoire Lagrange UMR7293 CNRS Nice06304 France Thüringer Landessternwarte Sternwarte 5 Tautenburg07778 Germany Department of Astronomy New Mexico State University P.O. Box 30001 MSC 4500 Las CrucesNM88003-8001 United States New Mexico Tech Department of Physics 801 Leroy Place SocorroNM87801 United States Université Paul Sabatier Institut de Recherche en Astrophysique et Planetologie Observatoire Midi-Pyrénées Toulouse France Université Côte d’Azur Observatoire de la Côte d’Azur Lagrange Nice France NASA Goddard Space Flight Center Solar System Exploration Division 8800 Greenbelt Road GreenbeltMD20771 United States University of California Center for Integrative Planetary Science 501 Campbell Hall BerkeleyCA94720-3411 United States Klipsch School of Electrical and Computer Engineering New Mexico State University MSC 3-O Goddard Annex 160B Las CrucesNM88003 United States Southwest Research Institute 1050 Walnut Street Suite 300 BoulderCO80302 United States Sunspot Solar Observatory P.O. Box 62 SunspotNM88349 United States Université Paris-Saclay Institut d’Astrophysique Spatiale UMR 8617 CNRS Bâtiment 121 Orsay91405 Cedex France Institute for Computational Science University of Zurich Winterthurerstr. 190 ZurichCH8057 Switzerland Mitaka Tokyo181-8588 Japan Department of Earth and Planetary Sciences School of Science Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo152-8551 Japan Department of Physics Kurume University 67 Asahimachi Fukuoka Kurume830-0011 Japan NAOJ Okayama Observatory Okayama Japan

We present three-dimensional (3D) maps of Jupiter’s atmospheric circulation at cloud-top level from Doppler-imaging data obtained in the visible domain with JIVE, the second node of the JOVIAL network, which is mounted on the Dunn Solar Telescope at Sunspot, New Mexico. We report on 12 nights of observations between 2018 May 4 and May 30, representing a total of about 80 hr. First, the average zonal wind profile derived from our data is compatible with that derived from cloud-tracking measurements performed on Hubble Space Telescope images obtained in 2018 April from the Outer Planet Atmospheres Legacy program. Second, we present the first ever 2D maps of Jupiter’s atmospheric circulation from Doppler measurements. The zonal velocity map highlights well-known atmospheric features, such as the equatorial hot spots and the Great Red Spot (GRS). In addition to zonal winds, we derive meridional and vertical velocity fields from the Doppler data. The motions attributed to vertical flows are mainly located at the boundary between the equatorial belts and tropical zones, which could indicate active motion in theses regions. Qualitatively, these results compare well to recent Juno data that have unveiled the 3D structure of Jupiter’s wind field. To the contrary, the motions attributed to meridional circulation are very different from what is obtained by cloud tracking, except at the GRS. Because of limitations with data resolution and processing techniques, we acknowledge that our measurements of the vertical or meridional flows of Jupiter are still to be confirmed. © 2023, CC BY.

关键词： Data handling

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Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000-17: analysis for the Global Burden of Disease Study 2017 (vol 395, pg 1779, 2020)

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LANCET 2020年第10239期395卷 1762-1762页

作者： Reiner, R. C., Jr. Hay, S., I Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Global Health School of Medicine University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States College of Health and Medical Sciences Haramaya University Harar Ethiopia Department of Epidemiology and Biostatistics Haramaya University Harar Ethiopia Department of Medical Laboratory Sciences Haramaya University Harar Ethiopia School of Nursing and Midwifery Haramaya University Harar Ethiopia School of Pharmacy Haramaya University Harar Ethiopia School of Public Health Haramaya University Harar Ethiopia Haramaya University Harar Ethiopia Advanced Diagnostic and Interventional Radiology Research Center Tehran University of Medical Sciences Tehran Iran Cancer Biology Research Center Tehran University of Medical Sciences Tehran Iran Cancer Research Institute Tehran University of Medical Sciences Tehran Iran Department of Economics and Management Sciences for Health Tehran University of Medical Sciences Tehran Iran Department of Environmental Health Engineering Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Department of Health Management and Economics Tehran University of Medical Sciences Tehran Iran Department of Microbiology Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Center Tehran University of Medical Sciences Tehran Iran Hematology-Oncology and Stem Cell Transplantation Research Center Tehran University of Medical Sciences Tehran Iran Iran National Institute of Health Research Tehran University of Medical Sciences Tehran Iran Metabolomics and

Summary Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood *** We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor *** The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1-65·8), 17·4% (7·7-28·4), and 59·5% (34·2-86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy *** By co-analysing geospatial trends in d

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

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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

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Inflammation Biomarkers: Label-Free Biophysical Markers from Whole Blood Microfluidic Immune Profiling Reveal Severe Immune Response Signatures (Small 12/2021)

