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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Zeng, Shuai Yuan, Yong Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728128535

The privacy issues become a major problem that should be resolved for the existing centralized online social networks, which have prompted researchers to consider the decentralization framework for online social networks. In this paper, we propose a novel decentralized social networking architecture enhanced by blockchain technology. We use a sharding framework to increase the system scalability, a blockchain system to ensure the data integrity and consistency, a reputation-based authority control method to improve the system security. © 2019 IEEE.

关键词： Blockchain

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Emissions reduction potential and feasibility of vehicle-to-grid for Beijing’s future electric vehicles

Cell Reports Physical Science

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Cell Reports Physical Science 2025年

作者： Jiaxin Xu Jiahui Chen Hongyi Wei Yinan Zhao Bowen Tian Yifan Wen Haiyang Jiang Ning Zhang Shaojun Zhang Ye Wu School of Environment Tsinghua University Beijing 100084 China Center for Sustainable Systems School for Environment and Sustainability University of Michigan Ann Arbor MI 48109 USA School of Electrical and Power Engineering Power System Research Institute Tsinghua University Beijing 100084 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084 China Beijing Laboratory of Environmental Frontier Technologies School of Environment Tsinghua University Beijing 100084 China State Key Laboratory of Regional Environment and Sustainability Tsinghua University Beijing 100084 China

Electric vehicles (EVs) offer significant potential to reduce greenhouse gas (GHG) emissions from road transport. However, nighttime charging increases peak demand and thermal power reliance. This study evaluates vehicle-to-grid (V2G) as a solution by integrating GPS-based EV travel data with hourly grid modeling for 2 million EVs in Beijing. Results show V2G boosts renewable energy use in charging to 66%, up from under 4% in uncoordinated charging. V2G cuts vehicle uncoordinated charging emissions by 20.6% and reduces the grid’s GHG footprint by replacing thermal power with discharging electricity. Commuter vehicles and the summer months offer the highest V2G emissions reduction potential. The study finds battery degradation manageable and highlights synergies between V2G, renewable capacity expansion, and economic incentives, while emphasizing the need for robust infrastructure and local grid networks to support large-scale EV adoption. This approach therefore offers a promising pathway to accelerate sustainable energy solutions amid increasing vehicle electrification and renewable integration.

关键词： electric vehicles vehicle to grid V2G GHG emissions travel pattern grid optimization

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Influence of initial oxidation and secondary oxidation on spontaneous combustion of lignite

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International Journal of Microstructure and Materials Properties 2019年第1期14卷 60-77页

作者： Huang, Zhi-An Zhang, Ling-Hua Wang, Jing-Jing Yang, Rui Zhang, Ying-Hua Wang, Hui Chen, Yu-Yan Gao, Yu-Kun State Key Laboratory of High-Efficient Mining Safety of Metal Mines University of Science and Technology Beijing Ministry of Education Beijing100083 China Work Safety Key Lab on Prevention and Control of Gas and Roof Disasters for Southern Coal Mines Hunan University of Science and Technology Xiangtan411201 China State Key Laboratory Cultivation Base for Gas Geology and Gas Control Henan Polytechnic University Jiaozuo454000 China Beijing Research Center of Urban System Engineering Beijing Key Laboratory of Operation Safety of Gas Heating and Underground Pipelines Beijing100035 China

In order to prevent the re-ignition of residual coal, this study presents a study of initial oxidation and secondary oxidation on the spontaneous combustion characteristics of coal. Three physical experiment methods:pore volume analysis, Fourier transform infrared spectroscopy and cross point temperature method, were used to study the spontaneous combustion of lignite. The results show that the pore volume of coal increases with the increase of oxidation temperature. With the increase of temperature, different functional groups in the coal sample show different trends. Compared with initial oxidation, the tendency of the functional group changes again during the secondary oxidation. In the case of constant initial temperature of secondary oxidation, the crossing point temperature of coal samples show a decreasing trend at first and rising later. And in the case of constant initial temperature of initial oxidation, the crossing point temperature of coal samples show a trend of rising. © 2019 Inderscience Enterprises Ltd.

