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SCIENCE 2018年第6406期361卷 990-+页

作者： Hastings, Alan Abbott, Karen C. Cuddington, Kim Francis, Tessa Gellner, Gabriel Lai, Ying-Cheng Morozov, Andrew Petrovskii, Sergei Scranton, Katherine Zeeman, Mary Lou Department of Environmental Science and Policy University of California Davis CA 95616 USA. Department of Biology Case Western Reserve University Cleveland OH 44106 USA. Department of Biology University of Waterloo Waterloo Ontario N2L 3G1 Canada. Puget Sound Institute University of Washington Tacoma WA 98421 USA. Department of Biology Colorado State University Fort Collins CO 80523 USA. School of Electrical Computer and Energy Engineering Arizona State University Tempe AZ 85287 USA. Department of Mathematics University of Leicester Leicester LE1 7RH UK. Shirshov Institute of Oceanology Moscow 117851 Russia. Department of Ecology and Evolutionary Biology University of California Los Angeles CA 90095 USA. Department of Mathematics Bowdoin College Brunswick ME 04011 USA.

The importance of transient dynamics in ecological systems and in the models that describe them has become increasingly recognized. However, previous work has typically treated each instance of these dynamics separately. We review both empirical examples and model systems, and outline a classification of transient dynamics based on ideas and concepts from dynamical systems theory. This classification provides ways to understand the likelihood of transients for particular systems, and to guide investigations to determine the timing of sudden switches in dynamics and other characteristics of transients. Implications for both management and underlying ecological theories emerge.

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Smart building energy efficiency via social game: a robust utility learning framework for closing–the–loop

Smart building energy efficiency via social game: a robust u...

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International Workshop on Science of Smart City Operations and Platforms engineering (SCOPE) in partnership with Global City Teams Challenge (GCTC) (SCOPE - GCTC)

作者： Ioannis C. Konstantakopoulos Lillian J. Ratliff Ming Jin Costas Spanos S. Shankar Sastry Scholar of the Alexander S. Onassis Public Benefit Foundation Department of Electrical Engineering and Computer Sciences University of California Berkeley CA

ISBN: (纸本)9781509011704

Given a non-cooperative, continuous game, we describe a framework for parametric utility learning. Using heteroskedasticity inference, we adapt a Constrained Feasible Generalized Least Squares (cFGLS) utility learning method in which estimator variance is reduced, unbiased, and consistent. We extend our utility learning method using bootstrapping and bagging. We show the performance of the proposed method using data from a social game experiment designed to encourage energy efficient behavior amongst building occupants. Using occupant voting data we simulate the game defined by the estimated utility functions and show that the performance of our robust utility learning method and quantify its improvement over classical methods such as Ordinary Least Squares (OLS).

关键词： Games Nash equilibrium Estimation Lighting Robustness Smart buildings

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Genomic investigations of unexplained acute hepatitis in children

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Nature 2023年第7961期617卷 564-573页

