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arXiv 2017年

作者： Bae, Ho Lee, Byunghan Kwon, Sunyoung Yoon, Sungroh Interdisciplinary Program in Bioinformatics Seoul National University Seoul08826 Electrical and Computer Engineering Seoul National University Seoul08826 Electronic and IT Media Engineering Seoul National University of Science and Technology Seoul01811 Korea Republic of Clova AI Research NAVER Corp. Seongnam13561 ASRI INMC Seoul National University Seoul08826

Recent advances in next-generation sequencing technologies have facilitated the use of deoxyribonucleic acid (DNA) as a novel covert channels in steganography. There are vari-ous methods that exist in other domains to detect hidden messages in conventional covert channels. However, they have not been applied to DNA steganography. The current most common detection approaches, namely frequency analysis-based methods, often overlook important signals when directly applied to DNA steganography because those methods de-pend on the distribution of the number of sequence characters. To address this limitation, we propose a general sequence learning-based DNA steganalysis framework. The proposed approach learns the intrinsic distribution of coding and non-coding sequences and detects hidden messages by exploiting distribution variations after hiding these messages. Using deep recurrent neural networks (RNNs), our framework identifies the distribution varia-tions by using the classification score to predict whether a sequence is to be a coding or non-coding sequence. We compare our proposed method to various existing methods and biological sequence analysis methods implemented on top of our framework. According to our experimental results, our approach delivers a robust detection performance compared to other tools. Copyright © 2017, The Authors. All rights reserved.

关键词： Steganography

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Procedural content generation via machine learning (PCGML)

arXiv

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arXiv 2017年

作者： Summerville, Adam Snodgrass, Sam Guzdial, Matthew Holmgård, Christoffer Hoover, Amy K. Isaksen, Aaron Nealen, Andy Togelius, Julian Department of Computational Media University of California Santa CruzCA95064 United States College of Computing and Informatics Drexel University PhiladelpiaPA19104 United States School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States Duck and Cover Games ApS Copenhagen K1311 Denmark College of Arts Media and Design Northeastern University BostonMA02115 United States Department of Computer Science and Engineering New York University BrooklynNY11201 United States

This survey explores Procedural Content Generation via Machine Learning (PCGML), defined as the generation of game content using machine learning models trained on existing content. As the importance of PCG for game development increases, researchers explore new avenues for generating high-quality content with or without human involvement;this paper addresses the relatively new paradigm of using machine learning (in contrast with search-based, solver-based, and constructive methods). We focus on what is most often considered functional game content such as platformer levels, game maps, interactive fiction stories, and cards in collectible card games, as opposed to cosmetic content such as sprites and sound effects. In addition to using PCG for autonomous generation, co-creativity, mixed-initiative design, and compression, PCGML is suited for repair, critique, and content analysis because of its focus on modeling existing content. We discuss various data sources and representations that affect the generated content. Multiple PCGML methods are covered, including neural networks: long short-term memory (LSTM) networks, autoencoders, and deep convolutional networks;Markov models: n-grams and multi-dimensional Markov chains;clustering;and matrix factorization. Finally, we discuss open problems in PCGML, including learning from small datasets, lack of training data, multi-layered learning, style-transfer, parameter tuning, and PCG as a game mechanic. Copyright © 2017, The Authors. All rights reserved.

关键词： Knowledge representation

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The electron-capture origin of supernova 2018zd