关键词： Spontaneous combustion

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Extreme temperatures amplify air pollution risks to childhood respiratory health in school environment in Jiangsu province, China

Communications Earth & Environment

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Communications Earth & Environment 2025年第1期6卷 1-11页

作者： Yangyang Wu Biran Cheng Chen Li Lei Huang Jie Yang Hong Sun Jing Wei Yiyi Wang Peng Wang State Key Laboratory of Water Pollution Control and Green Resource Recycling School of the Environment Nanjing University 163 Xianlin Avenue Qixia Nanjing 210023 China Department of Civil and Environmental Engineering The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong Center for Public Health Research Medical School Nanjing University Nanjing Jiangsu 210093 China Basic Science Center for Energy and Climate Change Beijing 100081 China Jiangsu Provincial Center for Disease Control and Prevention Jiangsu Road 172 Nanjing 210009 China Department of Atmospheric and Oceanic Science Earth System Science Interdisciplinary Center University of Maryland College Park MD USA School of Energy and Environment Anhui University of Technology Maanshan 243002 China Jiangsu University Faculty of Civil Engineering and Mechanics 301 Xuefu Road Jingkou District Zhenjiang Jiangsu 212013 China

Childhood respiratory diseases remain a major global health concern, with school-centered exposures to air pollution and extreme temperatures posing significant risks. We conducted a spatiotemporal stratified multi-city, school-based design to evaluate underexplored risk patterns of fine particulate matter with an aerodynamic diameter ≤1 µm, nitrate, sulfate, ammonium, chloride, black carbon, and temperature exposures including daily mean, extremes, and short-term variability. The analysis included 265,076 pneumonia and/or tracheitis cases among schoolchildren in Jiangsu Province, China. We observed significant urban–rural disparities and spatial clustering in air pollution and temperature variation. Cumulative exposure to all pollutants was positively associated with increased risk of illness-related absences, with stronger effects observed in urban schools and during low-temperature conditions overall. Boys showed higher initial sensitivity to air pollution, while girls exhibited greater vulnerability after 10–14 days. Notably, urban children were most affected by combined exposures to low temperature-high pollution, whereas rural children experienced greater combined risks under high-temperature conditions. In contrast, short-term temperature variability contributed minimally to the observed health effects. These findings support the development of early warning systems for composite exposures, informed by exposure–risk profiles, to enable timely school intervention and protect schoolchildren’s respiratory health.

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SLV: Spatial Likelihood Voting for Weakly Supervised Object Detection

arXiv

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arXiv 2020年

作者： Chen, Ze Fu, Zhihang Jiang, Rongxin Chen, Yaowu Hua, Xian-sheng Zhejiang University Institute of Advanced Digital Technology and Instrument Zhejiang University Embedded System Engineering Research Center Ministry of Education of China Zhejiang University State Key Laboratory of Industrial Control Technology Zhejiang Provincial Key Laboratory for Network Multimedia Technologies Alibaba DAMO Academy Alibaba Group

Based on the framework of multiple instance learning (MIL), tremendous works have promoted the advances of weakly supervised object detection (WSOD). However, most MIL-based methods tend to localize instances to their discriminative parts instead of the whole content. In this paper, we propose a spatial likelihood voting (SLV) module to converge the proposal localizing process without any bounding box annotations. Specifically, all region proposals in a given image play the role of voters every iteration during training, voting for the likelihood of each category in spatial dimensions. After dilating alignment on the area with large likelihood values, the voting results are regularized as bounding boxes, being used for the final classification and localization. Based on SLV, we further propose an end-to-end training framework for multi-task learning. The classification and localization tasks promote each other, which further improves the detection performance. Extensive experiments on the PASCAL VOC 2007 and 2012 datasets demonstrate the superior performance of SLV. Copyright © 2020, The Authors. All rights reserved.

