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Square root-based multi-source early PSD estimation and recursive RETF update in reverberant environments by means of the orthogonal procrustes problem

arXiv

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arXiv 2019年

作者： Dietzen, Thomas Doclo, Simon Moonen, Marc van Waterschoot, Toon STADIUS Center for Dynamical Systems Signal Processing and Data Analytics and ETC Technology Cluster Electrical Engineering Leuven Belgium University of Oldenburg Dept. of Medical Physics and Acoustics Cluster of Excellence Hearing4all Oldenburg Germany KU Leuven ESAT STADIUS

Multi-channel short-time Fourier transform (STFT) domain-based processing of reverberant microphone signals commonly relies on power-spectral-density (PSD) estimates of early source images, where early refers to reflections contained within the same STFT frame. State-of-the-art approaches to multi-source early PSD estimation, given an estimate of the associated relative early transfer functions (RETFs), conventionally minimize the approximation error defined with respect to the early correlation matrix, requiring non-negative inequality constraints on the PSDs. Instead, we here propose to factorize the early correlation matrix and minimize the approximation error defined with respect to the early-correlation-matrix square root. The proposed minimization problem - constituting a generalization of the so-called orthogonal Procrustes problem - seeks a unitary matrix and the square roots of the early PSDs up to an arbitrary complex argument, making non-negative inequality constraints redundant. A solution is obtained iteratively, requiring one singular value decomposition (SVD) per iteration. The estimated unitary matrix and early PSD square roots further allow to recursively update the RETF estimate, which is not inherently possible in the conventional approach. An estimate of the said early-correlation-matrix square root itself is obtained by means of the generalized eigenvalue decomposition (GEVD), where we further propose to restore non-stationarities by desmoothing the generalized eigenvalues in order to compensate for inevitable recursive averaging. Simulation results indicate fast convergence of the proposed multi-source early PSD estimation approach in only one iteration if initialized appropriately, and better performance as compared to the conventional approach. Copyright © 2019, The Authors. All rights reserved.

关键词： Singular value decomposition

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Faster algorithms for min-max-min robustness for combinatorial problems with budgeted uncertainty

arXiv

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arXiv 2018年

作者： Chassein, André Goerigk, Marc Kurtz, Jannis Poss, Michael Data Analytics Center of Excellence Deutsche Post DHL Group Bonn Germany Network and Data Science Management University of Siegen Germany Department of Mathematics RWTH Aachen University Germany LIRMM University of Montpellier CNRS France

We consider robust combinatorial optimization problems where the decision maker can react to a scenario by choosing from a finite set of k solutions. This approach is appropriate for decision problems under uncertainty where the implementation of decisions requires preparing the ground. We focus on the case that the set of possible scenarios is described through a budgeted uncertainty set and provide three algorithms for the problem. The first algorithm solves heuristically the dualized problem, a non-convex mixed-integer non-linear program (MINLP), via an alternating optimization approach. The second algorithm solves the MINLP exactly for k = 2 through a dedicated spatial branch-and-bound algorithm. The third approach enumerates k-tuples, relying on strong bounds to avoid a complete enumeration. We test our methods on shortest path instances that were used in the previous literature and on randomly generated knapsack instances, and find that our methods considerably outperform previous approaches. Many instances that were previously not solved within hours can now be solved within few minutes, often even faster. Copyright © 2018, The Authors. All rights reserved.

关键词： Combinatorial optimization

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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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Global Consensus Recommendations for Metabolic Dysfunction-Associated Steatotic Liver Disease and Steatohepatitis