arXiv

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arXiv 2020年

作者： Hiramatsu, Daichi Howell, D. Andrew van Dyk, Schuyler D. Goldberg, Jared A. Maeda, Keiichi Moriya, Takashi J. Tominaga, Nozomu Nomoto, Ken'ichi Hosseinzadeh, Griffin Arcavi, Iair McCully, Curtis Burke, Jamison Bostroem, K. Azalee Valenti, Stefano Dong, Yize Brown, Peter J. Andrews, Jennifer E. Bilinski, Christopher Williams, G. Grant Smith, Paul S. Smith, Nathan Sand, David J. Anand, Gagandeep S. Xu, Chengyuan Filippenko, Alexei V. Bersten, Melina C. Folatelli, Gastón Kelly, Patrick L. Noguchi, Toshihide Itagaki, Koichi Las Cumbres Observatory 6740 Cortona Drive Suite 102 GoletaCA93117-5575 United States Department of Physics University of California Santa BarbaraCA93106-9530 United States Caltech/Spitzer Science Center Caltech IPAC Mailcode 100-22 PasadenaCA91125 United States Department of Astronomy Kyoto University Kitashirakawa-Oiwake-cho Sakyo-ku Kyoto606-8502 Japan University of Tokyo Institutes for Advanced Study University of Tokyo 5-1-5 Kashiwanoha Kashiwa Chiba277-8583 Japan National Astronomical Observatory of Japan National Institutes of Natural Sciences 2-21-1 Osawa Mitaka Tokyo181-8588 Japan School of Physics and Astronomy Faculty of Science Monash University ClaytonVIC3800 Australia Department of Physics Faculty of Science and Engineering Konan University 8-9-1 Okamoto Hyogo Kobe658-8501 Japan Center for Astrophysics Harvard & Smithsonian 60 Garden Street CambridgeMA02138-1516 United States School of Physics and Astronomy Tel Aviv University Tel Aviv69978 Israel CIFAR Azrieli Global Scholars Program CIFAR Toronto Canada Department of Physics University of California 1 Shields Ave DavisCA95616-5270 United States Mitchell Institute for Fundamental Physics and Astronomy Texas A&M University College StationTX77843 United States Steward Observatory University of Arizona 933 North Cherry Avenue TucsonAZ85721-0065 United States MMT Observatory P.O. Box 210065 TucsonAZ85721-0065 United States Infrared Processing and Analysis Center California Institute of Technology PasadenaCA91125 United States Institute for Astronomy University of Hawai'i 2680 Woodlawn Drive HonoluluHI96822 United States Media Arts and Technology University of California Santa BarbaraCA93106-6065 United States Department of Astronomy University of California BerkeleyCA94720-3411 United States Miller Institute for Basic Research in Science University of California BerkeleyCA94720 United States CONICET Argentina Facultad de Ciencias Astronómi

In the transitional mass range (∼ 8-10 solar masses) between white dwarf formation and iron core-collapse supernovae, stars are expected to produce an electron-capture supernova. Theoretically, these progenitors are thought to be super-asymptotic giant branch stars with a degenerate O+Ne+Mg core, and electron capture onto Ne and Mg nuclei should initiate core collapse1,2,3,4. However, no supernovae have unequivocally been identified from an electron-capture origin, partly because of uncertainty in theoretical predictions. Here we present six indicators of electron-capture supernovae and show that supernova 2018zd is the only known supernova having strong evidence for or consistent with all six: progenitor identification, circumstellar material, chemical composition5,6,7, explosion energy, light curve, and nucleosynthesis8,9,10,11,12. For supernova 2018zd, we infer a super-asymptotic giant branch progenitor based on the faint candidate in the pre-explosion images and the chemically-enriched circumstellar material revealed by the early ultraviolet colours and flash spectroscopy. The light-curve morphology and nebular emission lines can be explained by the low explosion energy and neutron-rich nucleosynthesis produced in an electron-capture supernova. This identification provides insights into the complex stellar evolution, supernova physics, cosmic nucleosynthesis, and remnant populations in the transitional mass range. Copyright © 2020, The Authors. All rights reserved.