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Small 2021年第12期17卷

作者： Kerwin Kwek Zeming Rohan Vernekar Mui Teng Chua Kai Yun Quek Greg Sutton Timm Krüger Win Sen Kuan Jongyoon Han Singapore-MIT Alliance for Research and Technology (SMART) – Critical Analytics for Manufacturing of Personalized Medicine (CAMP) IRG 1 Create Way Enterprise Wing #04-13/14 Singapore 138602 Singapore School of Engineering Institute for Multiscale Thermofluids University of Edinburgh Peter Guthrie Tait Road King's Buildings Edinburgh EH9 3FD UK Department of Surgery Yong Loo Lin School of Medicine National University of Singapore 1E Kent Ridge Road Level 8 NUHS Tower Block Singapore 119228 Singapore Emergency Medicine Department National University Hospital National University Health System National University Centre for Oral Health 9 Lower Kent Ridge Road Level 4 Singapore 119085 Singapore University/BHF Centre for Cardiovascular Science The Queen's Medical Research Institute 47 Little France Crescent Edinburgh EH16 4TJ UK Department of Electrical Engineering and Computer Science & Department of Biological Engineering Massachusetts Institute of Technology 77 Massachusetts Avenue Room 36–841 Cambridge MA 02139 USA

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Predicting Spring Phenology in Deciduous Broadleaf Forests: An Open Community Forecast Challenge

SSRN

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SSRN 2023年

作者： Wheeler, Kathryn I. Dietze, Michael C. LeBauer, David Peters, Jody Richardson, Andrew D. Thomas, R. Quinn Zhu, Kai Bhat, Uttam Munch, Stephan Buzbee, Raphaela Floreani Chenp, Min Goldstein, Benjamin Guo, Jessica S. Haoq, Dalei Jones, Chris Kelly-Fair, Mira Liup, Haoran Malmborg, Charlotte Neupane, Naresh Pal, Debasmita Ross, Arun A. Shirey, Vaughn Song, Yiluan Steen, McKalee Vance, Eric A. Woelmer, Whitney M. Wynne, Jacob Zachmann, Luke Department of Earth and Environment Boston University 685 Commonwealth Avenue BostonMA02215 United States Cooperative Programs for the Advancement of Earth System Science University Corporation for Atmospheric Research Foothills Laboratory Bldg 4 3300 Mitchell Lane BoulderCO80301 United States National Oceanic and Atmospheric Administration Foothills Laboratory Bldg 4 3300 Mitchell Lane BoulderCO80301 United States Department of Civil and Environmental Engineering Massachusetts Institute of Technology 15 Vassar St CambridgeMA02142 United States Arizona Experiment Station University of Arizona 1230 N Cherry Ave TucsonAZ85721 United States Department of Biological Sciences University of Notre Dame 100 Galvin Notre DameIN46556 United States School of Informatics Computing and Cyber Systems Northern Arizona University 1295 Knoles Dr. FlagstaffAZ86011 United States Center for Ecosystem Science and Society Northern Arizona University PO Box 5620 FlagstaffAZ86011 United States Department of Forest Resources and Environmental Conservation Virginia Polytechnic Institute State University 310 West Campus Drive BlacksburgVA24061 United States Department of Biological Sciences Virginia Polytechnic Institute State University 926 West Campus Drive BlacksburgVA24061 United States Institute for Global Change Biology University of Michigan 440 Church Street Ann ArborMI48109 United States School for Environment and Sustainability University of Michigan 440 Church Street Ann ArborMI48109 United States Institute of Marine Sciences University of California Santa Cruz 1156 High Street Santa CruzCA95060 United States Department of Applied Mathematics University of California Santa Cruz 1156 High Street Santa CruzCA95060 United States Department of Environmental Science Policy and Management University of California Berkeley 4004 Valley Life Sciences Building University of California Berkeley BerkeleyCA94720 United States Department of For

Accurate phenology models are important to predict how global climate change will continue to alter the timing of plant phenological events, such as spring greenup in deciduous broadleaf forests. While there is merit in long-term predictions, investigating how models can predict near-term (1– 35 days) canopy greenness throughout the spring allows us to validate performance and understanding now. The Ecological Forecasting Initiative’s NEON Forecasting Challenge, is an open challenge to the community to predict daily greenness values, measured through digital images collected by the PhenoCam Network at National Ecological Observatory Network (NEON) sites. For the first round of the challenge, which is presented here, teams were tasked to forecast phenology at eight deciduous broadleaf sites. A total of 192,536 predictions were submitted, representing eighteen models, including a persistence and a day of year mean null models. We found that forecast skill was highest when forecasting earlier in the greenup curve compared to the end, for shorter lead times, for sites that greened up earlier, and when submitting forecasts during times other than near budburst. The models based on day of year historical mean had the highest predictive skill across the challenge period. In this first round of the challenge, by synthesizing across forecasts, we started to elucidate what factors affect the predictive skill of near-term phenology forecasts, which future rounds will continue to investigate. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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Predicting Spring Phenology in Deciduous Broadleaf Forests: Neon Phenology Forecasting Community Challenge

