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IEEE Innovative Smart Grid Technologies - Asia

作者： Likin Simon Naina, P. M. Shanti Swarup Universidad Politécnica de Madrid Universidad Politécnica de Madrid Madrid Spain Department for Analysis and Control of Advanced Robotic Systems German Aerospace Center Oberpfaffenhofen Germany Department for Perception and Cognition German Aerospace Center Oberpfaffenhofen Germany

ISBN: (纸本)9781538642924

The scarcity in the electrical power generation and huge demand of power promotes more renewable energy integration to the grid. This paper proposes a solution for Fault/Low Voltage Ride through (LVRT) problem with dynamic crowbar operation for grid connected Doubly Fed Induction Generator (DFIG) based Wind Energy Conversion systems (WECS). Stator and rotor equations are developed in dq frame which makes possible to control active and reactive powers independently. Crowbar resister is connected at the rotor terminals to limit the rotor currents to protect the converters during low voltage or fault conditions. During abnormal condition, the crow bar connected in series with the rotor windings dissipate the rotor energy and limit the converter currents. This paper proposes an adaptive crowbar resistance which can dynamically change the resistance value to control the amount of rotor power to be dissipated. A set of comprehensive simulation case studies are done to verify the proposed control strategy.

关键词： Rotors Stators Doubly fed induction generators Torque Reactive power Voltage control Circuit faults

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Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026

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The Lancet Global Health 2023年第3期11卷 e385-e413页

作者： Micah, Angela E. Bhangdia, Kayleigh Cogswell, Ian E. Lasher, Dylan Lidral-Porter, Brendan Maddison, Emilie R. Nguyen, Trang Nhu Ngoc Patel, Nishali Pedroza, Paola Solorio, Juan Stutzman, Hayley Tsakalos, Golsum Wang, Yifeng Warriner, Wesley Zhao, Yingxi Zlavog, Bianca S. Abbafati, Cristiana Abbas, Jaffar Abbasi-Kangevari, Mohsen Abbasi-Kangevari, Zeinab Abdelmasseh, Michael Abdulah, Deldar Morad Abedi, Aidin Abegaz, Kedir Hussein Abhilash, E.S. Aboagye, Richard Gyan Abolhassani, Hassan Abrigo, Michael R.M. Abubaker Ali, Hiwa Abu-Gharbieh, Eman Adem, Mohammed Hussien Afzal, Muhammad Sohail Ahmadi, Ali Ahmed, Haroon Ahmed Rashid, Tarik Aji, Budi Akbarialiabad, Hossein Akelew, Yibeltal Al Hamad, Hanadi Alam, Khurshid Alanezi, Fahad Mashhour Alanzi, Turki M. Al-Hanawi, Mohammed Khaled Alhassan, Robert Kaba Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Ameyaw, Edward Kwabena Amini-Rarani, Mostafa Amu, Hubert Ancuceanu, Robert Andrei, Tudorel Anwar, Sumadi Lukman Appiah, Francis Aqeel, Muhammad Arabloo, Jalal Arab-Zozani, Morteza Aravkin, Aleksandr Y. Aremu, Olatunde Aruleba, Raphael Taiwo Athari, Seyyed Shamsadin Avila-Burgos, Leticia Ayanore, Martin Amogre Azari, Samad Baig, Atif Amin Bantie, Abere Tilahun Barrow, Amadou Baskaran, Pritish Basu, Sanjay Batiha, Abdul-Monim Mohammad Baune, Bernhard T. Berezvai, Zombor Bhardwaj, Nikha Bhardwaj, Pankaj Bhaskar, Sonu Boachie, Micheal Kofi Bodolica, Virginia Botelho, João Silva Botelho Braithwaite, Dejana Breitborde, Nicholas J.K. Busse, Reinhard Cahuana-Hurtado, Lucero Catalá-López, Ferrán Chansa, Collins Charan, Jaykaran Chattu, Vijay Kumar Chen, Simiao Chukwu, Isaac Sunday Dadras, Omid Dandona, Lalit Dandona, Rakhi Dargahi, Abdollah Debela, Sisay Abebe Denova-Gutiérrez, Edgar Desye, Belay Dharmaratne, Samath Dhamminda Diao, Nancy Doan, Linh Phuong Dodangeh, Milad dos Santos, Wendel Mombaque Doshmangir, Leila Dube, John Eini, Ebrahim El Sayed Zaki, Maysaa El Tantawi, Maha Enyew, Daniel Berhanie Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Applied Mathematics University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Nuffield Department of Medicine University of Oxford Oxford United Kingdom Department of Juridical and Economic Studies La Sapienza University Rome Italy Antai College of Economics Shanghai Jiao Tong University Shanghai China Non-communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Children’s Medical Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Tehran Heart Center Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Tehran University of Medical Sciences Tehran Iran National Institute for Health Research Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Department of Cardiology Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Center Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Department of Neurology Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Epidemiology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Health Economics and Statistics Shahid Beheshti University of Medical Sciences Tehran Iran Department of Neurosurgery Shahid Beheshti University of Medical Sciences Tehran Iran Ophthalmic R

