Theoretical Foundation of Copernicus: A Unified System for Trajectory Design and Optimization

NASA Technical Reports Server (NTRS)

Ocampo, Cesar; Senent, Juan S.; Williams, Jacob

2010-01-01

The fundamental methods are described for the general spacecraft trajectory design and optimization software system called Copernicus. The methods rely on a unified framework that is used to model, design, and optimize spacecraft trajectories that may operate in complex gravitational force fields, use multiple propulsion systems, and involve multiple spacecraft. The trajectory model, with its associated equations of motion and maneuver models, are discussed.

Design-Comparable Effect Sizes in Multiple Baseline Designs: A General Modeling Framework

ERIC Educational Resources Information Center

Pustejovsky, James E.; Hedges, Larry V.; Shadish, William R.

2014-01-01

In single-case research, the multiple baseline design is a widely used approach for evaluating the effects of interventions on individuals. Multiple baseline designs involve repeated measurement of outcomes over time and the controlled introduction of a treatment at different times for different individuals. This article outlines a general…

Hierarchical spatial capture-recapture models: Modeling population density from stratified populations

USGS Publications Warehouse

Royle, J. Andrew; Converse, Sarah J.

2014-01-01

Capture–recapture studies are often conducted on populations that are stratified by space, time or other factors. In this paper, we develop a Bayesian spatial capture–recapture (SCR) modelling framework for stratified populations – when sampling occurs within multiple distinct spatial and temporal strata.We describe a hierarchical model that integrates distinct models for both the spatial encounter history data from capture–recapture sampling, and also for modelling variation in density among strata. We use an implementation of data augmentation to parameterize the model in terms of a latent categorical stratum or group membership variable, which provides a convenient implementation in popular BUGS software packages.We provide an example application to an experimental study involving small-mammal sampling on multiple trapping grids over multiple years, where the main interest is in modelling a treatment effect on population density among the trapping grids.Many capture–recapture studies involve some aspect of spatial or temporal replication that requires some attention to modelling variation among groups or strata. We propose a hierarchical model that allows explicit modelling of group or strata effects. Because the model is formulated for individual encounter histories and is easily implemented in the BUGS language and other free software, it also provides a general framework for modelling individual effects, such as are present in SCR models.

Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models.

PubMed

Preacher, Kristopher J; Hayes, Andrew F

2008-08-01

Hypotheses involving mediation are common in the behavioral sciences. Mediation exists when a predictor affects a dependent variable indirectly through at least one intervening variable, or mediator. Methods to assess mediation involving multiple simultaneous mediators have received little attention in the methodological literature despite a clear need. We provide an overview of simple and multiple mediation and explore three approaches that can be used to investigate indirect processes, as well as methods for contrasting two or more mediators within a single model. We present an illustrative example, assessing and contrasting potential mediators of the relationship between the helpfulness of socialization agents and job satisfaction. We also provide SAS and SPSS macros, as well as Mplus and LISREL syntax, to facilitate the use of these methods in applications.

Applying the compound Poisson process model to the reporting of injury-related mortality rates.

PubMed

Kegler, Scott R

2007-02-16

Injury-related mortality rate estimates are often analyzed under the assumption that case counts follow a Poisson distribution. Certain types of injury incidents occasionally involve multiple fatalities, however, resulting in dependencies between cases that are not reflected in the simple Poisson model and which can affect even basic statistical analyses. This paper explores the compound Poisson process model as an alternative, emphasizing adjustments to some commonly used interval estimators for population-based rates and rate ratios. The adjusted estimators involve relatively simple closed-form computations, which in the absence of multiple-case incidents reduce to familiar estimators based on the simpler Poisson model. Summary data from the National Violent Death Reporting System are referenced in several examples demonstrating application of the proposed methodology.

Semiparametric Thurstonian Models for Recurrent Choices: A Bayesian Analysis

ERIC Educational Resources Information Center

Ansari, Asim; Iyengar, Raghuram

2006-01-01

We develop semiparametric Bayesian Thurstonian models for analyzing repeated choice decisions involving multinomial, multivariate binary or multivariate ordinal data. Our modeling framework has multiple components that together yield considerable flexibility in modeling preference utilities, cross-sectional heterogeneity and parameter-driven…

Experimental models of demyelination and remyelination.

PubMed

Torre-Fuentes, L; Moreno-Jiménez, L; Pytel, V; Matías-Guiu, J A; Gómez-Pinedo, U; Matías-Guiu, J

2017-08-29

Experimental animal models constitute a useful tool to deepen our knowledge of central nervous system disorders. In the case of multiple sclerosis, however, there is no such specific model able to provide an overview of the disease; multiple models covering the different pathophysiological features of the disease are therefore necessary. We reviewed the different in vitro and in vivo experimental models used in multiple sclerosis research. Concerning in vitro models, we analysed cell cultures and slice models. As for in vivo models, we examined such models of autoimmunity and inflammation as experimental allergic encephalitis in different animals and virus-induced demyelinating diseases. Furthermore, we analysed models of demyelination and remyelination, including chemical lesions caused by cuprizone, lysolecithin, and ethidium bromide; zebrafish; and transgenic models. Experimental models provide a deeper understanding of the different pathogenic mechanisms involved in multiple sclerosis. Choosing one model or another depends on the specific aims of the study. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Managing Disease Risks from Trade: Strategic Behavior with Many Choices and Price Effects.

PubMed

Chitchumnong, Piyayut; Horan, Richard D

2018-03-16

An individual's infectious disease risks, and hence the individual's incentives for risk mitigation, may be influenced by others' risk management choices. If so, then there will be strategic interactions among individuals, whereby each makes his or her own risk management decisions based, at least in part, on the expected decisions of others. Prior work has shown that multiple equilibria could arise in this setting, with one equilibrium being a coordination failure in which individuals make too few investments in protection. However, these results are largely based on simplified models involving a single management choice and fixed prices that may influence risk management incentives. Relaxing these assumptions, we find strategic interactions influence, and are influenced by, choices involving multiple management options and market price effects. In particular, we find these features can reduce or eliminate concerns about multiple equilibria and coordination failure. This has important policy implications relative to simpler models.

