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Spatial Analysis of the Soil Carbon Sequestration Potential of Crop-residue Return in China Based on Model Simulation

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Journal of Resources and Ecology 2019年第2期10卷 184-195页

作者： CHEN Jinghua WANG Shaoqiang XU Xiyan SUN Leigang Key Laboratory of Ecosystem Network Observation and Modelling Institute of Geographic Sciences and Natural Resources Research Beijing 100101China College of Resources and Environment University of Chinese Academy of Sciences Beijing 100049 China School of Geography and Information Engineering China University of Geosciences Wuhan 430074 China Ecosystems Services and Management Program International Institute for Applied Systems Analysis Laxenburg A-2361 Austria Key Laboratory of Regional Climate-Environment for East Asia Institute of Atmospheric Physics Beijing 100029 China Hebei Engineering Research Center for Geographic Information Application Institute of Geographical Sciences Hebei Academy of SciencesShijiazhuang 050011 China

Crop-residue return is a recommended practice for soil and nutrient management and is important in soil organic carbon(SOC)sequestration and CO2 *** applied a process-based Environmental Policy Integrated Climate(EPIC)model to simulate the spatial pattern of topsoil organic carbon changes from 2001 to 2010under 4 crop-residue return scenarios in *** carbon loss(28.89 Tg yr–1)with all crop-residue removal(CR0%)was partly reduced by 22.38 Tg C yr–1 under the status quo CR30%(30% of crop-residue return).The topsoil in cropland of China would become a net carbon sink if the crop-residue return rate was increased from 30%to 50%,or even 75%.The national SOC sequestration potential of cropland was estimated to be 25.53 Tg C yr–1 in CR50%and 52.85 Tg C yr–1 in CR75%,but with high spatial variability across *** highest rate of SOC sequestration potential in density occurred in Northwest and North China while the lowest was in East *** in North China tended to have stronger regional SOC sequestration potential in *** the decade,the reduced CO2 emissions from enhanced topsoil carbon in CR50%and CR75% were equivalent to 1.4% and 2.9%of the total CO2 emissions from fossil fuels and cement production in China,*** conclusion,we recommend encouraging farmers to return crop-residue instead of burning in order to improve soil properties and alleviate atmospheric CO2 rises,especially in North China.

关键词： cropland crop-residue return soil carbon sequestration spatial pattern EPIC model

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Data quality measures and data cleansing for research information systems

arXiv

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arXiv 2019年

作者： Azeroual, Otmane Saake, Gunter Abuosba, Mohammad Berlin10117 Germany Otto-Von-Guericke University Magdeburg Department of Computer Science Institute for Technical and Business Information Systems Database Research Group P.O. Box 4120 Magdeburg39106 Germany University of Applied Sciences Htw Berlin Study Program Computational Science and Engineering Wilhelminenhofstrasse 75a Berlin12459 Germany

The collection, transfer and integration of research information into different research information systems can result in different data errors that can have a variety of negative effects on data quality. In order to detect errors at an early stage and treat them efficiently, it is necessary to determine the clean-up measures and the new techniques of data cleansing for quality improvement in research institutions. Thereby an adequate and reliable basis for decision-making using an RIS is provided, and confidence in a given dataset increased. In this paper, possible measures and the new techniques of data cleansing for improving and increasing the data quality in research information systems will be presented and how these are to be applied to the research information. Copyright © 2019, The Authors. All rights reserved.

关键词： Standardization

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A Note on Brake System of Train Set with Wheel Slide Protection System

A Note on Brake System of Train Set with Wheel Slide Protect...

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International Symposium on Soft Computing and Intelligent systems (SCIS)

作者： Yuya Kanazawa Yasunori Endo Shin-Ichi Nakazawa Daisuke Hijikata Master’s Program in Risk Engineering University of Tsukuba Ibaraki Japan Faculty of Engineering Information and Systems University of Tsukuba Ibaraki Japan Railway Technical Research Institute Tokyo Japan

ISBN: (纸本)9781538626344;9781538626337

In railways, brake control is the important factor on safety, punctuality and etc. However, the slip is likely to occur during brake control since the wheels and rails are made of metal. The slip makes the brake distance longer and the wheels damaged. The condition of the slip is mainly due to various factors such as the load, the state of the contact surface between the wheels and the rails, so the slip becomes a high uncertainty matter. Actual train uses the blending control of regenerative brake and pneumatic brake for wheel-slide-protection (WSP), but it can be more efficient to divide braking force because each of them performs independent. In this paper, we will construct a system that distributes braking force throughout the entire train set including not only pneumatic brake but also regenerative brake. And we will evaluate of the train set brake control with electro-pneumatic blending control.

