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SSRN 2020年

作者： Li, Bo Ma, Ziming He, Gang Hidalgo-Gonzalez, Patricia Fedorova, Natalie Chen, Minyou Kammen, Daniel M. School of Electrical Engineering State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing400030 China Renewable and Appropriate Energy Laboratory University of California BerkeleyCA94720 United States National Power Dispatching and Control Center Beijing100031 China Energy and Resources Group University of California BerkeleyCA94720 United States Department of Technology and Society College of Engineering and Applied Sciences Stony Brook University Stony BrookNY11794 United States Department of Mechanical and Aerospace Engineering University of California San DiegoCA92093 United States Goldman School of Public Policy University of California BerkeleyCA94720 United States Department of Nuclear Engineering University of California BerkeleyCA94720 United States

China is the world’s leading installer of wind turbines. Attention is rapidly rising in China to the potential of offshore wind. We utilize the SWITCH-China power sector capacity expansion model to explore the transformative role that offshore wind can play in China meeting the ambitious but critically needed 1.5 °C climate objective. We explore alternative energy mixes and analyze the resulting economic and CO2 emissions benefits of offshore wind as a major energy source for China. We find that offshore wind not only replaces coal-fired power plants, which dominate the energy mix in Chinese coastal regions, but also reduces the need for ultra-high-voltage (UHV) transmission lines to deliver the renewable energy generated in the West China to the coastal regions in the East. Offshore wind enables the coastal provinces to become a new hub of green electricity supply, with offshore wind could provide 2 % - 28.6 % of coastal generation (between 1% and 13.2% of total generation) by 2030 across cost-effective energy development scenarios. © 2020, The Authors. All rights reserved.

关键词： Coal

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Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study

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The Lancet Digital Health 2025年第5期7卷 100868页

作者： Meng, Ziyao Guan, Zhouyu Yu, Shujie Wu, Yilan Zhao, Yaoning Shen, Jie Lim, Cynthia Ciwei Chen, Tingli Yang, Dawei Ran, An Ran He, Feng Hamzah, Haslina Singh, Sarkaaj Abd Raof, Anis Syazwani Lee-Boey, Jian Wen Samuel Lim, Soo-Kun Sun, Xufang Ge, Shuwang Xu, Gang Su, Hua Cheng, Yang Lu, Feng Liao, Xiaofei Jin, Hai Deng, Chenxin Ruan, Lei Zhang, Cuntai Wu, Chan Dai, Rongping Jin, Yixiao Wang, Wenxiao Li, Tingyao Liu, Ruhan Li, Jiajia Shu, Jia Lu, Yuwei Wang, Xiangning Wu, Qiang Qin, Yiming Tang, Jin Sheng, Xiaohua Jiao, Qiong Yang, Xiaokang Guo, Minyi McKay, Gareth J Hogg, Ruth E Liew, Gerald Chee, Evelyn Yi Lyn Hsu, Wynne Lee, Mong Li Szeto, Simon Luk, Andrea O Y Chan, Juliana C N Cheung, Carol Y Tan, Gavin Siew Wei Tham, Yih-Chung Cheng, Ching-Yu Sabanayagam, Charumathi Lim, Lee-Ling Jia, Weiping Li, Huating Sheng, Bin Wong, Tien Yin 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 Institute for Proactive Healthcare 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 Centre for Diabetes Shanghai Key Laboratory of Diabetes Mellitus Shanghai China MOE Key Laboratory of AI School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Beijing Tsinghua Changgung Hospital Eye Center School of Clinical Medicine Tsinghua Medicine Tsinghua University Beijing China Medical Records and Statistics Office Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Department of Renal Medicine Singapore General Hospital SingHealth-Duke Academic Medical Centre Singapore Singapore Department of Ophthalmology Shanghai Health and Medical Center Wuxi China Department of Ophthalmology and Visual Sciences The Chinese University of Hong Kong Hong Kong Special Administrative Region China Singapore Eye Research Institute Singapore National Eye Centre Singapore Department of Medicine Faculty of Medicine Universiti Malaya Kuala Lumpur Malaysia Department of Ophthalmology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Hubei Wuhan China Department of Nephrology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China Department of Nephrology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China Department of Ophthalmology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China National Engineering Research Centre for Big Dat

