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作者： Mikic, Borjana Howe, Susannah Stables, Fraser Middlebrook, James Hauser, Angie Aiken, Chris Johnson, Reid Bertone Mendelowitz, Eitan Picker Engineering Program Smith College NorthamptonMA01063 United States Department of Art Smith College NorthamptonMA01063 United States Department of Dance Smith College NorthamptonMA01063 United States Program in Landscape Studies Smith College NorthamptonMA01063 United States Department of Computer Science Smith College NorthamptonMA01063 United States

The national conversation regarding the future of liberal arts education often fixates on a false dichotomy between the humanities and STEM fields;thus, the time seems right to reimagine a framework in which the humanities, social sciences and STEM fields work in synergy to not only prepare students for creative engagement with the complex and challenging problems facing our world, but also for the active creation of the new realities that they have imagined as possible. In this paper, we describe the origins and progress to date of a pilot cross-campus initiative in Design Thinking and the Liberal Arts at Smith College, an all women's residential liberal arts college in Northampton, MA. In addition, we share insights from our experiences to assist those at other institutions who might be interested in engaging in similar kinds of endeavors. © 2016 TEMPUS Publications.

关键词： Students

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Neuroimaging Biomarkers of cognitive Decline in Healthy Older Adults via Unified Learning

Neuroimaging Biomarkers of Cognitive Decline in Healthy Olde...

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IEEE Symposium Series on Computational Intelligence

作者： Tayo Obafemi-Ajayi Khalid Al-Jabery Lauren Salminen David Laidlaw Ryan Cabeen Donald Wunsch Robert Paul Engineering Program Missouri State University Springfield MO Dept. of Electrical and Computer Eng. Missouri University of Science and Technology Rolla MO University of Southern California Imaging Genetics Center Los Angeles CA Dept. of Computer Science Brown University Providence RI USC Stevens Neuroimaging and Informatics Institute Los Angeles CA Dept. of Psychological Sciences University of Missouri St. Louis MO

cognitive aging in healthy adults exhibits significant and heterogeneous variability. In this study, we apply a robust unified learning framework to cluster subgroups using neuroimaging data (brain volume and white matter), to identify neurological phenotypes that can sort out the heterogeneity in cognitive aging and help identify potential risk factors for suboptimal brain aging. Using machine learning analytics, results revealed two unique subgroups in healthy older adults with different patterns of white matter integrity and brain volumetric measures. The classification of phenotypical subgroups in healthy older adults may inform the understanding of the complexity of brain changes before the onset of clinical symptoms. The identified neuroimaging features that defined group classification are recognized as important structures that subserve cognitive performance. Further analysis of these potential biomarkers that help predict trajectory of cognitive decline in symptom free individuals could lead to the detection of early stages of neurodegenerative diseases.

关键词： Neuroimaging Feature extraction Aging Clustering algorithms Algorithm design and analysis Predictive models Biological system modeling

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Publisher Correction: MEMOTE for standardized genome-scale metabolic model testing

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Nature biotechnology 2020年第4期38卷 504页

