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arXiv 2020年

作者： Hu, Liang Tian, Xueyang Wu, Guiling Kong, Mengya Shen, Jianguo Chen, Jianping State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China Shanghai Institute for Advanced Communication and Data Science Shanghai Jiao Tong University Shanghai200240 China the College of Physics and electronic information Engineering Zhejiang Normal University Jinhua321004 China

—We report a technique for coherence transfer of laser light through a fiber link, where the optical phase noise induced by environmental perturbation via the fiber link is compensated by remote users with passive phase noise correction, rather than at the input as is conventional. Neither phase discrimination nor active phase tracking is required due to the open-loop design, mitigating some technical problems such as the limited compensation speed and the finite compensation precision as conventional active phase noise cancellation. We theoretically analyze and experimentally demonstrate that the delay effect introduced residual fiber phase noise after noise compensation is a factor of 7 higher than the conventional techniques. Using this technique, we demonstrate the transfer laser light through a 145-km-long, lab-based spooled fiber. After being compensated, the relative frequency instability in terms of overlapping Allan deviation is 1.9 × 10−15 at 1s averaging time and scales down 5.3×10−19 at 10,000 s averaging time. The frequency uncertainty of the light after transferring through the fiber relative to that of the input light is (−0.36 ± 2.6) × 10−18. As the transmitted optical signal remains unaltered until it reaches the remote sites, it can be transmitted simultaneously to multiple remote sites on an arbitrarily complex fiber network, paving a way to develop a multi-node optical frequency dissemination system with post automatic phase noise correction for a number of end users. Copyright © 2020, The Authors. All rights reserved.

关键词： Natural frequencies

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A strategic review on sustainable approaches in municipal solid waste management andenergy recovery: Role of artificial intelligence,economic stability andlife cycle assessment

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Bioresource technology 2023年 379卷 129044页

作者： Rajendiran Naveenkumar Jayaraj Iyyappan Ravichandran Pravin Seifedine Kadry Jeehoon Han Raveendran Sindhu Mukesh Kumar Awasthi Samuel Lalthazuala Rokhum Gurunathan Baskar Biological Systems Engineering University of Wisconsin-Madison Madison WI 53706 United States Forest Products Laboratory USDA Forest Service Madison WI 53726 United States. Department of Biotechnology Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Thandalam Chennai 602107 India. Department of Biotechnology St. Joseph's College of Engineering Chennai 600119. India. Department of Applied Data Science Noroff University College Kristiansand Norway Artificial Intelligence Research Center (AIRC) Ajman University Ajman 346 United Arab Emirates Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon. Department of Chemical Engineering Pohang University of Science and Technology Pohang 37673 Republic of Korea. Department of Food Technology TKM Institute of Technology Kollam Kerala India. College of Natural Resources and Environment Northwest A&F University Yangling Shaanxi Province 712100 China. Department of Chemistry National Institute of Technology Silchar 788010 Assam India. Department of Biotechnology St. Joseph's College of Engineering Chennai 600119. India Department of Applied Data Science Noroff University College Kristiansand Norway. Electronic address: basg2002@***.

The consumption of energy levels has increased in association with economic growth and concurrently increased the energy demand from renewable sources. The need under Sustainable Development Goals (SDG) intends to explore various technological advancements for the utilization of waste to energy. Municipal Solid Waste (MSW) has been reported as constructive feedstock to produce biofuels, biofuel carriers and biochemicals using energy-efficient technologies in risk freeways. The present review contemplates risk assessment and challenges in sorting and transportation of MSW and different aspects of conversion of MSW into energy are critically analysed. The circular bioeconomy of energy production strategies and management of waste are also analysed. The current scenario on MSW and its impacts on the environment are elucidated in conjunction with various policies and amendments equipped for the competent management of MSW in order to fabricate a sustained environment.