作者： Morfopoulou, Sofia Buddle, Sarah Torres Montaguth, Oscar Enrique Atkinson, Laura Guerra-Assunção, José Afonso Moradi Marjaneh, Mahdi Zennezini Chiozzi, Riccardo Storey, Nathaniel Campos, Luis Hutchinson, J. Ciaran Counsell, John R. Pollara, Gabriele Roy, Sunando Venturini, Cristina Antinao Diaz, Juan F. Siam, Ala’a Tappouni, Luke J. Asgarian, Zeinab Ng, Joanne Hanlon, Killian S. Lennon, Alexander McArdle, Andrew Czap, Agata Rosenheim, Joshua Andrade, Catarina Anderson, Glenn Lee, Jack C. D. Williams, Rachel Williams, Charlotte A. Tutill, Helena Bayzid, Nadua Martin Bernal, Luz Marina Macpherson, Hannah Montgomery, Kylie-Ann Moore, Catherine Templeton, Kate Neill, Claire Holden, Matt Gunson, Rory Shepherd, Samantha J. Shah, Priyen Cooray, Samantha Voice, Marie Steele, Michael Fink, Colin Whittaker, Thomas E. Santilli, Giorgia Gissen, Paul Kaufer, Benedikt B. Reich, Jana Andreani, Julien Simmonds, Peter Alrabiah, Dimah K. Castellano, Sergi Chikowore, Primrose Odam, Miranda Rampling, Tommy Houlihan, Catherine Hoschler, Katja Talts, Tiina Celma, Cristina Gonzalez, Suam Gallagher, Eileen Simmons, Ruth Watson, Conall Mandal, Sema Zambon, Maria Chand, Meera Hatcher, James De, Surjo Baillie, Kenneth Semple, Malcolm Gracie Bellos, Evangelos Broderick, Claire Channon-Wells, Samuel De, Tisham D’Souza, Giselle Elorrieta, Leire Estramiana Estrada-Rivadeneyra, Diego Galassini, Rachel Habgood-Coote, Dominic Hamilton, Shea Jackson, Heather Kavanagh, James Marjaneh, Mahdi Moradi Menikou, Stephanie Nichols, Samuel Nijman, Ruud Patel, Harsita Pennisi, Ivana Powell, Oliver Reid, Ruth Vito, Ortensia Whittaker, Elizabeth Wilson, Clare Womersley, Rebecca Abdulla, Amina Darnell, Sarah Mustafa, Sobia Georgiou, Pantelis Manzano, Jesus-Rodriguez Moser, Nicolas Carter, Michael Tibby, Shane Cohen, Jonathan Davis, Francesca Kenny, Julia Wellman, Paul White, Marie Fish, Matthew Jennings, Aislinn Shankar-Hari Fidler, Katy Agranoff, Dan Richmond, Vivien Seal, Matthew Faust, Saul Owen, Dan Ensom, Ruth McKay, Sarah Mondo, Diana Shaji, Mariya Schra Infection Immunity and Inflammation Department Great Ormond Street Institute of Child Health University College London London United Kingdom Section for Paediatrics Department of Infectious Diseases Faculty of Medicine Imperial College London London United Kingdom Department of Microbiology Virology and Infection Control Great Ormond Street Hospital for Children NHS Foundation Trust London United Kingdom Section of Virology Department of Infectious Diseases Faculty of Medicine Imperial College London London United Kingdom University College London Mass Spectrometry Science Technology Platform Division of Biosciences University College London London United Kingdom Histopathology Department Great Ormond Street Hospital for Children NHS Foundation Trust London United Kingdom Research Department of Targeted Intervention Division of Surgery and Interventional Science University College London London United Kingdom Division of Infection and Immunity University College London London United Kingdom Gene Transfer Technology Group EGA-Institute for Women’s Health University College London London United Kingdom Genetics and Genomic Medicine Department Great Ormond Street Institute of Child Health University College London London United Kingdom Department of Neurodegenerative Disease Queen Square Institute of Neurology University College London London United Kingdom Wales Specialist Virology Centre Public Health Wales Microbiology Cardiff University Hospital of Wales Cardiff United Kingdom Department of Medical Microbiology Edinburgh Royal Infirmary Edinburgh United Kingdom Public Health Agency Northern Ireland Belfast United Kingdom School of Medicine University of St. Andrews St. Andrews United Kingdom Public Health Scotland Edinburgh United Kingdom West of Scotland Specialist Virology Centre Glasgow United Kingdom Micropathology Ltd University of Warwick Science Park Coventry United Kingdom Molecular and Cellular Immunology Great Ormond Street Institute of C

Since its first identification in Scotland, over 1,000 cases of unexplained paediatric hepatitis in children have been reported worldwide, including 278 cases in the UK1. Here we report an investigation of 38 cases, 6...

Since its first identification in Scotland, over 1,000 cases of unexplained paediatric hepatitis in children have been reported worldwide, including 278 cases in the UK¹. Here we report an investigation of 38 cases, 66 age-matched immunocompetent controls and 21 immunocompromised comparator participants, using a combination of genomic, transcriptomic, proteomic and immunohistochemical methods. We detected high levels of adeno-associated virus 2 (AAV2) DNA in the liver, blood, plasma or stool from 27 of 28 cases. We found low levels of adenovirus (HAdV) and human herpesvirus 6B (HHV-6B) in 23 of 31 and 16 of 23, respectively, of the cases tested. By contrast, AAV2 was infrequently detected and at low titre in the blood or the liver from control children with HAdV, even when profoundly immunosuppressed. AAV2, HAdV and HHV-6 phylogeny excluded the emergence of novel strains in cases. Histological analyses of explanted livers showed enrichment for T cells and B lineage cells. Proteomic comparison of liver tissue from cases and healthy controls identified increased expression of HLA class 2, immunoglobulin variable regions and complement proteins. HAdV and AAV2 proteins were not detected in the livers. Instead, we identified AAV2 DNA complexes reflecting both HAdV-mediated and HHV-6B-mediated replication. We hypothesize that high levels of abnormal AAV2 replication products aided by HAdV and, in severe cases, HHV-6B may have triggered immune-mediated hepatic disease in genetically and immunologically predisposed children. © 2023, The Author(s).

