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THE GEOMETRICAL-CONVEXITY OF A FUNCTION RELATED TO THE MINC-SATHRE RATIO

UPB Scientific Bulletin, Series A: applied mathematics and Physics 2024年第4期86卷 3-10页

作者： Mortici, Cristinel Postolache, Mihai Valahia University of Târgovişte Târgovişte Romania National University of Science & Technology Politehnica Bucharest Department of Mathematics and Informatics Bucharest060042 Romania Academy of Romanian Scientists 3 Ilfov Bucharest050044 Romania Gheorghe Mihoc-Caius Iacob Institute of Mathematical Statistics and Applied Mathematics of the Romanian Academy Bucharest050711 Romania The Key Laboratory of Intelligent Information and Big Data Processing of NingXia Province and Health Big Data Research Institute North Minzu University Yinchuan750021 China

In this paper we give a new proof for the fact that the function Γ (x)1 x−1 is geometrically convex. As an application, we give an improvement of Minc-Sathre inequality. © 2024, Politechnica University of Buchar... 详细信息

关键词： Choquet integral

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ABACUS: An Electronic Structure Analysis Package for the AI Era

arXiv

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arXiv 2025年

作者： Zhou, Weiqing Zheng, Daye Liu, Qianrui Lu, Denghui Liu, Yu Lin, Peize Huang, Yike Peng, Xingliang Bao, Jie J. Cai, Chun Jin, Zuxin Wu, Jing Zhang, Haochong Jin, Gan Ji, Yuyang Shen, Zhenxiong Liu, Xiaohui Sun, Liang Cao, Yu Sun, Menglin Liu, Jianchuan Chen, Tao Liu, Renxi Li, Yuanbo Han, Haozhi Liang, Xinyuan Bao, Taoni Chen, Nuo Ren, Hongxu Zhang, Xiaoyang Liu, Zhaoqing Fu, Yiwei Liu, Maochang Li, Zhuoyuan Wen, Tongqi Tang, Zechen Xu, Yong Duan, Wenhui Wang, Xiaoyang Gu, Qiangqiang Dai, Fu-Zhi Zheng, Qijing Zhao, Jin Zhang, Yuzhi Ou, Qi Jiang, Hong Liu, Shi Xu, Ben Xu, Shenzhen Ren, Xinguo He, Lixin Zhang, Linfeng Chen, Mohan AI for Science Institute Beijing100080 China HEDPS CAPT School of Physics College of Engineering Peking University Beijing100871 China College of Engineering Peking University Beijing100871 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230026 China Key Laboratory of Quantum Information University of Science and Technology of China Hefei230026 China Supercomputing Center University of Science and Technology of China Anhui Hefei230026 China Institute of Physics Chinese Academy of Sciences Beijing100190 China School of Materials Science and Engineering Peking University Beijing100871 China School of Electrical Engineering and Electronic Information Xihua University Chengdu610039 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China College of Chemistry and Molecular Engineering Peking University Beijing100871 China International Research Center for Renewable Energy State Key Laboratory of Multiphase Flow Xi’an Jiaotong University Shaanxi Xi’an710049 China Suzhou Academy of Xi’an Jiaotong University Jiangsu Suzhou215123 China Center for Structural Materials Department of Mechanical Engineering The University of Hong Kong Hong Kong The University of Hong Kong Shenzhen China State Key Laboratory of Low Dimensional Quantum Physics Department of Physics Tsinghua University Beijing100084 China Frontier Science Center for Quantum Information Beijing China Saitama Wako351-0198 Japan Institute for Advanced Study Tsinghua University Beijing100084 China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Fenghao East Road 2 Beijing100094 China School of Artificial Intelligence and Data Science University of Science and Technology of China Hefei230026 China School of Materials Science and Engineering University of Science and Technology Beijing Beijing100083 China Department of Physics University of Science and

ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source software for first-principles electronic structure calculations and molecular dynamics simulations. It mainly features density functional theory (DFT) and is compatible with both plane-wave basis sets and numerical atomic orbital basis sets. ABACUS serves as a platform that facilitates the integration of various electronic structure methods, such as Kohn-Sham DFT, stochastic DFT, orbital-free DFT, and real-time time-dependent DFT, etc. In addition, with the aid of high-performance computing, ABACUS is designed to perform efficiently and provide massive amounts of first-principles data for generating general-purpose machine learning potentials, such as DPA models. Furthermore, ABACUS serves as an electronic structure platform that interfaces with several AI-assisted algorithms and packages, such as DeePKS-kit, DeePMD, DP-GEN, DeepH, DeePTB, etc. Copyright © 2025, The Authors. All rights reserved.