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Gastroenterology 2025年

作者： Zobair M Younossi Shira Zelber-Sagi Jeffrey V Lazarus Vincent Wai-Sun Wong Yusuf Yilmaz Ajay Duseja Yuichiro Eguchi Laurent Castera Mário Guimarães Pessoa Claudia Pinto Oliveira Mohamed El-Kassas Emmanuel Tsochatzis Jian-Gao Fan C Wendy Spearman Frank Tacke Marlen Ivon Castellanos Fernandez Naim Alkhouri Jörn M Schattenberg Manuel Romero-Gómez Mazen Noureddin Alina M Allen Janus P Ong Stuart K Roberts Jay H Shubrook Patrizia Burra Rohit Kohli Achim Kautz Adriaan G Holleboom Brian Lam Scott Isaacs Paula Macedo Amalia Gastaldelli Linda Henry Dana Ivancovsky-Wajcman Fatema Nader Leyla de Avila Jillian K Price Henry E Mark Marcela Villota-Rivas Aurora Barberá Markos Kalligeros Lynn H Gerber Saleh A Alqahtani The Global MASH Council Washington DC United States Beatty Liver and Obesity Research Program Inova Health System Falls Church VA. Electronic address: zobair.younossi@***. School of Public Health University of Haifa Haifa Israel. Barcelona Institute for Global Health (ISGlobal) Barcelona Spain. Medical Data Analytics Center Department of Medicine and Therapeutics The Chinese University of Hong Kong Hong Kong China. Department of Gastroenterology School of Medicine Recep Tayyip Erdoğan University Rize Turkey. Department of Hepatology Post Graduate Institute of Medical Education and Research Chandigarh India. Loco Medical General Institute Saga Japan. Department of Hepatology Beaujon Hospital Université Paris-Cité Clichy France. Departamento de Gastroenterologia Hospital das Clínicas (LIM 07) da Faculdade de Medicina daUniversidade de São Paulo São Paulo Brasil. Endemic Medicine Department Faculty of Medicine Helwan University Cairo Egypt. UCL Institute for Liver and Digestive Health Royal Free Hospital and UCL London UK. Department of Gastroenterology Xinhua Hospital Shanghai Jiaotong University School of Medicine Shanghai China. Division of Hepatology Department of Medicine Faculty of Health Sciences University of Cape Town Cape Town South Africa. Department of Hepatology and Gastroenterology Charité - Universitätsmedizin Berlin Berlin Germany. Institute of Gastroenterology University of Medical Sciences of Havana Havana Cuba. Arizona Liver Health Chandler AZ USA. Department of Internal Medicine II Saarland University Medical Center and Saarland University Faculty of Medicine 66421 Homburg Germany. UCM Digestive Diseases. Virgen del Rocío University Hospital. Institute of Biomedicine of Seville (HUVR/CSIC/US). CIBEREHD ISCIII. Department of Medicine. University of Seville Seville Spain. Houston Methodist Hospital Houston Texas. Division of Gastroenterology and Hepatology Mayo Clinic Rochester MN USA. College of Medicine University of the Philippine

BACKGROUND AND AIM:Metabolic dysfunction-associated steatotic liver disease (MASLD) and steatohepatitis (MASH) are associated with adverse clinical outcomes, impaired health-related quality of life, and large economic burden. The growing burden of MASLD and MASH has led to the publication of a large number of MASLD/MASH guidelines by national and international societies. However, important differences among the recommendations have created confusion. contributing to low rate of implementation and suboptimal management of MASLD and MASH. Creating a consensus recommendation has become more important since the approval of a partial agonist of thyroid hormone β receptor (resmetirom) for MASH treatment in the United States. We built a consensus among the most recently published recommendations for MASLD/MASH. METHODS:A comprehensive search for MASLD and MASH guidelines, guidance, or similar documents from January 2018-January 2025 using PubMed, Embase, Web of Science and Society Websites was conducted. Each selected document was assessed across 8 specific domains with 145 variables. Variables with <50% concordance were used for the Delphi statement development. A supermajority of 67% was set for Delphi statement acceptance. RESULTS:There were 61 documents published from 2018 through January 2025. Four rounds of Delphi were conducted: 46 statements were generated for Round 1, 32 statements for Round 2, 16 statements for Round 3, and 8 statements for Round 4, whereby 100% of statements achieved a greater than 90% agreement. All final consensus recommendations were summarized in tables and algorithms. CONCLUSIONS:Our study provides an extensive set of recommendations generated based on a comprehensive review of the most recent MASLD/MASH guidelines and a consensus-building process.

关键词： Global Guideline MASH MASLD

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Domain Adaptation for Ontology Localization

SSRN

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SSRN 2018年

作者： McCrae, John P. Arcan, Mihael Asooja, Kartik Gracia, Jorge Buitelaar, Paul Cimiano, Philipp Center of Excellence Universität Bielefeld Inspiration 1 Bielefeld33615 Germany Insight Centre for Data Analytics National University of Ireland Galway IDA Business Park Galway Ireland Ontology Engineering Group Universidad Polit´ecnica de Madrid Campus de Montegancedo Boadilla del Monte28660 Spain Unit for Natural Language Processing Semantic Computing Group