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Correction: Improving Nutrition and Activity Behaviors Using Digital Technology and Tailored Feedback: Protocol for the Tailored Diet and Activity (ToDAy) Randomized Controlled Trial

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JMIR research protocols 2020年第12期9卷 e25940页

作者： Rhiannon E Halse Charlene L Shoneye Christina M Pollard Jonine Jancey Jane A Scott Iain S Pratt Satvinder S Dhaliwal Richard Norman Leon M Straker Carol J Boushey Edward J Delp Fengqing Zhu Amelia J Harray Maria A Szybiak Anne Finch Joanne A McVeigh Barbara Mullan Clare E Collins Syed Aqif Mukhtar Kieran N Edwards Janelle D Healy Deborah A Kerr School of Public Health Curtin University Perth Western Australia Australia. East Metropolitan Health Service Perth Western Australia Australia. Cancer Council WA Perth Western Australia Australia. Health Psychology & Behavioural Medicine Research Group School of Psychology Curtin University Perth Western Australia Australia. School of Physiotherapy and Exercise Science Curtin University Perth Western Australia Australia. Cancer Epidemiology Program University of Hawaii Cancer Center Honolulu HI United States. Department of Nutrition Purdue University West Lafayette IN United States. School of Electrical and Computer Engineering Purdue University West Lafayette IN United States. School of Occupational Therapy Speech Therapy & Social Work Curtin University Perth Western Australia Australia. Movement Physiology Laboratory University of Witwatersrand Johannesburg South Africa. School of Health Sciences Faculty of Health and Medicine University of Newcastle Callaghan New South Wales Australia. Priority Research Centre in Physical Activity and Nutrition University of Newcastle Callaghan New South Wales Australia. Curtin Institute of Computation Curtin University Perth Western Australia Australia.

[This corrects the article DOI: 10.2196/12782.].

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Neglecting model structural uncertainty underestimates upper tails of flood hazard

arXiv

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arXiv 2017年

作者： Wong, Tony E. Klufas, Alexandra Srikrishnan, Vivek Keller, Klaus Earth and Environmental Systems Institute Pennsylvania State University University ParkPA16802 United States Department of Mathematics Wellesley College WellesleyMA02481 United States Department of Energy and Mineral Engineering Pennsylvania State University University ParkPA16802 United States Department of Geosciences Pennsylvania State University University ParkPA16802 United States Department of Engineering and Public Policy Carnegie Mellon University PittsburghPA15289 United States Department of Computer Science University of Colorado BoulderCO80309 United States

Coastal flooding drives considerable risks to many communities, but projections of future flood risks are deeply uncertain. The paucity of observations of extreme events often motivates the use of statistical approaches to model the distribution of extreme storm surge events. One key deep uncertainty that is often overlooked is model structural uncertainty. There is currently no strong consensus among experts regarding which class of statistical model to use as a "best practice". Robust management of coastal flooding risks requires coastal managers to consider the distinct possibility of non-stationarity in storm surges. This increases the complexity of the potential models to use, which tends to increase the data required to constrain the model. Here, we use a Bayesian model averaging approach to analyze the balance between (i) model complexity sufficient to capture decision-relevant risks and (ii) data availability to constrain complex model structures. We characterize deep model structural uncertainty through a set of calibration experiments. Specifically, we calibrate a set of models ranging in complexity using long-term tide gauge observations from the Netherlands and the United States. We find that in both considered cases, roughly half of the model weight is associated with the non-stationary models. Our approach provides a formal framework to integrate information across model structures, in light of the potentially sizable modeling uncertainties. By combining information from multiple models, our inference sharpens for the projected storm surge 100-year return levels, and estimated return levels increase by several centimeters. We assess the impacts of data availability through a set of experiments with temporal subsets and model comparison metrics. Our analysis suggests that about 70 years of data are required to stabilize estimates of the 100-year return level, for the locations and methods considered here. Copyright © 2017, The Authors. All rights reserv