关键词： Stochastic systems

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Linguistic Pythagorean fuzzy Aczel–Alsina aggregation operators and their application in multi-attribute group decision-making: An approach for smart city development

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Engineering Applications of Artificial Intelligence 2025年 156卷

作者： Shahid Hussain Gurmani Zunaira Rasool Rifaqat Ali Shehr Bano Huayou Chen Yuming Feng Rana Muhammad Zulqarnain School of Artificial Intelligence and Computer Science Nantong University Nantong 226019 China College of Agriculture Engineering and Food Science Shandong University of Technology Zibo China Department of Botany College of Life Sciences Government College University Allama Iqbal Road Faisalabad 38000 Pakistan Department of Mathematics Applied College in Mohayil Asir King Khalid University Abha Saudi Arabia Institute of Zoology Bahauddin Zakariya University Multan Pakistan School of Big Data and Statistics Anhui University Hefei 230601 Anhui China Institute of Intelligent Information Processing South China Business College of Guangdong University of Foreign Studies Guangzhou 510545 Guangdong China Department of Mathematics Saveetha School of Engineering SIMATS Thandalam Chennai 602105 Tamilnadu India

This paper aims to present a new multi-attribute group decision-making (MAGDM) approach for solving problems in an uncertain and complex environment. In any MAGDM problem, the key challenge is how to quantify and aggregate the objective uncertainty information contained in the data. To answer this, in this paper, we utilize the idea of linguistic Pythagorean fuzzy set (LP y FS) to describe the information in terms of linguistic membership degree (LMD) and linguistic non-membership degree (LNMD). We first present some new operations of LP y FS, including Aczel–Alsina (AA) sum, AA product, and AA scalar multiplication. At that point, we develop various LP y F aggregation operators which are based on these defined operations, including the LP y F Aczel–Alsina weighted averaging (LP y FAAWA) operator, the LP y F Aczel–Alsina ordered weighted averaging (LP y FAAOWA) operator, LP y F Aczel–Alsina weighted geometric (LP y FAAWG) operator and LP y F Aczel–Alsina ordered weighted geometric (LP y FAAOWG) operator. We configure these operators with different characteristics. It can be seen that the proposed operators have commutativity, monotonicity, boundary, and idempotency properties. Then, we design a new technique dependent on these operators to solve MAGDM problems. The applicability of the established approach is demonstrated through a case study related to smart city development. The result demonstrates the new technique's feasibility and applicability. In the end, sensitivity analysis and a systematic comparison between the prevailing and suggested techniques are given.

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INTRODUCTION

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Bulletin of the American Meteorological society 2024年第8期105卷 S1-S11页

作者： Boyer, T. Blunden, J. Dunn, R.J.H. NOAA/NESDIS National Centers for Environmental Information Silver Spring Maryland NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Met Office Hadley Centre Exeter United Kingdom European Centre for Medium-Range Weather Forecasts Reading United Kingdom University of Maryland College Park Maryland Scripps Institution of Oceanography University of California San Diego La Jolla California NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland Brandenburg University of Technology (BTU) Cottbus-Senftenberg Germany Servicio Meteorológico Nacional Buenos Aires Argentina NOAA/OAR Physical Sciences Laboratory Boulder Colorado European Centre for Medium-Range Weather Forecasts Bonn Germany Center for Geophysical Research and School of Physics University of Costa Rica San José Costa Rica Department of Meteorology and National Centre for Earth Observation University of Reading Reading United Kingdom Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN São Paulo Brazil Université Grenoble Alpes Institut des Géosciences de l’Environnement IRD CNRS Grenoble INP Grenoble France Hampton University Hampton Virginia Seychelles Meteorological Authority Mahe Seychelles Section for Glaciers Ice and Snow Norwegian Water Resources and Energy Directorate Oslo Norway National Research Institute for Agriculture Food and Environment (INRAE) CARRTEL Université Savoie Mont Blanc Thonon les Bains France Graduate School of Agriculture Osaka Metropolitan University Sakai Japan Science Faculty Universidad Nacional de Colombia Bogotá Colombia University of Bremen Bremen Germany NOAA Global Monitoring Laboratory Boulder Colorado Servicio Nacional de Meteorología e Hidrología del Perú Lima Perú Centro de Investigaciones sobre Desertificación – Spanish National Research Council (CSIC-UV-GVA) Valencia Spain Hydro-Climate Extremes Lab (H-CEL) Ghent University Ghent Belgium Department o

