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arXiv 2020年

作者： Liu, Zhu Ciais, Philippe Deng, Zhu Lei, Ruixue Davis, Steven J. Feng, Sha Zheng, Bo Cui, Duo Dou, Xinyu He, Pan Zhu, Biqing Lu, Chenxi Ke, Piyu Sun, Taochun Wang, Yuan Yue, Xu Wang, Yilong Lei, Yadong Zhou, Hao Cai, Zhaonan Wu, Yuhui Guo, Runtao Han, Tingxuan Xue, Jinjun Boucher, Olivier Boucher, Eulalie Chevallier, Frederic Wei, Yimin Zhong, Haiwang Kang, Chongqing Zhang, Ning Chen, Bin Xi, Fengming Marie, François Zhang, Qiang Guan, Dabo Gong, Peng Kammen, Daniel M. He, Kebin Schellnhuber, Hans Joachim Department of EarthSystem Science Tsinghua University Beijing100084 China Laboratoire des Sciences du Climate et de l'Environnement LSCE Orme de Merisiers Gif-sur-Yvette91191 France Department of Meteorology andAtmospheric Science The Pennsylvania State University University ParkPA16802 United States Department of Earth System Science University of California Irvine 3232 Croul Hall IrvineCA92697-3100 United States Division of Geological and Planetary Sciences California Institute of Technology PasadenaCA United States Jet Propulsion Laboratory California Institute of Technology PasadenaCA United States Nanjing210044 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China Climate Change Research Center Institute of Atmospheric Physics Chinese Academy of Sciences Beijing100029 China Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric Physics Chinese Academy of Sciences Beijing100029 China School of Environment Tsinghua University Beijing100084 China School of Mat hemat ical School T singhua University Beijing100084 China Department of Mathematical Sciences Tsinghua University Beijing100084 China Center of Hubei Cooperative Innovation for Emissions Trading System Wuhan China Faculty of Management and Economics Kunming University of Science and Technology 13 Kunming China Economic Research Centre of Nagoya University Furo-cho Chikusa-ku Nagoya Japan Institute Pierre-Simon Laplace Sorbonne Université CNRS Paris France Center for Energy and Environmental Policy Research Beijing Institute of Technology Beijing China Department of Electrical Engineering Tsinghua University Beijing100084 China Jinan University Guangzhou China Beijing Normal University Beijing China Institute of Applied Ecology Chinese Academy of Sciences Shenyang China Energy and Resources Group Goldman School of Pub

The considerable cessation of human activities during the COVID-19 pandemic has affected global energy use and CO2 emissions. Here we show the unprecedented decrease in global fossil CO2 emissions from January to April 2020 was of 7.8% (938 Mt CO2 with a +6.8% of 2-σ uncertainty) when compared with the period last year. In addition other emerging estimates of COVID impacts based on monthly energy supply1 or estimated parameters2, this study contributes to another step that constructed the near-real-time daily CO2 emission inventories based on activity from power generation (for 29 countries), industry (for 73 countries), road transportation (for 406 cities), aviation and maritime transportation and commercial and residential sectors emissions (for206 countries). The estimates distinguished the decline of CO2 due to COVID-19 from the daily, weekly and seasonal variations as well as the holiday events. The COVID-related decreases in CO2 emissions in road transportation (340.4 Mt CO2, -15.5%), power (292.5 Mt CO2, -6.4% compared to 2019), industry (136.2 Mt CO2, -4.4%), aviation (92.8 Mt CO2, -28.9%), residential (43.4 Mt CO2, - 2.7%), and international shipping (35.9Mt CO2, -15%). Regionally, decreases in China were the largest and earliest (234.5 Mt CO2,-6.9%), followed by Europe (EU-27 & UK) (138.3 Mt CO2, -12.0%) and the U.S. (162.4 Mt CO2, -9.5%). The declines of CO2 are consistent with regional nitrogen oxides concentrations observed by satellites and ground-based networks, but the calculated signal of emissions decreases (about 1Gt CO2) will have little impacts (less than 0.13ppm by April 30, 2020) on the overserved global CO2 concertation. However, with observed fast CO2 recovery in China and partial re-opening globally, our findings suggest the longer-term effects on CO2 emissions are unknown and should be carefully monitored using multiple measures. Copyright © 2020, The Authors. All rights reserved.