关键词： Floods

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Title: Learning bundled care opportunities from electronic medical records

arXiv

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arXiv 2017年

作者： Chen, You Kho, Abel N. Liebovitz, David Ivory, Catherine Osmundson, Sarah Bian, Jiang Malin, Bradley A. Dept. of Biomedical Informatics School of Medicine Vanderbilt University NashvilleTN United States Institute for Public Health and Medicine Northwestern University ChicagoIL United States School of Medicine University of Chicago ChicagoIL United States School of Nursing Vanderbilt University NashvilleTN United States Dept. of Obstetrics and Gynecology School of Medicine Vanderbilt University NashvilleTN United States Dept. of Health Outcomes and Policy University of Florida GainesvilleFL United States Dept. of Biostatistics School of Medicine Vanderbilt University NashvilleTN United States Dept. of Electrical Engineering and Computer Science School of Engineering Vanderbilt University NashvilleTN United States

Objective: The traditional fee-for-service approach to healthcare leads to the management of a patient's conditions in an independent manner, inducing various negative consequences. It is recognized that a bundled care approach to healthcare-one that manages a collection of health conditions together-may enable greater efficacy and cost savings. However, it is not always evident which sets of conditions should be managed in a bundled manner. Thus, we investigated how a data-driven approach could be applied to automatically learn potential bundles and evaluate their plausibility. Methods: To accomplish this research, we designed a data-driven framework to infer clusters of health conditions, which we referred to as phenotypic patterns, via their shared clinical workflows, which we refer to as coordinating care patterns, from the data inherent in electronic medical records (EMRs). We applied the framework with approximately 16,500 inpatient stays from a large medical center. The plausibility of the inferred health condition clusters for bundled care was assessed through a survey (whose responses were analyzed via an analysis of variance (ANOVA) under a 95% confidence interval) of a panel of five experts. Furthermore, the face validity of the inferred health condition clusters was confirmed by evidence in the published literature. Results: The framework inferred four condition clusters: 1) fetal abnormalities, 2) late pregnancies, 3) prostate problems, and 4) chronic diseases (with congestive heart failure featuring prominently). Each cluster had evidence in the literature and was deemed to be plausible for bundled care via ANOVA on the survey responses under a 95% confidence interval. Conclusions: The findings suggest that data from EMRs can provide a basis for discovering new directions in bundled care. Still, translating such findings into actual care management will require further refinement, implementation, and evaluation. Copyright © 2017, The Authors. All right

关键词： Data mining

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Tweet for behavior change: Using social media for the dissemination of public health messages

arXiv

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arXiv 2017年

作者： Gough, Aisling Hunter, Ruth F. Ajao, Oluwaseun Jurek, Anna McKeown, Gary Hong, Jun Barrett, Eimear Ferguson, Marbeth McElwee, Gerry McCarthy, Miriam Kee, Frank UKCRC Centre of Excellence in Public Health Northern Ireland School of Medicine Dentistry & Biomedical Sciences Queen's University Belfast Belfast United Kingdom UKCRC Centre of Excellence in Public Health Northern Ireland School of Medicine Dentistry & Biological Sciences Queen's University Belfast Belfast United Kingdom School of Electronics Electrical Engineering & Computer Science Queen's University Belfast Belfast United Kingdom School of Psychology Queen's University Belfast Belfast United Kingdom Cancer Focus Northern Ireland Belfast United Kingdom Public Health Agency Northern Ireland Belfast United Kingdom