In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. A

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The 2025 Roadmap to Ultrafast Dynamics: Frontiers of Theoretical and Computational Modelling

arXiv

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arXiv 2025年

作者： Caruso, Fabio Sentef, Michael A. Attaccalite, Claudio Bonitz, Michael Draxl, Claudia De Giovannini, Umberto Eckstein, Martin Ernstorfer, Ralph Fechner, Michael Grüning, Myrta Hübener, Hannes Joost, Jan-Philip Juraschek, Dominik M. Karrasch, Christoph Kennes, Dante Marvin Latini, Simone Lu, I-Te Neufeld, Ofer Perfetto, Enrico Rettig, Laurenz Pela, Ronaldo Rodrigues Rubio, Angel Rudzinski, Joseph F. Ruggenthaler, Michael Sangalli, Davide Schüler, Michael Shallcross, Samuel Sharma, Sangeeta Stefanucci, Gianluca Werner, Philipp Institute of Theoretical Physics and Astrophysics University of Kiel Leibnizstrasse 15 Kiel24116 Germany Institute for Theoretical Physics Bremen Center for Computational Materials Science University of Bremen Bremen28359 Germany Luruper Chaussee 149 Hamburg22761 Germany CNRS Aix-Marseille Université Centre Interdisciplinaire de Nanoscience de Marseille UMR 7325 Campus de Luminy Marseille13288 cedex 9 France Physics Department CSMB Adlershof Humboldt-Universität zu Berlin Berlin12489 Germany Università degli Studi di Palermo Dipartimento di Fisica e Chimica—Emilio Segrè PalermoI-90123 Italy Institute for Theoretical Physics University of Hamburg Notkestraße 9-11 Hamburg22607 Germany The Hamburg Centre for Ultrafast Imaging Hamburg Germany Fritz Haber Institute Max Planck Society Faradayweg 4-6 Berlin14195 Germany Institut für Optik und Atomare Physik Technische Universität Berlin Straße des 17 Juni 135 Berlin10623 Germany Max Planck Institute for the Structure and Dynamics of Matter Hamburg Germany School of Mathematics and Physics Queen’s University Belfast University Road BelfastBT7 1NN United Kingdom Max Planck Institute for the Structure and Dynamics of Matter Center for Free Electron Laser Science Hamburg22761 Germany Department of Applied Physics and Science Education Eindhoven University of Technology Eindhoven Netherlands Technische Universität Braunschweig Institut für Mathematische Physik Mendelssohnstr. 3 Braunschweig38106 Germany Institut für Theorie der Statistischen Physik RWTH Aachen University JARA – Fundamentals of Future Information Technology Aachen52056 Germany Max Planck Institute for the Structure and Dynamics of Matter Center for Free Electron Laser Science Hamburg22761 Germany Department of Physics Technical University of Denmark Kgs Lyngby2800 Denmark Max Planck Institute for the Structure and Dynamics of Matter Center for Free-Electron Laser Science Luruper Chaussee 149 Hamburg22761 Germany Schulich Fac

The exploration of ultrafast phenomena is a frontier of condensed matter research, where the interplay of theory, computation, and experiment is unveiling new opportunities for understanding and engineering quantum materials. With the advent of advanced experimental techniques and computational tools, it has become possible to probe and manipulate nonequilibrium processes at unprecedented temporal and spatial resolutions, providing insights into the dynamical behavior of matter under extreme conditions. These capabilities have the potential to revolutionize fields ranging from optoelectronics and quantum information to catalysis and energy storage. This Roadmap captures the collective progress and vision of leading researchers, addressing challenges and opportunities across key areas of ultrafast science. Contributions in this Roadmap span the development of ab initio methods for time-resolved spectroscopy, the dynamics of driven correlated systems, the engineering of materials in optical cavities, and the adoption of FAIR principles for data sharing and analysis. Together, these efforts highlight the interdisciplinary nature of ultrafast research and its reliance on cutting-edge methodologies, including quantum electrodynamical density-functional theory, correlated electronic structure methods, nonequilibrium Green’s function approaches, quantum and ab initio simulations. Copyright © 2025, The Authors. All rights reserved.