Ontology localization is the task of adapting an ontology to a different cultural context, and has been identified as an important task in the context of the Multilingual Semantic Web vision. The key task in ontology localization is translating the lexical layer of an ontology, i.e., its labels, into some foreign language. For this task, we hypothesise that the translation quality can be improved by adapting a machine translation system to the domain of the ontology. To this end, we build on the success of existing statistical machine translation (SMT) approaches, and investigate the impact of different domain adaptation techniques on the task. In particular, we investigate three techniques: i) enriching a phrase table by domain-specific translation candidates acquired from existing Web resources, ii) relying on Explicit Semantic Analysis as an additional technique for scoring a certain translation of a given source phrase, as well as iii) adaptation of the language model by means of weighting n-grams with scores obtained from topic modelling. We present in detail the impact of each of these three techniques on the task of translating ontology labels. We show that these techniques have a generally positive effect on the quality of translation of the ontology and that, in combination, they provide a significant improvement in quality. © 2018, The Authors. All rights reserved.

关键词： Ontology

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Linked data for lexicons (Invited tutorial) 12th

Linked data for lexicons (Invited tutorial)

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12th Summer School on Linguistic Linked Open data, EUROLAN 2015 and Workshop on Social Media and the Web of Linked data, RUMOUR-2015

作者： McCrae, John P. Cognitive Interaction Technology Center of Excellence Bielefeld University and Insight Centre for Data Analytics National University of Ireland Galway Ireland

ISBN: (纸本)9783319329413

Lexicons form a crucial part of how we build natural language systems that allow humans to interact with machines and to build web applications that can use web standards such as OWL but express them in natural language, we developed a vocabulary called lemon (Lexicon Model for Ontologies). This tutorial details the model and enables participants to apply it in line with common patterns of usage. © Springer International Publishing Switzerland 2016.

关键词： Semantic Web

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Trust in government moderates the association between fear of COVID-19 as well as empathic concern and preventive behaviour

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Communications Psychology 2023年第1期1卷 1-16页

作者： Arzu Karakulak Beyza Tepe Radosveta Dimitrova Mohamed Abdelrahman Azzam Amin Plamen Akaliyski Rana Alaseel Batoul Bakkar Wassim Gharz Edine Fatema Mohsen Yousuf Abdulqader Alkamali Danny A. Lizarzaburu Aguinaga Andrii Andres John Jamir Benzon R. Aruta Marios Assiotis Olga Solomontos-Kountouri Hrant Avanesyan Maria Muradyan Norzihan Ayub Maria Bacikova-Sleskova Raushan Baikanova Aidos Bolatov Telman Seisembekov Sunčica Bartoluci Ksenija Bosnar Anna Janovská Darko Katović Franjo Prot David Benitez Rita Rivera Ivanna Bodnar Iuliia Pavlova Judyta Borchet Maria Kazmierczak Aleksandra Lewandowska-Walter Justyna Michalek-Kwiecien Katarzyna Skrzypińska Yunier Broche-Pérez Carmen Buzea Rosalinda Cassibba Pasquale Musso Fabiola Silletti Marta Martín Carbonell Bin-Bin Chen Gordana Ristevska Dimitrovska Dương Công Doanh Alejandra del Carmen Dominguez Espinosa Nelli Ferenczi Regina Fernández-Morales Jorge Gaete Yiqun Gan Suely Giolo Rubia Carla Formighieri Giordani Camila Muhl José Rasia Maria-Therese Friehs Shahar Gindi Biljana Gjoneska Juan Carlos Godoy Lorena Cecilia López Steinmetz Maria del Pilar Grazioso Marinés Mejía Camellia Hancheva Given Hapunda Shogo Hihara Russell Sarwar Kabir Tinka Delakorda Kawashima Kazumi Sugimura Brett Walter Mohd Saiful Husain Md Saiful Islam Sadia Sultana Nino Javakhishvili Ana Makashvili Veljko Jovanović Nor Ba’yah Abdul Kadir Johannes Karl Zhumaly Kauyzbay Richa Khanna Meetu Khosla Martina Klicperová-Baker Iva Poláčková Šolcová Ana Kozina Steven Eric Krauss Rodrigo Landabur Katharina Lefringhausen Yun-Hsia Liang Sadia Malik Denisse Manrique-Millones Stefanos Mastrotheodoros Breeda McGrath Enkeleint A. Mechili Samson Mhizha Diana Miconi Rodrigo Moreta-Herrera Andrej Naterer Arash Nemat Felix Neto Joana Neto Luz Marina Alonso Palacio Hassan Okati-Aliabad Carlos Iván Orellana Ligia María Orellana Sushanta Kumar Mishra Joonha Park Eddy Peralta Petro Petrytsa Saša Pišot Benedicta Prihatin Dwi Riyanti Laura Francisca Sudarnoto Angela Oktavia Suryani Adil Samekin Danielius Serapinas Rasa Pilkaus Istanbul Policy Center Sabanci University Istanbul Turkey Department of Psychology MEF University Istanbul Turkey Department of Psychology Stockholm University Stockholm Sweden Social Psychology Department Doha Institute for Graduate Studies Doha Qatar Mokhtass for Consultations and Research Doha Qatar Department of Sociology and Social Policy Lingnan University Hong Kong SAR China Faculty of Medicine Syrian Private University Damascus Syrian Arab Republic Ipswich Hospital Ipswich UK United Private School Athaiba Oman Universidad César Vallejo Trujillo Peru Department of Physical Education Lviv Polytechnic National University Lviv Ukraine Department of Psychology De La Salle University Manila Philippines Theological School Church of Cyprus Nicosia Cyprus General Psychology Chair Yerevan State University Yerevan Armenia Faculty of Psychology and Education University of Malaysia Sabah Sabah Malaysia Department of Educational Psychology and Health Psychology Pavol Jozef Šafárik University Košice Slovakia Astana Medical University Astana Kazakhstan University of Zagreb Zagreb Croatia Clinical Psychology Department Albizu University Miami FL USA Counseling & Psychological Services Duke University Durham NC USA Lviv State University of Physical Culture Lviv Ukraine Institute of Psychology University of Gdansk Gdansk Poland Polish Society for the Psychology of Religion University of Gdańsk Gdańsk Poland Department of Psychology Universidad Central Marta Abreu de Las Villas Santa Clara Cuba Department of Social Sciences and Communication Transilvania University of Brasov Brasov Romania Department of Education Psychology Communication University of Bari Bari Italy Faculty of Psychology Cooperative University of Colombia Santa Marta Colombia Psychology Department Fudan University Shanghai China Higher Medical School University St. Kliment Ohridski Bitola North Macedonia PHI Psihomedika Bitola North Macedonia National Economics University