Background: Improving the accessibility of screening diabetic kidney disease (DKD) and differentiating isolated diabetic nephropathy from non-diabetic kidney disease (NDKD) are two major challenges in the field of diabetes care. We aimed to develop and validate an artificial intelligence (AI) deep learning system to detect DKD and isolated diabetic nephropathy from retinal fundus images. Methods: In this population-based study, we developed a retinal image-based AI-deep learning system, DeepDKD, pretrained using 734 084 retinal fundus images. First, for DKD detection, we used 486 312 retinal images from 121 578 participants in the Shanghai Integrated Diabetes Prevention and Care System for development and internal validation, and ten multi-ethnic datasets from China, Singapore, Malaysia, Australia, and the UK (65 406 participants) for external validation. Second, to differentiate isolated diabetic nephropathy from NDKD, we used 1068 retinal images from 267 participants for development and internal validation, and three multi-ethnic datasets from China, Malaysia, and the UK (244 participants) for external validation. Finally, we conducted two proof-of-concept studies: a prospective real-world study with 3 months' follow-up to evaluate the effectiveness of DeepDKD in screening DKD;and a longitudinal analysis of the effectiveness of DeepDKD in differentiating isolated diabetic nephropathy from NDKD on renal function changes with 4·6 years' follow-up. Findings: For detecting DKD, DeepDKD achieved an area under the receiver operating characteristic curve (AUC) of 0·842 (95% CI 0·838–0·846) on the internal validation dataset and AUCs of 0·791–0·826 across external validation datasets. For differentiating isolated diabetic nephropathy from NDKD, DeepDKD achieved an AUC of 0·906 (0·825–0·966) on the internal validation dataset and AUCs of 0·733–0·844 across external validation datasets. In the prospective study, compared with the metadata model, DeepDKD could detect DKD wit

关键词： Deep learning

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Case study of content development needs for tele-therapy in an Asian context 18

Case study of content development needs for tele-therapy in ...

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2nd Asian CHI Symposium 2018: Emerging Research Collections, Asian HCI 2018

作者： Foong, Pin Sym Wong, Nicholas Guo, Yiting Emily Shih-Cheng, Yen Ee Beng, Arthur Tay Huat, Gerald Koh Choon Saw Swee Hock School of Public Health National University of Singapore Japan Department of Rehabilitation National University Hospital Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (纸本)9781450356411

Content for Asian tele-therapy contexts are not easily available. Particularly for older adults, who form the bulk of rehabilitation clients, cultural and language appropriateness can promote acceptance and engagement with digital rehabilitative systems. In this case study, we lay out the specific challenges faced in developing Asian, localized content. Our findings showed difficulties related to the translation of content across linguistic and cultural differences. The challenge of localizing content is worsened by the constraints on distribution introduced by moving a health service online. This study contributes a description of these challenges, and concludes with an urgent call for more research focus on supporting efficient, low-resource content development. © 2018 Copyright is held by the owner/author(s).

关键词： Patient rehabilitation

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Comparing Changes in Diet Quality Between Two Technology-Based Diet Tracking Devices

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Journal of Technology in Behavioral Science 2019年第1期4卷 25-32页

作者： Boutté, Alycia K. Turner-McGrievy, Gabrielle M. Wilcox, Sara Hutto, Brent Muth, Eric Hoover, Adam 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 Health Promotion Education and Behavior Arnold School of Public Health University of South Carolina 915 Greene Street Room 552 Columbia 29208 SC United States Department of Exercise Science Prevention Research Center Arnold School of Public Health University of South Carolina 921 Assembly Street Public Health Research Center 117 Columbia 29208 SC United States Statistician Prevention Research Center Arnold School of Public Health University of South Carolina 921 Assembly Street Public Health Research Center 129 Columbia 29208 SC United States Department of Psychology Clemson University 418 Brackett Hall Clemson 29634 SC United States Holcombe Department of Electrical and Computer Engineering Clemson University 433 Calhoun Dr. Clemson 29634 SC United States