关键词： Supernovae

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The overlapping burden of the three leading causes of disability and death in sub-Saharan African children

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Nature Communications 2022年第1期13卷 1-14页

作者： Reiner, Robert C. Welgan, Catherine A. Troeger, Christopher E. Baumann, Mathew M. Weiss, Daniel J. Deshpande, Aniruddha Blacker, Brigette F. Miller-Petrie, Molly K. Earl, Lucas Bhatt, Samir Abolhassani, Hassan Abosetugn, Akine Eshete Abu-Gharbieh, Eman Adekanmbi, Victor Adetokunboh, Olatunji O. Aghaali, Mohammad Aji, Budi Alahdab, Fares Al-Aly, Ziyad Alhassan, Robert Kaba Ali, Saqib Alizade, Hesam Aljunid, Syed Mohamed Almasi-Hashiani, Amir Al-Mekhlafi, Hesham M. Altirkawi, Khalid A. Alvis-Guzman, Nelson Amare, Azmeraw T. Amini, Saeed Amugsi, Dickson A. Ancuceanu, Robert Andrei, Catalina Liliana Ansari, Fereshteh Anvari, Davood Appiah, Seth Christopher Yaw Arabloo, Jalal Aremu, Olatunde Atout, Maha Moh’d Wahbi Ausloos, Marcel Ausloos, Floriane Ayanore, Martin Amogre Aynalem, Yared Asmare Azene, Zelalem Nigussie Badawi, Alaa Baig, Atif Amin Banach, Maciej Bedi, Neeraj Bhagavathula, Akshaya Srikanth Bhandari, Dinesh Bhardwaj, Nikha Bhardwaj, Pankaj Bhattacharyya, Krittika Bhutta, Zulfiqar A. Bijani, Ali Birhanu, Tesega Tesega Mengistu Bitew, Zebenay Workneh Boloor, Archith Brady, Oliver J. Butt, Zahid A. Car, Josip Carvalho, Felix Casey, Daniel C. Chattu, Vijay Kumar Chowdhury, Mohiuddin Ahsanul Kabir Chu, Dinh-Toi Coelho, Camila H. Cook, Aubrey J. Damiani, Giovanni Daoud, Farah Gela, Jiregna Darega Darwish, Amira Hamed Daryani, Ahmad Das, Jai K. Davis Weaver, Nicole Deribe, Kebede Desalew, Assefa Dharmaratne, Samath Dhamminda Dianatinasab, Mostafa Diaz, Daniel Djalalinia, Shirin Dorostkar, Fariba Dubljanin, Eleonora Duko, Bereket Dwyer-Lindgren, Laura Effiong, Andem El Sayed Zaki, Maysaa El Tantawi, Maha Enany, Shymaa Fattahi, Nazir Feigin, Valery L. Fernandes, Eduarda Ferrara, Pietro Fischer, Florian Foigt, Nataliya A. Folayan, Morenike Oluwatoyin Foroutan, Masoud Frostad, Joseph Jon Fukumoto, Takeshi Gaidhane, Abhay Motiramji Gebrekrstos, Hailemikael Gebrekidan G. K. Gebremeskel, Leake Gebreslassie, Assefa Ayalew Gething, Peter W. Gezae, Kebede Embaye Ghadiri, Keyghobad Ghashghaee, Ahmad Golechha, Mahaveer Gubar 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 Malaria Atlas Project University of Oxford Oxford United Kingdom Imperial College London London United Kingdom Department of Laboratory Medicine Karolinska University Hospital Huddinge Sweden Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Public Health Debre Berhan University Debre Berhan Ethiopia Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Population Health Sciences King’s College London London United Kingdom Centre of Excellence for Epidemiological Modelling and Analysis Stellenbosch University Stellenbosch South Africa Department of Global Health Stellenbosch University Cape Town South Africa Department of Epidemiology and Biostatistics Qom University of Medical Sciences Qom Iran Faculty of Medicine and Public Health Jenderal Soedirman University Purwokerto Indonesia 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 Department of Veterans Affairs St Louis MO United States Institute of Health Research University of Health and Allied Sciences Ho Ghana Department of Information Systems College of Economics and Political Science Sultan Qaboos University Muscat Oman Infectious and Tropical Disease Research Center Hormozgan University of Medical Sciences Bandar Abbas Iran Department of Health Policy and Management Kuwait University Safat Kuwait International Centre for Casemix and Clinical Coding National University of Malaysia Bandar Tun Razak Malaysia Department of Epidemiology Arak University of Medical Sciences Arak Iran Medical Research Center