关键词： Carbon dioxide

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穿山甲可能不是新型冠状病毒的中间宿主

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中国预防兽医学报 2020年第12期42卷 1311-1311页

作者： LIU PING JIANG JING-ZHE WANXIU-FENG Guangdong Key Laboratory of Animal Conservation and Resource Utilization Guangdong Public Laboratory of Wild Animal Conservation and Utilization Guangdong Institute of Applied Biological Resources Guangdong Academy of Science Guangzhou Guangdong Province China. Key Laboratory of South China Sea Fishery Resources Exploitation & Utilization Ministry of Agriculture South China Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Guangzhou Guangdong Province China. Department of Molecular Microbiology and Immunology School of Medicine University of Missouri Columbia Missouri United States of America. Department of Electrical Engineering & Computer Science College of Engineering University of Missouri Columbia Missouri United States of America. MU Center for Research on Influenza Systems Biology (CRISB) University of Missouri Columbia Missouri United States of America. Bond Life Sciences Center University of Missouri Columbia Missouri United States of America. MU Institute for Data Science and Informatics University of Missouri Columbia Missouri United States of America. Guangdong Provincial Key Laboratory of Silviculture Protection and Utilization Guangdong Academy of Forestry Guangzhou Guangdong Province China. Institute of Animal Health Guangdong Academy of Agricultural Sciences Guangzhou Guangdong Province China. Guangdong Provincial Wildlife Rescue Center Guangzhou Guangdong Province China.

当前,新型冠状病毒肺炎(COVID-19)疫情仍在全球范围内肆虐,新冠肺炎的防控工作依然是重中之重。研究表明新型冠状病毒与中菊头蝠携带的Bat-CoV-RaTG13冠状病毒全基因组核苷酸一致性高达96%,推测该病毒可能起源于蝙蝠,再由中间野生动物... 详细信息

当前,新型冠状病毒肺炎(COVID-19)疫情仍在全球范围内肆虐,新冠肺炎的防控工作依然是重中之重。研究表明新型冠状病毒与中菊头蝠携带的Bat-CoV-RaTG13冠状病毒全基因组核苷酸一致性高达96%,推测该病毒可能起源于蝙蝠,再由中间野生动物宿主进一步传播,但目前中间宿主仍然未知。

关键词：中间宿主防控工作动物宿主穿山甲冠状病毒全球范围全基因组肺炎

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Byte by bite: Use of a mobile Bite Counter and weekly behavioral challenges to promote weight loss

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Smart Health 2017年 3-4卷 20-26页

作者： Turner-McGrievy, Gabrielle M. Boutté, Alycia Crimarco, Anthony Wilcox, Sara Hutto, Brent E. Hoover, Adam Muth, Eric R. Department of Health Promotion Education and Behavior Arnold School of Public Health University of South Carolina 915 Greene Street Room 529 Columbia 29208 SC United States Department of Exercise Science Director Prevention Research Center Arnold School of Public Health University of South Carolina Columbia SC United States Prevention Research Center Arnold School of Public Health University of South Carolina Columbia SC United States Holcombe Department of Electrical and Computer Engineering Clemson University Clemson SC United States Department of Psychology Clemson University Clemson SC United States

