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Publisher Correction: Global estimates on the number of people blind or visually impaired by cataract: a meta-analysis from 2000 to 2020

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Eye (London, England) 2024年第11期38卷 2229-2231页

作者： Konrad Pesudovs Hugh R. Taylor Tabassom Sedighi Rupert R. A. Bourne Shahina Pardhan Van Charles Lansingh John H. Kempen Ian Tapply Arthur G. Fernandes Maria Vittoria Cicinelli Alessandro Arrigo Nicolas Leveziel Serge Resnikoff Seth Flaxman Mukkharram M. Bikbov Tasanee Braithwaite Alain Bron Ching-Yu Cheng Monte A. Del Monte Joshua R. Ehrlich Leon B. Ellwein David Friedman João M. Furtado Gus Gazzard Ronnie George M. Elizabeth Hartnett Jost B. Jonas Rim Kahloun Moncef Khairallah Rohit C. Khanna Janet Leasher Julie-Anne Little Vinay Nangia Michal Nowak Tunde Peto Pradeep Ramulu Fotis Topouzis Mitiadis Tsilimbaris Ya Xing Wang Ningli Wang Paul Svitil Briant Theo Vos Katrin Burkart Kaleb Coberly Xiaochen Dai Stephen S. Lim Tomislav Mestrovic Ali H. Mokdad Christopher J. L. Murray Jaimie D. Steinmetz Awoke Misganaw Yohannes Habtegiorgis Abate Mohammad Abdollahi Mozhan Abdollahi Ayele Mamo Abebe Olumide Abiodun Richard Gyan Aboagye Woldu Aberhe Abrha Hasan Abualruz Hiwa Abubaker Ali Eman Abu-Gharbieh Salahdein Aburuz Tadele Girum Girum Adal Mesafint Molla Adane Isaac Yeboah Addo Qorinah Estiningtyas Sakilah Adnani Muhammad Sohail Afzal Muhammad Umair Shahin Aghamiri Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Ali Ahmadi Siamak Sabour Ayman Ahmed Haroon Ahmed Ahmad Samir Alfaar Abid Ali Syed Shujait Shujait Ali Awais Altaf Hubert Amu Emmanuel Manu Sofia Androudi Rodrigo Anguita Abhishek Anil Rimple Jeet Kaur Muhammad Aaqib Shamim Saeid Anvari Anayochukwu Edward Anyasodor Francis Appiah Jalal Arabloo Haleh Ayatollahi Mosab Arafat Damelash Areda Reza Arefnezhad Brhane Berhe Aregawi Akeza Awealom Asgedom Tahira Ashraf Seyyed Shamsadin Athari Bantalem Tilaye Tilaye Atinafu Birhan Tsegaw Taye Maha Moh’d Wahbi Atout Alok Atreya Ahmed Y. Azzam Hassan Babamohamadi Sara Bagherieh Yogesh Bahurupi Atif Amin Baig Shumaila Nargus Biswajit Banik Mainak Bardhan Saurav Basu Kavita Batra Nebiyou Simegnew Bayileyegn Fatemeh Bazvand Addisu Shunu Beyene Awoke Masrie Asrat Derese Devidas S. Bhagat Akshaya Srikanth Bhagavathula Pankaj Bh Medicine & Health University of New South Wales Sydney NSW Australia School of Optometry and Vision Science University of New South Wales Sydney NSW Australia School of Population and Global Health University of Melbourne Carlton VIC Australia Vision and Eye Research Institute Anglia Ruskin University Cambridge UK HelpMeSee Instituto Mexicano de Oftalmologia Santiago de Querétaro Mexico University of Miami Gables FL USA University of Utah Salt Lake City UT USA Chief Medical Office HelpMeSee New York NY USA Mexican Institute of Ophthalmology Queretaro Mexico Department of Ophthalmology Massachusetts Eye and Ear/Shepens Eye Research Institute/Harvard Medical School Boston MA USA Eye Unit MyungSung Christian Medical Center (MCM) Comprehensive Specialized Hospital and MyungSun Medical College Addis Ababa Ethiopia Department of Ophthalmology Addis Ababa University Addis Ababa Ethiopia Sight for Souls Bellevue WA USA Department of Ophthalmology Harvard University Boston MA USA Eye Unit MyungSung Medical College Addis Ababa Ethiopia Addenbrooke’s Hospital Cambridge UK Department of Ophthalmology Cambridge University Hospitals Cambridge UK Federal University of Sao Paolo Sao Paolo SP Brazil University of Calgary Calgary AB Canada Department of Ophthalmology and Visual Sciences Federal University of São Paulo Sao Paulo Brazil School of Medicine Vita-Salute San Raffaele University Milan Italy Department of Ophthalmology IRCCS San Raffaele Scientific Institute Milan Italy Department of Ophthalmology San Raffaele Scientific Institute Milano Italy IRCCS San Raffaele Scientific Institute Vita-Salute University Milan Italy Scientific Institute San Raffaele Hospital Vita-Salute University Milan Italy University of Poitiers Poitiers France CHU de Poitiers Poitiers France Ophthalmology Department CHU de Poitiers (Poitiers University Hospital) Poitiers France Unité 1084 National Institute of Health and Medical Research (INSERM) Poitiers France

