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Mechanism of friction-induced chemical reaction high-efficient polishing single crystal 4H-SiC wafer using pure iron

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Tribology International 2024年 193卷

作者： Wu, Min Huang, Hui Wu, Yueqin Xu, Zhiteng Li, Tukun Macleod, Iain Wu, Xiaolei National and Local Joint Engineering Research Center for Intelligent Manufacturing Technology of Brittle Material Products Huaqiao University Xiamen 361021 China Institute of Manufacturing Engineering Huaqiao University Xiamen 361021 China State Key Laboratory of High-Performance Tools Zhengzhou 450001 China EPSRC Future Advanced Metrology Hub Centre for Precision Technologies School of Computing and Engineering University of Huddersfield Huddersfield HD1 3DH United Kingdom IMA Ltd 29 Clay Lane Cheshire WA15 8PJ United Kingdom Zhengzhou Research Institute for Abrasives & Grinding Co. Ltd Zhengzhou 450001 China

This paper proposes a novel method for friction-induced chemical reaction machining of single-crystal 4H-SiC wafers using pure iron. Material Removal Rate (MRR) and surface quality of single-crystal 4H-SiC were studied, and the results demonstrate that both high surface quality and high MRR (Ra: 2.2 nm, MRR: 375 nm/min) were obtained. The mechanism of material removal during friction was investigated by examining the critical roles of friction speed. Solid-state chemical reactions between metal and SiC surfaces can be induced by friction, and the subsequent removal of reactants, resulting in a near-damage-free machined surface. A removal mechanism model of friction was established, which reveals that both the rates of solid-state reaction and reactant removal significantly impact the final removal rate of friction. © 2024 Elsevier Ltd

关键词： Friction-induced chemical reaction Pure iron Removal mechanism SiC

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Research on Computer Network Technology System Based on Artificial Intelligence Technology

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Journal of Physics: Conference Series 2021年第4期1802卷

作者： Jinling Yao Jie Liu College of Electronic Information and Engineering Tianjin Vocational institute Tianjin 300000 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin 300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology) Tianjin 300384 China

This article introduces computer network intrusion detection systems and their classification based on artificial intelligence technology, and points out the challenges that intrusion detection systems (IDS) are facing in wireless sensor computer networks. On this basis, a hierarchical multi-layer wireless sensor network intrusion detection system and technology based on artificial intelligence technology Agent is proposed, and its network structure, working principle and performance are analysed.

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Finite Element Analysis of Absorbable Sheath to Prevent Stress Shielding of Tibial Interlocking Intramedullary Nail

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IOP Conference Series: Materials Science and Engineering 2017年第1期224卷

作者： Yansheng Dong Yongqing Wang Limin Dong Peng Jia Fengcheng Lu Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System School of Mechanical Engineering Tianjin University of Technology Tianjin 300384 China Dept of Orthopaedics the Fourth Central Hospital of Tianjin Tianjin 300140 China Tianjin University of Traditional Chinese Medicine Tianjin 300314 China Dept of Orthopaedics Tianjin Medical University Tianjin 300314 China

The nail with absorbable sheath (AS nail) is designed to reduce the stress shielding effect of internal fixation with interlocking intramedullary nail. In order to verify its feasibility, two types of the finite element models of internal fixation of tibia with the AS nail and the common metal nail (CM nail) are established using the Softwares of Mimics, Geomagic, SolidWorks and ANSYS according to the CT scanning data of tibia. The result of the finite element analysis shows that the AS nail has great advantages compared with the CM nail in reducing the stress shielding effect in different periods of fracture healing. The conclusion is that the AS nail can realize the static fixation to the dynamic fixation from the early to the later automatically to shorten the time of fracture healing, which also provides a new technique to the interlocking intramedullary nail.

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong Institute of Materials Research and Engineering (IMRE) Agency for Science Technology and Research (A*STAR) 2 Fusionopolis Way #08-03 Innovis Singapore 138634 Republic of Singapore；Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States；Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden；Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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Correction to: A method of VR‑EEG scene cognitive rehabilitation training

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Health information science and systems 2021年第1期9卷 7页

作者： Wenjun Tan Yang Xu Pan Liu Chunyan Liu Yujin Li Yanrui Du Chao Chen Yuping Wang Yanchun Zhang Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang 110189 China. Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou 510006 China. Department of Neurology Xuanwu Hospital Capital Medical University Beijing 100053 China. Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology Tianjin 300384 China. Institute for Sustainable Industries and Liveable Cities Victoria University Melbourne VIC 8001 Australia.

