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International Conference on Computers and Computing, ICCC'11

作者： Robu, Andreea Stoicu-Tivadar, Lacramioara Neagu, Adrian Department of Automation and Applied Informatics Politehnica University of Timisoara 2 Vasile Parvan Bv. 300223 Timişoara Romania Center for Modeling Biological Systems and Data Analysis Department of Biophysics and Medical Informatics Victor Babes University of Medicine and Farmacy Timisoara 2 Eftimie Murgu Bv. 300041 Timisoara Romania

ISBN: (纸本)9781618040008

Tissue engineering is a revolutionary domain which offers an alternative to traditional transplants, through in vitro synthesis of tissue constructs. Tissue constructs are obtained by harvesting cells extracted from patients, on a porous scaffold. The quality of the tissue construct and the rapidity with which it is obtained are two very important factors for clinical applications. The paper presents the evolution of a spherical multicellular aggregate located on the surface of a porous scaffold, observing the conditions that lead to an uniform and rapid distribution of cells in the scaffold. The evolution of the multicellular system was simulated using an algorithm based on the Metropolis Monte Carlo method, considering that cells tend to form a large number of connections with their neighbours (other cells or substrate). Based on different configurations obtained after running a number of Monte Carlo steps, the influence of the cell-cell interaction energy, the cellsubstrate interaction energy as well as the influence of the scaffold's geometry on the distribution of cells in the scaffold is studied. An analysis is made on the evolution of the cells' centre of mass , as well as on the evolution of the concentration of cells remained in the culture medium, after running a number of Monte Carlo steps.

关键词： Cells

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Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science : Seattle, WA, USA. 24-26 September 2015

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Implementation science : IS 2016年第1期11 Suppl 1卷 85页

作者： Cara Lewis Doyanne Darnell Suzanne Kerns Maria Monroe-DeVita Sara J. Landes Aaron R. Lyon Cameo Stanick Shannon Dorsey Jill Locke Brigid Marriott Ajeng Puspitasari Caitlin Dorsey Karin Hendricks Andria Pierson Phil Fizur Katherine A. Comtois Lawrence A. Palinkas Patricia Chamberlain Gregory A. Aarons Amy E. Green Mark. G. Ehrhart Elise M. Trott Cathleen E. Willging Maria E. Fernandez Nicholas H. Woolf Shuting Lily Liang Natalia I. Heredia Michelle Kegler Betsy Risendal Andrea Dwyer Vicki Young Dayna Campbell Michelle Carvalho Yvonne Kellar-Guenther Laura J. Damschroder Julie C. Lowery Sarah S. Ono Kathleen F. Carlson Erika K. Cottrell Maya E. O’Neil Travis L. Lovejoy Joanna J. Arch Jill L. Mitchell Cara C. Lewis Brigid R. Marriott Kelli Scott Jennifer Schurer Coldiron Eric J. Bruns Alyssa N. Hook Benjamin C. Graham Katelin Jordan Rochelle F. Hanson Angela Moreland Benjamin E. Saunders Heidi S. Resnick Shannon Wiltsey Stirman Cassidy A. Gutner Jennifer Gamarra Dawne Vogt Michael Suvak Jennifer Schuster Wachen Katherine Dondanville Jeffrey S. Yarvis Jim Mintz Alan L. Peterson Elisa V. Borah Brett T. Litz Alma Molino Stacey Young McCaughan Patricia A. Resick Nancy Pandhi Nora Jacobson Neftali Serrano Armando Hernandez Elizabeth Zeidler- Schreiter Natalie Wietfeldt Zaher Karp Michael D. Pullmann Barbara Lucenko Bridget Pavelle Jacqueline A. Uomoto Andrea Negrete Molly Cevasco Suzanne E. U. Kerns Robert P. Franks Christopher Bory Edward J. Miech Teresa M. Damush Jason Satterfield Derek Satre Maria Wamsley Patrick Yuan Patricia O’Sullivan Helen Best Susan Velasquez Miya Barnett Lauren Brookman-Frazee Jennifer Regan Nicole Stadnick Alison Hamilton Anna Lau Scott Roesch Byron J. Powell Thomas J. Waltz Matthew J. Chinman Laura Damschroder Jeffrey L. Smith Monica M. Matthieu Enola K. Proctor JoAnn E. Kirchner Monica J. Matthieu Craig S. Rosen Sarah C. Walker Asia S. Bishop Mariko Lockhart Allison L. Rodriguez Luisa Manfredi Andrea Nevedal Joel Rosenthal Daniel M. Blonigen Anne M. Mauricio Thomas D. Dishion Jenna Rudo-Stern Department of Psychological and Brain Sciences Indiana University Bloomington USA Department of Psychiatry & Behavioral Sciences University of Washington Seattle USA Psychology Department University of Montana Missoula USA Department of Psychology La Salle University Philadelphia USA Division of Public Behavioral Health and Justice Policy University of Washington Seattle USA National Center for PTSD VA Palo Alto Health Care System Menlo Park USA Department of Psychiatry University of Arkansas for Medical Sciences Little Rock USA Department of Psychology University of Washington Seattle USA Department of Speech and Hearing Sciences University of Washington Seattle USA Department of Psychological Sciences University of Missouri Columbia USA Department of Children Youth and Families School of Social Work University of Southern California Los Angeles USA Oregon Social Learning Center Eugene USA Department of Psychiatry University of California San Diego La Jolla USA Child and Adolescent Services Research Center (CASRC) San Diego USA Department of Psychology San Diego State University San Diego USA Pacific Institute for Research and Evaluation Behavioral Health Research Center of the Southwest Albuquerque USA School of Public Health University of Texas Health Science Center at Houston Houston USA Woolf Consulting Santa Barbara USA Rollins School of Public Health Emory University Atlanta USA University of Colorado Cancer Center at Denver Aurora USA South Carolina Primary Health Care Association Columbia USA Veterans Affairs (VA) Ann Arbor Center for Clinical Management Research Ann Arbor USA Personalizing Options through Veteran Engagement (PROVE) Quality Enhancement Research Initiative (QUERI) Program Ann Arbor USA Center to Improve Veteran Involvement in Care (CIVIC) Veterns Affairs (VA) Portland Health Care System (VAPORHCS) Portland USA Department of Family Medicine Oregon Health & Science University Portland USA Division of General Internal Medi