Despite substantial declines since 2000, lower respiratory infections (LRIs), diarrhoeal diseases, and malaria remain among the leading causes of nonfatal and fatal disease burden for children under 5 years of age (under 5), primarily in sub-Saharan Africa (SSA). The spatial burden of each of these diseases has been estimated subnationally across SSA, yet no prior analyses have examined the pattern of their combined burden. Here we synthesise subnational estimates of the burden of LRIs, diarrhoea, and malaria in children under-5 from 2000 to 2017 for 43 sub-Saharan countries. Some units faced a relatively equal burden from each of the three diseases, while others had one or two dominant sources of unit-level burden, with no consistent pattern geographically across the entire subcontinent. Using a subnational counterfactual analysis, we show that nearly 300 million DALYs could have been averted since 2000 by raising all units to their national average. Our findings are directly relevant for decision-makers in determining which and targeting where the most appropriate interventions are for increasing child survival. © 2022, The Author(s).

关键词： Biogeography Epidemiology Infectious diseases Malaria

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Attitude and opinion of Bicycle-Helmet Signal

Attitude and opinion of Bicycle-Helmet Signal

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International Conference on Industrial engineering, Management Science and Applications, ICIMSA 2015

作者： Longani, Pattama Thinnukool, Orawit Yodjaiphet, Anusorn College of Arts Media and Technology Chiang Mai University Chiang Mai50200 Thailand Department of Electrical Engineering Chiang Mai University 50200 Thailand

ISBN: (纸本)9783662471999

This paper aims to studies the opinion, attitude and compliance of cyclists who ride a bicycle in Chiang Mai city, Thailand, with a Bicycle-Helmet Signal (BHS). The purpose of BHS is to help decreasing accidents for cyclists. The device automatically shows turning signal when cyclists lean their head to the left or right-hand side. The findings are based on a sample size of 30 which were taken from the local cyclists. Two groups have been separated to test the confidence, the group of cyclists using BHS and the other cyclists who use the same road with the first group. The results of five sections of questionnaires have been analyzed and show the quality of BHS. The details of opinions, attitudes and compliance are valuable for the design of BHS which provides safety on the road. © Springer-Verlag Berlin Heidelberg 2015.

关键词： Bicycles

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Author Correction: Federated learning enables big data for rare cancer boundary detection

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Nature communications 2023年第1期14卷 436页