关键词： Object recognition

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Seasonal association between viral causes of hospitalised acute lower respiratory infections and meteorological factors in China: a retrospective study

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The Lancet Planetary Health 2021年第3期5卷 e154-e163页

作者： Xu, Bing Wang, Jinfeng Li, Zhongjie Xu, Chengdong Liao, Yilan Hu, Maogui Yang, Jing Lai, Shengjie Wang, Liping Yang, Weizhong The State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China Sino-Danish College University of Chinese Academy of Sciences Beijing China Key Laboratory of Surveillance and Early-Warning on Infectious Disease Chinese Center for Disease Control and Prevention Beijing China School of Population Medicine & Public Health Chinese Academy of Medical Sciences/Peking Union Medical College Beijing China Sino-Danish Center for Education and Research Beijing China Beijing Research Center for Information Technology in Agriculture Beijing Academy of Agriculture and Forestry Sciences Beijing China National Engineering Research Center for Information Technology in Agriculture Beijing China WorldPop School of Geography and Environmental Science University of Southampton Southampton United Kingdom

Background: Acute lower respiratory infections (ALRIs) caused by respiratory viruses are common and persistent infectious diseases worldwide and in China, which have pronounced seasonal patterns. Meteorological factors have important roles in the seasonality of some major viruses, especially respiratory syncytial virus (RSV) and influenza virus. Our aim was to identify the dominant meteorological factors and to model their effects on common respiratory viruses in different regions of China. Methods: We analysed monthly virus data on patients hospitalised with ALRI from 81 sentinel hospitals in 22 provinces in mainland China from Jan 1, 2009, to Sept 30, 2013. We considered seven common respiratory viruses: RSV, influenza virus, human parainfluenza virus, adenovirus, human metapneumovirus, human bocavirus, and human coronavirus. Meteorological data of the same period were used to analyse relationships between virus seasonality and seven meteorological factors according to region (southern vs northern China). The geographical detector method was used to quantify the explanatory power of each meteorological factor, individually and interacting in pairs, on the respiratory viruses. Findings: 28 369 hospitalised patients with ALRI were tested, 10 387 (36·6%) of whom were positive for at least one virus, including RSV (4091 [32·0%] patients), influenza virus (2665 [20·8%]), human parainfluenza virus (2185 [17·1%]), adenovirus (1478 [11·6%]), human bocavirus (1120 [8·8%]), human coronavirus (637 [5·0%]), and human metapneumovirus (615 [4·8%]). RSV and influenza virus had annual peaks in the north and biannual peaks in the south. Human parainfluenza virus and human bocavirus had higher positive rates in the spring–summer months. Human metapneumovirus had an annual peak in winter–spring, especially in the north. Adenovirus and human coronavirus exhibited no clear annual seasonality. Temperature, atmospheric pressure, vapour pressure, and rainfall had most explanatory power o

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Coalition game based user association for mmWave mobile relay systems in rail traffic scenarios

arXiv

引用

arXiv 2021年

作者： Chen, Chen Niu, Yong Mao, Shiwen Zhang, Xiaodan Han, Zhu Ai, Bo Gao, Meilin Xiao, Huahua Wang, Ning The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-Speed Railway System Beijing Jiaotong University Beijing100044 China The National Mobile Communications Research Laboratory Southeast University Nanjing211189 China The Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States The School of Management Shenzhen Institute of Information Technology Shenzhen518172 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of The Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China The Tsinghua Space Center Tsinghua University Beijing100091 China The ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China The School of Information Engineering Zhengzhou University Zhengzhou450001 China

Rail transportation, especially, high-speed rails (HSR), is an important infrastructure for the development of national economy and the promotion of passenger experience. Due to the large bandwidth, millimeter wave (mmWave) communication is regarded as a promising technology to meet the demand of high data rates. However, since mmWave communication has the characteristic of high attenuation, mobile relay (MR) is considered in this paper. Also, full-duplex (FD) communications have been proposed to improve the spectral efficiency. However, because of the high speed, as well as the problem of penetration loss, passengers on the train have a poor quality of service. Consequently, an effective user association scheme for HSR in mmWave band is necessary. In this paper, we investigate the user association optimization problem in mmWave mobile relay systems where the MRs operate in the FD mode. To maximize the system capacity, we propose a cooperative user association approach based on coalition formation game, and develop a coalition formation algorithm to solve the challenging NP-hard problem. We also prove the convergence and Nash-stable property of the proposed algorithm. Extensive simulations are done to show the system performance of the proposed scheme under various network settings. It is demonstrated that the proposed distributed low complexity scheme achieves a near-optimal performance and outperforms two baseline schemes in terms of average system throughput. Copyright © 2021, The Authors. All rights reserved.