关键词： Time-resolved spectroscopy

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Efficient MedSAMs: Segment Anything in Medical Images on Laptop

arXiv

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arXiv 2024年

作者： Ma, Jun Li, Feifei Kim, Sumin Asakereh, Reza Le, Bao-Hiep Nguyen-Vu, Dang-Khoa Pfefferle, Alexander Wei, Muxin Gao, Ruochen Lyu, Donghang Yang, Songxiao Purucker, Lennart Marinov, Zdravko Staring, Marius Lu, Haisheng Dao, Thuy Thanh Ye, Xincheng Li, Zhi Brugnara, Gianluca Vollmuth, Philipp Foltyn-Dumitru, Martha Cho, Jaeyoung Mahmutoglu, Mustafa Ahmed Bendszus, Martin Pflüger, Irada Rastogi, Aditya Ni, Dong Yang, Xin Zhou, Guang-Quan Wang, Kaini Heller, Nicholas Papanikolopoulos, Nikolaos Weight, Christopher Tong, Yubing Udupa, Jayaram K. Patrick, Cahill J. Wang, Yaqi Zhang, Yifan Contijoch, Francisco McVeigh, Elliot Ye, Xin He, Shucheng Haase, Robert Pinetz, Thomas Radbruch, Alexander Krause, Inga Kobler, Erich He, Jian Tang, Yucheng Yang, Haichun Huo, Yuankai Luo, Gongning Kushibar, Kaisar Amankulov, Jandos Toleshbayev, Dias Mukhamejan, Amangeldi Egger, Jan Pepe, Antonio Gsaxner, Christina Luijten, Gijs Fujita, Shohei Kikuchi, Tomohiro Wiestler, Benedikt Kirschke, Jan S. de la Rosa, Ezequiel Bolelli, Federico Lumetti, Luca Grana, Costantino Xie, Kunpeng Wu, Guomin Puladi, Behrus Martín-Isla, Carlos Lekadir, Karim Campello, Victor M. Shao, Wei Brisbane, Wayne Jiang, Hongxu Wei, Hao Yuan, Wu Li, Shuangle Zhou, Yuyin Wang, Bo AI Collaborative Centre University Health Network Department of Laboratory Medicine and Pathobiology University of Toronto Vector Institute Toronto Canada Peter Munk Cardiac Centre University Health Network Toronto Canada Toronto General Hospital Research Institute University Health Network Department of Computer Science University of Toronto University Health Network Vector Institute Toronto Canada University of Science Vietnam National University Ho Chi Minh City Viet Nam Institute of Computer Science University of Freiburg Freiburg Germany School of Medicine and Health Harbin Institute of Technology Harbin China Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Department of System and Control Engineering School of Engineering Institute of Science Tokyo Formerly Tokyo Institute of Technology Tokyo Japan Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia School of Cyberspace Hangzhou Dianzi University Hangzhou China Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Radiology and Clinical AI Department of Neuroradiology University Hospital Bonn Germany School of Biomedical Engineering Shenzhen University Shenzhen China School of Biological Science and Medical Engineering Southeast University Nanjing China Department of Urology Cleveland Clinic Cleveland United States Department of Computer Science University of Minnesota Minneapolis United St

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice. In this work, we organized the first international competition dedicated to promptable medical image segmentation, featuring a large-scale dataset spanning nine common imaging modalities from over 20 different institutions. The top teams developed lightweight segmentation foundation models and implemented an efficient inference pipeline that substantially reduced computational requirements while maintaining state-of-the-art segmentation accuracy. Moreover, the post-challenge phase advanced the algorithms through the design of performance booster and reproducibility tasks, resulting in improved algorithms and validated reproducibility of the winning solution. Furthermore, the best-performing algorithms have been incorporated into the open-source software with a user-friendly interface to facilitate clinical adoption. The data and code are publicly available to foster the further development of medical image segmentation foundation models and pave the way for impactful real-world applications. © 2024, CC BY-NC-SA.

关键词： Open source software

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Why is the Winner the Best?

Why is the Winner the Best?

