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arXiv 2018年

作者： Agarwal, Girish Allen, Roland E. Bezdìková, Iva Boyd, Robert W. Chen, Goong Hanson, Ronald Hawthorne, Dean L. Hemmer, Philip Kim, Moochan B. Kocharovskaya, Olga Lee, David M. Lidström, Sebastian K. Lidström, Suzy Losert, Harald Maier, Helmut Neuberger, John W. Padgett, Miles J. Raizen, Mark Rajendran, Surjeet Rasel, Ernst Schleich, Wolfgang P. Scully, Marlan O. Shchedrin, Gavriil Shvets, Gennady Sokolov, Alexei Svidzinsky, Anatoly Walsworth, Ronald L. Weiss, Rainer Wilczek, Frank Willner, Alan E. Yablonovich, Eli Zheludev, Nikolay Department of Physics and Astronomy Texas A&M University College StationTX77843 United States Department of Physics Faculty of Nuclear Sciences and Physical Engineering Czech Technical University in Prague Brehova 7 Praha 1-Staré mìsto11519 Czech Republic Department of Physics Technical University of Ostrava 17 Listopadu 15 Ostrava-Poruba70833 Czech Republic Department of Physics School of Electrical Engineering and Computer Science University of Ottawa OttawaONK1N6N5 Canada Institute of Optics Department of Physics and Astronomy University of Rochester RochesterNY14627 United States School of Physics and Astronomy University of Glasgow GlasgowG128QQ United Kingdom Department of Mathematics Texas A&M University College StationTX77843 United States Science Program Texas A&M University at Qatar Education City Doha Qatar Texas A&M University College StationTX77843 United States QuTech and Kavli Institute of Nanoscience Delft University of Technology P.O. Box 5046 Delft2600 GA Netherlands Cornell Laboratory of Ornithology Cornell University IthacaNY14850 United States Laboratory of Atomic and Solid State Physics Cornell University IthacaNY14853 United States Department of Electrical & Computer Engineering Texas A&M Energy Institute Texas A&M University TX77843 United States Department of Physics Strathclyde University GlasgowG11XJ United Kingdom Physica Scripta Royal Swedish Academy of Sciences StockholmSE-10405 Sweden Universität Ulm Albert-Einstein-Allee 11 Ulm89081 Germany Institut für Zahlentheorie und Wahrscheinlichkeitstheorie Universität Ulm Albert-Einstein-Allee 11 Ulm89081 Germany Department of Mathematics University of North Texas DentonTX76203-5017 United States College of Natural Sciences University of Texas AustinTX78712 United States Department of Physics University of California BerkeleyCA94720-7300 United States Institut fuer Quantenoptik QUEST-LFS Welfengarten 1 Hannover30167 Germany Hagler Insti

The Winter Colloquium on the Physics of Quantum Electronics (PQE) has been a seminal force in quantum optics and related areas since 1971. It is rather mindboggling to recognize how the concepts presented at these conferences have transformed scientific understanding and human society. In January, 2017, the participants of PQE were asked to consider the equally important prospects for the future, and to formulate a set of questions representing some of the greatest aspirations in this broad field. The result is this multi-authored paper, in which many of the world's leading experts address the following fundamental questions: (1) What is the future of gravitational wave astronomy? (2) Are there new quantum phases of matter away from equilibrium that can be found and exploited-such as the time crystal? (3) Quantum theory in uncharted territory: What can we learn? (4) What are the ultimate limits for laser photon energies? (5) What are the ultimate limits to temporal, spatial, and optical resolution? (6) What novel roles will atoms play in technology? (7) What applications lie ahead for nitrogen-vacancy centers in diamond? (8) What is the future of quantum coherence, squeezing, and entanglement for enhanced superresolution and sensing? (9) How can we solve (some of) humanity's biggest problems through new quantum technologies? (10) What new understanding of materials and biological molecules will result from their dynamical characterization with free electron lasers? (11) What new technologies and fundamental discoveries might quantum optics achieve by the end of this century? (12) What novel topological structures can be created and employed in quantum optics? Copyright © 2018, The Authors. All rights reserved.