The goal of this study was to examine the usability and feasibility of the mobile Bite Counter (a watch-like device that detects when a user consumes food or beverage) and the impact of weekly behavioral challenges on diet and physical activity outcomes. Overweight (mean BMI 31.1±4.9 kg/m²) adults (n=12) were recruited to participate in a four-week study to test both the usability and feasibility of using the device as part of a behavioral weight loss intervention. Participants were instructed to self-monitor number of bites/day using the Bite Counter, attend weekly group sessions, and listen to weekly podcasts. Participants were given weekly challenges: use a daily bite limit goal (wk1), turn off Bite Counter when fruits/vegetables are consumed (wk2), self-monitor kilocalories vs. bites (wk3), and receive a 10 bites/day bonus for every 30 min of exercise (wk4). Participants lost a mean of −1.2±1.3 kg. Only the wk3 challenge produced significant differences in kcal change (wk3 1302±120 kcal/day vs. baseline 2042±302 kcal/d, P<0.05). Bite Counter use was significantly correlated with weight loss (r= −0.58, P<0.05). Future studies should examine the use of the Bite Counter and impact of behavioral challenges over a longer period of time in a controlled study. © 2017 Elsevier Inc.

关键词： Dietary self-monitoring Mobile health Mobile technology Personal health device Weight loss

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Resilient Wide-Area Damping Control for Interarea Oscillation Considering Communication Failure

Resilient Wide-Area Damping Control for Interarea Oscillatio...

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IEEE Power and Energy Society General Meeting

作者： Yu Shen Wei Yao Jinyu Wen Haibo He Cheng Luo State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science & Technology Department of Electrical Computer and Biomedical Engineering University of Rhode Island Northern Indiana Public Service Company (NIPSCO)

ISBN: (纸本)9781538622131;9781538622124

The wide-area damping controller, which uses the wide-area signal transmitted by communication network as the input signal, is an effective measure to suppress interarea oscillations. However, communication failure may occur when communication device fault, disaster or even attack occur. It would lead to the loss of wide-area signal and may disable the wide-area damping controller (WADC). To address this problem, this paper proposes a resilient WADC by employing both a wide-area signal and a local signal as the input signals to combine the observability and reliability of input signals. Moreover, a goal representation heuristic dynamic programming (GrHDP) algorithm is employed to design the resilient WADC of voltage source converter high voltage direct current (VSC-HVDC) transmission system for interarea oscillation. The proposed resilient GrHDP-WADC has the ability of online learning and strong adaptivity to handle the communication failure. Meanwhile, it does not need the exact model of the power system. Case study is undertaken based on a 10-machine 39-bus system with one VSC-HVDC transmission line. Simulation results show that the proposed resilient GrHDP-WADC can maintain a good control performance under communication failure.

关键词： Oscillators Power transmission lines Damping Power conversion Mathematical model Neural networks

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Conditional Survival Analysis of Patients With Locally Advanced Laryngeal Cancer: Construction of a Dynamic Risk Model and Clinical Nomogram

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SCIENTIFIC REPORTS 2017年第1期7卷 1-10页

作者： Sheu, Tommy Vock, David M. Mohamed, Abdallah S. R. Gross, Neil Mulcahy, Collin Zafereo, Mark Gunn, G. Brandon Garden, Adam S. Sevak, Parag Phan, Jack Lewin, Jan S. Frank, Steven J. Beadle, Beth M. Morrison, William H. Lai, Stephen Y. Hutcheson, Katherine Marai, G. Elisabeta Canahuate, Guadalupe M. Kies, Merrill El-Naggar, Adel Weber, Randal S. Rosenthal, David I. Fuller, Clifton D. Department of Radiation Oncology The University of Texas MD Anderson Cancer Center Houston Texas USA Department of Clinical Oncology and Nuclear Medicine University of Alexandria Alexandria Egypt Division of Biostatistics University of Minnesota School of Public Health Minneapolis Minnesota USA Department of Head and Neck Surgery The University of Texas MD Anderson Cancer Center Houston Texas USA Department of Radiation Oncology Henry Ford Hospital Detroit MI USA Department of Computer Science University of Illinois at Chicago Chicago Illinois USA Department of Electrical & Computer Engineering University of Iowa Iowa City IA USA Department of Medical Oncology The University of Texas MD Anderson Cancer Center Houston Texas USA Department of Pathology The University of Texas MD Anderson Cancer Center Houston Texas USA