关键词： Circular bioeconomy Municipal Solid Waste Risk assessment Sustainable Waste Management

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Translating the grid: How a translational approach shaped the development of grid computing

arXiv

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arXiv 2020年

作者： Foster, Ian Kesselman, Carl Data Science and Learning Division Argonne National Lab LemontIL60439 United States Department of Computer Science University of Chicago ChicagoIL60637 United States Information Sciences Institute Marina del ReyCA90292 United States Department of Industrial and Systems Engineering U. Southern California Los AngelesCA90089 United States

A growing gap between progress in biological knowledge and improved health outcomes inspired the new discipline of translational medicine, in which the application of new knowledge is an explicit part of a research plan. Abramson and Parashar argue that a similar gap between complex computational technologies and ever-more-challenging applications demands an analogous discipline of translational computer science, in which the deliberate movement of research results into large-scale practice becomes a central research focus rather than an afterthought. We revisit from this perspective the development and application of grid computing from the mid-1990s onwards, and find that a translational framing is useful for understanding the technology’s development and impact. We discuss how the development of grid computing infrastructure, and the Globus Toolkit, in particular, benefited from a translational approach. We identify lessons learned that can be applied to other translational computer science initiatives. Copyright © 2020, The Authors. All rights reserved.

关键词： Grid computing

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Multi-organ metabolome biological age implicates cardiometabolic conditions and mortality risk

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Nature Communications 2025年第1期16卷 1-14页

作者： Aisen, Paul Rafii, Michael S. Bai, Wenjia Walker, Keenan A. Ferrucci, Luigi Tian, Ye Ella Zalesky, Andrew Anagnostakis, Filippos Ko, Sarah Saadatinia, Mehrshad Wang, Jingyue Davatzikos, Christos Wen, Junhao Laboratory of AI and Biomedical Science (LABS) Columbia University New York NY United States Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL) Center for AI and Data Science for Integrated Diagnostics (AI2D) Perelman School of Medicine University of Pennsylvania Philadelphia PA United States Department of Radiology Columbia University New York NY United States New York Genome Center (NYGC) New York NY United States Department of Biomedical Engineering (BME) Columbia University New York NY United States Data Science Institute (DSI) Columbia University New York NY United States Zuckerman Institute Columbia University New York NY United States Center for Innovation in Imaging Biomarkers and Integrated Diagnostics (CIMBID) Department of Radiology Columbia University New York NY United States Systems Lab Department of Psychiatry Melbourne Medical School The University of Melbourne Melbourne VIC Australia National Institute on Aging National Institutes of Health Baltimore MD United States Laboratory of Behavioral Neuroscience National Institute on Aging National Institutes of Health Baltimore MD United States Department of Brain Sciences and Department of Computing Imperial College London London United Kingdom Alzheimer’s Therapeutic Research Institute Keck School of Medicine of the University of Southern California San Diego 92121 CA United States

Multi-organ biological aging clocks across different organ systems have been shown to predict human disease and mortality. Here, we extend this multi-organ framework to plasma metabolomics, developing five organ-specific metabolome-based biological age gaps (MetBAGs) using 107 plasma non-derivatized metabolites from 274,247 UK Biobank participants. Our age prediction models achieve a mean absolute error of approximately 6 years (0.25data due to multicollinearity. Genome-wide associations identify 405 MetBAG-locus pairs (P < 5 × 10⁻⁸/5). Using SBayesS, we estimate the SNP-based heritability (0.09

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Chemical identification and indexing in full-text articles: an overview of the NLM-Chem track at BioCreative VII

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database 2023年第2023期2023卷 baad005-baad005页