作者： Christian Lieven Moritz E Beber Brett G Olivier Frank T Bergmann Meric Ataman Parizad Babaei Jennifer A Bartell Lars M Blank Siddharth Chauhan Kevin Correia Christian Diener Andreas Dräger Birgitta E Ebert Janaka N Edirisinghe José P Faria Adam M Feist Georgios Fengos Ronan M T Fleming Beatriz García-Jiménez Vassily Hatzimanikatis Wout van Helvoirt Christopher S Henry Henning Hermjakob Markus J Herrgård Ali Kaafarani Hyun Uk Kim Zachary King Steffen Klamt Edda Klipp Jasper J Koehorst Matthias König Meiyappan Lakshmanan Dong-Yup Lee Sang Yup Lee Sunjae Lee Nathan E Lewis Filipe Liu Hongwu Ma Daniel Machado Radhakrishnan Mahadevan Paulo Maia Adil Mardinoglu Gregory L Medlock Jonathan M Monk Jens Nielsen Lars Keld Nielsen Juan Nogales Intawat Nookaew Bernhard O Palsson Jason A Papin Kiran R Patil Mark Poolman Nathan D Price Osbaldo Resendis-Antonio Anne Richelle Isabel Rocha Benjamín J Sánchez Peter J Schaap Rahuman S Malik Sheriff Saeed Shoaie Nikolaus Sonnenschein Bas Teusink Paulo Vilaça Jon Olav Vik Judith A H Wodke Joana C Xavier Qianqian Yuan Maksim Zakhartsev Cheng Zhang Novo Nordisk Foundation Center for Biosustainability Technical University of Denmark Lyngby Denmark. Systems Biology Lab Amsterdam Institute of Molecular and Life Sciences (AIMMS) Vrije Universiteit Amsterdam Amsterdam the Netherlands. BioQUANT/COS Heidelberg University Heidelberg Germany. Ecole Polytechnique Fédérale de Lausanne Laboratory of Computational Systems Biotechnology Lausanne Switzerland. iAMB-Institute of Applied Microbiology ABBt-Aachen Biology and Biotechnology RWTH Aachen University Aachen Germany. Department of Bioengineering University of California La Jolla CA USA. Department of Chemical Engineering and Applied Chemistry University of Toronto Toronto Ontario Canada. Human Systems Biology Laboratory Instituto Nacional de Medicina Genomica & Coordinación de la Investigación Científica-Red de Apoyo a la Investigación UNAM Mexico City Mexico. Institute for Systems Biology Seattle WA USA. Computational Systems Biology of Infection and Antimicrobial-Resistant Pathogens Institute for Biomedical Informatics (IBMI) Tübingen Germany. Department of Computer Science University of Tübingen Tübingen Germany. German Center for Infection Research (DZIF) partner site Tübingen Tübingen Germany. Australian Institute for Bioengineering and Nanotechnology The University of Queensland Brisbane Queensland Australia. Argonne National Laboratory Lemont IL USA. Analytical Biosciences Division of Systems Biomedicine and Pharmacology Leiden Academic Centre for Drug Research Leiden University Leiden the Netherlands. Department of Systems Biology Centro Nacional de Biotecnología Consejo Superior de Investigaciones Científicas (CNB-CSIC) Madrid Spain. Centro de Biotecnología y Genómica de Plantas (CBGP UPM-INIA) Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA) Madrid Spain. Department of Animal and Aquacultural Sciences Faculty of Biosciences Norwegian University of Life Sciences Oslo Norway

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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Fuzzy techniques provide a theoretical explanation for the heuristic ℓp-regularization of signals and images

Fuzzy techniques provide a theoretical explanation for the h...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Fernando Cervantes Brian Usevitch Leobardo Valera Vladik Kreinovich Olga Kosheleva Department of Electrical and Computer Engineering University of Texas at El Paso El Paso TX USA Computational Science Program University of Texas at El Paso El Paso TX USA

ISBN: (纸本)9781509006274

One of the main techniques used to de-noise and deblur signals and images is regularization, which is based on the fact that signals and images are usually smoother than noise. Traditional Tikhonov regularization assumes that signals and images are differentiable, but, as Mandelbrot has shown in his fractal theory, many signals and images are not differentiable. To de-noise and de-blur such images, researchers have designed a heuristic method of ℓ p -regularization. ℓ p -regularization leads to good results, but it is not used as widely as should be, because it lacks a convincing theoretical explanation - and thus, practitioners are often reluctant to use it, especially in critical situations. In this paper, we show that fuzzy techniques provide a theoretical explanation for the ℓ p -regularization. Fuzzy techniques also enables us to come up with natural next approximations to be used when the accuracy of the ℓ p -based denoising and de-blurring is not sufficient.

关键词： Image reconstruction Time measurement Measurement units Distortion measurement Noise reduction Fractals Conferences

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On the Study of PEM Fuel Cells by Transmission Electron Microscopy

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Microscopy and Microanalysis 2016年第S3期22卷 1280-1281页

作者： S. Rasouli D. Groom K. Yu A. Godoy A. Bovik D. Myers Naotoshi Nakashima P. J. Ferreira Materials Science and Engineering Program University of Texas at Austin Austin TX Department of Electrical and Computer Engineering University of Texas at Austin Austin TX Argonne National Laboratory Argonne Illinois United States Department of Applied Chemistry Kyushu University Fukuoka Japan

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Design of Decision Support System Determination of Inventory Inventory Using Single Exponential Smoothing Forecasting Method

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Muhammad Iqbal Dahlan Abdullah H Hartono Cut Ita Erliana S Sriadhi Nurmawati M Adhi Prasnowo Abdurrozzaq Hasibuan Akbar Iskandar Kundharu Saddhono Abdussakir Hastuti Musa Muhammad Ikhsan Setiawan Youmeni Sagala Rumiris Siahaan Eka Mayastika Sinaga Anggraini Syahputri Feby Milanie Henry Aspan Muammar Khaddafi Department of Computer System Universitas Pembangunan Panca Budi Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Department of Industrial Engineering Universitas Maarif Hasyim Latif Sidoarjo Indonesia Faculty of Engineering Universitas Islam Sumatera UtaraMedan-Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Mathematics Education State Islamic University of Malang Malang Indonesia Department of Mathematics Universitas Muhammadiyah Parepare Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia STIE Bina Karya Tebing Tinggi Indonesia Universitas Pembangunan Panca Budi Medan Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

