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arXiv 2020年

作者： Arnaud, M. Ettori, S. Pratt, Gabriel W. Rossetti, M. Eckert, D. Gastaldello, F. Gavazzi, R. Kay, S.T. Lovisari, L. Maughan, B.J. Pointecouteau, E. Sereno, M. Bartalucci, I. Bonafede, A. Bourdin, H. Cassano, R. Duffy, R.T. Iqbal, A. Maurogordato, S. Rasia, E. Sayers, J. Andrade-Santos, F. Aussel, H. Barnes, D.J. Barrena, R. Borgani, S. Burkutean, S. Clerc, N. Corasaniti, P.-S. Cuillandre, J.-C. de Grandi, S. de Petris, M. Dolag, K. Donahue, M. Ferragamo, A. Gaspari, M. Ghizzardi, S. Gitti, M. Haines, C.P. Jauzac, M. Johnston-Hollitt, M. Jones, C. Kéruzoré, F. LeBrun, A.M.C. Mayet, F. Mazzotta, P. Melin, J.-B. Molendi, S. Nonino, M. Okabe, N. Paltani, S. Perotto, L. Pires, S. Radovich, M. Rubino-Martin, J.-A. Salvati, L. Saro, A. Sartoris, B. Schellenberger, G. Streblyanska, A. Tarrío, P. Tozzi, P. Umetsu, K. van der Burg, R.F.J. Vazza, F. Venturi, T. Yepes, G. Zarattini, S. AIM CEA CNRS Université Paris-Saclay Université Paris Diderot Sorbonne Paris Cité Gif-sur-YvetteF-91191 France INAF Osservatorio di Astrofisica e Scienza dello Spazio via Pietro Gobetti 93/3 Bologna40129 Italy INFN Sezione di Bologna viale Berti Pichat 6/2 BolognaI-40127 Italy INAF IASF-Milano via A. Corti 12 MilanoI-20133 Italy Department of Astronomy University of Geneva ch. d'Écogia 16 VersoixCH-1290 Switzerland CNRS Sorbonne Université UMR 7095 Institut d'Astrophysique de Paris 98 bis Boulevard Arago Paris75014 France Jodrell Bank Centre for Astrophysics Department of Physics and Astronomy School of Natural Sciences The University of Manchester ManchesterM13 9PL United Kingdom Center for Astrophysics | Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States HH Wills Physics Laboratory University of Bristol Tyndall Ave BristolBS8 1TL United Kingdom IRAP Université de Toulouse CNRS CNES UPS 9 av du colonel Roche BP44346 Toulouse Cedex 431028 France Dipartimento di Fisica e Astronomia Universitá di Bologna Via Gobetti 92/3 Bologna40121 Italy INAF Istituto di Radio Astronomia Via Gobetti 101 Bologna40129 Italy Hamburger Sternwarte Gojenbergsweg 112 Hamburg21029 Germany Università degli studi di Roma Tor Vergata via della ricerca scientifica 1 Roma00133 Italy Université Côte d'Azur Observatoire de la Côte d'Azur CNRS Laboratoire Lagrange Nice France INAF - Osservatorio Astronomico di Trieste via Tiepolo 11 TriesteI-34131 Italy IFPU - Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy California Institute of Technology PasadenaCA91125 United States Department of Physics Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology CambridgeMA02139 United States C/ Vía Láctea s/n La Laguna TenerifeE-38205 Spain Universidad de La Laguna Departamento de Astrofísica C/ Astrofísico Francisco Sánchez s/n La Laguna TenerifeE-38206 Spain D