作者： Leaman, Robert Islamaj, Rezarta Adams, Virginia Alliheedi, Mohammed A. Almeida, João Rafael Antunes, Rui Bevan, Robert Chang, Yung-Chun Erdengasileng, Arslan Hodgskiss, Matthew Ida, Ryuki Kim, Hyunjae Li, Keqiao Mercer, Robert E. Mertová, Lukrécia Mobasher, Ghadeer Shin, Hoo-Chang Sung, Mujeen Tsujimura, Tomoki Yeh, Wen-Chao Lu, Zhiyong National Center for Biotechnology Information (NCBI) National Library of Medicine National Institutes of Health 8600 Rockville Pike Bethesda 20894 MD United States Nvidia 2788 San Tomas Expressway Santa Clara 95051 CA United States Department of Computer Science Al Baha University 4781 King Fahd Rd Al Aqiq 65779 Saudi Arabia Department of Electronics Telecommunications and Informatics (DETI) Institute of Electronics and Informatics Engineering of Aveiro (IEETA) University of Aveiro Campus Universitário de Santiago Aveiro 3810-193 Portugal Department of Information and Communications Technologies University of A Coruña Camiño Do Lagar de Castro A Coruña 15008 Spain Informatics Department Medicines Discovery Catapult Alderley Park Block 35 Mereside Macclesfield SK10 4ZF United Kingdom Graduate Institute of Data Science Taipei Medical University No. 172-1 Section 2 Keelung Rd Da’an District Taipei City 106 Taiwan Department of Statistics Florida State University 117 N. Woodward Ave Tallahassee 32306 FL United States Computational Intelligence Laboratory Toyota Technological Institute 2-12-1 Hisakata Tempaku-ku Nagoya Aichi 468-8511 Japan Department of Computer Science and Engineering Korea University 145 Anam-ro Seongbuk-gu Seoul 02841 South Korea Department of Computer Science The University of Western Ontario Middlesex College Room 355 London N6A 5B7 ON Canada Scientific Databases and Visualization Group Heidelberg Institute for Theoretical Studies (HITS GGmbH) Schloss-Wolfsbrunnenweg 35 Heidelberg 69118 Germany Institute of Computer Science Heidelberg University Im Neuenheimer Feld 205 Heidelberg 69120 Germany Institute of Information Systems and Applications National Tsing Hua University No. 101 Section 2 Kuang-Fu Road Hsinchu 30013 Taiwan

The BioCreative National Library of Medicine (NLM)-Chem track calls for a community effort to fine-tune automated recognition of chemical names in the biomedical literature. Chemicals are one of the most searched biomedical entities in PubMed, and - as highlighted during the coronavirus disease 2019 pandemic - their identification may significantly advance research in multiple biomedical subfields. While previous community challenges focused on identifying chemical names mentioned in titles and abstracts, the full text contains valuable additional detail. We, therefore, organized the BioCreative NLM-Chem track as a community effort to address automated chemical entity recognition in full-text articles. The track consisted of two tasks: (i) chemical identification and (ii) chemical indexing. The chemical identification task required predicting all chemicals mentioned in recently published full-text articles, both span [i.e. named entity recognition (NER)] and normalization (i.e. entity linking), using Medical Subject Headings (MeSH). The chemical indexing task required identifying which chemicals reflect topics for each article and should therefore appear in the listing of MeSH terms for the document in the MEDLINE article indexing. This manuscript summarizes the BioCreative NLM-Chem track and post-challenge experiments. We received a total of 85 submissions from 17 teams worldwide. The highest performance achieved for the chemical identification task was 0.8672 F-score (0.8759 precision and 0.8587 recall) for strict NER performance and 0.8136 F-score (0.8621 precision and 0.7702 recall) for strict normalization performance. The highest performance achieved for the chemical indexing task was 0.6073 F-score (0.7417 precision and 0.5141 recall). This community challenge demonstrated that (i) the current substantial achievements in deep learning technologies can be utilized to improve automated prediction accuracy further and (ii) the chemical indexing task is substanti

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TDP-43 loss and ALS-risk SNPs drive mis-splicing and depletion of UNC13A (vol 603, pg 131, 2022)

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NATURE 2024年第8020期631卷 E7-E7页