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Author Correction: High-Gain Metasurface in Polyimide On-Chip Antenna Based on CRLH-TL for Sub-Terahertz Integrated Circuits

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Scientific reports 2020年第1期10卷 13650页

作者： Mohammad Alibakhshikenari Bal S Virdee Chan H See Raed A Abd-Alhameed Francisco Falcone Ernesto Limiti Electronic Engineering Department University of Rome "Tor Vergata" Via del Politecnico 1 00133 Rome Italy. alibakhshikenari@ing.uniroma2.it. London Metropolitan University Center for Communications Technology & Mathematics School of Computing & Digital Media London N7 8DB UK. School of Engineering & the Built Environment Edinburgh Napier University 10 Colinton Road Edinburgh EH10 5DT UK. School of Engineering University of Bolton Deane Road Bolton BL3 5AB UK. School of Electrical Engineering & Computer Science University of Bradford Bradford BD7 1DP UK. Electrical and Electronic Engineering Department Public University of Navarre 31006 Pamplona Spain. Electronic Engineering Department University of Rome "Tor Vergata" Via del Politecnico 1 00133 Rome Italy.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Turning the crank for machine learning: ease, at what expense? (vol 1, pg 198, 2019)

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LANCET DIGITAL HEALTH 2019年第6期1卷 E260-E260页

作者： Pollard, T. J. Chen, I Wiens, J. Massachusetts Institute of Technology Cambridge MA 02139 USA Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA Beth Israel Deaconess Medical Center Boston MA USA Guy's and St Thomas’ Hospitals NHS Foundation Trust London UK University of Toronto Vector Institute Toronto ON Canada Harvard T H Chan School of Public Health Harvard University Cambridge MA USA Wellframe Boston MA USA

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Making Cubesats and space science more accessible through educational outreach 69

Making Cubesats and space science more accessible through ed...

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69th International Astronautical Congress: #InvolvingEveryone, IAC 2018

作者： Roy, Aimee S. Ferrari, Ruth E. Damkjar, Stefan Sarai, Simran Fairgrieve-Park, Logan Lissina, Callie Kale, Andy Mann, Ian R. Elliott, Duncan Department of Elementary Education University of Alberta EdmontonABT6G 2G5 Canada Edmonton Public School Board 1 Kingsway NW EdmontonABT5H 4G9 Canada Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 1H9 Canada Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 1H9 Canada Department of Physics University of Alberta EdmontonABT6G 2E1 Canada Department of Mechanical Engineering University of Alberta EdmontonABT6G 2G8 Canada Department of Physics University of Alberta EdmontonABT6G 2E1 Canada Department of Physics University of Alberta EdmontonABT6G 2E1 Canada Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 1H9 Canada

CubeSatellites offer a more accessible option for the study of space science while also providing an outlet for a variety of educational outreach programs. AlbertaSat, a student group at the University of Alberta which focuses on CubeSatellite design, has created such a program for primary students, students in kindergarten through grade six, and secondary students, students in grades seven to twelve (7-12). Created in 2014, the program recognized that since an understanding of CubeSatellites is not embedded in the Alberta school's curriculum, many teachers did not have the content knowledge for this area, while we lacked the pedagogical knowledge to teach this. Our program has become very collaborative as we have relied heavily on people from an educational background as well as Science, Technology, engineering, and Mathematics (STEM) disciplines working together. In the last year, the program has undergone a great deal of growth and change. Since 2014, this program has grown from one successful presentation to eight different program options for teachers. We have developed five new sessions for primary and secondary school. We now have four sessions for primary and four for secondary. This is up from three sessions in the 2016/2017 academic year, two for primary and one for secondary. Our program covers a variety of STEM topics which focus on space science and project design. We have also recently completed our first program booklet;a resource for teachers interested in teaching our sessions. In this booklet, we outline our sessions using common teaching strategies such as scaffolding and step-by-step instruction to encourage the use of our sessions in the classroom, reduce cognitive overload, and provide a useful resource for teachers. This was done to make space science more accessible. Our program has been well-received and highly successful. Between July 2016 and March 2018, we will have reached approximately 1600 primary and secondary students. We hope to rea