Background: Social media public health campaigns have the advantage of tailored messaging at low cost and large reach, but little is known about what would determine their feasibility as tools for inducing attitude and behavior change. Objective: The aim of this study was to test the feasibility of designing, implementing, and evaluating a social media–enabled intervention for skin cancer prevention. Methods: A quasi-experimental feasibility study used social media (Twitter) to disseminate different message "frames" related to care in the sun and cancer prevention. Phase 1 utilized the Northern Ireland cancer charity’s Twitter platform (May 1 to July 14, 2015). Following a 2-week "washout" period, Phase 2 commenced (August 1 to September 30, 2015) using a bespoke Twitter platform. Phase 2 also included a Thunderclap, whereby users allowed their social media accounts to automatically post a bespoke message on their behalf. Message frames were categorized into 5 broad categories: humor, shock or disgust, informative, personal stories, and opportunistic. Seed users with a notable following were contacted to be "influencers" in retweeting campaign content. A pre- and postintervention Web-based survey recorded skin cancer prevention knowledge and attitudes in Northern Ireland (population 1.8 million). Results: There were a total of 417,678 tweet impressions, 11,213 engagements, and 1211 retweets related to our campaign. Shocking messages generated the greatest impressions (shock, n=2369;informative, n=2258;humorous, n=1458;story, n=1680), whereas humorous messages generated greater engagement (humorous, n=148;shock, n=147;story, n=117;informative, n=100) and greater engagement rates compared with story tweets. Informative messages, resulted in the greatest number of shares (informative, n=17;humorous, n=10;shock, n=9;story, n=7). The study findings included improved knowledge of skin cancer severity in a pre- and postintervention Web-based survey, with greater awareness

关键词： Dermatology

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Advances in Microwave Ablation Antennas for Breast Tumor Treatment

Advances in Microwave Ablation Antennas for Breast Tumor Tre...

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European Conference on Antennas and Propagation

作者： R. Owen Mays L. M. Neira H. Luyen L. G. Wilke N. Behdad S. C. Hagness Department of Electrical and Computer Engineering College of Engineering University of Wisconsin-Madison Madison WI USA Department of Surgery School of Medicine and Public Health University of Wisconsin-Madison Madison WI USA

ISBN: (纸本)9781509022342

In contrast to other types of cancer, breast cancer remains a relatively unexplored target for microwave ablation (MWA) technology. We highlight two recent developments towards the clinical realization of MWA for breast tumor treatment: the design of miniaturized MWA antennas that achieve compact heating patterns without the use of a balun and the investigation of microwave-induced heating in the heterogeneous tissue environment of the breast. Our electromagnetic and thermal simulation results using 3D MRI-derived breast phantoms as testbeds show the potential of MWA as a viable minimally invasive modality for treating breast cancer.

关键词： microwave ablation miniaturized antennas microwave thermal therapy breast cancer treatment breast phantoms

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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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International Conference on Applied System Innovation (ICASI)

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

ISBN: (纸本)9781509048984

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.

关键词： Dispatching Technological innovation MATLAB Feature extraction Roads Urban areas Conferences

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Promoting resilience for food, energy, and water interdependencies

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Journal of Environmental Studies and Sciences 2016年第1期6卷 50-61页

作者： Zimmerman, Rae Zhu, Quanyan Dimitri, Carolyn Institute for Civil Infrastructure Systems (www.nyu.edu/icis) Robert F. Wagner Graduate School of Public Service New York University 295 Lafayette Street–2nd Floor New York 10012 NY United States Department of Electrical and Computer Engineering Tandon School of Engineering New York University 5 MetroTech Center-LC200A Brooklyn 11201 NY United States Departments of Nutrition Food Studies and Public Health Steinhardt School New York University New York 10003 NY United States

This paper presents relationships among food, energy, and water (FEW) systems, reflecting the interconnections among the energy/water, water/energy, water/food, and energy/food sectors. First, a unique approach uses metrics and quantification to reflect interdependencies among these sectors. Next, changes in food technology and practices are put forth in terms of impacts changes are likely to produce for a set of FEW system relationships. Organic farming or shifts in food consumption patterns, such as reduced meat consumption, are two examples of changes in food technology and practices that could affect water and energy use. From a policy perspective, changes in energy and water policy can potentially facilitate increased water conservation and greater use of renewable energy sources;such policy shifts are addressed in terms of changes to metrics and/or their values. The purpose of this work is to establish a network model that quantifies interdependencies among different sectors in terms of resource usage. The model is flexible and can accommodate other factors such as cyberphysical and logical interdependencies. The established model that these metrics provide inputs for enables analysis and design of the resilience mechanisms for FEW complex systems. Examples are used to illustrate the concepts developed in this work. © 2016, AESS.

关键词： Food-energy-water production tradeoffs Infrastructure interdependencies Network analysis Organic agriculture Resilience

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