The Cluster HEritage project with XMM-Newton - Mass Assembly and Thermodynamics at the Endpoint of structure formation (CHEX-MATE) is a three-mega-second Multi-Year Heritage programme to obtain X-ray observations of a minimally-biased, signal-to-noise-limited sample of 118 galaxy clusters detected by Planck through the Sunyaev-Zeldovich effect. The programme, described in detail in this paper, aims to study the ultimate products of structure formation in time and mass. It is composed of a census of the most recent objects to have formed (Tier-1: 0.05 14 M 500 14 M), together with a sample of the highest mass objects in the Universe (Tier-2: z 500 > 7.25 × 1014 M). The programme will yield an accurate vision of the statistical properties of the underlying population, measure how the gas properties are shaped by collapse into the dark matter halo, uncover the provenance of non-gravitational heating, and resolve the major uncertainties in mass determination that limit the use of clusters for cosmological parameter estimation. We will acquire X-ray exposures of uniform depth, designed to obtain individual mass measurements accurate to 15 − 20% under the hydrostatic assumption. We present the project motivations, describe the programme definition, and detail the ongoing multi-wavelength observational (lensing, SZ, radio) and theoretical effort that is being deployed in support of the project. Copyright © 2020, The Authors. All rights reserved.

关键词： Thermodynamics

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BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series

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Global Ecology and Biogeography 2025年第5期34卷

作者： Maria Dornelas Laura H. Antão Amanda E. Bates Viviana Brambilla Jonathan M. Chase Cher F. Y. Chow Ada Fontrodona-Eslava Anne E. Magurran Inês S. Martins Faye Moyes Alban Sagouis Samuel Adu-Acheampong Daniel Acquah-Lamptey Dušan Adam Penelope A. Ajani Aitor Albaina Pablo Almaraz Jeongseop An Roger Sigismund Anderson Madelaine Jean Robertson Anderson Alexsander Z. Antunes Ivan Arismendi Linda Armbrecht Pedro Aros-Mardones Sreejith Kalpuzha Ashtamoorthy Narayanan Ayyappan Gal Badihi Joseph J. Bailey Andrew H. Baird Mark Edward Baird Sreekumar Vadakkethil Balakrishnan José António L. Barão-Nóbrega Adi Barash Miguel Barbosa Jos Barlow Claus Bässler Matthieu Beaumont Natalie Beenaerts Tiago Octavio Begot Wallace Beiroz Ricardo Beldade David M. Bell Alecia Bellgrove Jonathan Belmaker Lisandro Benedetti-Cecchi Cassandra E. Benkwitt Pamela Medina-van Berkum Brandon T. Bestelmeyer Matthew G. Betts Maxwell Kelvin Billah Anne D. Bjorkman Magdalena Błażewicz Christopher P. Bloch Shane A. Blowes Antonio Bode Juliano A. Bogoni Thomas Bolger Timothy C. Bonebrake Erik Bonsdorff Roberta Bottarin Luke N. Brokensha Rob W. Brooker Andrew J. Brooks Helge Bruelheide Thiago Almeida Bueno Claire Laguionie Mariana Lopes Campagnoli James Cant Erica Pellegrini Caramaschi Alexandre Caron Tadhg Carroll Tancredi Caruso Juan Carvajal-Quintero Giuseppe Castaldelli Edward Castañeda-Moya Pedro V. Castilho Sonia Zanini Cechin Shahar Chaikin Uchangi Manjunatha Chandrashekara Tory J. Chase Chaolun Allen Chen Jorge José Cherem Sei-Woong Choi Erica M. Christensen Alexander V. Christianini Jackson Wing Four Chu Peter Coad Carl Van Colen Lise Comte Elisabeth J. Cooper J. Hans C. Cornelissen Eddy Cosson Unai Cotano Luc Crevecoeur Shannan Kyle Crow Graeme S. Cumming Vanessa S. Daga Gabriella Damasceno Gergana N. Daskalova Claire H. Davies Robert A. Davis Frank P. Day Sussy De-La-Zerda Amy Elizabeth Deacon Indradatta de Castro-Arrazola Steven Degraer Kharran Deonarinesingh Juan C. Diaz-Ricaurte Christopher R. Dickman Tara Dirilgen Ciaran John Dolan J. Emmet Centre for Biological Diversity School of Biology University of St Andrews Fife UK MARE—Centro de Ciências do Mar e do Ambiente Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Research Centre for Ecological Change Organismal and Evolutionary Biology Research Programme Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland Department of Biology University of Victoria Victoria British Columbia Canada German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig Leipzig Germany Department of Computer Science Martin Luther University Halle-Wittenberg Halle (Saale) Germany Leverhulme Centre for Anthropocene Biodiversity Department of Biology University of York York UK Department of Animal Biology and Conservation Science University of Ghana Accra Ghana Philipps Universität Marburg Marburg Germany Department of Forest Ecology Silva Tarouca Research Institute Brno Czech Republic School of Life Sciences University of Technology Sydney Sydney New South Wales Australia Zoology and Animal Cell Biology Department University of the Basque Country (UPV/EHU) Leioa Spain Grupo de Oceanografía de Ecosistemas Instituto de Ciencias Marinas de Andalucía CSIC Campus Universitario de Puerto Real Puerto Real Spain National Institute of Ecology Seocheon Republic of Korea African Regional Postgraduate Programme in Insect Science University of Ghana Accra Ghana Département de Biologie Université de Sherbrooke Sherbrooke Quebec Canada Núcleo de Conservação da Biodiversidade Instituto de Pesquisas Ambientais Secretaria de Meio Ambiente Infraestrutura e Logística do Estado de São Paulo São Paulo Brazil Department of Fisheries Wildlife and Conservation Sciences Oregon State University Corvallis Oregon USA Institute for Marine and Antarctic Studies Ecology & Biodiversity Centre University of Tasmania Hobart Tasmania Australia Graduate Program in Oceanography Department of Oceanography Faculty of Natural Scienc

Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

关键词： assemblage biodiversity community database ecoinformatics species taxa time

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Computation of grounding grids parameter on unconventional geometry

Computation of grounding grids parameter on unconventional g...

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CHILEAN Conference on Electrical, Electronics engineering, Information and Communication Technologies (CHILECON)

作者： Thyago G. Pires Carlos L. B. Silva Diogo N. Oliveira Jose W. L. Nerys Aylton J. Alves Wesley P. Calixto School of Electrical and Computer Engineering Federal University of Goias Goiania Brazil Graduate Program in Electronic and Automation Systems Engineering University of Brasilia Brasilia Brazil Experimental & Technologic Researsh and Study Group Federal Institute of Education Goiania Brazil

ISBN: (纸本)9781467387576

This paper deals with the computation of ground resistance, surface voltage, touch voltage and step voltage, to mesh with horizontal wires arranged in different angles. The computer program implemented used in the mathematical modeling is based on the method proposed by Heppe, which allows obtaining the grounding parameters for homogeneous soil and soil stratified in two layers. Furthermore, the results obtained by the Variable Currents Method (VCM) have been compared to traditional methods and the simplified method of ANSI-IEEE Std. 80/2013. They also present the results using a grounding grid with wires on various angles.

关键词： Soil Leakage currents Image segmentation Conductivity Grounding Surface resistance

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2D and 3D photogrammetric models for respiratory analysis in adolescents

2D and 3D photogrammetric models for respiratory analysis in...

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13th Mediterranean Conference on Medical and Biological engineering and Computing 2013, MEDICON 2013

作者： Ripka, W.L. Ulbricht, Leandra Neves, E.B. Gewehr, P.M. Federal University of Technology-Paraná Graduate Program in Electrical Engineering and Computer Science Curitiba Brazil Federal University of Technology-Paraná Graduate Program in Biomedical Engineering Curitiba Brazil

