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Ph.D. Research in Microelectronics and Electronics (PRIME)

作者： M. Pilar Garde Antonio Lopez-Martin Jaime Ramírez-Angulo Institute of Smart Cities Public University of Navarra Pamplona Spain Klipsch School of Electrical and computer Engineering New Mexico State University Las Cruces NM

A fully differential Super Class AB Operational Transconductance Amplifier (OTA) is presented. To provide additional dynamic current boosting and increased gain-bandwidth product (GBW), not only adaptive biasing techniques has been applied at the differential input stage, but also Local Common Mode Feedback (LCMFB). Additionally, Quasi Floating Gate (QFG) transistors are employed, enhancing the performance of the amplifier. The OTA has been fabricated in a standard 0.5-μm CMOS process. Simulation results yield a slew rate improvement by factor 86 and a GBW enhancement by factor 16 when compared to the class A OTA while driving the same 70-pF load. Supply voltages are ±1-V and the value of the quiescent current is 10 μA. The overhead in terms of quiescent power, silicon area, and noise level is small.

关键词： Transistors Resistors Capacitance Transconductance Boosting Current measurement Capacitors

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A Critical Analysis on the Thin Crystalline Silicon PV Module of the Lightweight PV System

A Critical Analysis on the Thin Crystalline Silicon PV Modul...

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2017 IEEE 44th Photovoltaic Specialist Conference (PVSC)

作者： Meixi Chen Abhishek Iyer Cheng-Hao Shih Lado Kurdgelashvili Robert Opila Department of Material Science and Engineering University of Delaware Newark Delaware USA Department of Electrical and Computer Engineering University of Delaware Newark Delaware USA Department of Energy and Environmental Policy University of Delaware Newark Delaware USA

This work provides an analysis of the thin crystalline silicon PV module for a Lightweight PV (LPV) system. We first examine the advantages of the LPV system and then discuss the technical and economic challenges of the thin crystalline silicon PV module in assisting LPV system development for future market penetration. A critical analysis is conducted on the efficiency and yield challenge, and the system weight and costs reduction of thin crystalline silicon PV for the future development of the LPV system. It has shown that the key in speeding up thin silicon LPV market diffusion lies in developing cost-effective passivation and light trapping methods, as well as high-yield thin silicon fabrication technologies.

关键词： Silicon Passivation Fabrication Light trapping Photovoltaic systems

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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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Abstracts

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JOURNAL OF SPINAL CORD MEDICINE 2021年第SUPPL 1期44卷 S278-S324页

作者： [Anonymous] Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto Toronto ON CA KITE - Toronto Rehabilitation Institute University Health Network Toronto ON CA Institute for Health Policy Management and Evaluation University of Toronto Toronto ON CA Rehabilitation Sciences Institute University of Toronto Toronto ON CA Institute of Medical Sciences University of Toronto Toronto ON CA. Rehabilitation Sciences Institute University of Toronto ON CA KITE Research Institute-Toronto Rehab-University Health Network Toronto ON CA Physical Therapy Department University of Toronto ON CA Praxis Spinal Cord Institute Vancouver BC Université de Montréal (École de réadaptation) Montreal QC CA Institut de réadaptation Gingras-Linsay-de-Montréal Montreal QC CA Division of Physical Medicine & Rehabilitation Department of Medicine Faculty of Medicine & Dentistry University of Alberta Edmonton AB CA University of Calgary Calgary AB CA Alberta Health Services Centre for Family Medicine Kitchener ON CA McMaster University Department of Family Medicine Hamilton ON CA Dept. of Physical Therapy University of Toronto Toronto ON CA KITE-University Health Network Toronto ON CA Praxis Spinal Cord Institute Vancouver BC CA Center for Interdisciplinary Research in Rehabilitation and Social Integration (CIRRIS) Quebec City QC CA Dept. of Rehabilitation Laval University Quebec City QC CA Institute of Health Policy Management and Evaluation University of Toronto Toronto ON CA School of Rehabilitation Science University of Saskatchewan Saskatoon SK CA Ontario Neurotrauma Foundation Toronto ON CA Canadian Spinal Research Organization Toronto ON CA CIUSSS du Centre-Sud-de-l ‘Île-de-Montréal (Installation Gingras-Lindsay) Montréal QC CA École de réadaptation Université de Montréal Montréal QC CA First Steps Wellness Centre Regina SK CA Stan Cassidy Centre for Rehabilitation Horizon Health Network Fredericton NB CA Departmen

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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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Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: the Global Burden of Diseases Study 2019

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The Lancet HIV 2021年第10期8卷 e633-e651页