作者： Brown, Anna-Leigh Wilkins, Oscar G. Keuss, Matthew J. Hill, Sarah E. Zanovello, Matteo Lee, Weaverly Colleen Bampton, Alexander Lee, Flora C. Y. Masino, Laura Qi, Yue A. Bryce-Smith, Sam Gatt, Ariana Hallegger, Martina Fagegaltier, Delphine Phatnani, Hemali Phatnani, Hemali Newcombe, Jia Gustavsson, Emil K. Seddighi, Sahba Reyes, Joel F. Coon, Steven L. Ramos, Daniel Schiavo, Giampietro Fisher, Elizabeth M. C. Raj, Towfique Secrier, Maria Lashley, Tammaryn Ule, Jernej Buratti, Emanuele Humphrey, Jack Ward, Michael E. Fratta, Pietro UCL Queen Square Motor Neuron Disease Centre Department of Neuromuscular Diseases UCL Queen Square Institute of Neurology UCL London UK The Francis Crick Institute London UK UK Dementia Research Institute University College London London UK Department of Molecular Biology and Nanobiotechnology National Institute of Chemistry Ljubljana Slovenia National Institute of Neurological Disorders and Stroke NIH Bethesda MD USA Medical Scientist Training Program Johns Hopkins University School of Medicine Baltimore MD USA Center for Alzheimer’s and Related Dementias National Institutes of Health Bethesda MD USA Queen Square Brain Bank UCL Queen Square Institute of Neurology University College London London UK Department of Neurodegenerative Disease UCL Queen Square Institute of Neurology University College London London UK Great Ormond Street Institute of Child Health Genetics and Genomic Medicine University College London London UK Center for Genomics of Neurodegenerative Disease New York Genome Center (NYGC) New York NY USA NeuroResource Department of Neuroinflammation UCL Queen Square Institute of Neurology London UK Molecular Genomics Core Eunice Kennedy Shriver National Institute of Child Health and Human Development NIH Bethesda MD USA Nash Family Department of Neuroscience and Friedman Brain Institute Icahn School of Medicine at Mount Sinai New York NY USA Ronald M. Loeb Center for Alzheimer’s Disease Icahn School of Medicine at Mount Sinai New York NY USA Department of Pathology Fishberg Department of Neuroscience Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics and Genomic Sciences and Icahn Institute for Data Science and Genomic Technology Icahn School of Medicine at Mount Sinai New York NY USA Estelle and Daniel Maggin Department of Neurology Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics Evolution and Environment UCL Genetics Institute University College London London UK Mole

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Operations & Supply Chain Management: Principles and Practice

arXiv

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arXiv 2025年

作者： Petropoulos, Fotios Akkermans, Henk Aksin, O. Zeynep Ali, Imran Babai, Mohamed Zied Barbosa-Povoa, Ana Battaïa, Olga Besiou, Maria Boysen, Nils Brammer, Stephen Brandon-Jones, Alistair Briskorn, Dirk Browning, Tyson R. Buijs, Paul Centobelli, Piera Chiarini, Andrea Cousins, Paul Cudney, Elizabeth A. Davies, Andrew Day, Steven J. de Koster, René Dekker, Rommert Denicol, Juliano Despeisse, Mélanie Disney, Stephen M. Dolgui, Alexandre Duong, Linh El-Qallali, Malek Fahimnia, Behnam Fakhredin, Fatemeh Gershwin, Stanley B. Ghamat, Salar Giannikas, Vaggelis Glock, Christoph H. Godsell, Janet Govindan, Kannan Hannibal, Claire Haug, Anders Hernaus, Tomislav Hsuan, Juliana Ivanov, Dmitry Jahre, Marianne Johansson, Björn Kalidoss, Madan Shankar Kanellopoulos, Argyris Kannan, Devika Karul, Elif Katsikopoulos, Konstantinos V. Kilic-Ararat, Ayse Begüm Kolisch, Rainer Koppenberg, Maximilian Kumar, Maneesh Kuo, Yong-Hong Kusiak, Andrew Lewis, Michael A. Lim, Stanley Frederick W.T. Limère, Veronique Liu, Jiyin Maghazei, Omid Marić, Matija Meissner, Joern Meuwissen, Miranda Micheli, Pietro Nanayakkara, Samudaya Özdemir, Bengü Nur Papadopoulos, Thanos Pavelin, Stephen Perera, Srinath Phillips, Wendy Prak, Dennis Pun, Hubert Qazi, Sharfah Ahmad Ramanathan, Usha Reiner, Gerald Reitsma, Ewout Roehrich, Jens K. Sanders, Nada R. Sarkis, Joseph Schmid, Nico André Schmidt, Christoph G. Schroeder, Andreas Selviaridis, Kostas Seuring, Stefan Shi, Chuan Son, Byung-Gak Spring, Martin Squire, Brian van der Valk, Wendy van Donk, Dirk Pieter van Houtum, Geert-Jan Wilhelm, Miriam Wynstra, Finn Zheng, Ting School of Management University of Bath Bath United Kingdom Department of Information Systems & Operations Management Tilburg School of Economics and Management Tilburg University Netherlands College of Administrative Sciences and Economics Koc University Turkey School of Business and Law Central Queensland University Australia Kedge Business School France Center for Management Studies Instituto Superior Técnico University of Lisbon Portugal Kühne Logistics University Hamburg Germany Friedrich-Schiller-Universität Jena Lehrstuhl für Operations Management Germany Bergische Universität Wuppertal Germany Neeley School of Business Texas Christian University Fort WorthTX United States Department of Operations University of Groningen Netherlands Department of Industrial Engineering University of Naples "Federico II" Italy Department of Management University of Verona Italy Management School University of Liverpool United Kingdom John E. Simon School of Business Maryville University of Saint Louis Missouri United States Science Policy Research Unit University of Sussex Business School Brighton United Kingdom School of Management Zhejiang University China Rotterdam School of Management Erasmus University Netherlands Erasmus School of Economics Erasmus University Netherlands Bartlett School of Sustainable Construction The Bartlett Faculty of the Built Environment University College London United Kingdom Department of Industrial and Material Sciences Chalmers University of Technology Sweden Center for Simulation Analytics and Modelling University of Exeter Business School United Kingdom IMT Atlantique LS2N-CNRS Nantes France College of Business and Law University of the West of England United Kingdom Rabdan Academy United Arab Emirates Institute of Transport and Logistics Studies The University of Sydney Business School Australia Kühne Logistics University Germany Department of Mechanical Engineering Massachusetts Institute of Technology Massachusetts United S