ISBN: (纸本)9783319008455

The aim of this study was to test the correlation between a two dimensional (2D) and three dimensional (3D) biomechanical photogrammetric model, with inspiratory and expiratory lung capacities in adolescents. This was a cross sectional study, in which 40 adolescents of both genders were assessed, aged between 14 and 17 years old. Anthropometric data were collected (body mass, height and thorax length). Then, three tests were performed for forced vital capacity (FVC) in the supine position, using a spirometer. For FVC proof assessments, the volunteers were subjected to a mapping of body structures with adhesive markers and, after the test, one was selected with better respiratory performance for computational analysis of photogrammetric thoracoabdominal mobility. The results showed average values of 15.40, 61.29, 1.66 and 25.54, for age (years), body mass (kg), height (m) and thorax length (cm), respectively. The analysis found respiratory values of: 3:22 l for forced expiratory volume in one second, 3.87 l for forced vital capacity, 6.50 l/s for peak expiratory flow and 3.59 l for deep inspiration. The correlation showed better values for 3D photogrammetry as compared to 2D. The inclusion of the third dimension has been applied in order to adequate photogrammetric methodology to existing kinematics analysis tools as videogrammetry computed and plethysmography. © Springer International Publishing Switzerland 2014.

关键词： Photogrammetry

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Erratum: An intrinsic mechanism controls reactivation of neural stem cells by spindle matrix proteins

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Nature communications 2017年第1期8卷 1298页

作者： Song Li Chwee Tat Koe Su Ting Tay Angie Lay Keng Tan Shenli Zhang Yingjie Zhang Patrick Tan Wing-Kin Sung Hongyan Wang Neuroscience and Behavioural Disorders Program Duke-NUS Medical School 8 College Road Singapore 169857 Singapore. Cancer and Stem Cell Biology Program Duke-NUS Medical School 8 College Road Singapore 169857 Singapore. NUS Graduate School for Integrative Sciences and Engineering National University of Singapore 28 Medical Drive Singapore 117456 Singapore. Cellular and Molecular Research National Cancer Centre Singapore 169610 Singapore. Cancer Science Institute of Singapore National University of Singapore Singapore 119074 Singapore. Genome Institute of Singapore 60 Biopolis Street Genome 02-01 Singapore 138672 Singapore. Department of Computer Science National University of Singapore Singapore 117417 Singapore. Neuroscience and Behavioural Disorders Program Duke-NUS Medical School 8 College Road Singapore 169857 Singapore. hongyan.wang@duke-nus.edu.sg. NUS Graduate School for Integrative Sciences and Engineering National University of Singapore 28 Medical Drive Singapore 117456 Singapore. hongyan.wang@duke-nus.edu.sg. Department of Physiology Yong Loo Lin School of Medicine National University of Singapore Singapore 117597 Singapore. hongyan.wang@duke-nus.edu.sg.

A correction to this article has been published and is linked from the HTML version of this article.

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Multi-class classification of objects in images using principal component analysis and genetic programming

Multi-class classification of objects in images using princi...

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Latin America Congress on Computational Intelligence (LA-CCI)

作者： Manassés Ribeiro Heitor Silvério Lopes Federal Catarinense Institute of Education Science and Technology (IFC) Videira Santa Catarina Brazil Graduate Program in Electrical and Computer Engineering (CPGEI) Federal University of Technology of Paraná (UTFPR) Curitiba Paraná Brazil

This work presents a methodology for using Principal Component Analysis (PCA) and Genetic programming (GP) for the classification of multi-class objects found in digital images. The image classification process is performed by using features extracted from images, through feature extraction algorithms, reduced by PCA and labeled by similarity comparing with other previously classified objects. GP uses two sets of elements: terminals, composed by the features extracted by PCA; and non-terminals, composed by algebraic operations. The fitness function was defined by the product of sensibility and specificity, two performance measures. A penalty term is also used to decrease the number of nodes of the tree, while minimally affecting the quality of solutions. The proposed approach was applied to set of 2739 digital images divided into objects representing airplanes, motorbikes, background from google, faces and watch classes, provided by the Caltech101 image database. The proposed approach was compared with SVM, Naïve Bayes and C4.5. Results suggest that the approach PCA+GP is able to evolve solutions for the problem as a simple classification rule with true positive rate above 70%. Additionally, we observe that PCA+PG obtained results slightly better than SVM and C4.5, besides these methods give a result that is not comprehensible by humans.