Background: The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic;characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic;and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods: In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings: In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95% uncertainty interval [UI] 9·1–9·3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7·3 trillion (95% UI 7·2–7·4) in 2019;293·7 times the $24·8 billion (95% UI 24·3–25·3) spent by low-income countries in 2019. That same year, $43·1 billion in development assistance was provided

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Passivity-based stability in explicit force control of robots

Passivity-based stability in explicit force control of robot...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Ribin Balachandran Mikael Jorda Jordi Artigas Jee-Hwan Ryu Oussama Khatib Department for Analysis and Control of Advanced Robotic Systems German Aerospace Center (DLR) Germany Robotics Lab Stanford University Stanford USA BioRobotics Laboratory of Korea University of Technology and Education Cheonan Korea

Direct force control of robots is challenging, particularly since the interaction with the environment can render the robot unstable. This paper presents the results of novel approaches for passivity-based stability for a particular direct force control method, namely explicit force control. A step-by-step procedure to passivate and stabilise the control loop is presented and it explains how Time Domain Passivity Approach, a passivity-based tool widely used in teleoperation and haptics has been extended and applied in explicit force control. The electrical circuit and network-port representations derived in the process allows the analytical evaluation of the system and can be applied in other control architectures as well. The stability methods are presented both qualitatively and quantitatively with simulations and hardware experiments. A discussion about the results obtained and the energy behavior is also provided. Results are promising and suggest that these methods can be used for stable and high-bandwidth force control of robotic manipulators.

关键词： Force Force control Robots Iron Stability criteria Ports (Computers)

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AIFORCOVID: Predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. an Italian multicentre study

arXiv

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arXiv 2020年

作者： Soda, Paolo D’Amico, Natascha Claudia Tessadori, Jacopo Valbusa, Giovanni Guarrasi, Valerio Bortolotto, Chandra Akbar, Muhammad Usman Sicilia, Rosa Cordelli, Ermanno Fazzini, Deborah Cellina, Michaela Oliva, Giancarlo Callea, Giovanni Panella, Silvia Cariati, Maurizio Cozzi, Diletta Miele, Vittorio Stellato, Elvira Carrafiello, Gian Paolo Castorani, Giulia Simeone, Annalisa Preda, Lorenzo Iannello, Giulio Bue, Alessio Del Tedoldi, Fabio Alì, Marco Sona, Diego Papa, Sergio Unit of Computer Systems and Bioinformatics Department of Engineering University Campus Bio-Medico of Rome Via Alvaro del Portillo 21 Rome00128 Italy Department of Diagnostic Imaging and Stereotactic Radiosurgey Centro Diagnostico Italiano S.p.A. Via S. Saint Bon 20 Milan20147 Italy Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Via Morego 30 Genoa16163 Italy Bracco Imaging S.p.A. Via Caduti di Marcinelle 13 Milan20134 Italy Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Rome00185 Italy Radiology Institute Fondazione IRCCS Policlinico San Matteo Viale Golgi 19 Pavia27100 Italy Department of Naval Electrical Electronic and Telecommunications Engineering - University of Genova Via All’Opera Pia 11 A Genoa16145 Italy Radiology Department ASST Fatebenefratelli Sacco Piazza Principessa Clotilde 3 Milan20121 Italy Diagnostic and interventional radiology unit ASST Santi Paolo e Carlo - San Paolo Hospital Via Antonio di Rudinì 8 Milan20142 Italy Department of Advanced Diagnostic Technologies - Therapeutic Diagnostic and Radiology Units ASST Santi Paolo e Carlo - San Paolo Hospital Via Antonio di Rudinì 8 Milan20142 Italy Department of Emergency Radiology Careggi University Hospital Largo Piero Palagi 1 Florence50139 Italy Operative Unit of Radiology Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico of Milan Via della Commenda 10 Milan20122 Italy Department of Health Sciences Univeristy of Milan Via Festa del Perdono 7 Milan20122 Italy Diagnostic Imaging Postgraduate Medical School University of Foggia Via Antonio Gramsci 89 Foggia71122 Italy Department of Diagnostic Imaging IRCCS Ospedale Casa Sollievo della Sofferenza Viale Cappuccini 1 San Giovanni Rotondo71013 Italy Radiology Unit Department of Clinical Surgical Diagnostic and Pediatric Sciences University of Pavia Corso Str. Nuova 65 Pavia27100 Italy Neuroinformatics Laboratory Fondazione Bru