[This corrects the article DOI: 10.1007/s13755-020-00132-6.].

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The association for the advancement of artificial intelligence 2020 workshop program

The association for the advancement of artificial intelligen...

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作者： Bang, Grace Barash, Guy Bea, Ryan Cali, Jacques Castillo-Effen, Mauricio Chen, Xin Cynthia Chhaya, Niyati Dhoopar, Rohan Dumancic, Sebastijan Espinoza, Huáscar Farchi, Eitan Fioretto, Ferdinando Fuentetaja, Raquel Galley, Michel Geib, Christopher Hernández-Orallo, José Huang, Xiaowei Keren, Sarah Kim, Seokhwan Jaidka, Kokil Liu, Xiaomo Lu, Tyler Ma, Zhiqiang Mallah, Richard McDermid, John Michalowski, Martin Mirsky, Reuth Héigeartaigh, Seán Ó. Ramachandran, Deepak Segovia-Aguas, Javier Shaban-Nejad, Arash Shehory, Onn Shwartz, Vered Srivastava, Siddharth Talamadupula, Kartik Tang, Jian Zhang, Dell Zhang, Jian S&P Global. Western Digital University of Southampton United Kingdom Blue Prism Group PLC Lockheed Martin's Advanced Technology Laboratories ArlingtonVA United States University of Hong Kong Hong Kong Adobe Research Google Research Katholieke Universiteit Leuven Belgium Commissariat à ĺÉnergie Atomique France IBM Research Department of Electrical Engineering and Computer Science Syracuse University United States Universidad Carlos III de Madrid Spain Microsoft Research AI SIFT LLC Universitat Politècnica de València Spain Leverhulme Centre for the Future of Intelligence United Kingdom Department of Computer Science University of Liverpool United Kingdom National University of Singapore Singapore Harvard School of Engineering and Applied Sciences in the of Fields of Multiagent Environment Design and Goal Recognition Design Amazon Alexa AI Future of Life Institute United States University of York Assuring Autonomy International Program United Kingdom University of Minnesota School of Nursing MinneapolisMN United States University of Texas at Austin AustinTX United States Institut de Robòtica i Informàtica Industrial Spanish Council for Scientific Research Technical University of Catalonia Spain Oak Ridge National Laboratory Center for Biomedical Informatics Department of Pediatrics University of Tennessee Health Science Center United States Bar Ilan University Israel University of Washington SeattleWA United States Autonomous Agents and Intelligent Robots lab of the School of Computing Informatics Decision Systems Arizona State University United States DiDi AI Labs School of Industrial and System Engineering Georgia Institute of Technology United States University of London United Kingdom Microsoft Azure

The Association for the Advancement of Artificial Intelligence 2020 Workshop Program included twenty-three workshops covering a wide range of topics in artificial intelligence. This report contains the required reports, which were submitted by most, but not all, of the workshop chairs. Copyright © 2020, Association for the Advancement of Artificial Intelligence. All rights reserved.

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Current progress in corrosion of multi principal element alloys

arXiv

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arXiv 2024年

作者： Ghorbani, M. Li, Z. Qiu, Y. Marcus, P. Scully, J.R. Gharbi, O. Luo, H. Gupta, R.K. Zeng, Z.R. Fraser, H.L. Taheri, M.L. Birbilis, N. Faculty of Science Engineering and the Built Environment Deakin University VIC Australia College of Engineering Computing and Cybernetics Australian National University ACT Australia Faculty of Materials Wuhan University of Science and Technology Wuhan China PSL University CNRS Chimie ParisTech Institut de Recherche de Chimie Paris Physical Chemistry of Surfaces Group Paris France Department of Materials Science and Engineering University of Virginia VA United States CNRS Sorbonne Université Laboratoire de Réactivité de Surface LRS Paris France National Materials Corrosion and Protection Data Center Institute for Advanced Materials and Technology University of Science and Technology Beijing Beijing China Department of Materials Science and Engineering North Carolina State University RaleighNC United States State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan University Changsha China Department of Materials Science and Engineering The Ohio State University ColumbusOH United States Department of Materials Science and Engineering Johns Hopkins University BaltimoreMD United States

Whilst multi-principal element alloys (MPEAs) remain a promising class of materials owing to several attractive mechanical properties, their corrosion performance is also unique. In this concise review, we present an emerging overview of some of the general features related to MPEA corrosion, following a decade of work in the field. This includes highlighting some of the key aspects related to the electrochemical phenomena in MPEA corrosion, and the relevant future works required for a holistic mechanistic understanding. In addition, a comprehensive database of the reported corrosion performance of MPEAs is presented – based on works reported to date. The database is assembled to also allow users to undertake machine learning or their own data analysis, with a parsed representation of alloy composition, test electrolyte, and corrosion related parameters. © 2024, CC BY-NC-ND.