Conditional survival (CS), the survival beyond a pre-defined time interval, can identify periods of higher mortality risk for patients with locally advanced laryngeal cancer who face treatment-related toxicity and comorbidities related to alcohol and smoking in the survivorship setting. Using Weibull regression modeling, we analyzed retrospectively abstracted data from 638 records of patients who received radiation to identify prognostic factors for overall survival (OS) and recurrence free survival (RFS) for the first 3 years of survival and for OS conditional upon 3 years of survival. The CS was iteratively calculated, stratifying on variables that were statistically significant on multivariate regression. Predictive nomograms were generated. The median total follow up time was 175 months. The 3-and 6-year actuarial overall survival (OS) was 68% (95% confidence interval [CI] 65-72%) and 49% (CI 45-53%). The 3-year conditional overall survival (COS) at 3 years was 72% (CI 65-74%). Black patients had worse COS over time. Nodal disease was significantly associated with recurrence, but after 3 years, the 3-year conditional RFS converged for all nodal groups. In conclusion, the CS analysis in this patient cohort identified subgroups and time intervals that may represent opportunities for intervention.

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Dynamic constraints on activity and connectivity during the learning of value

arXiv

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arXiv 2018年

作者： Adebimpe, Azeez Bertolero, Maxwell Khambhati, Ankit N. Mattar, Marcelo G. Romer, Daniel Thompson-Schill, Sharon L. Bassett, Danielle S. Annenberg Public Policy Center University of Pennsylvania PhiladelphiaPA19104 United States Department of Psychiatry Perelman School of Medicine University of Pennsylvania PhiladelphiaPA19104 United States Department of Bioengineering School of Engineering & Applied Science University of Pennsylvania PA19104 United States Department of Neurological Surgery University of California San FranciscoCA94122 United States Princeton Neuroscience Institute Princeton University PrincetonNJ United States Department of Psychology School of Arts & Sciences University of Pennsylvania PA19104 United States Department of Electrical & Systems Engineering School of Engineering & Applied Science University of Pennsylvania PA19104 United States Department of Psychiatry Perelman School of Medicine University of Pennsylvania PhiladelphiaPA19104 United States Department of Physics & Astronomy College of Arts & Sciences University of Pennsylvania PhiladelphiaPA19104 United States

Human learning is a complex process in which future behavior is altered via the modulation of neural activity. Yet, the degree to which brain activity and functional connectivity during learning is constrained across subjects, for example by conserved anatomy and physiology or by the nature of the task, remains unknown. Here, we measured brain activity and functional connectivity in a longitudinal experiment in which healthy adult human participants learned the values of novel objects over the course of four days. We assessed the presence of constraints on activity and functional connectivity using an intersubject correlation approach. Constraints on activity and connectivity were greater in magnitude than expected in a non-parametric permutation-based null model, particularly in primary sensory and motor systems, as well as in regions associated with the learning of value. Notably, inter-subject connectivity in activity and connectivity displayed marked temporal variations, with inter-subject correlations in activity exceeding those in connectivity during early learning and visa versa in later learning. Finally, individual differences in performance accuracy tracked the degree to which a subject's connectivity, but not activity, tracked subject-general patterns. Taken together, our results support the notion that brain activity and connectivity are constrained across subjects in early learning, with constraints on activity, but not connectivity, decreasing in later learning. Copyright © 2018, The Authors. All rights reserved.