This study aimed to examine changes in Healthy Eating Index-2010 (HEI-2010) scores, components, and energy intake between automated Bite Counter (Bite) and traditional diet tracking mobile app (App) groups. This was a secondary analysis of the DIET Mobile study, a 6-month weight loss intervention. Assessments were conducted at baseline, 3 and 6 months. Twenty-four-hour dietary recall data were collected. Overweight/obese adults (N = 81) were randomized to Bite or App groups. The intervention was delivered through behavioral podcasts. Participants were provided customized calorie/bite goals and used their device to track intake. We assessed changes in HEI-2010 scores from baseline to 6 months between groups. t tests, chi-square, and repeated measures ANOVA were performed. Models included time, group, and group×time interaction, controlling for no other covariates. There were no significant changes in HEI-2010 scores, components, or energy intake between groups at 3 or 6 months. This study found that both the Bite and App groups were able to reduce their energy intake and there was no difference in changes in diet quality between groups, which provides some support for using the less intensive, more automated method (Bite Counter) for long-term dietary self-monitoring. The study had a low sample size according to power calculations. Future interventions aimed at improving diet quality through mHealth technology should investigate the potential to develop a new app or modify an existing app that would allow for dietary self-monitoring that provides specific feedback on how users’ diets align with diet quality components in the HEI to improve overall diet quality. © 2018, Springer Nature Switzerland AG.

关键词： Dietary self-monitoring Healthy diet Mobile health Obesity

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Examining Interconnection and Net Metering policy for Distributed Generation in the United States

SSRN

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SSRN 2019年

作者： Schelly, Chelsea Louie, Edward P. Pearce, Joshua M. Dept. of Social Sciences Michigan Technological University 1400 Townsend Drive HoughtonMI49931 United States School of Public Policy Oregon State University CorvallisOR97331-3703 United States Materials Science and Engineering Department of Electrical & Computer Engineering Michigan Technological University 1400 Townsend Drive HoughtonMI49931 United States

Following requirements of the Energy policy Act of 2005, most U.S. states require utility companies to adopt interconnection and net metering policies, allowing customers to become prosumers who both consume and produce electricity, generating electricity using distributed renewable energy technologies, connecting to the existing electric utility grid and receiving compensation for excess electricity generation. This paper reviews existing interconnection and net metering policies instituted by investor owned utilities (IOUs) across the U.S., specifically focused on policies regulating installations of small scale, residential or Tier 1 (a term used to indicate policies applicable to smaller scale rather than larger scale, although the size at which DG systems are classified as either Tier 1 or higher tiers varies by utility). publicly available data from each IOU reveal inconsistencies in interconnection and net metering policies, within states and even within individual companies. In addition, accurate information is often unavailable to consumers. Perhaps most importantly, results suggest that compensation for excess distributed generation often lacks transparent articulation in utility policy. The results of this study provide important insight into interconnection and net metering policies for distributed renewable energy generation, as states and utilities continue to modify interconnection and net metering policies in response to increased adoption of distributed renewable energy systems. © 2019, The Authors. All rights reserved.

关键词： Electric utilities

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Publisher Correction: Systemically-delivered biodegradable PLGA alters gut microbiota and induces transcriptomic reprogramming in the liver in an obesity mouse model

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Scientific reports 2020年第1期10卷 16010页

作者： Alice Chaplin Huiyun Gao Courteney Asase Palanivel Rengasamy Bongsoo Park Danielle Skander Gürkan Bebek Sanjay Rajagopalan Andrei Maiseyeu School of Medicine Cardiovascular Research Institute Case Western Reserve University 10900 Euclid Ave Cleveland OH 44106 USA. Environmental Health and Engineering Johns Hopkins Bloomberg School of Public Health Johns Hopkins University Baltimore MD USA. Department of Nutrition Department of Electrical Engineering and Computer Science Center for Proteomics and Bioinformatics Case Western Reserve University 10900 Euclid Ave Cleveland OH 44106 USA. School of Medicine Cardiovascular Research Institute Case Western Reserve University 10900 Euclid Ave Cleveland OH 44106 USA. axm1079@case.edu.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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arXiv