关键词： Brakes Force Wheels Rail transportation Fuzzy logic Axles Rails

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Work in Progress – Establishing a Master program in Cyber Physical systems: Basic Findings and Future Perspectives

Work in Progress – Establishing a Master Program in Cyber P...

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International Conference on Promising Electronic Technologies (ICPET)

作者： Isam Ishaq Rashid Jayousi Salaheddin Odeh Ezzaldeen Edwan Asmaa Shaheen Mohamed Elnaggar Ahmed Elagha Samy Salamah Christian Weber Hasan Abu Rasheed Raimund Kirner Martina Doolan Hamidreza Ahmadian Roman Obermaisser Dhiah el Diehn I. Abou-Tair Ala Khalifeh Sahel Alouneh Zaid Alhalhouli Khalid Alemerien Faiez Gargouri Bassem Bouaziz Nadia Aloui Mohammad Saleh Computer Engineering and Science Departments Al-Quds University Jerusalem Palestine Engineering Program and Computer Department Palestine Technical College - Deir El-Balah Deir El-Balah Palestine Institute of Knowledge Based Systems & Knowledge Management University of Siegen Siegen Germany University of Siegen Siegen Germany School of Engineering and Computer Science University of Hertfordshire Hatfield UK Chair of Embedded Systems University of Siegen Siegen Germany German Jordanian University Amman Jordan School of Electrical Engineering and Information Technology German Jordanian University Amman Jordan Computer and Information Technology Department Tafila Technical University Tafila Jordan Higher Institute of Computer Science and Multimedia University of Sfax Sfax Tunisia Higher Institute of Applied Sciences and Technology of Mateur University of Carthage Mateure Tunisia KTH Royal Institute of Technology Stockholm Sweden

This paper reports on the basic findings and future perspectives of a capacity building project funded by the European Union. The International Master of Science on Cyber Physical systems (MS@CPS) is a collaborative project that aims to establish a master program in cyber physical systems (CPS). A consortium composed of nine partners proposed the project. Three partners are European and from Germany, UK and Sweden; while the other six partners are from the South Mediterranean region and include: Palestine, Jordan and Tunisia. The consortium is led by the University of Siegen in Germany who also manages the implementation of the work packages. CPS is an emerging engineering subject with significant economic and societal implications, which motivated the consortium to propose the establishment of a master program to offer educational and training opportunities at graduate level in the fields of CPS. In this paper, CPS as a field of study is presented with an emphasis on its importance, especially with regard to meeting local needs. A brief description of the project is presented in conjunction with the methodology for developing the courses and their learning outcomes.

关键词： Computer science Internet of Things Industries Knowledge engineering Embedded systems Europe Collaboration

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FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

arXiv

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arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

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The Japanese Vision for the Black Hole Explorer Mission