SSRN

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SSRN 2023年

作者： Wheeler, Kathryn I. Dietze, Michael C. LeBauer, David Peters, Jody Richardson, Andrew D. Ross, Arun A. Thomas, R. Quinn Zhu, Kai Bhat, Uttam Munch, Stephan Buzbee, Raphaela Floreani Chen, Min Goldstein, Benjamin Guo, Jessica Hao, Dalei Jones, Chris Kelly-Fair, Mira Liu, Haoran Malmborg, Charlotte Neupane, Naresh Pal, Debasmita Shirey, Vaughn Song, Yiluan Steen, McKalee Vance, Eric A. Woelmer, Whitney M. Wynne, Jacob Zachmann, Luke Department of Earth and Environment Boston University 685 Commonwealth Avenue BostonMA02215 United States Cooperative Programs for the Advancement of Earth System Science University Corporation for Atmospheric Research Foothills Laboratory Bldg 4 3300 Mitchell Lane BoulderCO80301 United States National Oceanic and Atmospheric Administration Foothills Laboratory Bldg 4 3300 Mitchell Lane BoulderCO80301 United States Department of Civil and Environmental Engineering Massachusetts Institute of Technology 15 Vassar St CambridgeMA02142 United States Arizona Experiment Station University of Arizona 1230 N Cherry Ave TucsonAZ85721 United States Department of Biological Sciences University of Notre Dame 100 Galvin Notre DameIN46556 United States School of Informatics Computing and Cyber Systems Northern Arizona University 1295 Knoles Dr. FlagstaffAZ86011 United States Center for Ecosystem Science and Society Northern Arizona University PO Box 5620 FlagstaffAZ86011 United States Department of Computer Science and Engineering Michigan State University 428 South Shaw Lane East LansingMI48824 United States Department of Forest Resources and Environmental Conservation Virginia Polytechnic Instit 310 West Campus Drive BlacksburgVA24061 United States Department of Biological Sciences Virginia Tech 926 West Campus Drive BlacksburgVA24061 United States Institute for Global Change Biology University of Michigan 440 Church Street Ann ArborMI48109 United States School for Environment and Sustainability University of Michigan 440 Church Street Ann ArborMI48109 United States Institute of Marine Sciences University of California Santa Cruz 1156 High Street Santa CruzCA95060 United States Department of Applied Mathematics University of California Santa Cruz 1156 High Street Santa CruzCA95060 United States Department of Environmental Science Policy and Management University of California Berkeley 4004 Valley Life Sciences Building Universi

Accurate models are important to predict how global climate change will continue to alter plant phenology and near-term ecological forecasts can be used to iteratively improve models and evaluate predictions that are made a priori. The Ecological Forecasting Initiative’s National Ecological Observatory Network (NEON) Forecasting Challenge, is an open challenge to the community to forecast daily greenness values, measured through digital images collected by the PhenoCam Network at NEON sites before the data are collected. For the first round of the challenge, which is presented here, we forecasted canopy greenness throughout the spring at eight deciduous broadleaf sites to investigate what factors impact current predictive skill of phenology forecasts. A total of 192,536 predictions were submitted, representing eighteen models, including a persistence and a day of year mean null models. We found that overall forecast skill was highest when forecasting earlier in the greenup curve compared to the end, for shorter lead times, for sites that greened up earlier, and when submitting forecasts during times other than near budburst. The models based on day of year historical mean had the highest predictive skill across the challenge period. In this first round of the challenge, by synthesizing across forecasts, we started to elucidate what factors affect the predictive skill of near-term phenology forecasts. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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Publisher Correction: An Artificial Intelligence-guided signature reveals the shared host immune response in MIS-C and Kawasaki disease

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Nature communications 2022年第1期13卷 4729页

作者： Pradipta Ghosh Gajanan D Katkar Chisato Shimizu Jihoon Kim Soni Khandelwal Adriana H Tremoulet John T Kanegaye Joseph Bocchini Soumita Das Jane C Burns Debashis Sahoo Department of Cellular and Molecular Medicine University of California San Diego San Diego USA. prghosh@ucsd.edu. Department of Medicine University of California San Diego San Diego USA. prghosh@ucsd.edu. Department of Cellular and Molecular Medicine University of California San Diego San Diego USA. Department of Pediatrics University of California San Diego San Diego USA. Rady Children's Hospital-San Diego San Diego CA USA. Department of Biomedical informatics University of California San Diego San Diego USA. Department of Computer Science and Engineering Jacob's School of Engineering University of California San Diego San Diego USA. Willis-Knighton Health System Shreveport LA USA. Department of Pathology University of California San Diego USA. Department of Pediatrics University of California San Diego San Diego USA. jcburns@health.ucsd.edu. Rady Children's Hospital-San Diego San Diego CA USA. jcburns@health.ucsd.edu. Department of Pediatrics University of California San Diego San Diego USA. dsahoo@ucsd.edu. Department of Computer Science and Engineering Jacob's School of Engineering University of California San Diego San Diego USA. dsahoo@ucsd.edu.

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