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arXiv 2020年

作者： Li, Jiashuo Zhou, Sili Wei, Wendong Qi, Jianchuan Li, Yumeng Chen, Bin Zhang, Ning Guan, Dabo Qian, Haoqi Wu, Xiaohui Miao, Jiawen Chen, Long Liang, Sai Feng, Kuishuang Institute of Blue and Green Development Shandong University Weihai264209 State Key Laboratory of Coal Combustion School of Energy and Power Engineering Huazhong University of Science and Technology Wuhan430074 China School of International and Public Affairs Shanghai Jiao Tong University Shanghai200030 China State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Beijing Normal University Beijing100875 China Laboratory of Anthropogenic Systems Ecology College of Engineering Peking University Beijing100871 China Department of Earth System Science Tsinghua University Beijing100871 China Institute for Global Public Policy Fudan University Shanghai200433 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Key Laboratory of Geographic Information Science Ministry of Education School of Geographic Sciences East China Normal University Shanghai200241 China

China has implemented retrofitting measures in coal-fired power plants (CFPPs) to reduce air pollution through small unit shutdown (SUS), the installation of air pollution control devices (APCDs) and power generation efficiency (PGE) improvement. The reductions in highly toxic Hg emissions and their related health impacts by these measures have not been well studied. To refine mitigation options, we evaluated the health benefits of reduced Hg emissions via retrofitting measures during China's 12th Five-Year Plan by combining plant-level Hg emission inventories with the China Hg Risk Source-Tracking Model. We found that the measures reduced Hg emissions by 23.5 tons (approximately 1/5 of that from CFPPs in 2010), preventing 0.0021 points of per-foetus intelligence quotient (IQ) decrements and 114 deaths from fatal heart attacks. These benefits were dominated by CFPP shutdowns and APCD installations. Provincial health benefits were largely attributable to Hg reductions in other regions. We also demonstrated the necessity of considering human health impacts, rather than just Hg emission reductions, in selecting Hg control devices. This study also suggests that Hg control strategies should consider various factors, such as CFPP locations, population densities and trade-offs between reductions of total Hg (THg) and Hg2+. Copyright © 2020, The Authors. All rights reserved.

关键词： Fossil fuel power plants

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Target-specificity of different amyrin subunits in impeding HCV influx mechanism inside the human cells considering the quantum tunnel profiles and molecular strings of the CD81 receptor: a combined in silico and in vivo study

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In silico pharmacology 2023年第1期11卷 8页

作者： Anika Jabin Mohammad Fahim Uddin Salauddin Al Azad Ashfaque Rahman Fawzia Tabassum Pritthy Sarker A K M Helal Morshed Samiur Rahman Fatima Fairuz Raisa Musfiqur Rahman Sakib Abeer Hasan Olive Tabassum Islam Ramisha Tahsin Shahlaa Zernaz Ahmed Partha Biswas Mst Umme Habiba Mahbuba Siddiquy Maryam Jafary Department of Biochemistry and Microbiology North South University Dhaka 1229 Bangladesh. College of Material Science and Engineering Zhejiang Sci-Tech University Hangzhou 310018 Zhejiang People's Republic of China. Key Laboratory of Industrial Biotechnology Ministry of Education School of Biotechnology Jiangnan University Wuxi 214122 Jiangsu Province People's Republic of China. Department of Genetic Engineering and Biotechnology Shahjalal University of Science and Technology Sylhet 3114 Bangladesh. Pathology and Pathophysiology Major Academy of Medical Science Zhengzhou University Zhengzhou City 450001 Henan Province People's Republic of China. Department of Electrical and Electronic Engineering Brac University Dhaka 1212 Bangladesh. Department of Pharmacy Bangabandhu Sheikh Mujibur Rahman Science and Technology University Gopalganj 8100 Bangladesh. Department of Pharmacy East West University Dhaka 1212 Bangladesh. Department of Computer Science and Engineering East West University Dhaka 1212 Bangladesh. Department of Pharmaceutical Sciences North South University Dhaka 1229 Bangladesh. Department of Genetic Engineering and Biotechnology Jashore University of Science and Technology Jashore 7408 Bangladesh. Data Science Research Unit RPG Interface Lab Jashore 7400 Bangladesh. State Key Laboratory of Food Science and Technology Jiangnan University Wuxi 214122 Jiangsu Province People's Republic of China. Division of Food Safety and Hygiene Department of Environmental Health Engineering School of Public Health Tehran University of Medical Sciences Tehran *** Iran.