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： M. Eisenmann A. Reinke V. Weru M. D. Tizabi F. Isensee T. J. Adler S. Ali V. Andrearczyk M. Aubreville U. Baid S. Bakas N. Balu S. Bano J. Bernal S. Bodenstedt A. Casella V. Cheplygina M. Daum M. De Bruijne A. Depeursinge R. Dorent J. Egger D. G. Ellis S. Engelhardt M. Ganz N. Ghatwary G. Girard P. Godau A. Gupta L. Hansen K. Harada M. Heinrich N. Heller A. Hering A. Huaulmé P. Jannin A. E. Kavur O. Kodym M. Kozubek J. Li H. Li J. Ma C. Martín-Isla B. Menze A. Noble V. Oreiller N. Padoy S. Pati K. Payette T. Rädsch J. Rafael-Patiño V. Singh Bawa S. Speidel C. H. Sudre K. Van Wijnen M. Wagner D. Wei A. Yamlahi M. H. Yap C. Yuan M. Zenk A. Zia D. Zimmerer D. Aydogan B. Bhattarai L. Bloch R. Brüngel J. Cho C. Choi Q. Dou I. Ezhov C. M. Friedrich C. Fuller R. R. Gaire A. Galdran Á. García Faura M. Grammatikopoulou S. Hong M. Jahanifar I. Jang A. Kadkhodamohammadi I. Kang F. Kofler S. Kondo H. Kuijf M. Li M. Luu T. Martinčič P. Morais M. A. Naser B. Oliveira D. Owen S. Pang J. Park S. Park S. Płotka E. Puybareau N. Rajpoot K. Ryu N. Saeed A. Shephard P. Shi D. Štepec R. Subedi G. Tochon H. R. Torres H. Urien J. L. Vilaça K. A. Wahid H. Wang J. Wang L. Wang X. Wang B. Wiestler M. Wodzinski F. Xia J. Xie Z. Xiong S. Yang Y. Yang Z. Zhao K. Maier-Hein P. F. Jäger A. Kopp-Schneider L. Maier-Hein Division of Intelligent Medical Systems German Cancer Research Center (DKFZ) Heidelberg Germany Helmholtz Imaging German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Biostatistics German Cancer Research Center (DKFZ) Heidelberg Germany Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Engineering and Physical Sciences School of Computing University of Leeds Leeds UK Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Sierre Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Lausanne Switzerland Technische Hochschule Ingolstadt Ingolstadt Germany Center for Artificial Intelligence and Data Science for Integrated Diagnostics (AI2D) and Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology University of Washington Seattle WA USA Department of Computer Science Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) University College London London UK Universitat Autònoma de Barcelona & Computer Vision Center Barcelona Spain Division of Translational Surgical Oncology National Center for Tumor Diseases (NCT/UCC) Dresden Dresden Germany Department of Advanced Robotics Istituto Italiano di Tecnologia Italy Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy IT University of Copenhagen Copenhagen Denmark Department of General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg Germany Department of Radiology and Nuc

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multicenter study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), image preprocessing (97%), data curation (79%), and post-processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work.

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Changing life expectancy in European countries 1990–2021: a subanalysis of causes and risk factors from the Global Burden of Disease Study 2021

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The Lancet Public Health 2025年第3期10卷 e172-e188页