关键词： Quantum optics

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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ISS Properties of Sliding-Mode Controllers for Systems with Matched and Unmatched Disturbances

ISS Properties of Sliding-Mode Controllers for Systems with ...

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European Control Conference

作者： Andrea Aparicio Martinez Fernando Castanos Leonid Fridman Electrical Engineering PhD Program of the Faculty of Engineering Universidad Nacional Autonoma de Mexico Departamento de Control Automatico Cinvestav IPN Faculty of Engineering Universidad Nacional Autonoma de Mexico

ISBN: (纸本)9781467371605

In this paper we present a controller that achieves global input-to-state stability for a linear system of arbitrary relative degree, subjected to matched and unmatched disturbances. This controller combines the properties of a discontinuous term, and a linear one, enforcing a conventional sliding mode using only partial state information. A direct and simple way of choosing the gains for this controller is also provided.

关键词： Convergence Upper bound Backstepping Trajectory Linear systems Asymptotic stability

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Real time textile defect detection using GLCM in DCT-based compressed images

Real time textile defect detection using GLCM in DCT-based c...

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International Conference on Modeling, Simulation and Applied Optimization (ICMSAO)

作者： Fitri Arnia Khairul Munadi Graduate Program in Electrical Engineering Syiah Kuala University Indonesia Department of Electrical Engineering Faculty of Engineering

This paper proposes a framework for textile defect detection on the basis of energy and contrast features of the gray-level co-occurrence matrix (GLCM). We calculate these features in DCT-based compressed image (DCTb-I), which was produced by using only a small number of DCT coefficients. The proposed detection approach complies with the Moving Picture Experts Group (MPEG) and Motion Joint Photographic Experts Group (MJPEG) video compression standards, which improves the defect detection efficiency, in terms of space and computational cost by replacing the frame grabbers with MPEG encoders and by only considering I-frames in the MPEG or specific frames in the MJPEG sequence. We determine (1) the detection accuracy of using DCTb-Is with various compression rates, and (2) the lowest DCTb-I rates that allow defect detection. The DCTb-Is are tiled into blocks from which the energy and contrast features are calculated. The highest energy and lowest contrast blocks are detected and located in the textile as defects. The proposed approach is suitable for real-time detection because, unlike common defect-detection approaches, prior feature extraction from reference images is not required. Simulation results suggest that holes, stains and drop stitches can be detected and located from DCTb-Is if the compression rate is greater than 25%.

关键词： Textiles Discrete cosine transforms Image coding Transform coding Real-time systems Feature extraction Standards

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A software tool for induced voltages and currents calculation caused by lightning electromagnetic field in PV systems

A software tool for induced voltages and currents calculatio...

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International Conference on electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON

作者： Yuttana Fuangfung Saliltip Sinthusonthishat Peerawut Yutthagowith Faculty of Engineering The Electrical Engineering Graduate Program MUT Bangkok Thailand Dept. of Electrical Engineering Faculty of Engineering MUT Bangkok Thailand Dept. of Electrical Engineering Faculty of Engineering KMITL Bangkok Thailand

This article aims to introduce a software tool for induced voltages and currents calculation inside structure caused by electromagnetic field radiated by lightning strike to PV systems which are installed on the top of the structure. The methodology used in the calculation is accordance with standard IEC 62305 - 4: 2010. This program has been developed to determine electromagnetic field, induced loop voltages and currents in a lightning protection zone 1 (LPZ 1). As a result, the software is very useful in calculation of induced over-voltage and current and helps engineers in lightning protection design.

关键词： IEC Standards Lightning protection Magnetic fields Software Photovoltaic systems

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Amplitude-integrated EEG Processing and its Performance for Automatic Seizure Detection

Amplitude-integrated EEG Processing and its Performance for ...