Introduction to the 3rd Biennial Conference of the Society for Implementation Research Collaboration: advancing efficient methodologies through team science and community partnerships Cara Lewis, Doyanne Darnell, Suzanne Kerns, Maria Monroe-DeVita, Sara J. Landes, Aaron R. Lyon, Cameo Stanick, Shannon Dorsey, Jill Locke, Brigid Marriott, Ajeng Puspitasari, Caitlin Dorsey, Karin Hendricks, Andria Pierson, Phil Fizur, Katherine A. Comtois A1: A behavioral economic perspective on adoption, implementation, and sustainment of evidence-based interventions Lawrence A. Palinkas A2: Towards making scale up of evidence-based practices in child welfare systems more efficient and affordable Patricia Chamberlain A3: Mixed method examination of strategic leadership for evidence-based practice implementation Gregory A. Aarons, Amy E. Green, Mark. G. Ehrhart, Elise M. Trott, Cathleen E. Willging A4: Implementing practice change in Federally Qualified Health Centers: Learning from leaders’ experiences Maria E. Fernandez, Nicholas H. Woolf, Shuting (Lily) Liang, Natalia I. Heredia, Michelle Kegler, Betsy Risendal, Andrea Dwyer, Vicki Young, Dayna Campbell, Michelle Carvalho, Yvonne Kellar-Guenther A3: Mixed method examination of strategic leadership for evidence-based practice implementation Gregory A. Aarons, Amy E. Green, Mark. G. Ehrhart, Elise M. Trott, Cathleen E. Willging A4: Implementing practice change in Federally Qualified Health Centers: Learning from leaders’ experiences Maria E. Fernandez, Nicholas H. Woolf, Shuting (Lily) Liang, Natalia I. Heredia, Michelle Kegler, Betsy Risendal, Andrea Dwyer, Vicki Young, Dayna Campbell, Michelle Carvalho, Yvonne Kellar-Guenther A5: Efficient synthesis: Using qualitative comparative analysis and the Consolidated Framework for Implementation Research across diverse studies Laura J. Damschroder, Julie C. Lowery A6: Establishing a veterans engagement group to empower patients and inform Veterans Affairs (VA) health services research Sara

关键词： Veteran Affair Motivational Interview Veteran Health Administration Dialectical Behavior Therapy Qualitative Comparative analysis

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Feature selection in high dimensional EEG features spaces for epileptic seizure prediction

Feature selection in high dimensional EEG features spaces fo...

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作者： Direito, Bruno Duarte, João Teixeira, César Schelter, Björn Le Van Quyen, Michel Schulze-Bonhage, Andreas Sales, Francisco Dourado, António Center for Informatics and Systems of the University of Coimbra University of Coimbra Portugal IBILI - Institute of Biomedical Research in Light and Image Faculty of Medicine University of Coimbra Portugal Centre de Recherche Institut du Cerveau et de la Moelle Epinière-INSERM Hôpital de la Pitié-Salpêtrière Germany Freiburg Center for Data Analysis and Modelling Albert-Ludwigs-Universität Freiburg Germany Epilepsy Center University Hospital of Freiburg Germany Hospitals of the University of Coimbra Portugal