Recent epidemiological data report that worldwide more than 53 million people have been infected by SARS-CoV-2, resulting in 1.3 million deaths. The disease has been spreading very rapidly and few months after the identification of the first infected, shortage of hospital resources quickly became a problem. In this work we investigate whether chest X-ray (CXR) can be used as a possible tool for the early identification of patients at risk of severe outcome, like intensive care or death. CXR is a radiological technique that compared to computed tomography (CT) it is simpler, faster, more widespread and it induces lower radiation dose. We present a dataset including data collected from 820 patients by six Italian hospitals in spring 2020 during the first COVID-19 emergency. The dataset includes CXR images, several clinical attributes and clinical outcomes. We investigate the potential of artificial intelligence to predict the prognosis of such patients, distinguishing between severe and mild cases, thus offering a baseline reference for other researchers and practitioners. To this goal, we present three approaches that use features extracted from CXR images, either handcrafted or automatically by convolutional neuronal networks, which are then integrated with the clinical data. Exhaustive evaluation shows promising performance both in 10-fold and leave-one-centre-out cross-validation, implying that clinical data and images have the potential to provide useful information for the management of patients and hospital resources. © 2020, CC BY-NC-ND.

关键词： Deep learning

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Native diversity buffers against severity of non-native tree invasions ( vol 621,pg 773 , 2023 )

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NATURE 2023年第7982期622卷 E2-E2页