Operations and Supply Chain Management (OSCM) has continually evolved, incorporating a broad array of strategies, frameworks, and technologies to address complex challenges across industries. This encyclopedic article provides a comprehensive overview of contemporary strategies, tools, methods, principles, and best practices that define the field’s cutting-edge advancements. It also explores the diverse environments where OSCM principles have been effectively implemented. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. © 2025, CC BY.

关键词： Supply chain management

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Complete mitochondrial genome sequences of two ground crickets,Dianemobius fascipes nigrofasciatusandPolionemobius taprobanensis(Orthoptera: Grylloidea: trigonidiidae)

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Mitochondrial DNA Part B 2023年第12期8卷

作者： Kohyoh Murata Kosuke Kataoka Ryuto Sanno Kazuhiro Satomura Atsushi Ogura Toru Asahi Kei Yura Takeshi Suzuki a Graduate School of Bio-Applications and Systems Engineering Tokyo University of Agriculture and Technology Tokyo Japan b Comprehensive Research Organization Waseda University Tokyo Japan c Graduate School of Advanced Science and Engineering Waseda University Tokyo Japan d Department of Bioscience Nagahama Institute of Bio-Science and Technology Shiga Japan b Comprehensive Research Organization Waseda University Tokyo Japanc Graduate School of Advanced Science and Engineering Waseda University Tokyo Japane Global Consolidated Research Institute for Science Wisdom Waseda University Tokyo Japanf Institute for Advanced Research of Biosystem Dynamics Waseda Research Institute for Science and Engineering Waseda University Tokyo Japang Research Organization for Nano & Life Innovation Waseda University Tokyo Japan c Graduate School of Advanced Science and Engineering Waseda University Tokyo Japanh Graduate School of Humanities and Sciences Ochanomizu University Tokyo Japani Computational Bio Big-Data Open Innovation Laboratory (CBBD-OIL) National Institute of Advanced Industrial Science and Technology Tokyo Japan

The authors sequenced the complete mitochondrial (mt) genomes of the band-legged ground cricket (Dianemobius fascipes nigrofasciatusMatsumura, 1904) and a temperate form of the lawn ground cricket (Polionemobius taprobanensisWalker, 1869), collected in Japan. The length of the mt genome sequences was 15,354 bp inD. fascipes nigrofasciatusand 16,063 bp inP. taprobanensis. Annotation of the mt genome sequences revealed 13 protein-coding genes, two rRNA genes, and 22 tRNA genes. The orientation of the genes was the same as in other Grylloidea species, and the order was the same as in other Trigonidiidae species. In our phylogenetic analysis,D. fascipes nigrofasciatusformed a clade withD. fascipescollected in China, and the temperate form ofP. taprobanensisformed a clade withP. taprobanensiscollected in China. Comparison of the numbers of positions with different amino acid residues encoded by the protein-coding genes implied the separate species status of each member of each of the two pairs of ground crickets. The mt genome sequences ofD. fascipes nigrofasciatusandP. taprobanensiswill contribute to phylogenetic and taxonomic studies of the Trigonidiidae.