作者： Jahagirdar, Deepa Walters, Magdalene K. Novotney, Amanda Brewer, Edmond D. Frank, Tahvi D. Carter, Austin Biehl, Molly H. Abbastabar, Hedayat Abhilash, E.S. Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Adekanmbi, Victor Adeyinka, Daniel Adedayo Adnani, Qorinah Estiningtyas Sakilah Afzal, Saira Aghababaei, Soodabeh Ahinkorah, Bright Opoku Ahmad, Sajjad Ahmadi, Keivan Ahmadi, Sepideh Ahmadpour, Ehsan Ahmed, Muktar Beshir Rashid, Tarik Ahmed Salih, Yusra Ahmed Aklilu, Addis Akram, Tayyaba Akunna, Chisom Joyqueenet Al Hamad, Hanadi Alahdab, Fares Alanezi, Fahad Mashhour Aleksandrova, Ekaterina A. Alene, Kefyalew Addis Ali, Liaqat Alipour, Vahid Almustanyir, Sami Alvis-Guzman, Nelson Ameyaw, Edward Kwabena Amu, Hubert Andrei, Catalina Liliana Andrei, Tudorel Anvari, Davood Arabloo, Jalal Aremu, Olatunde Arulappan, Judie Atnafu, Desta Debalkie Quintanilla, Beatriz Paulina Ayala Ayza, Muluken Altaye Azari, Samad Darshan, B.B. Banach, Maciej Bärnighausen, Till Winfried Barra, Fabio Barrow, Amadou Basu, Sanjay Bazargan-Hejazi, Shahrzad Belay, Habtamu Gebrehana Berheto, Tezera Moshago Bezabhe, Woldesellassie Mequanint Bezabih, Yihienew Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Nikha Bhardwaj, Pankaj Bhattacharyya, Krittika Bibi, Sadia Bijani, Ali Bisignano, Catherine Bolarinwa, Obasanjo Afolabi Boloor, Archith Boltaev, Azizbek A. Briko, Nikolay Ivanovich Buonsenso, Danilo Burkart, Katrin Butt, Zahid A. Cao, Chao Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Choudhari, Sonali Gajanan Chu, Dinh-Toi Couto, Rosa A.S. Cowden, Richard G. Dachew, Berihun Assefa Dadras, Omid Dagnew, Amare Belachew Dahlawi, Saad M.A. Dai, Xiaochen Dandona, Lalit Dandona, Rakhi das Neves, José Degenhardt, Louisa Demeke, Feleke Mekonnen Desta, Abebaw Alemayehu Deuba, Keshab Dhamnetiya, Deepak Dhungana, Govinda Prasad Dianatinasab, Mostafa Diaz, Daniel Djalalinia, Shirin Doan, Linh Phuong Dorostkar, Fariba Edinur, Hisham Atan Effiong, Andem Eftekharzadeh, Sahar El Sayed Zaki, Maysaa Elayedath, Rajesh Elhadi, Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Allergy and Infectious Diseases University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States School of Social Work University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Vagelos College of Physicians and Surgeones Columbia University Medical Center New York NY United States Division of Data Analytics and Delivery for Impact WHO Geneva Switzerland Advanced Diagnostic and Interventional Radiology Research Centre Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Centre Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Paediatric Chronic Kidney Disease Research Centre Tehran University of Medical Sciences Tehran Iran Department of Psychiatry Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Centre Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Centre Tehran University of Medical Sciences Tehran Iran Research Centre for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Centre Tehran University of Medical Sciences Tehran Iran Department of Botany Sree Narayana Guru College Chelannur Kozhikode India Clinical Sciences Department University of Sharjah Sharjah United Arab Emirates Mass Communication Department University of Sharjah Sharjah United Arab Emirates Department of Health-Care Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Department of Population Medicine Ca

Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. Methods: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). Findings: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1–38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78–0·91) per female living with HIV in 2019, 0·99 male infections (0·91–1·10) for every female infection, and 1·02 male deaths (0·95–1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58–35·43, and a 39·66% decrease in deaths, 36·49–42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05–0·06) and the global incidence-to-mortality ratio was

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Abstract #9: Brain Correlates of Non-Invasive Vagal Nerve Stimulation in Stress

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Brain Stimulation 2019年第2期12卷 e3-e4页

作者： J. Douglas Bremner Matt Wittbrodt Nil Z. Gurel Jon Nye Zuhayr Alam Viola Vaccarino Stacy L. Ladd Lucy H. Shallenberger Minxuan Huang Yi-Yan Ko Brad Pearce Mobashir H. Shandhi Amit Shah Omer T. Inan Departments of Psychiatry & Behavioral Neuroscience Rollins School of Public Health Emory Universiity Atlanta GA USA Departments of Radiology Rollins School of Public Health Emory Universiity Atlanta GA USA Atlanta VA Medical Center Decatur GA USA School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Departments of Medicine (Cardiology) Rollins School of Public Health Emory Universiity Atlanta GA USA Departments of Epidemiology Emory University School of Medicine Atlanta GA USA Departments of Biostatistics Emory Universiity Atlanta GA USA

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Publisher Correction: Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

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Nature medicine 2022年第10期28卷 2218页