作者： Delavaux, Camille S. Crowther, Thomas W. Zohner, Constantin M. Robmann, Niamh M. Lauber, Thomas van den Hoogen, Johan Kuebbing, Sara Liang, Jingjing de-Miguel, Sergio Nabuurs, Gert-Jan Reich, Peter B. Abegg, Meinrad Yao, Yves C. Adou Alberti, Giorgio Zambrano, Angelica M. Almeyda Alvarado, Braulio Vilchez Alvarez-Davila, Esteban Alvarez-Loayza, Patricia Alves, Luciana F. Ammer, Christian Anton-Fernandez, Clara Araujo-Murakami, Alejandro Arroyo, Luzmila Avitabile, Valerio Aymard, Gerardo A. Baker, Timothy R. Balazy, Radomir Banki, Olaf Barroso, Jorcely G. Bastian, Meredith L. Bastin, Jean-Francois Birigazzi, Luca Birnbaum, Philippe Bitariho, Robert Boeckx, Pascal Bongers, Frans Bouriaud, Olivier Brancalion, Pedro H. S. Brandl, Susanne Brienen, Roel Broadbent, Eben N. Bruelheide, Helge Bussotti, Filippo Gatti, Roberto Cazzolla Cesar, Ricardo G. Cesljar, Goran Chazdon, Robin Chen, Han Y. H. Chisholm, Chelsea Cho, Hyunkook Cienciala, Emil Clark, Connie Clark, David Colletta, Gabriel D. Coomes, David A. Valverde, Fernando Cornejo Corral-Rivas, Jose J. Crim, Philip M. Cumming, Jonathan R. Dayanandan, Selvadurai de Gasper, Andre L. Decuyper, Mathieu Derroire, Geraldine DeVries, Ben Djordjevic, Ilija Dolezal, Jiri Dourdain, Aurelie Obiang, Nestor Laurier Engone Enquist, Brian J. Eyre, Teresa J. Fandohan, Adande Belarmain Fayle, Tom M. Feldpausch, Ted R. Ferreira, Leandro V. Fischer, Markus Fletcher, Christine Frizzera, Lorenzo Gamarra, Javier G. P. Gianelle, Damiano Glick, Henry B. Harris, David J. Hector, Andrew Hemp, Andreas Hengeveld, Geerten Herault, Bruno Herbohn, John L. Herold, Martin Hillers, Annika Coronado, Euridice N. Honorio Hui, Cang Ibanez, Thomas T. Amaral, Ieda Imai, Nobuo Jagodzinski, Andrzej M. Jaroszewicz, Bogdan Johannsen, Vivian Kvist Joly, Carlos A. Jucker, Tommaso Jung, Ilbin Karminov, Viktor Kartawinata, Kuswata Kearsley, Elizabeth Kenfack, David Kennard, Deborah K. Kepfer-Rojas, Sebastian Keppel, Gunnar Khan, Mohammed Latif Killeen, Timothy J. Kim, Hyun Seok Kitayama, Kanehiro Kohl, Michael Korju Institute of Integrative Biology ETH Zurich (Swiss Federal Institute of Technology) Zurich Switzerland Department of Genetics Evolution and Environment University College London London UK The Forest School at The Yale School of the Environment Yale University New Haven CT USA Department of Forestry and Natural Resources Purdue University West Lafayette IN USA Department of Agriculture Forestry and Bioresources Seoul National University Seoul South Korea Department of Crop and Forest Sciences University of Lleida Lleida Spain Joint Research Unit CTFC–AGROTECNIO–CERCA Solsona Spain Wageningen University and Research Wageningen The Netherlands World Agroforestry (ICRAF) Nairobi Kenya Department of Forest Resources University of Minnesota St Paul MN USA Hawkesbury Institute for the Environment Western Sydney University Penrith New South Wales Australia Institute for Global Change Biology and School for Environment and Sustainability University of Michigan Ann Arbor MI USA Swiss Federal Institute for Forest Snow and Landscape Research WSL Birmensdorf Switzerland UFR Biosciences University Félix Houphouët-Boigny Abidjan Côte d’Ivoire Department of Agricultural Food Environmental and Animal Sciences University of Udine Udine Italy Faculty of Science and Technology Free University of Bolzano Bolzano Italy Spatial Ecology and Conservation Laboratory Department of Tourism Recreation and Sport Management University of Florida Gainesville FL USA Forestry School Tecnológico de Costa Rica TEC Cartago Costa Rica Fundacion ConVida Universidad Nacional Abierta y a Distancia UNAD Medellin Colombia Field Museum of Natural Histiory Chicago IL USA Center for Tropical Research Institute of the Environment and Sustainability UCLA Los Angeles CA USA Silviculture and Forest Ecology of the Temperate Zones University of Göttingen Göttingen Germany Division of Forest and Forest Resources Norwegian Institute of Bioeconomy Research (NIBIO) Ås Norway Museo de Hi

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Characterising acute and chronic care needs: insights from the Global Burden of Disease Study 2019

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Nature communications 2025年第1期16卷 4235-4235页