The development of information and communication technology at this time has touched all sides of life. Almost no side of human life is not touched by this information technology, which is more synonymous with the world of computerization. No exception also with the computerization that is popular in the corporate environment and government agencies. If in ancient times everything was still done manually. However, at this time all leaders and management have realized the importance of this information technology products that can facilitate them in carrying out the day-to-day corporate functions. Decision Making System of goods purchasing is one of the determinants of the accumulation of goods. If the decision is taken right then stockpiling of goods can be avoided. In this thesis the authors designed a web-based system that helps Management in making the decision of the purchase amount of goods. the system was developed by using Microsoft Visual Studio 2010 and using SQL Server database processing applications. The end result of system design is expected to help minimize the accumulation of goods.

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Author Correction: A consensus protocol for functional connectivity analysis in the rat brain

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Nature neuroscience 2023年 2023 Apr 18页

作者： Joanes Grandjean Gabriel Desrosiers-Gregoire Cynthia Anckaerts Diego Angeles-Valdez Fadi Ayad David A Barrière Ines Blockx Aleksandra Bortel Margaret Broadwater Beatriz M Cardoso Marina Célestine Jorge E Chavez-Negrete Sangcheon Choi Emma Christiaen Perrin Clavijo Luis Colon-Perez Samuel Cramer Tolomeo Daniele Elaine Dempsey Yujian Diao Arno Doelemeyer David Dopfel Lenka Dvořáková Claudia Falfán-Melgoza Francisca F Fernandes Caitlin F Fowler Antonio Fuentes-Ibañez Clément M Garin Eveline Gelderman Carla E M Golden Chao C G Guo Marloes J A G Henckens Lauren A Hennessy Peter Herman Nita Hofwijks Corey Horien Tudor M Ionescu Jolyon Jones Johannes Kaesser Eugene Kim Henriette Lambers Alberto Lazari Sung-Ho Lee Amanda Lillywhite Yikang Liu Yanyan Y Liu Alejandra López-Castro Xavier López-Gil Zilu Ma Eilidh MacNicol Dan Madularu Francesca Mandino Sabina Marciano Matthew J McAuslan Patrick McCunn Alison McIntosh Xianzong Meng Lisa Meyer-Baese Stephan Missault Federico Moro Daphne M P Naessens Laura J Nava-Gomez Hiroi Nonaka Juan J Ortiz Jaakko Paasonen Lore M Peeters Mickaël Pereira Pablo D Perez Marjory Pompilus Malcolm Prior Rustam Rakhmatullin Henning M Reimann Jonathan Reinwald Rodrigo Triana Del Rio Alejandro Rivera-Olvera Daniel Ruiz-Pérez Gabriele Russo Tobias J Rutten Rie Ryoke Markus Sack Piergiorgio Salvan Basavaraju G Sanganahalli Aileen Schroeter Bhedita J Seewoo Erwan Selingue Aline Seuwen Bowen Shi Nikoloz Sirmpilatze Joanna A B Smith Corrie Smith Filip Sobczak Petteri J Stenroos Milou Straathof Sandra Strobelt Akira Sumiyoshi Kengo Takahashi Maria E Torres-García Raul Tudela Monica van den Berg Kajo van der Marel Aran T B van Hout Roberta Vertullo Benjamin Vidal Roël M Vrooman Victora X Wang Isabel Wank David J G Watson Ting Yin Yongzhi Zhang Stefan Zurbruegg Sophie Achard Sarael Alcauter Dorothee P Auer Emmanuel L Barbier Jürgen Baudewig Christian F Beckmann Nicolau Beckmann Guillaume J P C Becq Erwin L A Blezer Radu Bolbos Susann Boretius Sandrine Bouvard Eike Budinger Joseph D Buxbaum Diana Cash Victor Donders Institute for Brain Behaviour and Cognition Radboud University Nijmegen The Netherlands. joanes.grandjean@radboudumc.nl. Department for Medical Imaging Radboud University Medical Center Nijmegen The Netherlands. joanes.grandjean@radboudumc.nl. Cerebral Imaging Centre Douglas Mental Health University Institute Verdun QC Canada. Integrated Program in Neuroscience McGill University Montreal QC Canada. Bio-imaging Lab University of Antwerp Antwerp Belgium. µNEURO Research Centre of Excellence University of Antwerp Antwerp Belgium. Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro Mexico. Biological and Biomedical Engineering McGill University Montreal QC Canada. McConnell Brain Imaging Centre McGill University Montreal QC Canada. Montreal Neurological Institute McGill University Montreal QC Canada. UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction Physiologie de la reproduction et des comportements Centre de recherche INRAE de Nouzilly Tours France. Department of Neurology and Neurosurgery McGill University Montreal QC Canada. Center for Animal MRI University of North Carolina at Chapel Hill Chapel Hill NC USA. Department of Neurology University of North Carolina at Chapel Hill Chapel Hill NC USA. Biomedical Research Imaging Center University of North Carolina at Chapel Hill Chapel Hill NC USA. Preclinical MRI Champalimaud Research Champalimaud Centre for the Unknown Lisbon Portugal. Laboratoire des Maladies Neurodégénératives Molecular Imaging Research Center (MIRCen) Université Paris-Saclay Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA) CNRS Fontenay-aux-Roses France. Departamento de Neurobiología Conductual y Cognitiva Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro México. Translational Neuroimaging and Neural Control Group High-Field Magnetic Resonance Max Planck Institute for Biological Cyberneti