关键词： Brain

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Implementation of Data Mining to Classify the Consumer's Complaints of Electricity Usage Based on Consumer's Locations Using Clustering Method

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Journal of Physics: Conference Series 2019年第1期1363卷

作者： A M H Pardede Yusdiana Br Sembiring Akbar Iskandar Dyah Retno Pitasari S Sriadhi Dian Rianita Muhammad Arifin Mersy Yoslin Ririhena Nurintan Asyiah Siregar Supriyono Ayu Esteka Sari Simson Tondo Muhammad Zarlis Edy Winarno Tulus STMIK Kaputama Binjai Sumatera Utara Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Department of Law Universitas Halmahera Tobelo Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Department of Public Administrations Universitas Lancang Kuning Indonesia Department of Information System Faculty of Engineering Universitas Muria Kudus Indonesia Department of Accounting Universitas Halmahera Indonesia Department of Management STIE Labuhanbatu Sumatera Utara Indonesia Department of Information System Universitas Muria Kudus Kudus Indonesia Department of Management STIE Sakti Alam Kerinci Jambi Indonesia Department of Public Administration Universitas Halmahera Tobelo Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia Faculty of Information Technology Universitas Stikubank Semarang Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia

Data collected by PLN staff on customer's complaints in the usage of electricity are very huge and accumulate. Previously, there was no information about these kinds of complaints in all sub-districts included inside the company, PT. PLN Binjai. On the other hand, each year company experienced problems to classify all complaints in order to obtain customers with information to later be used as a basis for making policy/decision. Data mining used clustering method and K-Means algorithm to classify the data so that important information is obtained from customer's complaints on the electricity usage, using variable: types of complaints, power using by consumer and consumer's region. Data was analyzed using Matlab to produce cluster centers and obtained a relationship between variables obtained with groups with high number of complaints. Results revealed that from 500 customers who have complained, cluster 1 had 218 complaints namely NT Fuse Putus with power used was 1300 watt and was located in Binjai.

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MATLAB-based analysis of labor dispatch and work distribution: An example involving caseworkers in central Taiwan

MATLAB-based analysis of labor dispatch and work distributio...

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2017 IEEE International Conference on Applied System Innovation, ICASI 2017

作者： Oh, Chin-Yu Hsu, Meng-Chueh Tsai, Chang-Ming Jhang, Jyun-Yao Chen, Yu-Ren Chen, Bo-Xiang Chen, Yi-Chung Teng, Chun-Wen Chen, Shu-Hui Department of Information Engineering and Computer Science Feng Chia University Taichung40724 Taiwan Ph. D. Program of Business Feng Chia University Taichung40724 Taiwan Graduate Institute of Public Policy and social innovation Feng Chia University Taichung40724 Taiwan General Education Center Feng Chia University Taichung40724 Taiwan

ISBN: (纸本)9781509048977

The dispatching of labor and distribution of tasks among workers are important aspects of corporate operations. Labor dispatch refers to the dispatching of employees to meet with clients;however, dispatches commonly vary with time. This means that any analysis pertaining to labor dispatch and work distribution should also vary with time. In this study, MATLAB was used to analyze data from anonymous caseworkers in central Taiwan in order to identify relationships between the location of their offices and the homes of their clients. Our aim was to determine the rationality behind labor dispatch and work distribution. This led us to develop a novel method by which to dispatch labor in order to achieve a more equitable distribution of work. Simulations demonstrate the efficacy of the proposed scheme in improving labor dispatch and work distribution. © 2017 IEEE.

关键词： MATLAB

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Authorship Correction: International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study

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Journal of medical Internet research 2021年第11期23卷 e34625页