关键词： Game theory

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SLV: Spatial Likelihood Voting for Weakly Supervised Object Detection

SLV: Spatial Likelihood Voting for Weakly Supervised Object ...

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Ze Chen Zhihang Fu Rongxin Jiang Yaowu Chen Xian-Sheng Hua Zhejiang University Institute of Advanced Digital Technology and Instrument Zhejiang University Embedded System Engineering Research Center Ministry of Education of China Alibaba DAMO Academy Alibaba Group Zhejiang University the State Key Laboratory of Industrial Control Technology Zhejiang Provincial Key Laboratory for Network Multimedia Technologies

ISBN: (数字)9781728171685

ISBN: (纸本)9781728171692

关键词： Proposals Training Detectors Object detection Task analysis Feature extraction Computer vision

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Thermal pyrolysis of Si@ZIF-67 into Si@N-doped CNTs towards highly stable lithium storage

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Science Bulletin 2020年第6期65卷 452-459,M0003页

作者： Dun Jin Xianfeng Yang Yuqing Ou Mumin Rao Yaotang Zhong Guangmin Zhou Daiqi Ye Yongcai Qiu Yuping Wu Weishan Li School of Chemistry South China Normal UniversityGuangzhou 510006China Analytical and Testing Centre South China University of TechnologyGuangzhou 510640China Zhao Qing Outstanding Power Battery System Co. Ltd.Zhaoqing 526238.China Department of Materials Science and Engineering Stanford UniversityStanfordCA 94305USA Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control School of Environment and EnergySouth China University of TechnologyGuangzhou 510006China State Key Laboratory of Luminescent Materials and Devices South China University of TechnologyGuangzhou 510640China National and Local Joint Engineering Research Center of MPTES in High Energy and Safety LIBs Engineering Research Center of MTEES(Ministry of Education)and Key Laboratory of ETESPG(GHEI)South China Normal UniversityGuangzhou 510006China

Silicon is attracting considerable attention as an active anode material for advanced lithium-ion batteries due to its ultrahigh theoretical capacity. However, the reversible utilization of silicon-based anode materials is still hindered by the rapid capacity decay, as a consequence of the huge volume change of silicon during cycling. Herein, we use a Co-zeolitic imidazole framework(ZIF-67) to prepare silicon-wrapped nitrogen-doped carbon nanotubes(Si@N-doped CNTs) by controllable thermal pyrolysis. The asprepared nanocomposites can effectively prevent pulverization and accommodate volume fluctuations of silicon during cycling. It can deliver a highly reversible capacity of 1100 m Ah g-1 even after 750 cycles at a current density of 1000 m A g-1. As confirmed by an in situ transmission electron microscopy experiment, the remarkable electrochemical performance of Si@N-doped CNTs is attributed to the high electronic conductivity and flexibility of cross-linked N-doped CNTs network as a cushion to mitigate the mechanical stress and volume expansion. Furthermore, a full cell consisting of Si@N-doped CNTs anode and Li Fe PO4 cathode delivers a high reversible capacity of 1264 m Ah g-1 and exhibits good cycling stability(>85% capacity retention) over 140 cycles at 1/4 C(1 C = 4000 m A g-1) rate.

关键词： N-doped CNTs In situ growth Silicon nanoparticles Lithium storage Cyclic stability

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Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