关键词： Principal component analysis Image color analysis Feature extraction Histograms Shape Genetic programming Support vector machines

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Protected shortest path visiting specified nodes

Protected shortest path visiting specified nodes

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International Workshop on Reliable Networks Design and Modeling (RNDM)

作者： Teresa Gomes Sofia Marques Lúcia Martins Marta Pascoal David Tipper INESC Coimbra Coimbra Portugal Department of Electrical and Computer Engineering University of Coimbra Coimbra Portugal Department of Mathematics Coimbra Portugal Graduate Telecommunications and Networking Program University of Pittsburgh Pittsburgh PA USA

In this paper heuristics are proposed for finding the shortest loopless path, from a source node to a target node, that visits a given set of nodes in a directed graph, such that it can be protected using a node-disjoint path. This type of problem may arise due to network management constraints. The problem of calculating the shortest path that visits a given set of nodes is at least as difficult as the traveling salesman problem, and it has not received much attention. Nevertheless an efficient integer linear programming (ILP) formulation has been recently proposed for this problem. Here, the ILP formulation is adapted to include the constraint that the obtained path will be able to be protected by a node-disjoint path. Computational experiments show that this approach, namely in large networks, may fail to obtain a solution in a reasonable amount of time. Therefore three versions of a heuristic are proposed, for which extensive computational results show that they are able to find a solution in most cases, and that the calculated solutions present an acceptable relative error regarding the cost of the optimal active path. Further the CPU time required by the heuristics is significantly smaller than the required by the used ILP solver.

关键词： Algorithm design and analysis Heuristic algorithms Amplitude shift keying Mathematical model Routing Electronic mail Complexity theory

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Cough Detection Through Mechanomyographic Signal in Synchronized Respiratory Electrical Stimulation Systems

Cough Detection Through Mechanomyographic Signal in Synchron...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Taisa D. Costa Guilherme N. Nogueira-Neto Percy Nohama the Graduate Program in Electrical and Computer Engineering Federal University of Technology Parana Brazil Pontifical Catholic University of Parana Parana Brazil Pontifical Catholic University of Parana and Federal University of Technology Parana Brazil

ISBN: (纸本)9781424492695

Synchronization of transcutaneous functional electrical stimulation (TFES) with the spontaneous inspiration and expiration phases is a new approach for respiratory rehabilitation. One of the requirements for proper operation is the identification of cough events to automatically change the stimulation parameters in order to increase muscle strength during the cough. The aim of this work is to assess the viability in detection of cough events with a mechanomyographic (MMG) sensor on the abdominal region, and to evaluate if it can be used simultaneously with the synchronized TFES system. An MMG sensor was placed in contact with skin lined with the last ribs, above the rectus abdominis muscle and the linea alba. Two tests were accomplished which included quiet breathing, speaking and coughing episodes. The developed system efficiently distinguishes quiet breathing and coughing signals, but speaking is still confused with coughing episodes. The MMG sensor suffered detectable amplitude changes mainly during the forced expiration phase of the cough, but it could also detect the compression phase at lower amplitude. Therefore, the MMG system can be used for cough detection in this application.

关键词： TFES MMG cough Cough Rectus Abdominis respiration Electric Stimulation abdominal region normal operation

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Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM_2·5 air pollution, 1990–2019: an analysis of data from the Global Burden of Disease Study 2019

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The Lancet Planetary Health 2022年第7期6卷 e586-e600页