作者： Cecilia Anza-Ramirez J. Jaime Miranda Benedetta Armocida Jorge César Correia Harriette Gillian Christine Van Spall David Beran Amirali Aali Kalkidan Hassen Abate Semagn Mekonnen Abate Cristiana Abbafati Mohsen Abbasi-Kangevari Zeinab Abbasi-Kangevari Zahra Aryan Sina Azadnajafabad Mohammadreza Azangou-Khyavy Seyyed-Hadi Ghamari Mohammad Keykhaei Javad Khanali Sara Momtazmanesh Fateme Montazeri Shayan Rahmani Mohammad-Mahdi Rashidi Nazila Rezaei Negar Rezaei Sahar Saeedi Moghaddam Hossein Hassanian-Moghaddam Ali-Asghar Kolahi Ali Nikoobar Hedayat Abbastabar Ahmed M. Abdel-Azeem Michael Abdelmasseh Juan Sanabria Sherief Abd-Elsalam Ahmed Abdelwahab Gholamreza Abdoli Mohammad Abdollahi Meriem Abdoun Deldar Morad Abdulah Abu Yousuf Md Abdullah Ame Mehadi Abdurehman Getachew Abebe Aidin Abedi Chirag P. Doshi Vida Abedi Hassan Abidi Richard Gyan Aboagye Hassan Abolhassani Nima Rezaei Lucas Guimarães Abreu Michael R. M. Abrigo Yonas Derso Abtew Hiwa Abubaker Ali Eman Abu-Gharbieh Hiba Jawdat Barqawi Rabih Halwani Maha Mohamed Saber-Ayad Iman M. Talaat Ahmed Abu-Zaid Manfred Mario Kokou Accrombessi Juan Manuel Acuna Denberu Eshetie Adane Tigist Demssew Adane Isaac Yeboah Addo Giovanni Addolorato Oluwafemi Atanda Adeagbo Victor Adekanmbi Miracle Ayomikun Adesina Isaac Iyinoluwa Olufadewa Olatunji O. Adetokunboh Daniel Adedayo Adeyinka Qorinah Estiningtyas Sakilah Adnani Aanuoluwapo Adeyimika Afolabi Olayinka Stephen Ilesanmi Muhammad Sohail Afzal Saira Afzal Gina Agarwal Prerna Agarwal Pradyumna Agasthi Anurag Agrawal Marcela Agudelo-Botero Adolfo Martinez-Valle Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Sohail Ahmad Tauseef Ahmad Ali Ahmadi Siamak Sabour Keivan Ahmadi Sanjay Basu Sepideh Ahmadi Ali Ahmed Shaun Wen Huey Lee Ayman Ahmed Haroon Ahmed Jivan Qasim Ahmed Gahin Abdulraheem Tayib Yahya Yahya Luai A. Ahmed Iffat Elbarazi Syed Mahboob Shah Janardhana P. Aithala Marjan Ajami Budi Aji Hossein Akbarialiabad Yibeltal Akelew Meisam Akhlaghdoust Elham Jamshidi Addis Aklilu Azene Tesfaye Melat Woldemariam Maxwell Ak CRONICAS Center of Excellence in Chronic Diseases Universidad Peruana Cayetano Heredia Lima Peru School of Medicine Universidad Peruana Cayetano Heredia Lima Peru Sydney School of Public Health Faculty of Medicine and Health University of Sydney Sydney NSW Australia Faculty of Epidemiology and Population Health London School of Hygiene & Tropical Medicine London UK Division of Tropical and Humanitarian Medicine University of Geneva Geneva Switzerland Department of Cardiovascular Endocrine-metabolic Diseases and Aging Istituto Superiore di Sanità Rome Italy Division of Endocrinology Diabetology Nutrition and Therapeutic Patient Education Department of Medicine Geneva University Hospitals Geneva Switzerland Department of Medicine and Department of Health Research Evidence and Impact McMaster University Hamilton ON Canada Research Institute of St. Joe’s Hamilton ON Canada Population Health Research Institute Hamilton Canada Geneva University Hospitals Geneva Switzerland Faculty of Medicine Mashhad University of Medical Sciences Mashhad Iran Department of Nutrition and Dietetics Jimma University Jimma Ethiopia Anesthesiology Department Dilla University Addis Ababa Ethiopia Department of Juridical and Economic Studies La Sapienza University Rome Italy Non-Communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Brigham and Women’s Hospital Harvard University Boston MA USA Students’ Scientific Research Center (SSRC) Tehran University of Medical Sciences Tehran Iran School of Medicine Tehran University of Medical Sciences Tehran Iran School of Medicine Shahid Beheshti University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Institute Tehran University of Medical Sciences Tehran Iran Chapter of Addiction Medicine University of Sydney Sydney NSW Australia Advanced Diagnostic and Intervent