关键词： Database systems

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I3−/I−Redox Reaction-mediated Organic Zinc-Air Batteries with Accelerated Kinetics and Long Shelf Lives

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Angewandte Chemie 2023年第26期135卷

作者： Mangwei Cui Ninggui Ma Hao Lei Youfa Liu Wei Ling Sheng Chen Jiaqi Wang Prof. Hongfei Li Zhaohui Li Prof. Jun Fan Prof. Yan Huang State Key Laboratory of Advanced Welding and Joining Sauvage Laboratory for Smart Materials Shenzhen Key Laboratory of Flexible Printed Electronics Technology School of Materials Science and Engineering Harbin Institute of Technology (Shenzhen) Shenzhen 518055 China Department of Materials Science and Engineering City University of Hong Kong 83 Tat Chee Avenue Kowloon Hong Kong 999077 China Key Laboratory of Radiation Physics and Technology of Ministry of Education Institute of Nuclear Science and Technology Sichuan University Chengdu 610064 China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen 518055 China Songshan Lake Materials Laboratory Dongguan 523808 China Shenzhen China Star Optoelectronic Semiconductor Display Technology Co. Ltd. Shenzhen 518055 China

The storage time of Zn-air batteries (ZABs) for practical implementation have been neglected long-lastingly. ZABs based on organic solvents promise long shelf lives but suffer from sluggish kinetics. Here, we report a longly storable ZAB with accelerated kinetics mediated by I 3 − /I − redox. In the charge process, the electrooxidation of Zn 5 (OH) 8 Cl 2 ⋅H 2 O is accelerated by I 3 − chemical oxidation. In the discharge process, I − adsorbed on the electrocatalyst changes the energy level of oxygen reduction reaction (ORR). Benefitting from these advantages, the prepared ZAB shows remarkably improved round-trip efficiency (56.03 % vs. 30.97 % without the mediator), and long-term cycling time (>2600 h) in ambient air without replacing any components or applying any protective treatment to Zn anode and electrocatalyst. After resting for 30 days without any protection, it can still directly discharge continuously for 32.5 h and charge/discharge very stably for 2200 h (440 cycles), which is evidently superior to aqueous ZABs (only 0/0.25 h, and 50/25 h (10/5 cycles) by mild/alkaline electrolyte replenishment). This study provides a strategy to solve both storage and sluggish kinetics issues that have been plaguing ZABs for centuries, opening up a new avenue to the industrial application of ZABs.

关键词： Iodine-Containing Reaction Kinetics Redox Mediators Storage Time Zn-Air Batteries

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Mapping global lake dynamics reveals the emerging roles of small lakes (October, 10.1038/s41467-022-33239-3, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1-12页

作者： Pi, Xuehui Luo, Qiuqi Feng, Lian Xu, Yang Tang, Jing Liang, Xiuyu Ma, Enze Cheng, Ran Fensholt, Rasmus Brandt, Martin Cai, Xiaobin Gibson, Luke Liu, Junguo Zheng, Chunmiao Li, Weifeng Bryan, Brett A. School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen China Department of Urban Planning and Design The University of Hong Kong Hong Kong SAR China Urban Systems Institute The University of Hong Kong Hong Kong SAR China Department of Geosciences and Natural Resource Management University of Copenhagen Copenhagen Denmark School of Water Conservancy North China University of Water Resources and Electric Power 450046 Zhengzhou China EIT Institute for Advanced Study Ningbo China Institute for Climate and Carbon Neutrality The University of Hong Kong Hong Kong SAR China Department of Biology University of Copenhagen Copenhagen Denmark Department of Physical Geography and Ecosystem Science Lund University Lund Sweden Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China Institute of Geodesy and Geophysics Chinese Academy of Sciences Wuhan China Centre for Integrative Ecology School of Life and Environmental Sciences Deakin University Burwood Victoria Australia