作者： Burkart, Katrin Causey, Kate Cohen, Aaron J Wozniak, Sarah S Salvi, Devashri Digvijay Abbafati, Cristiana Adekanmbi, Victor Adsuar, Jose C Ahmadi, Keivan Alahdab, Fares Al-Aly, Ziyad Alipour, Vahid Alvis-Guzman, Nelson Amegah, Adeladza Kofi Andrei, Catalina Liliana Andrei, Tudorel Ansari, Fereshteh Arabloo, Jalal Aremu, Olatunde Aripov, Timur Babaee, Ebrahim Banach, MacIej Barnett, Anthony Bärnighausen, Till Winfried Bedi, Neeraj Behzadifar, Masoud Béjot, Yannick Bennett, Derrick A Bensenor, Isabela M Bernstein, Robert S Bhattacharyya, Krittika Bijani, Ali Biondi, Antonio Bohlouli, Somayeh Breitner, Susanne Brenner, Hermann Butt, Zahid A Cámera, Luis Alberto Cantu-Brito, Carlos Carvalho, Felix Cerin, Ester Chattu, Vijay Kumar Chauhan, Bal Govind Choi, Jee-Young Jasmine Chu, Dinh-Toi Dai, Xiaochen Dandona, Lalit Dandona, Rakhi Daryani, Ahmad Davletov, Kairat De Courten, Barbora Demeke, Feleke Mekonnen Denova-Gutiérrez, Edgar Dharmaratne, Samath Dhamminda Dhimal, Meghnath Diaz, Daniel Djalalinia, Shirin Duncan, Bruce B El Sayed Zaki, Maysaa Eskandarieh, Sharareh Fareed, Mohammad Farzadfar, Farshad Fattahi, Nazir Fazlzadeh, Mehdi Fernandes, Eduarda Filip, Irina Fischer, Florian Foigt, Nataliya A Freitas, Marisa Ghashghaee, Ahmad Gill, Paramjit Singh Ginawi, Ibrahim Abdelmageed Gopalani, Sameer Vali Guo, Yuming Gupta, Rajat Das Habtewold, Tesfa Dejenie Hamadeh, Randah R Hamidi, Samer Hankey, Graeme J Hasanpoor, Edris Hassen, Hamid Yimam Hay, Simon I Heibati, Behzad Hole, Michael K Hossain, Naznin Househ, Mowafa Irvani, Seyed Sina Naghibi Jaafari, Jalil Jakovljevic, Mihajlo Jha, Ravi Prakash Jonas, Jost B Jozwiak, Jacek Jerzy Kasaeian, Amir Kaydi, Neda Khader, Yousef Saleh Khafaie, Morteza Abdullatif Khan, Ejaz Ahmad Khan, Junaid Khan, Md Nuruzzaman Khatab, Khaled Khater, Amir M Kim, Yun Jin Kimokoti, Ruth W Kisa, Adnan Kivimäki, Mika Knibbs, Luke D Kosen, Soewarta Koul, Parvaiz A Koyanagi, Ai Defo, Barthelemy Kuate Kugbey, Nuworza Lauriola, Paolo Lee, Paul H Leili, Mostafa Lewycka, Sonia Li, Shanshan Lim, Lee-Ling Li 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 Plastic and Reconstructive Surgery University of Washington Seattle WA United States Research Insights and Innovation Seattle WA United States Health Effects Institute Boston MA United States School of Public Health Boston University Boston MA United States Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Population Medicine Cardiff University Cardiff United Kingdom Sport Science Department University of Extremadura Badajoz Spain School of Public Health Imperial College London London United Kingdom Department of Primary Care and Public Health Imperial College London London United Kingdom Mayo Evidence-based Practice Center Mayo Clinic Foundation for Medical Education and Research Rochester MN United States John T. Milliken Department of Internal Medicine Washington University in St. Louis St. Louis MO United States Clinical Epidemiology Center US Department of Veterans Affairs (VA) St Louis MO United States Health Management and Economics Research Center Iran University of Medical Sciences Tehran Iran Department of Health Economics Iran University of Medical Sciences Tehran Iran Preventive Medicine and Public Health Research Center Iran University of Medical Sciences Tehran Iran Pars Advanced and Minimally Invasive Medical Manners Research Center Iran University of Medical Sciences Tehran Iran Department of Community and Family Medicine Iran University of Medical Sciences Tehran Iran Research Group in Hospital Management and Health Policies Universidad de la Costa (University of the Coast) Barranquilla Colombia Research Group in Health Economics University of Cartagena Cartagena Colombia Department of Biomedical Science University of Cape Coast Cape Coast Ghana Cardiology Department Ca

Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM_2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM_2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM_2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM_2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM_2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South Am

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