Chronic care manages long-term, progressive conditions, while acute care addresses short-term conditions. Chronic conditions increasingly strain health systems, which are often unprepared for these demands. This study examines the burden of conditions requiring acute versus chronic care, including sequelae. Conditions and sequelae from the Global Burden of Diseases Study 2019 were classified into acute or chronic care categories. Data were analysed by age, sex, and socio-demographic index, presenting total numbers and contributions to burden metrics such as Disability-Adjusted Life Years (DALYs), Years Lived with Disability (YLD), and Years of Life Lost (YLL). Approximately 68% of DALYs were attributed to chronic care, while 27% were due to acute care. Chronic care needs increased with age, representing 86% of YLDs and 71% of YLLs, and accounting for 93% of YLDs from sequelae. These findings highlight that chronic care needs far exceed acute care needs globally, necessitating health systems to adapt accordingly. © 2025. The Author(s).

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Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: the Global Burden of Diseases Study 2019

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The Lancet HIV 2021年第10期8卷 e633-e651页

作者： Jahagirdar, Deepa Walters, Magdalene K. Novotney, Amanda Brewer, Edmond D. Frank, Tahvi D. Carter, Austin Biehl, Molly H. Abbastabar, Hedayat Abhilash, E.S. Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Adekanmbi, Victor Adeyinka, Daniel Adedayo Adnani, Qorinah Estiningtyas Sakilah Afzal, Saira Aghababaei, Soodabeh Ahinkorah, Bright Opoku Ahmad, Sajjad Ahmadi, Keivan Ahmadi, Sepideh Ahmadpour, Ehsan Ahmed, Muktar Beshir Rashid, Tarik Ahmed Salih, Yusra Ahmed Aklilu, Addis Akram, Tayyaba Akunna, Chisom Joyqueenet Al Hamad, Hanadi Alahdab, Fares Alanezi, Fahad Mashhour Aleksandrova, Ekaterina A. Alene, Kefyalew Addis Ali, Liaqat Alipour, Vahid Almustanyir, Sami Alvis-Guzman, Nelson Ameyaw, Edward Kwabena Amu, Hubert Andrei, Catalina Liliana Andrei, Tudorel Anvari, Davood Arabloo, Jalal Aremu, Olatunde Arulappan, Judie Atnafu, Desta Debalkie Quintanilla, Beatriz Paulina Ayala Ayza, Muluken Altaye Azari, Samad Darshan, B.B. Banach, Maciej Bärnighausen, Till Winfried Barra, Fabio Barrow, Amadou Basu, Sanjay Bazargan-Hejazi, Shahrzad Belay, Habtamu Gebrehana Berheto, Tezera Moshago Bezabhe, Woldesellassie Mequanint Bezabih, Yihienew Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Nikha Bhardwaj, Pankaj Bhattacharyya, Krittika Bibi, Sadia Bijani, Ali Bisignano, Catherine Bolarinwa, Obasanjo Afolabi Boloor, Archith Boltaev, Azizbek A. Briko, Nikolay Ivanovich Buonsenso, Danilo Burkart, Katrin Butt, Zahid A. Cao, Chao Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Choudhari, Sonali Gajanan Chu, Dinh-Toi Couto, Rosa A.S. Cowden, Richard G. Dachew, Berihun Assefa Dadras, Omid Dagnew, Amare Belachew Dahlawi, Saad M.A. Dai, Xiaochen Dandona, Lalit Dandona, Rakhi das Neves, José Degenhardt, Louisa Demeke, Feleke Mekonnen Desta, Abebaw Alemayehu Deuba, Keshab Dhamnetiya, Deepak Dhungana, Govinda Prasad Dianatinasab, Mostafa Diaz, Daniel Djalalinia, Shirin Doan, Linh Phuong Dorostkar, Fariba Edinur, Hisham Atan Effiong, Andem Eftekharzadeh, Sahar El Sayed Zaki, Maysaa Elayedath, Rajesh Elhadi, 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 Allergy and Infectious Diseases University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States School of Social Work University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Vagelos College of Physicians and Surgeones Columbia University Medical Center New York NY United States Division of Data Analytics and Delivery for Impact WHO Geneva Switzerland Advanced Diagnostic and Interventional Radiology Research Centre Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Centre Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Paediatric Chronic Kidney Disease Research Centre Tehran University of Medical Sciences Tehran Iran Department of Psychiatry Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Centre Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Centre Tehran University of Medical Sciences Tehran Iran Research Centre for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Centre Tehran University of Medical Sciences Tehran Iran Department of Botany Sree Narayana Guru College Chelannur Kozhikode India Clinical Sciences Department University of Sharjah Sharjah United Arab Emirates Mass Communication Department University of Sharjah Sharjah United Arab Emirates Department of Health-Care Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Department of Population Medicine Ca

Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. Methods: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). Findings: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1–38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78–0·91) per female living with HIV in 2019, 0·99 male infections (0·91–1·10) for every female infection, and 1·02 male deaths (0·95–1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58–35·43, and a 39·66% decrease in deaths, 36·49–42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05–0·06) and the global incidence-to-mortality ratio was

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Subnational mapping of HIV incidence and mortality among individuals aged 15–49 years in sub-Saharan Africa, 2000–18: a modelling study

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The Lancet HIV 2021年第6期8卷 e363-e375页

作者： Sartorius, Benn VanderHeide, John D. Yang, Mingyou Goosmann, Erik A. Hon, Julia Haeuser, Emily Cork, Michael A. Perkins, Samantha Jahagirdar, Deepa Schaeffer, Lauren E. Serfes, Audrey L. LeGrand, Kate E. Abbastabar, Hedayat Abebo, Zeleke Hailemariam Abosetugn, Akine Eshete Abu-Gharbieh, Eman Accrombessi, Manfred Mario Kokou Adebayo, Oladimeji M. Adegbosin, Adeyinka Emmanuel Adekanmbi, Victor Adetokunboh, Olatunji O. Adeyinka, Daniel Adedayo Ahinkorah, Bright Opoku Ahmadi, Keivan Ahmed, Muktar Beshir Akalu, Yonas Akinyemi, Oluwaseun Oladapo Akinyemi, Rufus Olusola Aklilu, Addis Akunna, Chisom Joyqueenet Alahdab, Fares Al-Aly, Ziyad Alam, Noore Alamneh, Alehegn Aderaw Alanzi, Turki M. Alemu, Biresaw Wassihun Alhassan, Robert Kaba Ali, Tilahun Alipour, Vahid Amini, Saeed Ancuceanu, Robert Ansari, Fereshteh Anteneh, Zelalem Alamrew Anvari, Davood Anwer, Razique Appiah, Seth Christopher Yaw Arabloo, Jalal Asemahagn, Mulusew A. Asghari Jafarabadi, Mohammad Asmare, Wondwossen Niguse Atnafu, Desta Debalkie Atout, Maha Moh'd Wahbi Atreya, Alok Ausloos, Marcel Awedew, Atalel Fentahun Ayala Quintanilla, Beatriz Paulina Ayanore, Martin Amogre Aynalem, Yared Asmare Ayza, Muluken Altaye Azari, Samad Azene, Zelalem Nigussie Babar, Zaheer-Ud-Din Baig, Atif Amin Balakrishnan, Senthilkumar Banach, Maciej Bärnighausen, Till Winfried Basu, Sanjay Bayati, Mohsen Bedi, Neeraj Bekuma, Tariku Tesfaye Bezabhe, Woldesellassie M. Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Pankaj Bhattacharyya, Krittika Bhutta, Zulfiqar A. Bibi, Sadia Bikbov, Boris Birhan, Tsegaye Adane Bitew, Zebenay Workneh Bockarie, Moses John Boloor, Archith Brady, Oliver J. Bragazzi, Nicola Luigi Briko, Andrey Nikolaevich Briko, Nikolay Ivanovich Burugina Nagaraja, Sharath Butt, Zahid A. Cárdenas, Rosario Carvalho, Felix Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Chowdhury, Mohiuddin Ahsanul Kabir Chu, Dinh-Toi Cook, Aubrey J. Cormier, Natalie Maria Cowden, Richard G. Culquichicon, Carlos Dagnew, Baye Dahlawi, Saad M.A. D Centre for Tropical Medicine and Global Health Nuffield Department of Medicine University of Oxford Oxford United Kingdom Malaria Atlas Project University of Oxford Oxford United Kingdom The George Institute for Global Health University of Oxford Oxford United Kingdom Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Insights Program Bill and Melinda Gates Foundation Seattle WA United States Global Programs Medical Teams International Seattle WA United States Department of Pediatric Newborn Medicine Brigham and Women's Hospital Boston MA United States Advanced Diagnostic and Interventional Radiology Research Center Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Pediatric Chronic Kidney Disease Research Center Tehran University of Medical Sciences Tehran Iran Department of Environmental Health Engineering Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Public Health Arba Minch University Arba Minch Ethiopia Department of Medical Laboratory Sciences Arba Minch University Arba Minch Ethiopia College of Medicine and Health Science Arba Minch University Arba Minch Ethiopia Department of Nursing Arba Minch University Arba Minch Ethiopia Department of Biomedical Sciences Arba Minch University Arba Minch Ethiopia Department of Public Health Debre Berhan University Debre Brehan