作者： Sarthak Pati Ujjwal Baid Brandon Edwards Micah Sheller Shih-Han Wang G Anthony Reina Patrick Foley Alexey Gruzdev Deepthi Karkada Christos Davatzikos Chiharu Sako Satyam Ghodasara Michel Bilello Suyash Mohan Philipp Vollmuth Gianluca Brugnara Chandrakanth J Preetha Felix Sahm Klaus Maier-Hein Maximilian Zenk Martin Bendszus Wolfgang Wick Evan Calabrese Jeffrey Rudie Javier Villanueva-Meyer Soonmee Cha Madhura Ingalhalikar Manali Jadhav Umang Pandey Jitender Saini John Garrett Matthew Larson Robert Jeraj Stuart Currie Russell Frood Kavi Fatania Raymond Y Huang Ken Chang Carmen Balaña Jaume Capellades Josep Puig Johannes Trenkler Josef Pichler Georg Necker Andreas Haunschmidt Stephan Meckel Gaurav Shukla Spencer Liem Gregory S Alexander Joseph Lombardo Joshua D Palmer Adam E Flanders Adam P Dicker Haris I Sair Craig K Jones Archana Venkataraman Meirui Jiang Tiffany Y So Cheng Chen Pheng Ann Heng Qi Dou Michal Kozubek Filip Lux Jan Michálek Petr Matula Miloš Keřkovský Tereza Kopřivová Marek Dostál Václav Vybíhal Michael A Vogelbaum J Ross Mitchell Joaquim Farinhas Joseph A Maldjian Chandan Ganesh Bangalore Yogananda Marco C Pinho Divya Reddy James Holcomb Benjamin C Wagner Benjamin M Ellingson Timothy F Cloughesy Catalina Raymond Talia Oughourlian Akifumi Hagiwara Chencai Wang Minh-Son To Sargam Bhardwaj Chee Chong Marc Agzarian Alexandre Xavier Falcão Samuel B Martins Bernardo C A Teixeira Flávia Sprenger David Menotti Diego R Lucio Pamela LaMontagne Daniel Marcus Benedikt Wiestler Florian Kofler Ivan Ezhov Marie Metz Rajan Jain Matthew Lee Yvonne W Lui Richard McKinley Johannes Slotboom Piotr Radojewski Raphael Meier Roland Wiest Derrick Murcia Eric Fu Rourke Haas John Thompson David Ryan Ormond Chaitra Badve Andrew E Sloan Vachan Vadmal Kristin Waite Rivka R Colen Linmin Pei Murat Ak Ashok Srinivasan J Rajiv Bapuraj Arvind Rao Nicholas Wang Ota Yoshiaki Toshio Moritani Sevcan Turk Joonsang Lee Snehal Prabhudesai Fanny Morón Jacob Mandel Konstantinos Kamnitsas Ben Glocker Luke V M Dixon Matthew Williams Peter Zamp Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA. Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Informatics Technical University of Munich Munich Bavaria Germany. Intel Corporation Santa Clara CA USA. Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany. Clinical Cooperation Unit Neuropathology German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ) Heidelberg Germany. Department of Neuropathology Heidelberg University Hospital Heidelberg Germany. Division of Medical Image Computing German Cancer Research Center Heidelberg Germany. Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany. Neurology Clinic Heidelberg University Hospital Heidelberg Germany. Department of Radiology & Biomedical Imaging University of California San Francisco San Francisco CA USA. Symbiosis Center for Medical Image Analysis Symbiosis International University Pune Maharashtra India. Department of Neuroimaging and Interventional Radiology National Institute of Mental Health and Neurosciences Bangalore Karnataka India. Department of Radiology School of Medicine and Public Health University of Wisconsin Madison WI USA. Department of Medical Physics School of Medicine and Public Health University of Wisconsin Madison WI USA. Leeds Teaching Hospitals Trust Department of Radiology Leeds UK. Department of Radiology Brigham and Women's Hospital Harvard Medical School Boston MA USA. Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown MA USA. Catalan Institute of Oncology Badalona Spain. Consorci MAR Parc de Salut de Barcelona Catalonia Spain. Department of Radiology (IDI

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Participatory stoves: Designing renewable energy technologies for the rural sector

Participatory stoves: Designing renewable energy technologie...

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18th ACM Conference Companion on Computer Supported Cooperative Work and Social Computing, CSCW 2015 Companion

作者： Angel, Walter Savage, Saiph Moreno, Nataly Electrical Engineering Universidad Nacional Autonoma de Mexico Mexico Computer Science University of California Santa Barbara United States Media Arts and Technology University of California Santa Barbara United States

ISBN: (纸本)9781450329460

Wood represents a form of renewable energy that is widely available. In rural Mexico it represents the main source of energy. It is used not only for cooking, but also to heat houses, and to provide lighting. Most Mexican villagers use wood via stoves, however these appliances usually bring health hazards and are harmful for the environment. Due to these problems new technologies, such as efficient stoves, have been implemented to bring better combustion, reduce amount of smoke, and overall make the transfer of heat more efficient. However, the social adoption of efficient stoves is non-trivial. Our study shows how making efficient stoves follow the guidelines of appropriate technology, we can: 1) successfully understand the cultural and social aspects of how villagers use renewable energy;2) design technology that by considering a region's traditions, is used long term.

关键词： Sustainable development

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Digiti sonus v2: New interface for fingerprint data sonification using hand motion 33

Digiti sonus v2: New interface for fingerprint data sonifica...