Optimized production planning model for a multi-plant cultivation system under uncertainty

NASA Astrophysics Data System (ADS)

Ke, Shunkui; Guo, Doudou; Niu, Qingliang; Huang, Danfeng

2015-02-01

An inexact multi-constraint programming model under uncertainty was developed by incorporating a production plan algorithm into the crop production optimization framework under the multi-plant collaborative cultivation system. In the production plan, orders from the customers are assigned to a suitable plant under the constraints of plant capabilities and uncertainty parameters to maximize profit and achieve customer satisfaction. The developed model and solution method were applied to a case study of a multi-plant collaborative cultivation system to verify its applicability. As determined in the case analysis involving different orders from customers, the period of plant production planning and the interval between orders can significantly affect system benefits. Through the analysis of uncertain parameters, reliable and practical decisions can be generated using the suggested model of a multi-plant collaborative cultivation system.

Multiple steady states in atmospheric chemistry

NASA Technical Reports Server (NTRS)

Stewart, Richard W.

1993-01-01

The equations describing the distributions and concentrations of trace species are nonlinear and may thus possess more than one solution. This paper develops methods for searching for multiple physical solutions to chemical continuity equations and applies these to subsets of equations describing tropospheric chemistry. The calculations are carried out with a box model and use two basic strategies. The first strategy is a 'search' method. This involves fixing model parameters at specified values, choosing a wide range of initial guesses at a solution, and using a Newton-Raphson technique to determine if different initial points converge to different solutions. The second strategy involves a set of techniques known as homotopy methods. These do not require an initial guess, are globally convergent, and are guaranteed, in principle, to find all solutions of the continuity equations. The first method is efficient but essentially 'hit or miss' in the sense that it cannot guarantee that all solutions which may exist will be found. The second method is computationally burdensome but can, in principle, determine all the solutions of a photochemical system. Multiple solutions have been found for models that contain a basic complement of photochemical reactions involving O(x), HO(x), NO(x), and CH4. In the present calculations, transitions occur between stable branches of a multiple solution set as a control parameter is varied. These transitions are manifestations of hysteresis phenomena in the photochemical system and may be triggered by increasing the NO flux or decreasing the CH4 flux from current mean tropospheric levels.

Multiple dimensions of spirituality in recovery: a lagged mediational analysis of Alcoholics Anonymous' principal theoretical mechanism of behavior change.

PubMed

Krentzman, Amy R; Cranford, James A; Robinson, Elizabeth A R

2013-01-01

Alcoholics Anonymous (AA) states that recovery is possible through spiritual experiences and spiritual awakenings. Research examining spirituality as a mediator of AA's effect on drinking has been mixed. It is unknown whether such findings are due to variations in the operationalization of key constructs, such as AA and spirituality. To answer these questions, the authors used a longitudinal model to test 2 dimensions of AA as focal predictors and 6 dimensions of spirituality as possible mediators of AA's association with drinking. Data from the first 18 months of a 3-year longitudinal study of 364 alcohol-dependent individuals were analyzed. Structural equation modeling was used to replicate the analyses of Kelly et al. (Alcohol Clin Exp Res. 2011;35:454-463) and to compare AA attendance and AA involvement as focal predictors. Multiple regression analyses were used to determine which spirituality dimensions changed as the result of AA participation. A trimmed, data-driven model was employed to test multiple mediation paths simultaneously. The findings of the Kelly et al. study were replicated. AA involvement was a stronger predictor of drinking outcomes than AA attendance. AA involvement predicted increases in private religious practices, daily spiritual experiences, and forgiveness of others. However, only private religious practices mediated the relationship between AA and drinking.

Addendum to validation of FHWA's Traffic Noise Model (TNM) : phase 1

DOT National Transportation Integrated Search

2004-07-01

(FHWA) is conducting a multiple-phase study to assess the accuracy and make recommendations on the use of FHWAs Traffic Noise Model (TNM). The TNM Validation Study involves highway noise data collection and TNM modeling for the purpose of data com...

Progression of regional grey matter atrophy in multiple sclerosis

PubMed Central

Marinescu, Razvan V; Young, Alexandra L; Firth, Nicholas C; Jorge Cardoso, M; Tur, Carmen; De Angelis, Floriana; Cawley, Niamh; Brownlee, Wallace J; De Stefano, Nicola; Laura Stromillo, M; Battaglini, Marco; Ruggieri, Serena; Gasperini, Claudio; Filippi, Massimo; Rocca, Maria A; Rovira, Alex; Sastre-Garriga, Jaume; Geurts, Jeroen J G; Vrenken, Hugo; Wottschel, Viktor; Leurs, Cyra E; Uitdehaag, Bernard; Pirpamer, Lukas; Enzinger, Christian; Ourselin, Sebastien; Gandini Wheeler-Kingshott, Claudia A; Chard, Declan; Thompson, Alan J; Barkhof, Frederik; Alexander, Daniel C; Ciccarelli, Olga