arXiv

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arXiv 2024年

作者： Akiyama, Kazunori Niinuma, Kotaro Hada, Kazuhiro Doi, Akihiro Hagiwara, Yoshiaki Higuchi, Aya E. Honma, Mareki Kawashima, Tomohisa Kolev, Dimitar Koyama, Shoko Masui, Sho Ohsuga, Ken Sano, Hidetoshi Takami, Hideki Tsunetoe, Yuh Uzawa, Yoshinori Akahori, Takuya Akiyama, Yuto Galison, Peter Hayashi, Takayuki J. Hirota, Tomoya Inoue, Makoto Iwata, Yuhei Johnson, Michael D. Kino, Motoki Kofuji, Yutaro Mizuno, Yosuke Moriyama, Kotaro Nagai, Hiroshi Nakamura, Kenta Notsu, Shota Ono, Fumie Oya, Yoko Oyama, Tomoaki Rana, Hannah Saida, Hiromi Saito, Ryo Saito, Yoshihiko Sasada, Mahito Sawada-Satoh, Satoko Takahashi, Mikiya M. Takamura, Mieko Tong, Edward Tsuji, Hiroyuki Yoshioka, Shogo Watanabe, Yoshimasa Massachusetts Institute of Technology Haystack Observatory WestfordMA01886 United States Mizusawa VLBI Observatory National Astronomical Observatory of Japan Iwate023-0861 Japan Black Hole Initiative Harvard University CambridgeMA02138 United States Graduate School of Sciences and Technology for Innovation Yamaguchi University Yamaguchi753-8512 Japan The Graduate School of Science Nagoya City University Aichi467-0001 Japan Institute of Space and Astronautical Science Japan Aerospace Exploration Agency Kanagawa252-5210 Japan Department of Space and Astronautical Science The Graduate University for Advanced Studies SOKENDAI Kanagawa229-8510 Japan Natural Science Laboratory Toyo University Tokyo112-8606 Japan Division of Science School of Science and Engineering Tokyo Denki University Saitama350-0394 Japan Department of Astronomy Graduate School of Science The University of Tokyo Tokyo113-0033 Japan Institute for Cosmic Ray Research The University of Tokyo Chiba277-8582 Japan Space Communication Systems Laboratory Wireless Networks Research Center National Institute of Information and Communications Technology Tokyo184-8795 Japan Graduate School of Science and Technology Niigata University Niigata950-2181 Japan Advanced Technology Center National Astronomical Observatory of Japan Tokyo181-8588 Japan Center for Computational Sciences University of Tsukuba Ibaraki305-8577 Japan Faculty of Engineering Gifu University Gifu501-1193 Japan Harvard University CambridgeMA02138 United States Azabu Junior and Senior High School Tokyo106-0046 Japan Astronomical Science Program The Graduate University for Advanced Studies SOKENDAI Tokyo181-8588 Japan Institute of Astronomy and Astrophysics Academia Sinica Taipei10617 Taiwan Center for Astrophysics Harvard & Smithsonian CambridgeMA02138 United States Kogakuin University of Technology & Engineering Academic Support Center 2665-1 Nakano Hachioji Tokyo192-0015 Japan Tsung-Dao Lee Institut

The Black Hole Explorer (BHEX) is a next-generation space very long baseline interferometry (VLBI) mission concept that will extend the ground-based millimeter/submillimeter arrays into space. The mission, closely aligned with the science priorities of the Japanese VLBI community, involves an active engagement of this community in the development of the mission, resulting in the formation of the Black Hole Explorer Japan Consortium. Here we present the current Japanese vision for the mission, ranging from scientific objectives to instrumentation. The Consortium anticipates a wide range of scientific investigations, from diverse black hole physics and astrophysics studied through the primary VLBI mode, to the molecular universe explored via a potential single-dish observation mode in the previously unexplored 50-70 GHz band that would make BHEX the highest-sensitivity explorer ever of molecular oxygen. A potential major contribution for the onboard instrument involves supplying essential elements for its high-sensitivity dual-band receiving system, which includes a broadband 300 GHz SIS mixer and a space-certified multi-stage 4.5K cryocooler akin to those used in the Hitomi and XRISM satellites by the Japan Aerospace Exploration Agency. Additionally, the Consortium explores enhancing and supporting BHEX operations through the use of millimeter/submillimeter facilities developed by the National Astronomical Observatory of Japan, coupled with a network of laser communication stations operated by the National Institute of information and Communication Technology. Copyright © 2024, The Authors. All rights reserved.

关键词： Radio astronomy

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Linearization of two-state thruster models

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Journal of Physics: Conference Series 2020年第1期1490卷

作者： Dieky Adzkiya Hendro Nurhadi Teguh Herlambang Department of Mathematics Institut Teknologi Sepuluh Nopember Indonesia Center of Excellence for Mechatronics and Industrial Automation Research Center Institut Teknologi Sepuluh Nopember Indonesia Department of Industrial Mechanical Engineering Institut Teknologi Sepuluh Nopember Indonesia Study Program of Information Systems Universitas Nahdlatul Ulama Surabaya Indonesia

A thruster is a device used for station keeping, attitude control, in the reaction control system, or long-duration, low-thrust acceleration. Thruster is one of the main components in autonomous surface vehicle. In th...