ISBN: (纸本)9783902661937

Digital signal processing of Electroencephalogram (EEG) can support the diagnosis and alarming for the benefit of humans. About one third of all epileptic patients suffer from refractory epilepsy;seizure prediction based on the EEG information content is an area of intense activity since at least twenty years. In this paper we analyze the high dimensional feature space created by a variety of feature extraction methods for prediction of epileptic seizures. We combined features selection algorithm minimum redundancy maximum relevance (mRMR) and Support Vector Machines (SVMs) architectures to study the best features set for seizure prediction. We present the comparison between the classification results obtained by a feature set composed by 147 features and a reduced set based on the first 20-ranked features using mRMR scores. We critically discuss the composition of the feature subset. The results suggest some patient specificity in features and channel selection. The best models lead us to hypothesize the preference for wider preictal periods. © 2011 IFAC.

关键词： Classification (of information)

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Prediction of gestation length and nipple retention in rats after mixed exposure to low doses of dissimilarly acting endocrine disrupting pesticides

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Reproductive Toxicology 2011年第2期32卷 168-168页

作者： Pernille Rosenskjold Jacobsen Sofie Christiansen Line Harder Clemmensen Marta Axelstad Bjarne K. Ersbøll Ulla Hass Division of Toxicology and Risk Assessment National Food Institute Technical University of Denmark Denmark Division of Data Analysis Informatics and Mathematical Modelling Technical University of Denmark Denmark

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Feature selection in high dimensional EEG features spaces for epileptic seizure prediction

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IFAC Proceedings Volumes 2011年第1期44卷 6206-6211页

作者： Bruno Direito João Duarte César Teixeira Björn Schelter Michel Le Van Quyen Andreas Schulze-Bonhage Francisco Sales António Dourado Center for Informatics and Systems of the University of Coimbra University of Coimbra Portugal IBILI – Institute of Biomedical Research in Light and Image Faculty of Medicine of the University of Coimbra Portugal Centre de Recherche de l'Institut du Cerveau et de la Moelle Epinière-INSERM Unité Mixte de Recherche en Santé 975-Centre National de la Recherche Scientifique Unité Mixte de Recherche 7225 Hôpital de la Pitié-Salpětrière Freiburg Center for Data Analysis and Modelling Albert-Ludwigs-Universität Freiburg Germany Epilepsy Center University Hospital of Freiburg Germany Hospitals of the University of Coimbra Portugal

Abstract Digital signal processing of Electroencephalogram (EEG) can support the diagnosis and alarming for the benefit of humans. About one third of all epileptic patients suffer from refractory epilepsy; seizure prediction based on the EEG information content is an area of intense activity since at least twenty years. In this paper we analyze the high dimensional feature space created by a variety of feature extraction methods for prediction of epileptic seizures. We combined features selection algorithm minimum redundancy maximum relevance (mRMR) and Support Vector Machines (SVMs) architectures to study the best features set for seizure prediction. We present the comparison between the classification results obtained by a feature set composed by 147 features and a reduced set based on the first 20-ranked features using mRMR scores. We critically discuss the composition of the feature subset. The results suggest some patient specificity in features and channel selection. The best models lead us to hypothesize the preference for wider preictal periods.

关键词： Classification Methods Classification Feature Selection Seizure Prediction Epilepsy

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A computer simulation study of cell seeding of a porous biomaterial

A computer simulation study of cell seeding of a porous biom...

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IEEE International Joint Conferences on Computational Cybernetics and Technical informatics, ICCC-CONTI 2010

作者： Robu, A.P. Neagu, A. Stoicu-Tivadar, L. Department of Automation and Applied Informatics Politehnica University of Timisoara Bd. Vasile Parvan no. 2 300223 Timisoara Romania Center for Modeling Biological Systems Data Analysis Department of Biophysics and Medical Informatics Victor Babes University of Medicine and Farmacy Timisoara Bd. Eftimie Murgu no.2 300041 Timisoara Romania

ISBN: (纸本)9781424474332

Tissue engineering is a part of regenerative medicine that handles in vitro creation of biological tissue substitutes which may repair or substitute injured or diseased parts of the body. In order to create tissue structures, biocompatible materials with a porous structure (scaffolds) are used as support for cells. The paper presents the stages of development and the software application that results, used as support for the study of cell seeding of a three-dimensional scaffold. The application uses an algorithm based on the Metropolis Monte Carlo method. The program was developed by using the Visual *** programming environment. Ideally, cell seeding should be fast and should achieve an uniform distribution of the cell population in the scaffold. In a first stage, the program creates the initial configuration of the system consisting of a cell suspension placed in the neighborhood of a scaffold immersed in cell culture medium. Starting from this configuration, using our software application the movement of the cells in suspension is studied as well as their potential of getting attached to the biomaterial. © 2010 IEEE.