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IEEE International Conference on Signal and Image Processing Applications

作者： Chavin Satirasethawong Apiwat Lek-uthai Krisnachai Chomtho Biomedical Engineering Program Faculty of Engineering Department of Electrical Engineering Faculty of Engineering Department of Pediatrics Faculty of Medicine Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9781479989973

Amplitude-integrated EEG (aEEG) is an easy-to-use screening tool for monitoring electrical seizures which is widely used in hospitals nowadays. The purpose of this paper is to develop the process for creating aEEG in details and to present an algorithm for a single-channel automatic seizure detection. To create an aEEG signal, a raw EEG signal was passed through a band-pass filter, peak-to-peak rectification, smoothing, semilogarithmic compression and time compression. The processed signal was qualitatively evaluated by widely used commercial software. The algorithm was developed based on statistic methods and tested with CHB-MIT Scalp EEG Database in order to detect seizures which last longer than 50 seconds (total 85 seizures with annotations in 683 EDF files) from a single selected channel of each data record which has maximum amplitude in ictal period. The performance measurement showed average sensitivity of 88.50% (33.33-100.00%), false detection rate of 0.18 (0.00-0.58) false positives per hour and the percentage of false detection duration of 0.34% (0.00-0.93%). The results showed that aEEG with automatic seizure detection developed by our process was an effective screening tool to monitor seizures.

关键词： Amplitude-integrated EEG Seizure Detection CHB-MIT Scalp EEG Database Seizures Cerebral function analysing monitor Data logging Epilepsy Time compression AUTOMATIC tool monitor Performance metrics ANNOTATIONS

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Sensor Fault Diagnosis and Fault Tolerant Control using intelligent-Output-Estimator Applied on Quadrotor UAV

Sensor Fault Diagnosis and Fault Tolerant Control using inte...

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International Conference on Unmanned Aircraft Systems

作者： Younes A1 Younes Abdelhamid Rabhi Hassan Noura Ahmed El Hajjaji Mechanical Engineering Faculty at Higher Colleges of Technology Al Ain UAE and PhD student at the University of Picardie Jules Verne Amiens France Assistant Professor in Modeling Information & System Lab - Control & Vehicle Group- at University of Picardie Amiens France Professor and Chairman of Electrical Engineering Department at United Arab Emirates University A1 Ain UAE Professor in Modeling Information & System Lab - Control & Vehicle Group- at University of Picardie Amiens France

ISBN: (纸本)9781467393355

In this paper, Fault Diagnosis and Fault Tolerant Control algorithms are proposed to compensate for a bias type sensor fault applied on the quadrotor vehicle. A novel output estimator design called intelligent Output-Estimator (iOE) is introduced to detect and isolate the sensor fault. The estimation of the fault magnitude is done through a proposed structured algorithm that senses the maximum error deviation between the output estimation and the measured outputs. Then the fault compensation is achieved by regenerating the desired path. Real-flight results validated the proposed algorithms and showed the sensor fault accommodation process.

关键词： iOE Sensor UAV

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Fuzzy PID Controller Design Using Q-Learning Algorithm with a Manipulated Reward Function

Fuzzy PID Controller Design Using Q-Learning Algorithm with ...

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European Control Conference

作者： Vahid Tavakol Aghaei Ahmet Onat Ibrahim Eksin Mujde Guzelkaya Faculty of Engineering and Natural Sciences Mechatronics Engineering Sabanci University Faculty of Electrical and Electronics Engineering Control Engineering Program Istanbul Technical University

ISBN: (纸本)9781467371605

In this paper we propose a manipulated reward function for the Q-learning algorithm which is a reinforcement learning technique and utilize the proposed algorithm to tune the parameters of the input-output membership functions of fuzzy logic controllers. The use of a reward signal to formalize the idea of a goal is one of the most distinctive features of reinforcement learning. To improve both the performance and convergence criteria of the mentioned algorithm we propose a fuzzy structure for the reward function. In order to demonstrate the effectiveness of the algorithm we apply it to two second order linear systems with and without time delay and finally a nonlinear system will be examined.

关键词： Reward fuzzy PID controller learning (artificial intelligence) convergence criterion algorithms Linear system

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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).

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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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