关键词： Students

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Hyperthyroidism and hypothyroidism in patients with hidradenitis suppurativa: a systematic review and meta-analysis

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International journal of dermatology 2023年第3期62卷 e116-e120页

作者： Shuo-Yan Gau Chien-Ying Lee Yu-Hsiang Kuan Kevin Sheng-Kai Ma James Cheng-Chung Wei School of Medicine Chung Shan Medical University Taichung Taiwan. Department of Medical Education Chung Shan Medical University Hospital Taichung Taiwan. Department of Pharmacology Chung Shan Medical University Taichung Taiwan. Department of Pharmacy Chung Shan Medical University Hospital Taichung Taiwan. Department of Dermatology Massachusetts General Hospital Boston MA USA. Department of Epidemiology Harvard T.H. Chan School of Public Health Boston MA USA. Center for Global Health Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Graduate Institute of Biomedical Electronics and Bioinformatics College of Electrical Engineering and Computer Science National Taiwan University Taipei Taiwan. Department of Allergy Immunology and Rheumatology Chung Shan Medical University Hospital Taichung Taiwan. Institute of Medicine Chung Shan Medical University Taichung Taiwan. Graduate Institute of Integrated Medicine China Medical University Taichung City Taiwan.

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Directly constraining marginal prices in distribution grids using demand-side flexibility

arXiv

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arXiv 2018年

作者： Chakraborty, Shantanu Baker, Kyri Cvetkovic, Milos Verzijlbergh, Remco Lukszo, Zofia Faculty of Technology Policy and Management Delft University of Technology Delft2628 BX Netherlands Department of Civil Environmental and Architectural Engineering University of Colorado at Boulder BoulderCO80309 United States Department of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 CD Netherlands

— Recently, the volatility associated with marginal prices has increased due to large scale integration of renewable generation. Price volatility is undesirable from a consumer perspective. To address this issue, we present a framework for hedging that uses duality theory for quantifying the amount of demand-side flexibility required for constraining marginal prices to the consumers maximum willingness to pay for electricity. Using our formulation, we investigate the ability of an Energy Storage System (ESS), as a demand-side flexibility source, to hedge against electricity price volatility across a multi-time period horizon while accounting for its inter-temporal constraints. Additionally, we analyze the economical benefit that operating the ESS under information forecasts brings to the consumers. Copyright © 2018, The Authors. All rights reserved.

关键词： Electric energy storage

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Single-View Food Portion Estimation: Learning Image-to-Energy Mappings Using Generative Adversarial Networks

Single-View Food Portion Estimation: Learning Image-to-Energ...

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IEEE International Conference on Image Processing

作者： Shaobo Fang Zeman Shao Runyu Mao Chichen Fu Edward J. Delp Fengqing Zhu Deborah A. Kerr Carol J. Boushey School of Electrical and Computer Engineering Purdue University West Lafayette Indiana USA School of Public Health Curtin-University Perth Western Australia Cancer Epidemiology Program University of Hawaii Cancer Center Honolulu Hawaii USA

Due to the growing concern of chronic diseases and other health problems related to diet, there is a need to develop accurate methods to estimate an individual's food and energy intake. Measuring accurate dietary intake is an open research problem. In particular, accurate food portion estimation is challenging since the process of food preparation and consumption impose large variations on food shapes and appearances. In this paper, we present a food portion estimation method to estimate food energy (kilocalories) from food images using Generative Adversarial Networks (GAN). We introduce the concept of an “energy distribution” for each food image. To train the GAN, we design a food image dataset based on ground truth food labels and segmentation masks for each food image as well as energy information associated with the food image. Our goal is to learn the mapping of the food image to the food energy. We can then estimate food energy based on the energy distribution. We show that an average energy estimation error rate of 10.89% can be obtained by learning the image-to-energy mapping.