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Proteomics Standards Initiative's ProForma 2.0: Unifying the Encoding of Proteoforms and Peptidoforms

arXiv

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arXiv 2021年

作者： LeDuc, Richard D. Deutsch, Eric W. Binz, Pierre-Alain Fellers, Ryan T. Cesnik, Anthony J. Klein, Joshua A. Van Den Bossche, Tim Gabriels, Ralf Yalavarthi, Arshika Perez-Riverol, Yasset Carver, Jeremy Bittremieux, Wout Kawano, Shin Pullman, Benjamin Bandeira, Nuno Kelleher, Neil L. Thomas, Paul M. Vizcaíno, Juan Antonio National Resource for Translational and Developmental Proteomics Northwestern University EvanstonIL60611 United States Institute for Systems Biology SeattleWA98109 United States Clinical Chemistry Service Lausanne University Hospital Lausanne1011 Switzerland Department of Genetics Stanford University StanfordCA94305 United States Chan Zuckerberg Biohub 499 Illinois St San FranciscoCA94158 United States SciLifeLab School of Engineering Sciences in Chemistry Biotechnology and Health KTH-Royal Institute of Technology Stockholm 113 51 SolnaSE-171 21 Sweden Program for Bioinformatics Boston University BostonMA02215 United States VIB-UGent Center for Medical Biotechnology VIB Technologiepark 75-FSVM II Ghent9052 Belgium Department of Biomolecular Medicine Faculty of Medicine and Health Sciences Ghent University Ghent9000 Belgium Cambridge HinxtonCB10 1SD United Kingdom La Jolla CA92093 United States La Jolla CA92093 United States La Jolla CA92093 United States Toyama University of International Studies Toyama Higashikuromaki 6 5-1 Toyama930-1292 Japan Database Center for Life Science Joint Support-Center for Data Science Research Research Organization of Information and Systems Chiba Kashiwa277-0871 Japan

It is important for the proteomics community to have a standardized manner to represent all possible variations of a protein or peptide primary sequence, including natural, chemicallyinduced and artifactualmodifications. The Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) in collaboration with several members of the Consortium for Top-Down Proteomics (CTDP) has developed a standard notation called ProForma 2.0, which is a substantial extension of the original ProForma notation developed by the CTDP. ProForma 2.0 aims to unify the representation of proteoforms and peptidoforms. ProForma 2.0 supports use cases needed for bottom-up and middle-/top-down proteomics approaches and allows the encoding of highly modified proteins and peptides using a humanand machine-readable string. ProForma 2.0 can be used to represent protein modifications in a specified or ambiguous location, designated by mass shifts, chemical formulas, or controlled vocabulary terms, including cross-links (natural and chemical), and atomic isotopes. Notational conventions are based on public controlled vocabularies and ontologies. The most up-to-date full specification document and information about software implementations are available at http://***/proforma. © 2021, CC0.

关键词： Mass spectrometry

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用于糖尿病培训的大型语言模型:一项前瞻性研究（英文）

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Science Bulletin 2025年第6期 934-942页

作者：李灏萱江泽铧管洲榆包玉倩刘月星胡婷婷李佳佳刘茹涵吴量程棣纪宏伟王勇王亚星 Carol Y.Cheung 郑颖丰王继红李震吴卫兵 Cynthia Ciwei Lim Yong Mong Bee Hong Chang Tan Elif I.Ekinci David C.Klonoff Justin B.Echouffo-Tcheugui Nestoras Mathioudakis Leonor Corsino Rafael Simó Charumathi Sabanayagam Gavin Siew Wei Tan 程景煜黄天荫李华婷蔡淳毛丽娟 Lee-Ling Lim 覃宇宗盛斌贾伟平 Shanghai University of Sport School of Clinical Medicine Beijing Tsinghua Changgung Hospital Tsinghua Medicine Tsinghua University Beijing Visual Science and Translational Eye Research Institute(BERI) Tsinghua Medicine Tsinghua University Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Department of Endocrinology and Metabolism Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Diabetes Institute Shanghai Clinical Center for Diabetes MoE Key Lab of Artificial Intelligence Artificial Intelligence Institute Shanghai Jiao Tong University Department of Cardiology the Affiliated Hospital of Qingdao University CEMS NCMIS HCMS MADIS Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematics University of Chinese Academy of Sciences Chinese Academy of Sciences Key Laboratory of Systems Health Science of Zhejiang Province School of Life Science Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Beijing Institute of Ophthalmology Beijing Tongren Hospital Capital Medical University Beijing Ophthalmology and Visual Sciences Key Laboratory Department of Ophthalmology and Visual Sciences The Chinese University of Hong Kong State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual ScienceGuangdong Provincial Clinical Research Center for Ocular Diseases Department of Renal Medicine Singapore General Hospital Sing Health-Duke Academic Medical Centre Department of Endocrinology Singapore General Hospital Department of Endocrinology Austin Health Department of Medicine The University of Melbourne(Austin Health) Australian Centre for Accelerating Diabetes Innovations(ACADI) The Univ