2018-01-01

Abstract See Stankoff and Louapre (doi:10.1093/brain/awy114) for a scientific commentary on this article. Grey matter atrophy is present from the earliest stages of multiple sclerosis, but its temporal ordering is poorly understood. We aimed to determine the sequence in which grey matter regions become atrophic in multiple sclerosis and its association with disability accumulation. In this longitudinal study, we included 1417 subjects: 253 with clinically isolated syndrome, 708 with relapsing-remitting multiple sclerosis, 128 with secondary-progressive multiple sclerosis, 125 with primary-progressive multiple sclerosis, and 203 healthy control subjects from seven European centres. Subjects underwent repeated MRI (total number of scans 3604); the mean follow-up for patients was 2.41 years (standard deviation = 1.97). Disability was scored using the Expanded Disability Status Scale. We calculated the volume of brain grey matter regions and brainstem using an unbiased within-subject template and used an established data-driven event-based model to determine the sequence of occurrence of atrophy and its uncertainty. We assigned each subject to a specific event-based model stage, based on the number of their atrophic regions. Linear mixed-effects models were used to explore associations between the rate of increase in event-based model stages, and T2 lesion load, disease-modifying treatments, comorbidity, disease duration and disability accumulation. The first regions to become atrophic in patients with clinically isolated syndrome and relapse-onset multiple sclerosis were the posterior cingulate cortex and precuneus, followed by the middle cingulate cortex, brainstem and thalamus. A similar sequence of atrophy was detected in primary-progressive multiple sclerosis with the involvement of the thalamus, cuneus, precuneus, and pallidum, followed by the brainstem and posterior cingulate cortex. The cerebellum, caudate and putamen showed early atrophy in relapse-onset multiple sclerosis and late atrophy in primary-progressive multiple sclerosis. Patients with secondary-progressive multiple sclerosis showed the highest event-based model stage (the highest number of atrophic regions, P < 0.001) at the study entry. All multiple sclerosis phenotypes, but clinically isolated syndrome, showed a faster rate of increase in the event-based model stage than healthy controls. T2 lesion load and disease duration in all patients were associated with increased event-based model stage, but no effects of disease-modifying treatments and comorbidity on event-based model stage were observed. The annualized rate of event-based model stage was associated with the disability accumulation in relapsing-remitting multiple sclerosis, independent of disease duration (P < 0.0001). The data-driven staging of atrophy progression in a large multiple sclerosis sample demonstrates that grey matter atrophy spreads to involve more regions over time. The sequence in which regions become atrophic is reasonably consistent across multiple sclerosis phenotypes. The spread of atrophy was associated with disease duration and with disability accumulation over time in relapsing-remitting multiple sclerosis. PMID:29741648

Progression of regional grey matter atrophy in multiple sclerosis.

PubMed

Eshaghi, Arman; Marinescu, Razvan V; Young, Alexandra L; Firth, Nicholas C; Prados, Ferran; Jorge Cardoso, M; Tur, Carmen; De Angelis, Floriana; Cawley, Niamh; Brownlee, Wallace J; De Stefano, Nicola; Laura Stromillo, M; Battaglini, Marco; Ruggieri, Serena; Gasperini, Claudio; Filippi, Massimo; Rocca, Maria A; Rovira, Alex; Sastre-Garriga, Jaume; Geurts, Jeroen J G; Vrenken, Hugo; Wottschel, Viktor; Leurs, Cyra E; Uitdehaag, Bernard; Pirpamer, Lukas; Enzinger, Christian; Ourselin, Sebastien; Gandini Wheeler-Kingshott, Claudia A; Chard, Declan; Thompson, Alan J; Barkhof, Frederik; Alexander, Daniel C; Ciccarelli, Olga

2018-06-01

See Stankoff and Louapre (doi:10.1093/brain/awy114) for a scientific commentary on this article.Grey matter atrophy is present from the earliest stages of multiple sclerosis, but its temporal ordering is poorly understood. We aimed to determine the sequence in which grey matter regions become atrophic in multiple sclerosis and its association with disability accumulation. In this longitudinal study, we included 1417 subjects: 253 with clinically isolated syndrome, 708 with relapsing-remitting multiple sclerosis, 128 with secondary-progressive multiple sclerosis, 125 with primary-progressive multiple sclerosis, and 203 healthy control subjects from seven European centres. Subjects underwent repeated MRI (total number of scans 3604); the mean follow-up for patients was 2.41 years (standard deviation = 1.97). Disability was scored using the Expanded Disability Status Scale. We calculated the volume of brain grey matter regions and brainstem using an unbiased within-subject template and used an established data-driven event-based model to determine the sequence of occurrence of atrophy and its uncertainty. We assigned each subject to a specific event-based model stage, based on the number of their atrophic regions. Linear mixed-effects models were used to explore associations between the rate of increase in event-based model stages, and T2 lesion load, disease-modifying treatments, comorbidity, disease duration and disability accumulation. The first regions to become atrophic in patients with clinically isolated syndrome and relapse-onset multiple sclerosis were the posterior cingulate cortex and precuneus, followed by the middle cingulate cortex, brainstem and thalamus. A similar sequence of atrophy was detected in primary-progressive multiple sclerosis with the involvement of the thalamus, cuneus, precuneus, and pallidum, followed by the brainstem and posterior cingulate cortex. The cerebellum, caudate and putamen showed early atrophy in relapse-onset multiple sclerosis and late atrophy in primary-progressive multiple sclerosis. Patients with secondary-progressive multiple sclerosis showed the highest event-based model stage (the highest number of atrophic regions, P < 0.001) at the study entry. All multiple sclerosis phenotypes, but clinically isolated syndrome, showed a faster rate of increase in the event-based model stage than healthy controls. T2 lesion load and disease duration in all patients were associated with increased event-based model stage, but no effects of disease-modifying treatments and comorbidity on event-based model stage were observed. The annualized rate of event-based model stage was associated with the disability accumulation in relapsing-remitting multiple sclerosis, independent of disease duration (P < 0.0001). The data-driven staging of atrophy progression in a large multiple sclerosis sample demonstrates that grey matter atrophy spreads to involve more regions over time. The sequence in which regions become atrophic is reasonably consistent across multiple sclerosis phenotypes. The spread of atrophy was associated with disease duration and with disability accumulation over time in relapsing-remitting multiple sclerosis.

Neuropsychological Predictors of Math Calculation and Reasoning in School-Aged Children

ERIC Educational Resources Information Center

Schneider, Dana Lynn

2012-01-01

After multiple reviews of the literature, which documented that multiple cognitive processes may be involved in mathematics ability and disability, Geary (1993) proposed a model that included three subtypes of math disability: Semantic, Procedural, and Visuospatial. A review of the extant literature produced three studies that examined Geary's…

Hierarchical Modeling of Sequential Behavioral Data: Examining Complex Association Patterns in Mediation Models

ERIC Educational Resources Information Center

Dagne, Getachew A.; Brown, C. Hendricks; Howe, George W.