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Retraction: Design of Decision Support System Determination of Inventory Inventory Using Single Exponential Smoothing Forecasting Method (J. Phys.: Conf. Ser. 1114 012082)

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Journal of Physics: Conference Series 2018年第1期1114卷

This paper was retracted by IOP Publishing on 12 December 2018. This paper was published due to a technical error and was not intended to be included in this journal. Retraction published: 8 February 2019

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Discriminative fusion of multiple brain networks for early mild cognitive impairment detection

Discriminative fusion of multiple brain networks for early m...

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IEEE International Symposium on Biomedical Imaging

作者： Qi Wang Liang Zhan Paul M. Thompson Hiroko H. Dodge Jiayu Zhou Computer Science and Engineering Michigan State University East Lansing MI Computer Engineering Program University of Wisconsin-Stout Menomonie WI Imaging Genetics Center University of Southern California Marina del Rey CA Michigan Alzheimer's Disease Center University of Michigan Ann Arbor MI Department of Neurology Oregon Health & Science University Portland OR

ISBN: (纸本)9781479923519

In neuroimaging research, brain networks derived from different tractography methods may lead to different results and perform differently when used in classification tasks. As there is no ground truth to determine which brain network models are most accurate or most sensitive to group differences, we developed a new sparse learning method that combines information from multiple network models. We used it to learn a convex combination of brain connectivity matrices from 9 different tractography methods, to optimally distinguish people with early mild cognitive impairment from healthy control subjects, based on the structural connectivity patterns. Our fused networks outperformed the best single network model, Probtrackx (0.89 versus 0.77 cross-validated AUC), suggesting its potential for numerous connectivity analysis.

关键词： Magnetic resonance imaging Brain models Diseases Probabilistic logic Prediction algorithms Sensitivity

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Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000-17: analysis for the Global Burden of Disease Study 2017 (vol 395, pg 1779, 2020)

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LANCET 2020年第10239期395卷 1762-1762页

作者： Reiner, R. C., Jr. Hay, S., I Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Global Health School of Medicine University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States College of Health and Medical Sciences Haramaya University Harar Ethiopia Department of Epidemiology and Biostatistics Haramaya University Harar Ethiopia Department of Medical Laboratory Sciences Haramaya University Harar Ethiopia School of Nursing and Midwifery Haramaya University Harar Ethiopia School of Pharmacy Haramaya University Harar Ethiopia School of Public Health Haramaya University Harar Ethiopia Haramaya University Harar Ethiopia Advanced Diagnostic and Interventional Radiology Research Center Tehran University of Medical Sciences Tehran Iran Cancer Biology Research Center Tehran University of Medical Sciences Tehran Iran Cancer Research Institute Tehran University of Medical Sciences Tehran Iran Department of Economics and Management Sciences for Health Tehran University of Medical Sciences Tehran Iran Department of Environmental Health Engineering Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Department of Health Management and Economics Tehran University of Medical Sciences Tehran Iran Department of Microbiology Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Center Tehran University of Medical Sciences Tehran Iran Hematology-Oncology and Stem Cell Transplantation Research Center Tehran University of Medical Sciences Tehran Iran Iran National Institute of Health Research Tehran University of Medical Sciences Tehran Iran Metabolomics and

Summary Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood *** We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor *** The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1-65·8), 17·4% (7·7-28·4), and 59·5% (34·2-86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy *** By co-analysing geospatial trends in d

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