关键词： Estimation Image segmentation Generative adversarial networks Gallium nitride Three-dimensional displays Task analysis Training

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The role of demand-side flexibility in hedging electricity price volatility in distribution grids

arXiv

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arXiv 2018年

作者： Chakraborty, Shantanu Verzijlbergh, Remco Lukszo, Zofia Cvetkovic, Milos Baker, Kyri Faculty of Technology Policy and Management Delft University of Technology Delft2628BX Netherlands Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628CD Netherlands Civil Environmental and Architectural Engineering University of Colorado at Boulder BoulderCO80309 United States

Locational Marginal Price (LMP) is a dual variable associated with supply-demand matching and represents the cost of delivering power to a particular location if the load at that location increases. In recent times it become more volatile due to increased integration of renewables that are intermittent. The issue of price volatility is further heightened during periods of grid congestion. Motivated by these problems, we propose a market design where, by constraining dual variables, we determine the amount of demand-side flexibility required to limit the rise of LMP. Through our proposed approach a price requesting load can specify its maximum willingness to pay for electricity and through demand-side flexibility hedge against price volatility. For achieving this, an organizational structure for flexibility management is proposed that exhibits the coordination required between the Distribution System Operator (DSO), an aggregator and the price requesting load. To demonstrate the viability of our proposed formulation, we run an illustrative simulation under infinite and finite line capacities. Copyright © 2018, The Authors. All rights reserved.

关键词： Location

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Correction: An Alternative to the Light Touch Digital Health Remote Study: The Stress and Recovery in Frontline COVID-19 Health Care Workers Study

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JMIR formative research 2022年第4期6卷 e38188页

作者： Sarah M Goodday Emma Karlin Alexandria Alfarano Alexa Brooks Carol Chapman Rachelle Desille Shazia Rangwala Daniel R Karlin Hoora Emami Nancy Fugate Woods Adrien Boch Luca Foschini Mackenzie Wildman Francesca Cormack Nick Taptiklis Abhishek Pratap Marzyeh Ghassemi Anna Goldenberg Sujay Nagaraj Elaine Walsh Stephen Friend 4YouandMe Seattle WA United States. Department of Psychiatry University of Oxford Oxford United Kingdom. Nationwide Children's Hospital Columbus OH United States. MindMed New York NY United States. Tufts University School of Medicine Boston MA United States. Dalla Lana School of Public Health University of Toronto Toronto ON Canada. School of Nursing University of Washington Seattle WA United States. Evidation Health Inc San Mateo CA United States. Cambridge Cognition Cambridge United Kingdom. Department of Psychiatry University of Cambridge Cambridge United Kingdom. Krembil Center for Neuroinformatics Center for Addiction and Mental Health Toronto ON Canada. Vector Institute Toronto ON Canada. University of Washington Seattle WA United States. King's College London London United Kingdom. Institute for Medical Engineering and Science MIT Cambridge MA United States. Department of Electrical Engineering and Computer Science MIT Cambridge MA United States. The Hospital for Sick Children Toronto ON Canada. Department of Computer Science University of Toronto Toronto ON Canada. Canadian Institute for Advanced Research Toronto ON Canada.

[This corrects the article DOI: 10.2196/32165.].

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Single-view food portion estimation: Learning image-to-energy mappings using generative adversarial networks

arXiv

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arXiv 2018年

作者： Fang, Shaobo Shao, Zeman Mao, Runyu Fu, Chichen Kerr, Deborah A. Boushey, Carol J. Delp, Edward J. Zhu, Fengqing School of Electrical and Computer Engineering Purdue University West LafayetteIN United States School of Public Health Curtin University PerthWA Australia Cancer Epidemiology Program University of Hawaii Cancer Center HonoluluHI United States

Due to the growing concern of chronic diseases and other health problems related to diet, there is a need to develop accurate methods to estimate an individual's food and energy intake. Measuring accurate dietary intake is an open research problem. In particular, accurate food portion estimation is challenging since the process of food preparation and consumption impose large variations on food shapes and appearances. In this paper, we present a food portion estimation method to estimate food energy (kilocalories) from food images using Generative Adversarial Networks (GAN). We introduce the concept of an "energy distribution" for each food image. To train the GAN, we design a food image dataset based on ground truth food labels and segmentation masks for each food image as well as energy information associated with the food image. Our goal is to learn the mapping of the food image to the food energy. We can then estimate food energy based on the energy distribution. We show that an average energy estimation error rate of 10.89% can be obtained by learning the image-to-energy mapping. Copyright © 2018, The Authors. All rights reserved.

关键词： Mapping

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