关键词： Complete mitogenome crickets phylogenetic analysis speciation

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Blind identification of stochastic block models from dynamical observations

arXiv

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arXiv 2019年

作者： Schauby, Michael T. Segarraz, Santiago Tsitsiklisx, John N. Institute for Data Systems and Society Massachusetts Institute of Technology United States Department of Engineering Science University of Oxford Department of Electrical and Computer Engineering Rice University United States Laboratory of Information and Decision Systems Massachusetts Institute of Technology United States

We consider a blind identification problem in which we aim to recover a statistical model of a network without knowledge of the network's edges, but based solely on nodal observations of a certain process. More concretely, we focus on observations that consist of snapshots of a diffusive process that evolves over the unknown network. We model the network as generated from an independent draw from a latent stochastic block model (SBM), and our goal is to infer both the partition of the nodes into blocks, as well as the parameters of this SBM. We present simple spectral algorithms that provably solve the partition recovery and parameter estimation problems with high accuracy. Our analysis relies on recent results in random matrix theory and covariance estimation, and associated concentration inequalities. We illustrate our results with several numerical experiments. Copyright © 2019, The Authors. All rights reserved.

关键词： Blind equalization

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AB0214 ASSOCIATION BETWEEN ACCELEROMETER-MEASURED DAILY STEP COUNT AND INCIDENT RHEUMATOID ARTHRITIS: A PROSPECTIVE COHORT STUDY IN THE UK BIOBANK

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Annals of the Rheumatic Diseases 2024年 83卷 1345-1345页

作者： D. Mcgagh A. Acquah L. Portas C. Zisou A. Shreves C. Harper S. Fenton A. Doherty L.C. Coates University of Oxford Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences Oxford United Kingdom University of Oxford Nuffield Department of Population Health Oxford United Kingdom University of Oxford Big Data Institute Li Ka Shing Centre for Health Information and Discovery Oxford United Kingdom University of Oxford Department of Engineering Science Oxford United Kingdom National Institutes of Health Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda United States of America University Hospitals Birmingham NHS Foundation Trust National Institute for Health Research Birmingham Biomedical Research Centre Birmingham United Kingdom University of Birmingham School of Sport Exercise and Rehabilitation Sciences Birmingham United Kingdom

Background: Existing evidence on the association between physical activity and rheumatoid arthritis (RA) remains conflicted due to a reliance on self-reported physical activity questionnaires, which are crude and prone to recall bias. Wearable devices, such as accelerometers can continuously and more objectively measure physical activity level. Objectives: We aimed to examine the dose-response association between accelerometer-measured daily step count and incident rheumatoid arthritis. Methods: This prospective cohort study was based on wrist-worn accelerometer data from the UK Biobank, where participants wore a device for seven days. Participants with prevalent inflammatory arthritis (RA, psoriatic arthritis or ankylosing spondylitis) were excluded. Daily steps were computed using a validated hybrid self-supervised machine learning step detection algorithm. Physical activity was characterised as median daily step count over a seven-day period, as a continuous measurement, in quarters of steps (<6818, 6818-9055, 9056-11659, >11659 daily steps) and per 1000 step increase. Incident RA cases were identified via record linkage with hospital inpatient data. Cox proportional hazards models were utilised to investigate the association between daily step count and incident RA adjusting for sociodemographic and lifestyle factors. Subgroup analyses were conducted to explore the association per 1000 step increase and incident RA, stratified by sex, age group (40-49, 50-59, 60-69 and 70-79) and body mass index (BMI by categories: <25, 25-29.9, >30 kg/m2). Sensitivity analyses removing RA diagnoses within 2 and 4 years of accelerometer wear and further adjusting for BMI were conducted. Results: Amongst 91,069 participants aged 62.3 (SD 7.8) years and with a median follow-up of 7.9 years, there were 629 incident RA cases (87.4 cases per 100,000 person years). Higher median daily step count was associated with lower risk of incident RA, and this association was approximately inve

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