2007-01-01

This article presents new methods for modeling the strength of association between multiple behaviors in a behavioral sequence, particularly those involving substantively important interaction patterns. Modeling and identifying such interaction patterns becomes more complex when behaviors are assigned to more than two categories, as is the case…

A Study of Child Variance, Volume 1: Conceptual Models; Conceptual Project in Emotional Disturbance.

ERIC Educational Resources Information Center

Rhodes, William C.; Tracy, Michael L.

Presented are 11 papers discussing the following six models of emotional disturbance in children: biophysical, behavioral, psychodynamic, sociological, and ecological, models, and counter theory. Emotional disturbance is defined as a distinctive human state having multiple manifestations and involving disability, deviance, and alienation. All the…

Immunopharmacological role of the leukotriene receptor antagonists and inhibitors of leukotrienes generating enzymes in multiple sclerosis.

PubMed

Mirshafiey, Abbas; Jadidi-Niaragh, Farhad

2010-06-01

Multiple sclerosis (MS) is a chronic inflammatory disease that involves central nervous system, and is generally associated with demyelination and axonal lesion. The effective factors for initiation of the inflammatory responses have not been known precisely so far. Leukotrienes (LTs) are inflammatory mediators with increased levels in the cerebrospinal fluid of MS patients and in experimental models of multiple sclerosis. Inhibition of LT receptors with specific antagonists can decrease inflammatory responses. In this review article we try to clarify the role of LT receptor antagonists and also inhibitors of enzymes which are involved in LTs generating pathway for treating multiple sclerosis as new targets for MS therapy. Moreover, we suggest that blockage of LT receptors by potent specific antagonists and/or agonists can be as a novel useful method in treatment of MS.

Independent component model for cognitive functions of multiple subjects using [15O]H2O PET images.

PubMed

Park, Hae-Jeong; Kim, Jae-Jin; Youn, Tak; Lee, Dong Soo; Lee, Myung Chul; Kwon, Jun Soo

2003-04-01

An independent component model of multiple subjects' positron emission tomography (PET) images is proposed to explore the overall functional components involved in a task and to explain subject specific variations of metabolic activities under altered experimental conditions utilizing the Independent component analysis (ICA) concept. As PET images represent time-compressed activities of several cognitive components, we derived a mathematical model to decompose functional components from cross-sectional images based on two fundamental hypotheses: (1) all subjects share basic functional components that are common to subjects and spatially independent of each other in relation to the given experimental task, and (2) all subjects share common functional components throughout tasks which are also spatially independent. The variations of hemodynamic activities according to subjects or tasks can be explained by the variations in the usage weight of the functional components. We investigated the plausibility of the model using serial cognitive experiments of simple object perception, object recognition, two-back working memory, and divided attention of a syntactic process. We found that the independent component model satisfactorily explained the functional components involved in the task and discuss here the application of ICA in multiple subjects' PET images to explore the functional association of brain activations. Copyright 2003 Wiley-Liss, Inc.

Statistical methods for incomplete data: Some results on model misspecification.

PubMed

McIsaac, Michael; Cook, R J

2017-02-01

Inverse probability weighted estimating equations and multiple imputation are two of the most studied frameworks for dealing with incomplete data in clinical and epidemiological research. We examine the limiting behaviour of estimators arising from inverse probability weighted estimating equations, augmented inverse probability weighted estimating equations and multiple imputation when the requisite auxiliary models are misspecified. We compute limiting values for settings involving binary responses and covariates and illustrate the effects of model misspecification using simulations based on data from a breast cancer clinical trial. We demonstrate that, even when both auxiliary models are misspecified, the asymptotic biases of double-robust augmented inverse probability weighted estimators are often smaller than the asymptotic biases of estimators arising from complete-case analyses, inverse probability weighting or multiple imputation. We further demonstrate that use of inverse probability weighting or multiple imputation with slightly misspecified auxiliary models can actually result in greater asymptotic bias than the use of naïve, complete case analyses. These asymptotic results are shown to be consistent with empirical results from simulation studies.

Parent involvement and student academic performance: a multiple mediational analysis.

PubMed

Topor, David R; Keane, Susan P; Shelton, Terri L; Calkins, Susan D

2010-01-01

Parent involvement in a child's education is consistently found to be positively associated with a child's academic performance. However, there has been little investigation of the mechanisms that explain this association. The present study examines two potential mechanisms of this association: the child's perception of cognitive competence and the quality of the student-teacher relationship. This study used a sample of 158 seven-year-old participants, their mothers, and their teachers. Results indicated a statistically significant association between parent involvement and a child's academic performance, over and above the impact of the child's intelligence. A multiple mediation model indicated that the child's perception of cognitive competence fully mediated the relation between parent involvement and the child's performance on a standardized achievement test. The quality of the student-teacher relationship fully mediated the relation between parent involvement and teacher ratings of the child's classroom academic performance. Limitations, future research directions, and implications for public policy initiatives are discussed.

The Characterization of Cognitive Processes Involved in Chemical Kinetics Using a Blended Processing Framework

ERIC Educational Resources Information Center

Bain, Kinsey; Rodriguez, Jon-Marc G.; Moon, Alena; Towns, Marcy H.

2018-01-01

Chemical kinetics is a highly quantitative content area that involves the use of multiple mathematical representations to model processes and is a context that is under-investigated in the literature. This qualitative study explored undergraduate student integration of chemistry and mathematics during problem solving in the context of chemical…

On the importance of considering heterogeneity in witnesses' competence levels when reconstructing crimes from multiple witness testimonies.