作者： Steel, Nicholas Bauer-Staeb, Clarissa Maria Mercedes Ford, John A. Abbafati, Cristiana Abdalla, Mohammed Altigani Abdelkader, Atef Abdi, Parsa Zuñiga, Roberto Ariel Abeldaño Abiodun, Olugbenga Olusola Abolhassani, Hassan Abu-Gharbieh, Eman Abukhadijah, Hana J. Abu-Zaid, Ahmed Addo, Isaac Yeboah Addolorato, Giovanni Adekanmbi, Victor Adetunji, Juliana Bunmi Adeyeoluwa, Temitayo Esther Agardh, Emilie E. Agyemang-Duah, Williams Ahmad, Danish Ahmed, Ayman Ahmed, Syed Anees Akinosoglou, Karolina Akkaif, Mohammed Ahmed Al Awaidy, Salah Al Hasan, Syed Mahfuz Al Zaabi, Omar Ali Mohammed Aldridge, Robert W. Algammal, Abdelazeem M. Al-Gheethi, Adel Ali Saeed Ali, Abid Ali, Mohammed Usman Ali, Syed Shujait Ali, Waad Alicandro, Gianfranco Alif, Sheikh Mohammad Al-Jumaily, Adel Allebeck, Peter Alrawashdeh, Ahmad Al-Rifai, Rami H. Alsabri, Mohammed A. Alshahrani, Najim Z. Aluh, Deborah Oyine Al-Wardat, Mohammad Al-Zyoud, Walid A. Amiri, Sohrab Anderlini, Deanna Andrei, Catalina Liliana Anil, Abhishek Anvari, Saeid Anyasodor, Anayochukwu Edward Appiah, Seth Christopher Yaw Aquilano, Michele Arabloo, Jalal Arafat, Mosab Areda, Demelash Aremu, Abdulfatai Armani, Keivan Armocida, Benedetta Ärnlöv, Johan Asaduzzaman, Muhammad Astell-Burt, Thomas Aujayeb, Avinash Ausloos, Marcel Azadnajafabad, Sina Aziz, Shahkaar Azzam, Ahmed Y. Babu, Giridhara Rathnaiah Badache, Andreea Corina Badiye, Ashish D. Bahramian, Saeed Baig, Atif Amin Baker, Jennifer L. Bansal, Hansi Bärnighausen, Till Winfried Barone, Mark Thomaz Ugliara Barrow, Amadou Barteit, Sandra Bashir, Shahid Bashiru, Hameed Akande Basso, João Diogo Bastan, Mohammad-Mahdi Basu, Sanjay Batra, Kavita Bauckneht, Matteo Baune, Bernhard T. Beghi, Massimiliano Beiranvand, Maryam Béjot, Yannick Bell, Michelle L. Bello, Olorunjuwon Omolaja Belo, Luis Beloukas, Apostolos Beneke, Alice A. Bettencourt, Paulo J.G. Bhagavathula, Akshaya Srikanth Bhala, Neeraj Bhaskar, Sonu Bisulli, Francesca Bjørge, Tone Bodunrin, Aadam Olalekan Carvajal, Alejandro Botero Bouaoud, Souad Brayne, Carol Brenner, H Department of Primary Care and Public Health University of East Anglia Norwich United Kingdom Office for Health Improvement and Disparities Department of Health and Social Care London United Kingdom Department of Legal and Economic Studies La Sapienza University Rome Italy Rome Italy Hull York Medical School University of Hull Hull United Kingdom Department of Mathematics and Sciences Ajman University Ajman United Arab Emirates Department of Medicine Memorial University St. John's NL Canada Postgraduate Department University of Sierra Sur Miahuatlan de Porfirio Diaz Mexico Yhteiskuntadatatieteen keskus (Centre for Social Data Science) Helsinki Finland Department of Internal Medicine Federal Medical Centre Abuja Nigeria Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Medical Biochemistry and Biophysics Karolinska Institutet (Karolinska Institute) Stockholm Sweden Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Department of Biopharmaceutics and Clinical Pharmacy University of Jordan Amman Jordan Medical Research Center Hamad Medical Corporation Doha Qatar Department of Biochemistry and Molecular Medicine Alfaisal University Riyadh Saudi Arabia College of Graduate Health Sciences University of Tennessee Memphis TN United States School of Medicine Sydney NSW Australia Centre for Social Research in Health University of New South Wales Sydney NSW Australia Internal Medicine and Alcohol Related Disease Unit Fondazione Policlinico Universitario A. Gemelli IRCCS Rome Italy Department of Medical and Surgical Sciences Università Cattolica di Roma (Catholic University of Rome) Rome Italy Department of Obstetrics and Gynecology University of Texas Medical Branch Galveston TX United States Department of Biochemistry Osun State University Osogbo Nigeria Department of Pharmacology and Therapeutics University of Medical Sciences Ondo Ondo Nigeria Department of Veteri

Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factors and cause-specific death rates in different European countries related to changes in life expectancy in those countries before and during the COVID-19 pandemic. Methods: We used data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to compare changes in life expectancy at birth, causes of death, and population exposure to risk factors in 16 European Economic Area countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, and Sweden) and the four UK nations (England, Northern Ireland, Scotland, and Wales) for three time periods: 1990–2011, 2011–19, and 2019–21. Changes in life expectancy and causes of death were estimated with an established life expectancy cause-specific decomposition method, and compared with summary exposure values of risk factors for the major causes of death influencing life expectancy. Findings: All countries showed mean annual improvements in life expectancy in both 1990–2011 (overall mean 0·23 years [95% uncertainty interval [UI] 0·23 to 0·24]) and 2011–19 (overall mean 0·15 years [0·13 to 0·16]). The rate of improvement was lower in 2011–19 than in 1990–2011 in all countries except for Norway, where the mean annual increase in life expectancy rose from 0·21 years (95% UI 0·20 to 0·22) in 1990–2011 to 0·23 years (0·21 to 0·26) in 2011–19 (difference of 0·03 years). In other countries, the difference in mean annual improvement between these periods ranged from –0·01 years in Iceland (0·19 years [95% UI 0·16 to 0·21] vs 0·18 years [0·09 to 0·26]), to –0·18 years in England (0·25 years [0·24 to 0·25] vs 0·07 years [0·06 to 0·08]). In 2019–21, there was an overall decrease in mean annual life expectancy a