HCV is a hepatotropic RNA virus recognized for its frequent virulence and fatality worldwide. Despite many vaccine development programs underway, researchers are on a quest for natural bioactive compounds due to their multivalent efficiencies against viral infections, considering which the current research aimed to figure out the target-specificity and therapeutic potentiality of α, β, and δ subunits of amyrin, as novel bioactive components against the HCV influx mechanism. Initially, the novelty of amyrin subunits was conducted from 203 pharmacophores, comparing their in-silico pharmacokinetic and pharmacodynamic profiles. Besides, the best active site of CD81 was determined following the quantum tunneling algorithm. The molecular dynamic simulation was conducted (100 ns) following the molecular docking steps to reveal the parameters- RMSD (Å); Cα; RMSF (Å); MolSA (Å); Rg (nm); PSA (Å); SASA (Å), and the MM-GBSA dG binding scores. Besides, molecular strings of CD81, along with the co-expressed genes, were classified, as responsible for encoding CD81-mediated protein clusters during HCV infection, resulting in the potentiality of amyrins as targeted prophylactics in HCV infection. Finally, in vivo profiling of the oxidative stress marker, liver-specific enzymes, and antioxidant markers was conducted in the DMN-induced mice model, where -amyrin scored the most significant values in all aspects.

关键词： CD81 receptor Co-expressed genes behind HCV invasion DMN-induced hepatic fibrosis HCV infection In-silico pharmacokinetics and pharmacodynamics Target-specificity of amyrins

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Robots, telework, and the jobs of the future

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Science 2019年第6422期363卷 38页

作者： Jon Peha The reviewer is at the Department of Engineering and Public Policy and the Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA 15213 USA.

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Author Correction: Disrupting cellular memory to overcome drug resistance

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Nature communications 2024年第1期15卷 4264页

作者： Guillaume Harmange Raúl A Reyes Hueros Dylan L Schaff Benjamin Emert Michael Saint-Antoine Laura C Kim Zijian Niu Shivani Nellore Mitchell E Fane Gretchen M Alicea Ashani T Weeraratna M Celeste Simon Abhyudai Singh Sydney M Shaffer Cellular and Molecular Biology Graduate Group Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Biochemistry and Molecular Biophysics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Bioengineering School of Engineering and Applied Sciences University of Pennsylvania Philadelphia PA USA. Division of Biology and Biological Engineering California Institute of Technology Pasadena CA 91125 USA. Department of Electrical and Computer Engineering University of Delaware Newark DE 19716 USA. Abramson Family Cancer Research Institute Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Chemistry College of the Arts and Sciences University of Pennsylvania Philadelphia PA USA. Department of Physics College of the Arts and Sciences University of Pennsylvania Philadelphia PA USA. Department of Biology College of the Arts and Sciences University of Pennsylvania Philadelphia PA USA. The Wharton School University of Pennsylvania Philadelphia PA USA. Cancer Signaling and Microenvironment Research Program Fox Chase Cancer Center Philadelphia PA USA. Department of Biochemistry and Molecular Biology Johns Hopkins School of Public Health Baltimore MD USA. Sidney Kimmel Cancer Center Johns Hopkins School of Medicine Baltimore MD USA. Department of Cell and Developmental Biology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Bioengineering School of Engineering and Applied Sciences University of Pennsylvania Philadelphia PA USA. sydshaffer@***. Department of Pathology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. sydshaffer@***.

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