PubMed

Waubert de Puiseau, Berenike; Greving, Sven; Aßfalg, André; Musch, Jochen

2017-09-01

Aggregating information across multiple testimonies may improve crime reconstructions. However, different aggregation methods are available, and research on which method is best suited for aggregating multiple observations is lacking. Furthermore, little is known about how variance in the accuracy of individual testimonies impacts the performance of competing aggregation procedures. We investigated the superiority of aggregation-based crime reconstructions involving multiple individual testimonies and whether this superiority varied as a function of the number of witnesses and the degree of heterogeneity in witnesses' ability to accurately report their observations. Moreover, we examined whether heterogeneity in competence levels differentially affected the relative accuracy of two aggregation procedures: a simple majority rule, which ignores individual differences, and the more complex general Condorcet model (Romney et al., Am Anthropol 88(2):313-338, 1986; Batchelder and Romney, Psychometrika 53(1):71-92, 1988), which takes into account differences in competence between individuals. 121 participants viewed a simulated crime and subsequently answered 128 true/false questions about the crime. We experimentally generated groups of witnesses with homogeneous or heterogeneous competences. Both the majority rule and the general Condorcet model provided more accurate reconstructions of the observed crime than individual testimonies. The superiority of aggregated crime reconstructions involving multiple individual testimonies increased with an increasing number of witnesses. Crime reconstructions were most accurate when competences were heterogeneous and aggregation was based on the general Condorcet model. We argue that a formal aggregation should be considered more often when eyewitness testimonies have to be assessed and that the general Condorcet model provides a good framework for such aggregations.

Multiscale Modelling of Cancer Progression and Treatment Control: The Role of Intracellular Heterogeneities in Chemotherapy Treatment

NASA Astrophysics Data System (ADS)

Chaplain, Mark A. J.; Powathil, Gibin G.

Cancer is a complex, multiscale process involving interactions at intracellular, intercellular and tissue scales that are in turn susceptible to microenvironmental changes. Each individual cancer cell within a cancer cell mass is unique, with its own internal cellular pathways and biochemical interactions. These interactions contribute to the functional changes at the cellular and tissue scale, creating a heterogenous cancer cell population. Anticancer drugs are effective in controlling cancer growth by inflicting damage to various target molecules and thereby triggering multiple cellular and intracellular pathways, leading to cell death or cell-cycle arrest. One of the major impediments in the chemotherapy treatment of cancer is drug resistance driven by multiple mechanisms, including multi-drug and cell-cycle mediated resistance to chemotherapy drugs. In this article, we discuss two hybrid multiscale modelling approaches, incorporating multiple interactions involved in the sub-cellular, cellular and microenvironmental levels to study the effects of cell-cycle, phase-specific chemotherapy on the growth and progression of cancer cells.

Multiscale Modelling of Cancer Progression and Treatment Control: The Role of Intracellular Heterogeneities in Chemotherapy Treatment

NASA Astrophysics Data System (ADS)

Chaplain, Mark A. J.; Powathil, Gibin G.

2015-04-01

Cancer is a complex, multiscale process involving interactions at intracellular, intercellular and tissue scales that are in turn susceptible to microenvironmental changes. Each individual cancer cell within a cancer cell mass is unique, with its own internal cellular pathways and biochemical interactions. These interactions contribute to the functional changes at the cellular and tissue scale, creating a heterogenous cancer cell population. Anticancer drugs are effective in controlling cancer growth by inflicting damage to various target molecules and thereby triggering multiple cellular and intracellular pathways, leading to cell death or cell-cycle arrest. One of the major impediments in the chemotherapy treatment of cancer is drug resistance driven by multiple mechanisms, including multi-drug and cell-cycle mediated resistance to chemotherapy drugs. In this article, we discuss two hybrid multiscale modelling approaches, incorporating multiple interactions involved in the sub-cellular, cellular and microenvironmental levels to study the effects of cell-cycle, phase-specific chemotherapy on the growth and progression of cancer cells.

Ignition probability of polymer-bonded explosives accounting for multiple sources of material stochasticity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, S.; Barua, A.; Zhou, M., E-mail: min.zhou@me.gatech.edu

2014-05-07

Accounting for the combined effect of multiple sources of stochasticity in material attributes, we develop an approach that computationally predicts the probability of ignition of polymer-bonded explosives (PBXs) under impact loading. The probabilistic nature of the specific ignition processes is assumed to arise from two sources of stochasticity. The first source involves random variations in material microstructural morphology; the second source involves random fluctuations in grain-binder interfacial bonding strength. The effect of the first source of stochasticity is analyzed with multiple sets of statistically similar microstructures and constant interfacial bonding strength. Subsequently, each of the microstructures in the multiple setsmore » is assigned multiple instantiations of randomly varying grain-binder interfacial strengths to analyze the effect of the second source of stochasticity. Critical hotspot size-temperature states reaching the threshold for ignition are calculated through finite element simulations that explicitly account for microstructure and bulk and interfacial dissipation to quantify the time to criticality (t{sub c}) of individual samples, allowing the probability distribution of the time to criticality that results from each source of stochastic variation for a material to be analyzed. Two probability superposition models are considered to combine the effects of the multiple sources of stochasticity. The first is a parallel and series combination model, and the second is a nested probability function model. Results show that the nested Weibull distribution provides an accurate description of the combined ignition probability. The approach developed here represents a general framework for analyzing the stochasticity in the material behavior that arises out of multiple types of uncertainty associated with the structure, design, synthesis and processing of materials.« less

Effects of Inservice Teacher Training on Correct Implementation of Assessment and Instructional Procedures for Teachers of Students with Profound Multiple Disabilities

ERIC Educational Resources Information Center

Horrocks, Erin L.; Morgan, Robert L.

2011-01-01

A multicomponent training package (live training, video modeling, role playing, and feedback) was used to train teachers to conduct assessment and to instruct students with profound multiple disabilities. Phase 1 of the study involved training seven teachers to conduct assessment in three areas: (a) preference assessment (i.e., identification of…

Semiparametric bivariate zero-inflated Poisson models with application to studies of abundance for multiple species

USGS Publications Warehouse

Arab, Ali; Holan, Scott H.; Wikle, Christopher K.; Wildhaber, Mark L.