关键词： Cell culture

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A computer simulation study of cell seeding of a porous biomaterial

A computer simulation study of cell seeding of a porous biom...

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International Conference on Computational Cybernetics (ICCC)

作者： A. P. Robu A. Neagu L. Stoicu-Tivadar Department of Automation and Applied Informatics Politehnica University Timisoara Timisoara Romania Center for Modeling Biological Systems and Data Analysis Department of Biophysics and Medical Informatics Victor Babes University of Medicine and Pharmacy Timisoara Timisoara Romania

ISBN: (纸本)9781424474325;9781424474332

关键词： Computer simulation Application software Tissue engineering Regeneration engineering In vitro Biological tissues Biological materials Biomedical materials Programming environments Potential well

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ParaText: Scalable text modeling and analysis 10

ParaText: Scalable text modeling and analysis

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Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing

作者： Dunlavy, Daniel M. Shead, Timothy M. Stanton, Eric T. Comp. Sci. and Informatics Sandia National Laboratories M/S 1318 P.O. Box 5800 Albuquerque NM 87185-1318 United States Data Analysis and Visualization Sandia National Laboratories M/S 1323 P.O. Box 5800 Albuquerque NM 87185-1323 United States

ISBN: (纸本)9781605589428

Automated analysis of unstructured text documents (e.g., web pages, newswire articles, research publications, business reports) is a key capability for solving important problems in areas including decision making, risk assessment, social net- work analysis, intelligence analysis, scholarly research and others. However, as data sizes continue to grow in these ar- eas, scalable processing, modeling, and semantic analysis of text collections becomes essential. In this paper, we present the ParaText text analysis engine, a distributed memory software framework for processing, modeling, and analyzing collections of unstructured text documents. Results on sev- eral document collections using hundreds of processors are presented to illustrate the exibility, extensibility, and scal- ability of the the entire process of text modeling from raw data ingestion to application analysis. © Copyright 2010 ACM.

关键词： Risk assessment

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Analysing outbreak data in a heterogeneous population with migration

Analysing outbreak data in a heterogeneous population with m...

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作者： Wolkewitz, Martin Schumacher, Martin Freiburg Center of Data Analysis and Modelling University Medical Center Freiburg Freiburg Germany Institute of Medical Biometry and Medical Informatics University Medical Center Freiburg Freiburg Germany

ISBN: (纸本)9783902661494

Mathematical modelling of infectious diseases gains growing attention in epidemiology during the last decades. The major benefits of simulating compartmental models are the prediction of the consequences of potential interventions, a deeper understanding of epidemic dynamics and clinical decision support. The main limitation is however that several parameters are based on uncertain expert guesses (default values) and are not estimated from the study data. In this paper we build a bridge between the well-known deterministic S-I-R (Susceptible- Infectious-Removed) model which can be described with differential equations and the stochastic counterpart which can be used for statistical inference if outbreak data on an individual patient level are available. The possibly time-dependent transmission rate as well as the (basic) reproduction number are the main epidemiological parameters of interest. Furthermore, one important type of heterogeneity is considered: individuals may vary due to their susceptibility, i.e., risk factors for infection may be investigated. The Cox-Aalen survival model that is based on a multiplicative-additive hazard structure turned out to be a suitable tool for that purpose. The results give valuable informations for clinicians working in infection control and public health. © 2009 IFAC.

关键词： Differential equations

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Analysing outbreak data in a heterogeneous population with migration

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IFAC Proceedings Volumes 2009年第12期42卷 309-312页

作者： Martin Wolkewitz Martin Schumacher Freiburg Center of Data Analysis and Modelling University Medical Center Freiburg Freiburg Germany Institute of Medical Biometry and Medical Informatics University Medical Center Freiburg Freiburg Germany

Mathematical modelling of infectious diseases gains growing attention in epidemiology during the last decades. The major benefits of simulating compartmental models are the prediction of the consequences of potential interventions, a deeper understanding of epidemic dynamics and clinical decision support. The main limitation is however that several parameters are based on uncertain expert guesses (default values) and are not estimated from the study data. In this paper we build a bridge between the well-known deterministic S-I-R (Susceptible-Infectious-Removed) model which can be described with differential equations and the stochastic counterpart which can be used for statistical inference if outbreak data on an individual patient level are available. The possibly time-dependent transmission rate as well as the (basic) reproduction number are the main epidemiological parameters of interest. Furthermore, one important type of heterogeneity is considered: individuals may vary due to their susceptibility, i.e., risk factors for infection may be investigated. The Cox-Aalen survival model that is based on a multiplicative-additive hazard structure turned out to be a suitable tool for that purpose. The results give valuable informations for clinicians working in infection control and public health.

关键词： cross-infection epidemic outbreak transmission rate SIR model event history analysis

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