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Preface

ICMLCA 2021 - 2nd International Conference on Machine Learni...

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ICMLCA 2021 - 2nd International Conference on Machine Learning and Computer Application 2021年 iii页

作者： Ning, Xiansheng Feng, Yongxin Zhang, Wenbo Yue, Mingkai Du, Ke-Lin Huang, Shutao Zhou, Fang Ba, Shuhong Fu, Chong Shui, Penglang Xu, Shuwen Wu, Sheng Wang, Shushan Du, Zhonghua Gao, Zhijun Fan, Chunlong Li, Yufeng Wang, Yupeng Liu, Qingli Yu, Jingang Yin, Zhenyu Zhang, Deyu Gao, Hongwei Wen, Feng Guo, Cean Hao, Yongping Chan, Yung-Kuan Pavlovich, Vinogradov Gennady Kirpichnikova, Irina Qian, Zhihong Ivanov, Dmitriy V. Zhou, Xueguan Nezamabadi-Pour, Hossein Yang, Qing Zhang, Yongtang Liao, Haibin Huang, Ying Srinivasan, Kathiravan Xu, Zhenghua Pachori, Ram Bilas Zhang, Jialu AlShawabkeh, Mahmoud Guo, Chengjun Chaugule, Archana Ajit Lima, Alberto Sampaio Liu, Huayong Vidal, Jorge Maestre Alrshah, Mohamed A. Ghafoor, Kayhan Zrar Kubicek, Jan Chaugule, Archana Ajit Rodríguez-Pérez, Miguel Kumar, Gulshan Nasri, Mehdi Borrego, Carlos Persico, Valerio Wagh, Sanjeev Yan, Wenjun Yang, Li Yang, Dawei Xing, Yongkang Yang, Huadong Shang, Chengguo Chang, Xingong Shi, Hongbo Li, Aijun Feng, Liping Lv, Yali Liang, Minfu Wang, Kaixuan Bai, Zengliang Liang, Anhui Nan, Zhihong Ji, Suqin Chang, Liwei Zhou, Hongbin Yao, Chunli Cao, Guodong Zhang, Juling School of Information Science and Engineering Shenyang Ligong University China School of Equipment Engineering Shenyang Ligong University China Concordia University Canada School of Automotive and Transportation Shenyang Ligong University China School of Information Science and Engineering Shenyang Ligong University China School of Equipment Engineering Shenyang Ligong University China Northeastern University China Xidian University China Beijing University of Posts and Telecommunications China Beijing Institute of Technology China Nanjing University of Science & Technology China Shenyang Jianzhu University China Shenyang Aerospace University China Dalian University China Shenyang Institute of Computing Technology Chinese Academy of Sciences China Shenyang Ligong University China National Chun Hsing University Taiwan Department of Informatics and Applied Mathematics Russia South Ural State University Russia Jilin University China Samara State University of Transport Russia Naval Universit of Engineering China Shahid Bahonar University of Kermanto Iran Central China Normal University China Guangdong Neusoft Institute China Hubei University of Science and Technology China Liuzhou Railway Vocational Technical College China Vellore Institute of Technology India Hebei University of Technology China Indian Institute of Technology Indore India Xiangnan University China Guangxi Normal University for Nationalities China UESTC China Pimpri-Chinchwad College of Engineering & Research India Federal University of Ceará Brazil Complutense University of Madrid Spain Universiti Putra Malaysia Malaysia Shanghai Jiao Tong University China VŠB - Technical University of Ostrava Cuw Pimpri-Chinchwad College of Engineering & Research Ravet Pune India University of Vigo Spain Division of Research and Development India Islamic Azad University Iran Departament Enginyeria of Information Comunicacions Autonomous University of Barcelona Spain Opportunistic Networks United States Univers

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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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