2012-01-01

Ecological studies involving counts of abundance, presence–absence or occupancy rates often produce data having a substantial proportion of zeros. Furthermore, these types of processes are typically multivariate and only adequately described by complex nonlinear relationships involving externally measured covariates. Ignoring these aspects of the data and implementing standard approaches can lead to models that fail to provide adequate scientific understanding of the underlying ecological processes, possibly resulting in a loss of inferential power. One method of dealing with data having excess zeros is to consider the class of univariate zero-inflated generalized linear models. However, this class of models fails to address the multivariate and nonlinear aspects associated with the data usually encountered in practice. Therefore, we propose a semiparametric bivariate zero-inflated Poisson model that takes into account both of these data attributes. The general modeling framework is hierarchical Bayes and is suitable for a broad range of applications. We demonstrate the effectiveness of our model through a motivating example on modeling catch per unit area for multiple species using data from the Missouri River Benthic Fishes Study, implemented by the United States Geological Survey.

Aspects of porosity prediction using multivariate linear regression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Byrnes, A.P.; Wilson, M.D.

1991-03-01

Highly accurate multiple linear regression models have been developed for sandstones of diverse compositions. Porosity reduction or enhancement processes are controlled by the fundamental variables, Pressure (P), Temperature (T), Time (t), and Composition (X), where composition includes mineralogy, size, sorting, fluid composition, etc. The multiple linear regression equation, of which all linear porosity prediction models are subsets, takes the generalized form: Porosity = C{sub 0} + C{sub 1}(P) + C{sub 2}(T) + C{sub 3}(X) + C{sub 4}(t) + C{sub 5}(PT) + C{sub 6}(PX) + C{sub 7}(Pt) + C{sub 8}(TX) + C{sub 9}(Tt) + C{sub 10}(Xt) + C{sub 11}(PTX) + C{submore » 12}(PXt) + C{sub 13}(PTt) + C{sub 14}(TXt) + C{sub 15}(PTXt). The first four primary variables are often interactive, thus requiring terms involving two or more primary variables (the form shown implies interaction and not necessarily multiplication). The final terms used may also involve simple mathematic transforms such as log X, e{sup T}, X{sup 2}, or more complex transformations such as the Time-Temperature Index (TTI). The X term in the equation above represents a suite of compositional variable and, therefore, a fully expanded equation may include a series of terms incorporating these variables. Numerous published bivariate porosity prediction models involving P (or depth) or Tt (TTI) are effective to a degree, largely because of the high degree of colinearity between p and TTI. However, all such bivariate models ignore the unique contributions of P and Tt, as well as various X terms. These simpler models become poor predictors in regions where colinear relations change, were important variables have been ignored, or where the database does not include a sufficient range or weight distribution for the critical variables.« less

Quasi 3D modeling of water flow in vadose zone and groundwater

USDA-ARS?s Scientific Manuscript database

The complexity of subsurface flow systems calls for a variety of concepts leading to the multiplicity of simplified flow models. One habitual simplification is based on the assumption that lateral flow and transport in unsaturated zone are not significant unless the capillary fringe is involved. In ...

Target Acquisition Involving Multiple Unmanned Air Vehicles: Interfaces for Small Unmanned Air Systems (ISUS) Program

DTIC Science & Technology

2009-03-01

model locations, time of day, and video size. The models in the scene consisted of three-dimensional representations of common civilian automobiles in...oats, wheat). Identify automobiles as sedans or station wagons. Identify individual telephone/electric poles in residential neighborhoods. Detect

Digital Games as Multirepresentational Environments for Science Learning: Implications for Theory, Research, and Design

ERIC Educational Resources Information Center

Virk, Satyugjit; Clark, Douglas; Sengupta, Pratim

2015-01-01

Environments in which learning involves coordinating multiple external representations (MERs) can productively support learners in making sense of complex models and relationships. Educational digital games provide an increasing popular medium for engaging students in manipulating and exploring such models and relationships. This article applies…

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions.

PubMed

Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael

2015-11-26

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field.

Parent involvement and student academic performance: A multiple mediational analysis

PubMed Central

Topor, David R.; Keane, Susan P.; Shelton, Terri L.; Calkins, Susan D.

2011-01-01

Parent involvement in a child's education is consistently found to be positively associated with a child's academic performance. However, there has been little investigation of the mechanisms that explain this association. The present study examines two potential mechanisms of this association: the child's perception of cognitive competence and the quality of the student-teacher relationship. This study used a sample of 158 seven-year old participants, their mothers, and their teachers. Results indicated a statistically significant association between parent involvement and a child's academic performance, over and above the impact of the child's intelligence. A multiple mediation model indicated that the child's perception of cognitive competence fully mediated the relation between parent involvement and the child's performance on a standardized achievement test. The quality of the student-teacher relationship fully mediated the relation between parent involvement and teacher ratings of the child's classroom academic performance. Limitations, future research directions, and implications for public policy initiatives were discussed. PMID:20603757

Mesoscopic Modeling of Blood Clotting: Coagulation Cascade and Platelets Adhesion

NASA Astrophysics Data System (ADS)

Yazdani, Alireza; Li, Zhen; Karniadakis, George

2015-11-01

The process of clot formation and growth at a site on a blood vessel wall involve a number of multi-scale simultaneous processes including: multiple chemical reactions in the coagulation cascade, species transport and flow. To model these processes we have incorporated advection-diffusion-reaction (ADR) of multiple species into an extended version of Dissipative Particle Dynamics (DPD) method which is considered as a coarse-grained Molecular Dynamics method. At the continuum level this is equivalent to the Navier-Stokes equation plus one advection-diffusion equation for each specie. The chemistry of clot formation is now understood to be determined by mechanisms involving reactions among many species in dilute solution, where reaction rate constants and species diffusion coefficients in plasma are known. The role of blood particulates, i.e. red cells and platelets, in the clotting process is studied by including them separately and together in the simulations. An agonist-induced platelet activation mechanism is presented, while platelets adhesive dynamics based on a stochastic bond formation/dissociation process is included in the model.

Formal Derivation of Lotka-Volterra-Haken Amplitude Equations of Task-Related Brain Activity in Multiple, Consecutively Performed Tasks

NASA Astrophysics Data System (ADS)

Frank, T. D.