With the COVID-19 pandemic, behavioural scientists aimed to illuminate reasons why people comply with (or not) large-scale cooperative activities. Here we investigated the motives that underlie support for COVID-19 preventive behaviours in a sample of 12,758 individuals from 34 countries. We hypothesized that the associations of empathic prosocial concern and fear of disease with support towards preventive COVID-19 behaviours would be moderated by trust in the government. Results suggest that the association between fear of disease and support for COVID-19 preventive behaviours was strongest when trust in the government was weak (both at individual- and country-level). Conversely, the association with empathic prosocial concern was strongest when trust in the government was high, but this moderation was only found at individual-level scores of governmental trust. We discuss how motivations may be shaped by socio-cultural context, and outline how findings may contribute to a better understanding of collective action during global crises.

关键词： Human behaviour Infectious diseases

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

arXiv

引用

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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Electro-tactic ionic liquid droplets 19

Electro-tactic ionic liquid droplets

引用

19th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2015

作者： Francis, Wayne Wagner, Klaudia Beirne, Stephen Officer, David Wallace, Gordon Florea, Larisa Diamond, Dermot Insight Centre for Data Analytics National Center for Sensor Research School of Chemical Sciences Dublin City University Dublin 9 Ireland Australian Centre of Excellence for Electromaterials Science Intelligent Polymer Research Institute University of Wollongong Wollongong Australia

ISBN: (纸本)9780979806483

Herein we report the behavior of electro-guided, self-propelled droplets, which are composed solely of an ionic liquid (IL), namely trihexyl(tetradecyl)phosphonium chloride ([P6,6,6,14][Cl]). These selfpropelled droplets travel along an aqueous-air boundary, and are guided to specific destinations within the fluidic network through the use of electrochemically generated dynamic Cl- gradients. The speed, trajectory and direction of movement can be controlled by switching the voltage (ON or OFF in the range 5-9 V) and polarity of embedded electrodes that are in contact with a low ionic strength electrolyte solution (10-3 M NaCl) present in the channels. © 15CBMS-0001.

关键词： Drops

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