Diabetes poses a considerable global health challenge, with varying levels of diabetes knowledge among healthcare professionals, highlighting the importance of diabetes training. Large Language Models(LLMs)provide new insights into diabetes training, but their performance in diabetes-related queries remains uncertain, especially outside the English language like Chinese. We first evaluated the performance of ten LLMs: Chat GPT-3.5, Chat GPT-4.0, Google Bard, Lla MA-7B, Lla MA2-7B, Baidu ERNIE Bot, Ali Tongyi Qianwen, Med GPT, Huatuo GPT, and Chinese Lla MA2-7B on diabetes-related queries, based on the Chinese National Certificate Examination for Primary Diabetes Care in China(NCE-CPDC) and the English Specialty Certificate Examination in Endocrinology and Diabetes of Membership of the Royal College of Physicians of the United Kingdom. Second, we assessed the training of primary care physicians(PCPs) without and with the assistance of Chat GPT-4.0 in the NCE-CPDC examination to ascertain the reliability of LLMs as medical assistants. We found that Chat GPT-4.0 outperformed other LLMs in the English examination, achieving a passing accuracy of 62.50%, which was significantly higher than that of Google Bard, Lla MA-7B, and Lla MA2-7B. For the NCE-CPFC examination, Chat GPT-4.0, Ali Tongyi Qianwen, Baidu ERNIE Bot, Google Bard, Med GPT, and Chat GPT-3.5 successfully passed, whereas Lla MA2-7B, Huatuo GPT,Chinese LLa MA2-7B, and Lla MA-7B failed. Chat GPT-4.0(84.82%) surpassed all PCPs and assisted most PCPs in the NCE-CPDC examination(improving by 1%–6.13%). In summary, LLMs demonstrated outstanding competence for diabetes-related questions in both the Chinese and English language, and hold great potential to assist future diabetes training for physicians globally.

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Willingness to pay for flood insurance: a case study in Phang Khon, Sakon Nakhon Province, Thailand

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IOP Conference Series: Earth and Environmental Science 2020年第1期612卷

作者： S Paopid J Tang N Leelawat Risk and Disaster Management Program Graduate School Chulalongkorn University Phayathai Road Pathumwan Bangkok 10330 Thailand International School of Engineering Faculty of Engineering Chulalongkorn University Phayathai Road Pathumwan Bangkok 10330 Thailand Disaster and Risk Management Information Systems Research Group Chulalongkorn University Phayathai Road Pathumwan Bangkok 10330 Thailand Department of Industrial Engineering Faculty of Engineering Chulalongkorn University Phayathai Road Pathumwan Bangkok 10330 Thailand

Long droughts and floods can reduce agricultural productivity and negatively impact upon businesses in the agriculture and food industries. The prevention and response to floods require both public and private efforts (e.g., 'Pay for Flood' insurance) for utmost effectiveness. The purpose of this study was to determine the potential factors that influence the people of Phang Khon District, near the Nam Un Dam, in paying flood insurance. The regression results showed that the height and duration of flooding, house price, and flood damage, were all key factors that triggered the willingness to pay flood insurance. In contrast, having a house with stairs decreased the likelihood of paying insurance. Our research suggested that 12.69 -19.04 USD/month is a commonly accepted flood insurance premium in Thailand. These findings can guide governments and insurance providers and companies towards improving their flood insurance practices.

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