The Lotka-Volterra-Haken equations have been frequently used in ecology and pattern formation. Recently, the equations have been proposed by several research groups as amplitude equations for task-related patterns of brain activity. In this theoretical study, the focus is on the circular causality aspect of pattern formation systems as formulated within the framework of synergetics. Accordingly, the stable modes of a pattern formation system inhibit the unstable modes, whereas the unstable modes excite the stable modes. Using this circular causality principle it is shown that under certain conditions the Lotka-Volterra-Haken amplitude equations can be derived from a general model of brain activity akin to the Wilson-Cowan model. The model captures the amplitude dynamics for brain activity patterns in experiments involving several consecutively performed multiple-choice tasks. This is explicitly demonstrated for two-choice tasks involving grasping and walking. A comment on the relevance of the theoretical framework for clinical psychology and schizophrenia is given as well.

Bootstrap evaluation of a young Douglas-fir height growth model for the Pacific Northwest

Treesearch

Nicholas R. Vaughn; Eric C. Turnblom; Martin W. Ritchie

2010-01-01

We evaluated the stability of a complex regression model developed to predict the annual height growth of young Douglas-fir. This model is highly nonlinear and is fit in an iterative manner for annual growth coefficients from data with multiple periodic remeasurement intervals. The traditional methods for such a sensitivity analysis either involve laborious math or...

Mouse and Guinea Pig Models of Tuberculosis.

PubMed

Orme, Ian M; Ordway, Diane J

2016-08-01

This article describes the nature of the host response to Mycobacterium tuberculosis in the mouse and guinea pig models of infection. It describes the great wealth of information obtained from the mouse model, reflecting the general availability of immunological reagents, as well as genetic manipulations of the mouse strains themselves. This has led to a good understanding of the nature of the T-cell response to the infection, as well as an appreciation of the complexity of the response involving multiple cytokine- and chemokine-mediated systems. As described here and elsewhere, we have a growing understanding of how multiple CD4-positive T-cell subsets are involved, including regulatory T cells, TH17 cells, as well as the subsequent emergence of effector and central memory T-cell subsets. While, in contrast, our understanding of the host response in the guinea pig model is less advanced, considerable strides have been made in the past decade in terms of defining the basis of the immune response, as well as a better understanding of the immunopathologic process. This model has long been the gold standard for vaccine testing, and more recently is being revisited as a model for testing new drug regimens (bedaquiline being the latest example).

Socio-Historical Factors Mediating Collaborative Teaching and Learning: A Design-Based Investigation and Intervention

ERIC Educational Resources Information Center

Hackett, Jacob

2016-01-01

Collaborative (Co-)teaching is a complex instructional delivery model used to improve teaching practice in inclusive settings. The model involves multiple certified teachers--representing both special and general education--sharing the same space and presenting material to classrooms with a wide variance in learning needs. Co-teaching has become…

Modeling uncertainty of evapotranspiration measurements from multiple eddy covariance towers over a crop canopy

USDA-ARS?s Scientific Manuscript database

All measurements have random error associated with them. With fluxes in an eddy covariance system, measurement error can been modelled in several ways, often involving a statistical description of turbulence at its core. Using a field experiment with four towers, we generated four replicates of meas...

“SNP Snappy”: A Strategy for Fast Genome-Wide Association Studies Fitting a Full Mixed Model

PubMed Central

Meyer, Karin; Tier, Bruce

2012-01-01

A strategy to reduce computational demands of genome-wide association studies fitting a mixed model is presented. Improvements are achieved by utilizing a large proportion of calculations that remain constant across the multiple analyses for individual markers involved, with estimates obtained without inverting large matrices. PMID:22021386

Finite burn maneuver modeling for a generalized spacecraft trajectory design and optimization system.

PubMed

Ocampo, Cesar

2004-05-01

The modeling, design, and optimization of finite burn maneuvers for a generalized trajectory design and optimization system is presented. A generalized trajectory design and optimization system is a system that uses a single unified framework that facilitates the modeling and optimization of complex spacecraft trajectories that may operate in complex gravitational force fields, use multiple propulsion systems, and involve multiple spacecraft. The modeling and optimization issues associated with the use of controlled engine burn maneuvers of finite thrust magnitude and duration are presented in the context of designing and optimizing a wide class of finite thrust trajectories. Optimal control theory is used examine the optimization of these maneuvers in arbitrary force fields that are generally position, velocity, mass, and are time dependent. The associated numerical methods used to obtain these solutions involve either, the solution to a system of nonlinear equations, an explicit parameter optimization method, or a hybrid parameter optimization that combines certain aspects of both. The theoretical and numerical methods presented here have been implemented in copernicus, a prototype trajectory design and optimization system under development at the University of Texas at Austin.

Mechanism of amido-thiourea catalyzed enantioselective imine hydrocyanation: transition state stabilization via multiple non-covalent interactions.

PubMed

Zuend, Stephan J; Jacobsen, Eric N

2009-10-28

An experimental and computational investigation of amido-thiourea promoted imine hydrocyanation has revealed a new and unexpected mechanism of catalysis. Rather than direct activation of the imine by the thiourea, as had been proposed previously in related systems, the data are consistent with a mechanism involving catalyst-promoted proton transfer from hydrogen isocyanide to imine to generate diastereomeric iminium/cyanide ion pairs that are bound to catalyst through multiple noncovalent interactions; these ion pairs collapse to form the enantiomeric alpha-aminonitrile products. This mechanistic proposal is supported by the observation of a statistically significant correlation between experimental and calculated enantioselectivities induced by eight different catalysts (P < 0.01). The computed models reveal a basis for enantioselectivity that involves multiple stabilizing and destabilizing interactions between substrate and catalyst, including thiourea-cyanide and amide-iminium interactions.

Multiple memory systems as substrates for multiple decision systems

PubMed Central

Doll, Bradley B.; Shohamy, Daphna; Daw, Nathaniel D.