作者： Griffin M Weber Harrison G Zhang Sehi L'Yi Clara-Lea Bonzel Chuan Hong Paul Avillach Alba Gutiérrez-Sacristán Nathan P Palmer Amelia Li Min Tan Xuan Wang William Yuan Nils Gehlenborg Anna Alloni Danilo F Amendola Antonio Bellasi Riccardo Bellazzi Michele Beraghi Mauro Bucalo Luca Chiovato Kelly Cho Arianna Dagliati Hossein Estiri Robert W Follett Noelia García Barrio David A Hanauer Darren W Henderson Yuk-Lam Ho John H Holmes Meghan R Hutch Ramakanth Kavuluru Katie Kirchoff Jeffrey G Klann Ashok K Krishnamurthy Trang T Le Molei Liu Ne Hooi Will Loh Sara Lozano-Zahonero Yuan Luo Sarah Maidlow Adeline Makoudjou Alberto Malovini Marcelo Roberto Martins Bertrand Moal Michele Morris Danielle L Mowery Shawn N Murphy Antoine Neuraz Kee Yuan Ngiam Marina P Okoshi Gilbert S Omenn Lav P Patel Miguel Pedrera Jiménez Robson A Prudente Malarkodi Jebathilagam Samayamuthu Fernando J Sanz Vidorreta Emily R Schriver Petra Schubert Pablo Serrano Balazote Byorn Wl Tan Suzana E Tanni Valentina Tibollo Shyam Visweswaran Kavishwar B Wagholikar Zongqi Xia Daniela Zöller Isaac S Kohane Tianxi Cai Andrew M South Gabriel A Brat Department of Biomedical Informatics Harvard Medical School Boston MA United States. BIOMERIS (BIOMedical Research Informatics Solutions) Pavia Italy. Clinical Research Unit Botucatu Medical School São Paulo State University Botucatu Brazil. Division of Nephrology Department of Medicine Ente Ospedaliero Cantonale Lugano Switzerland. Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy. Information Technology Department Azienda Socio-Sanitaria Territoriale di Pavia Pavia Italy. Unit of Internal Medicine and Endocrinology Istituti Clinici Scientifici Maugeri SpA SB IRCCS Pavia Italy. Massachusetts Veterans Epidemiology Research and Information Center Veterans Affairs Boston Healthcare System Boston MA United States. Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy. Department of Medicine Massachusetts General Hospital Boston MA United States. Department of Medicine David Geffen School of Medicine University of California Los Angeles Los Angeles CA United States. Health Informatics Hospital Universitario 12 de Octubre Madrid Spain. Department of Learning Health Sciences University of Michigan Medical School Ann Arbor MI United States. Department of Biomedical Informatics University of Kentucky Lexington KY United States. Department of Biostatistics Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine Philadelphia PA United States. Institute for Biomedical Informatics University of Pennsylvania Perelman School of Medicine Philadelphia PA United States. Department of Preventive Medicine Northwestern University Chicago IL United States. Institute for Biomedical Informatics University of Kentucky Lexington KY United States. Medical University of South Carolina Charleston SC United States. Department of Computer Science Renaissance Computing Institute University of North Carolina at Chapel Hill Chapel Hill NC United States. Departm

[This corrects the article DOI: 10.2196/31400.].

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Update on carotid plaque instability quantification using strain indices from multiple regions of interest in carotid plaque

Update on carotid plaque instability quantification using st...

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2017 IEEE International Ultrasonics Symposium, IUS 2017

作者： Meshram, Nirvedh Mitchell, Carol Hermann, Bruce Wilbrand, Stephanie Jackson, Daren Dempsey, Robert Varghese, Tomy Department of Medical Physics University of Wisconsin School of Medicine and Public Health University of Wisconsin Madison MadisonWI United States Department of Electrical and Computer Engineering University of Wisconsin Madison MadisonWI United States Department of Medicine University of Wisconsin Madison MadisonWI United States Department of Neurology University of Wisconsin Madison MadisonWI United States Department of Neurological Surgery University of Wisconsin Madison MadisonWI United States

ISBN: (纸本)9781538633830

Carotid plaque rupture is a primary cause of ischemic strokes and transient ischemic attacks (TIAs). Probability of stroke and TIAs depend on the mechanical stability of plaque. Ultrasound strain can provide a non-invasive assessment of plaque stiffness to assess mechanical stability. We report on ultrasound strain indices from multiple regions of interest (ROI) in plaque as biomarkers for plaque instability. © 2017 IEEE.

关键词： Strain Correlation Ultrasonic imaging Stability criteria Biomarkers Biomedical imaging

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