Lakes are important natural resources and carbon gas emitters and are undergoing rapid changes worldwide in response to climate change and human activities. A detailed global characterization of lakes and their long-term dynamics does not exist, which is however crucial for evaluating the associated impacts on water availability and carbon emissions. Here, we map 3.4 million lakes on a global scale, including their explicit maximum extents and probability-weighted area changes over the past four decades. From the beginning period (1984–1999) to the end (2010–2019), the lake area increased across all six continents analyzed, with a net change of +46,278 km2, and 56% of the expansion was attributed to reservoirs. Interestingly, although small lakes (<1 km2) accounted for just 15% of the global lake area, they dominated the variability in total lake size in half of the global inland lake regions. The identified lake area increase over time led to higher lacustrine carbon emissions, mostly attributed to small lakes. Our findings illustrate the emerging roles of small lakes in regulating not only local inland water variability, but also the global trends of surface water extent and carbon emissions.

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An Early Stage Researcher's Primer on Systems Medicine Terminology

Network and Systems Medicine

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Network and Systems Medicine 2021年第1期4卷 2-50页

作者： Zanin, Massimiliano Aitya, Nadim A.A. Basilio, José Baumbach, Jan Benis, Arriel Behera, Chandan K. Bucholc, Magda Castiglione, Filippo Chouvarda, Ioanna Comte, Blandine Dao, Tien-Tuan Ding, Xuemei Pujos-Guillot, Estelle Filipovic, Nenad Finn, David P. Glass, David H. Harel, Nissim Iesmantas, Tomas Ivanoska, Ilinka Joshi, Alok Boudjeltia, Karim Zouaoui Kaoui, Badr Kaur, Daman Maguire, Liam P. McClean, Paula L. McCombe, Niamh De Miranda, João Luís Moisescu, Mihnea Alexandru Pappalardo, Francesco Polster, Annikka Prasad, Girijesh Rozman, Damjana Sacala, Ioan Sanchez-Bornot, Jose M. Schmid, Johannes A. Sharp, Trevor Solé-Casals, Jordi Spiwok, Vojtěch Spyrou, George M. Stalidzans, Egils Stres, Blaa Sustersic, Tijana Symeonidis, Ioannis Tieri, Paolo Todd, Stephen Van Steen, Kristel Veneva, Milena Wang, Da-Hui Wang, Haiying Wang, Hui Watterson, Steven Wong-Lin, Kongfatt Yang, Su Zou, Xin Schmidt, Harald H.H.W. Centro de Tecnología Biomédica Universidad Politécnica de Madrid Madrid Spain Intelligent Systems Research Centre School of Computing Engineering and Intelligent Systems Ulster University Ulster United Kingdom Center for Physiology and Pharmacology Institute of Vascular Biology and Thrombosis Research Medical University of Vienna Vienna Austria TUM School of Life Sciences Weihenstephan Technical University of Munich Freising Germany Holon Israel CNR National Research Council IAC Institute for Applied Computing Rome Italy Lab of Computing Medical Informatics and Biomedical Imaging Technologies School of Medicine Aristotle University of Thessaloniki Thessaloniki Greece Université Clermont Auvergne INRAE UNH Plateforme d'Exploration du Métabolisme MetaboHUB Clermont Clermont-Ferrand France Université de Technologie de Compiègne Compiègne France Labex MS2T Control of Technological Systems-of-Systems CNRS and Université de Technologie de Compiègne Compiègne France Faculty of Engineering University of Kragujevac Kragujevac Serbia Kragujevac Serbia Steinbeis Advanced Risk Technologies Institute Doo Kragujevac Kragujevac Serbia Pharmacology and Therapeutics School of Medicine Galway Neuroscience Centre National University of Ireland Galway Ireland School of Computing Ulster University Ulster United Kingdom Holon Israel Department of Mathematics and Natural Sciences Kaunas University of Technology Kaunas Lithuania Faculty of Computer Science and Engineering Ss. Cyril and Methodius University Skopje Macedonia Medicine Faculty Université Libre de Bruxelles CHU de Charleroi Charleroi Belgium Northern Ireland Centre for Stratified Medicine Biomedical Sciences Research Institute Ulster University Ulster United Kingdom Escola Superior de Tecnologia e Gestão Instituto Politécnico de Portalegre Portalegre Portugal Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal Faculty of Automatic Control and Computers University Politehnica of B

Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields. Methods: In this review, we collect and explain more than100 terms related to Systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references. Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic. © Massimiliano Zanin et al., 2021;Published by Mary Ann Liebert, Inc. 2021.

关键词： Semantics

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