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33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015

作者： Han, Yoon Chung Han, Byeong-Jun Media Arts and Technology University of California Santa Barbara Santa BarbaraCA93117 United States School of Electrical Engineering Korea University 145 Anam-ro Seongbuk-gu Seoul Korea Republic of

ISBN: (纸本)9781450331463

Digiti Sonus v2 is a new interface for fingerprint data sonification using audience's biometric data and apply their hand motions to control and modify their own audiovisual contents. This interface explores users' fingerprint data as personalized artistic materials, and allows them to rearrange and compare the data with others as pieces of a sonic puzzle by hand motion. This work expands the possibility of creating diverse audiovisual results based on users' interaction, and enhances easier and more intuitive interaction with hand motion using short-range depth camera.

关键词： Biometrics

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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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Getting Undergraduates Ready for China’s Belt and Road Initiative (BRI) Through an Overseas Experiential Learning Project

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China and the World 2021年第3期4卷

作者： Andrew Min Han Chin Thomas Menkhoff Hans-Dieter Evers Hoong Hui Daniel Gn Kevin Koh Chester Wey Lee Patrick H. M. Loh Linda Low Sebastian Tan Teng Seng Teo Natalie Yap Lee Kong Chian School of Business Singapore Management University (SMU) 81 Victoria Street Singapore 188065 Singapore Andrew Chin Min Han graduated from Tsinghua University in Beijing China with a Tsinghua–MIT Sloan International Master of Business Administration degree under the Singapore Government’s Asian Business Fellowship (ABF) scholarship program. He is the Program Director of Singapore Management University (SMU) Executive Certificate in China Business and of the SMU Internationalisation Series. He teaches as an Adjunct Faculty of Strategy and Organisation at the SMU Lee Kong Chian School of Business since January 2017. He teaches effectively in English and Chinese. With over 23 years of experience in education and publishing industry in Asia Andrew Chin’s multi-sector career has enabled him to experience the full spectrum of the education industry in his roles as the Singapore EDB Officer handling the World-Class University portfolio and the Specialist Information and Publishing Industry portfolio Chief Representative and Country Manager (China) at Thomson Learning (Fortune 500 company) and Co-founder and CEO for an early childhood education business. Andrew was a Business Development Director (Universities) at Sodexo Group (Fortune 500 company) for the Asia-Pacific region. After working 10 years in Beijing China Andrew returned to Singapore in 2012 to work closely with the top leadership at Singapore Management University on the SMU China & East Asia Initiatives. Thomas Menkhoff is the Professor of Organisational Behaviour & Human Resources (Education) at the Lee Kong Chian School of Business Singapore Management University (SMU). Two of his recent publications include: (i) Menkhoff Thomas Ning Kan Siew Evers Hans-Dieter and Chay Yue Wah eds. Living in Smart Cities: Innovation and Sustainability (New Jersey: World Scientific Publishing 2018) and (ii) Chay Yue Wah Menkhoff Thomas and Low Linda eds. China’s Belt and Road Initiative — Understanding the Dynamics of a Global Transfor

In this paper, we explain how an experiential learning course and study tour to Gansu Province (People’s Republic of China) enabled undergraduates at the Singapore Management University (SMU) to acquire 21st-century competencies and higher-order thinking skills by analyzing and evaluating specific aspects of China’s Belt and Road Initiative (BRI) and China–Singapore (Chongqing) Connectivity Initiative — New International Land–Sea Trade Corridor (CCI-ILSTC) with emphasis on developing viable Go-To-Market (GTM) strategies aimed at selling Gansu produce in four Southeast Asian markets. We share how the course was designed to support the attainment of key learning goals and discuss how we turned pedagogical aspirations into concrete learning outcomes. We introduce key aspects of the so-called “SMU-XO” project that the students conducted in partnership with an industry partner, Pacific International Lines (PIL), and discuss how the project work helped learners to gain global competency by (i) examining critical issues related to BRI such as multi-modal infrastructure connectivity, (ii) appreciating the local perspectives of project stakeholders in Lanzhou and Shanghai and (iii) successfully interacting with people from different cultures, namely China, Indonesia, Vietnam, Malaysia and Thailand.

关键词： Experiential learning Singapore China Belt and Road Initiative (BRI)

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