引用

The Lancet 2023年第10397期402卷 203-234页

作者： Ong, Kanyin Liane Stafford, Lauryn K. McLaughlin, Susan A. Boyko, Edward J. Vollset, Stein Emil Smith, Amanda E. Dalton, Bronte E. Duprey, Joe Cruz, Jessica A. Hagins, Hailey Lindstedt, Paulina A. Aali, Amirali Abate, Yohannes Habtegiorgis Abate, Melsew Dagne Abbasian, Mohammadreza Abbasi-Kangevari, Zeinab Abbasi-Kangevari, Mohsen ElHafeez, Samar Abd Abd-Rabu, Rami Abdulah, Deldar Morad Abdullah, Abu Yousuf Md Abedi, Vida Abidi, Hassan Aboagye, Richard Gyan Abolhassani, Hassan Abu-Gharbieh, Eman Abu-Zaid, Ahmed Adane, Tigist Demssew Adane, Denberu Eshetie Addo, Isaac Yeboah Adegboye, Oyelola A. Adekanmbi, Victor Adepoju, Abiola Victor Adnani, Qorinah Estiningtyas Sakilah Afolabi, Rotimi Felix Agarwal, Gina Aghdam, Zahra Babaei Agudelo-Botero, Marcela Arriagada, Constanza Elizabeth Aguilera Agyemang-Duah, Williams Ahinkorah, Bright Opoku Ahmad, Danish Ahmad, Rizwan Ahmad, Sajjad Ahmad, Aqeel Ahmadi, Ali Ahmadi, Keivan Ahmed, Ali Ahmed, Luai A. Ahmed, Syed Anees Ajami, Marjan Akinyemi, Rufus Olusola Al Hamad, Hanadi Al Hasan, Syed Mahfuz AL-Ahdal, Tareq Mohammed Ali Alalwan, Tariq A. Al-Aly, Ziyad AlBataineh, Mohammad T. Alcalde-Rabanal, Jacqueline Elizabeth Alemi, Sharifullah Ali, Hassam Alinia, Tahereh Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Amare, Firehiwot Ameyaw, Edward Kwabena Amiri, Sohrab Amusa, Ganiyu Adeniyi Andrei, Catalina Liliana Anjana, Ranjit Mohan Ansar, Adnan Ansari, Golnoosh Ansari-Moghaddam, Alireza Anyasodor, Anayochukwu Edward Arabloo, Jalal Aravkin, Aleksandr Y. Areda, Demelash Arifin, Hidayat Arkew, Mesay Armocida, Benedetta Arnlov, Johan Artamonov, Anton A. Arulappan, Judie Aruleba, Raphael Taiwo Arumugam, Ashokan Aryan, Zahra Asemu, Mulu Tiruneh Asghari-Jafarabadi, Mohammad Askari, Elaheh Asmelash, Daniel Astell-Burt, Thomas Athar, Mohammad Athari, Seyyed Shamsadin Atout, Maha Moh'd Wahbi Avila-Burgos, Leticia Awaisu, Ahmed Azadnajafabad, Sina Darshan, B.B. Babamohamadi, Hassan Badar, Muhammad Badawi, Alaa Badiye, Ashish D. Baghcheghi, Nayereh Baghe Institute for Health Metrics and Evaluation School of Medicine General Medicine Service Department of Veterans Affairs Seattle WA United States Department of Health Metrics Sciences School of Medicine Faculty of Medicine France Department of Clinical Governance and Quality Improvement Aleta Wondo Hospital Aleta Wondo Ethiopia Department of Nursing Woldia University Woldia Ethiopia Department of Nursing Department of Orthopedic Surgery Orthopaedic Surgery Social Determinants of Health Research Center Non-communicable Diseases Research Center Epidemiology Department Evidence-Based Practice Center Community and Maternity Nursing Unit University of Duhok Duhok Iraq School of Planning Faculty of Environment Department of Public Health Sciences Penn State College of Medicine Pennsylvania State University Hershey PA United States Biocomplexity Institute Virginia Tech Blacksburg VA United States College of Medicine Department of Public Health Laboratory Technology Sciences Department Department of Family and Community Health University of Health and Allied Sciences Ho Ghana Research Center for Immunodeficiencies Department of Biosciences and Nutrition Karolinska University Hospital Huddinge Sweden Clinical Sciences Department Department of Surgery Department of Surgery Department of Obstetrics & Gynecology College of Graduate Health Sciences University of Tennessee Memphis TN United States Department of Obstetrics & Gynecology Department of Clinical and Psychosocial Epidemiology Department of Anesthesia and Critical Care Centre for Social Research in Health Quality and Systems Performance Unit Cancer Institute NSW Sydney NSW Australia Department of Public Health and Tropical Medicine HIV and Infectious Diseases Department Jhpiego Abuja Nigeria Adolescent Research and Care Department Adolescent Friendly Research Initiative and Care Ado Ekiti Nigeria Department of Epidemiology Department of Epidemiology and Medical Statistics Department of Family Medicine McMaster University

Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined;these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs;defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims;type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative r

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