作者： Baptiste Vasey Myura Nagendran Bruce Campbell David A Clifton Gary S Collins Spiros Denaxas Alastair K Denniston Livia Faes Bart Geerts Mudathir Ibrahim Xiaoxuan Liu Bilal A Mateen Piyush Mathur Melissa D McCradden Lauren Morgan Johan Ordish Campbell Rogers Suchi Saria Daniel S W Ting Peter Watkinson Wim Weber Peter Wheatstone Peter McCulloch Nuffield Department of Surgical Sciences University of Oxford Oxford UK. baptiste.vasey@***. Institute of Biomedical Engineering Department of Engineering Science University of Oxford Oxford UK. baptiste.vasey@***. Critical Care Research Group Nuffield Department of Clinical Neurosciences University of Oxford Oxford UK. baptiste.vasey@***. UKRI Centre for Doctoral Training in AI for Healthcare Imperial College London London UK. University of Exeter Medical School Exeter UK. Royal Devon and Exeter Hospital Exeter UK. Institute of Biomedical Engineering Department of Engineering Science University of Oxford Oxford UK. Centre for Statistics in Medicine Nuffield Department of Orthopaedics Rheumatology & Musculoskeletal Sciences University of Oxford Oxford UK. Institute of Health Informatics University College London London UK. British Heart Foundation Data Science Centre London UK. Health Data Research UK London UK. UCL Hospitals Biomedical Research Centre London UK. University Hospitals Birmingham NHS Foundation Trust Birmingham UK. Academic Unit of Ophthalmology Institute of Inflammation and Ageing College of Medical and Dental Sciences University of Birmingham Birmingham UK. Moorfields Eye Hospital NHS Foundation Trust London UK. Healthplus.ai-R&D BV Amsterdam The Netherlands. Nuffield Department of Surgical Sciences University of Oxford Oxford UK. Department of Surgery Maimonides Medical Center Brooklyn NY USA. The Wellcome Trust London UK. The Alan Turing Institute London UK. Department of General Anesthesiology Anesthesiology Institute Cleveland Clinic Cleveland OH USA. The Hospital for Sick Children Toronto ON Canada. Dalla Lana School of Public Health University of Toronto Toronto ON Canada. Morgan Human Systems Ltd Shrewsbury UK. Medicines and Healthcare products Regulatory Agency London UK. HeartFlow Inc. Redwood City CA USA. Departments of Computer Science Statistics and Health Policy and Division of Informatics Johns Hopkins Un

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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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MFP-Unet: A novel deep learning based approach for left ventricle segmentation in echocardiography

arXiv

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arXiv 2019年

作者： Moradi, Shakiba Alizadehasl, Azin Dhooge, Jan Shiri, Isaac Oveisi, Niki Oveisi, Mehrdad Maleki, Majid Ghelich-Oghli, Mostafa Intelligent Imaging Technology Research Center Med Fanavarn Plus Co. 10th St. Shahid Babaee Blvd. Payam Special Economic Zone Karaj Department of Electrical Engineering Sharif University of Technology Tehran Iran Echocardiography and Cardiogenetic research centers Cardio-Oncology Department Rajaie Cardiovascular Medical & Research Center Tehran Department of Cardiovascular Sciences KU Leuven Leuven Belgium Department of Biomedical and Health Informatics Rajaie Cardiovascular Medical and Research Center Iran University of Medical Science Tehran Research Center for Molecular and Cellular Imaging Tehran University of Medical Sciences Tehran Iran School of Population and Public Health University of British Columbia BCV6T1Z4 Canada Department of Computer Science University of British Columbia VancouverBCV6T1Z4 Canada

Segmentation of the Left ventricle (LV) is a crucial step for quantitative measurements such as area, volume, and ejection fraction. However, the automatic LV segmentation in 2D echocardiographic images is a challenging task due to ill-defined borders, and operator dependence issues (insufficient reproducibility). U-net, which is a well-known architecture in medical image segmentation, addressed this problem through an encoder-decoder path. Despite outstanding overall performance, U-net ignores the contribution of all semantic strengths in the segmentation procedure. In the present study, we have proposed a novel architecture to tackle this drawback. Feature maps in all levels of the decoder path of U-net are concatenated, their depths are equalized, and up-sampled to a fixed dimension. This stack of feature maps would be the input of the semantic segmentation layer. The proposed network yielded state-of-the-art results when comparing with results from U-net, dilated U-net, and deeplabv3, using the same dataset. An average Dice Metric (DM) of 0.945, Hausdorff Distance (HD) of 1.62, Jaccard Coefficient (JC) of 0.97, and Mean Absolute Distance (MAD) of 1.32 are achieved. The correlation graph, bland-altman analysis, and box plot showed a great agreement between automatic and manually calculated volume, area, and length. Copyright © 2019, The Authors. All rights reserved.

关键词： Echocardiography

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