Background: High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. Methods: In this modelling study, we developed a framework that used the geographically specific HIV prevalence data collected in seroprevalence surveys and antenatal care clinics to train a model that estimates HIV incidence and mortality among individuals aged 15–49 years. We used a model-based geostatistical framework to estimate HIV prevalence at the second administrative level in 44 countries in sub-Saharan Africa for 2000–18 and sought data on the number of individuals on antiretroviral therapy (ART) by second-level administrative unit. We then modified the Estimation and Projection Package (EPP) to use these HIV prevalence and treatment estimates to estimate HIV incidence and mortality by second-level administrative unit. Findings: The estimates suggest substantial variation in HIV incidence and mortality rates both between and within countries in sub-Saharan Africa, with 15 countries having a ten-times or greater difference in estimated HIV incidence between the second-level administrative units with the lowest and highest estimated incidence levels. Across all 44 countries in 2018, HIV incidence ranged from 2·8 (95% uncertainty interval 2·1–3·8) in Mauritania to 1585·9 (1369·4–1824·8) cases per 100 000 people in Lesotho and HIV mortality ranged from 0·8 (0·7–0·9) in Mauritania to 676·5 (513·6–888·0) deaths per 100 000 people in Lesotho. Variation in both incidence and mortality was substantially greater at the subnational level than at the national level and the highest estimated rates were accordingly higher. Among second-level administrative units, Guijá District, Gaza Province, Mozambique,

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Performance comparison of Wave Variable Transformation and Time Domain Passivity Approaches for time-delayed teleoperation: Preliminary results

Performance comparison of Wave Variable Transformation and T...

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2016 IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Ribin Balachandran Jordi Artigas Usman Mehmood Jee-Hwan Ryu Department for Analysis and Control of Advanced Robotic Systems German Aerospace Center (DLR) Oberpfaffenhofen Germany BioRobotics Laboratory of Korea University of Technology and Education Cheonan Korea

ISBN: (纸本)9781509037636

This paper presents initial results of a set of experiments to compare time-delayed teleoperation performance of selected architectures based on two popular passivity based methods, namely, Wave Variables Transformation (WVT) and Time Domain Passivity Approach (TDPA). Five different architectures widely used and available in literature are selected: 2-channel and 3-channel for both WV and TDPA, and 4-channel based on TDPA. An empirical approach for measuring transparency is proposed, which presents three main qualities: 1) controller independency 2) Frequency dependency of performance and 3) Removal of the human operator out of the loop. In order to achieve this, the human operator is replaced by a linear actuator equipped with a force sensor. Deterministic interactions between the simulated operator and the rest of the system can thus be easily implemented and registered. Therefore, this approach allows to isolate pure effects of any control method and perform a proper analysis in terms of selected attributes for a desired metrics. In this article, these are chosen to be effective impedance and position tracking error, both in the frequency domain. In addition to the quantitative results, a qualitative analysis is presented which underlines practical implications of each architecture and control method. The comparison sample presented contains five different delays, varying from 0 to 200 milliseconds, five different environmental impedances and 5 bilateral control architectures along with an analysis of the results obtained.

关键词： Time-domain analysis Delays Impedance Force Robots Standards Frequency modulation

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The Liver Tumor Segmentation Benchmark (LiTS)

arXiv

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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

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