2014-01-01

It has recently become widely appreciated that value-based decision making is supported by multiple computational strategies. In particular, animal and human behavior in learning tasks appears to include habitual responses described by prominent model-free reinforcement learning (RL) theories, but also more deliberative or goal-directed actions that can be characterized by a different class of theories, model-based RL. The latter theories evaluate actions by using a representation of the contingencies of the task (as with a learned map of a spatial maze), called an “internal model.” Given the evidence of behavioral and neural dissociations between these approaches, they are often characterized as dissociable learning systems, though they likely interact and share common mechanisms. In many respects, this division parallels a longstanding dissociation in cognitive neuroscience between multiple memory systems, describing, at the broadest level, separate systems for declarative and procedural learning. Procedural learning has notable parallels with model-free RL: both involve learning of habits and both are known to depend on parts of the striatum. Declarative memory, by contrast, supports memory for single events or episodes and depends on the hippocampus. The hippocampus is thought to support declarative memory by encoding temporal and spatial relations among stimuli and thus is often referred to as a relational memory system. Such relational encoding is likely to play an important role in learning an internal model, the representation that is central to model-based RL. Thus, insofar as the memory systems represent more general-purpose cognitive mechanisms that might subserve performance on many sorts of tasks including decision making, these parallels raise the question whether the multiple decision systems are served by multiple memory systems, such that one dissociation is grounded in the other. Here we investigated the relationship between model-based RL and relational memory by comparing individual differences across behavioral tasks designed to measure either capacity. Human subjects performed two tasks, a learning and generalization task (acquired equivalence) which involves relational encoding and depends on the hippocampus; and a sequential RL task that could be solved by either a model-based or model-free strategy. We assessed the correlation between subjects’ use of flexible, relational memory, as measured by generalization in the acquired equivalence task, and their differential reliance on either RL strategy in the decision task. We observed a significant positive relationship between generalization and model-based, but not model-free, choice strategies. These results are consistent with the hypothesis that model-based RL, like acquired equivalence, relies on a more general-purpose relational memory system. PMID:24846190

Lattice Boltzmann simulations of immiscible displacement process with large viscosity ratios

NASA Astrophysics Data System (ADS)

Rao, Parthib; Schaefer, Laura

2017-11-01

Immiscible displacement is a key physical mechanism involved in enhanced oil recovery and carbon sequestration processes. This multiphase flow phenomenon involves a complex interplay of viscous, capillary, inertial and wettability effects. The lattice Boltzmann (LB) method is an accurate and efficient technique for modeling and simulating multiphase/multicomponent flows especially in complex flow configurations and media. In this presentation we present numerical simulation results of displacement process in thin long channels. The results are based on a new psuedo-potential multicomponent LB model with multiple relaxation time collision (MRT) model and explicit forcing scheme. We demonstrate that the proposed model is capable of accurately simulating the displacement process involving fluids with a wider range of viscosity ratios (>100) and which also leads to viscosity-independent interfacial tension and reduction of some important numerical artifacts.

Basic deprivation and involvement in risky sexual behaviour among out-of-school young people in a Lagos slum.

PubMed

Kunnuji, Michael

2014-01-01

Research has shown that in countries such as Nigeria many urban dwellers live in a state of squalour and lack the basic necessities of food, clothing and shelter. The present study set out to examine the association between forms of basic deprivation--such as food deprivation, high occupancy ratio as a form of shelter deprivation, and inadequate clothing--and two sexual outcomes--timing of onset of penetrative sex and involvement in multiple sexual partnerships. The study used survey data from a sample of 480 girls resident in Iwaya community. A survival analysis of the timing of onset of sex and a regression model for involvement in multiple sexual partnerships reveal that among the forms of deprivation explored, food deprivation is the only significant predictor of the timing of onset of sex and involvement in multiple sexual partnerships. The study concludes that the sexual activities of poor out-of-school girls are partly explained by their desire to overcome food deprivation and recommends that government and non-governmental-organisation programmes working with young people should address the problem of basic deprivation among adolescent girls.

Multiple solutions and numerical analysis to the dynamic and stationary models coupling a delayed energy balance model involving latent heat and discontinuous albedo with a deep ocean.

PubMed

Díaz, J I; Hidalgo, A; Tello, L

2014-10-08

We study a climatologically important interaction of two of the main components of the geophysical system by adding an energy balance model for the averaged atmospheric temperature as dynamic boundary condition to a diagnostic ocean model having an additional spatial dimension. In this work, we give deeper insight than previous papers in the literature, mainly with respect to the 1990 pioneering model by Watts and Morantine. We are taking into consideration the latent heat for the two phase ocean as well as a possible delayed term. Non-uniqueness for the initial boundary value problem, uniqueness under a non-degeneracy condition and the existence of multiple stationary solutions are proved here. These multiplicity results suggest that an S-shaped bifurcation diagram should be expected to occur in this class of models generalizing previous energy balance models. The numerical method applied to the model is based on a finite volume scheme with nonlinear weighted essentially non-oscillatory reconstruction and Runge-Kutta total variation diminishing for time integration.

Multiple solutions and numerical analysis to the dynamic and stationary models coupling a delayed energy balance model involving latent heat and discontinuous albedo with a deep ocean

PubMed Central

Díaz, J. I.; Hidalgo, A.; Tello, L.

2014-01-01

We study a climatologically important interaction of two of the main components of the geophysical system by adding an energy balance model for the averaged atmospheric temperature as dynamic boundary condition to a diagnostic ocean model having an additional spatial dimension. In this work, we give deeper insight than previous papers in the literature, mainly with respect to the 1990 pioneering model by Watts and Morantine. We are taking into consideration the latent heat for the two phase ocean as well as a possible delayed term. Non-uniqueness for the initial boundary value problem, uniqueness under a non-degeneracy condition and the existence of multiple stationary solutions are proved here. These multiplicity results suggest that an S-shaped bifurcation diagram should be expected to occur in this class of models generalizing previous energy balance models. The numerical method applied to the model is based on a finite volume scheme with nonlinear weighted essentially non-oscillatory reconstruction and Runge–Kutta total variation diminishing for time integration. PMID:25294969

A survey of real face modeling methods

NASA Astrophysics Data System (ADS)

Liu, Xiaoyue; Dai, Yugang; He, Xiangzhen; Wan, Fucheng

2017-09-01

The face model has always been a research challenge in computer graphics, which involves the coordination of multiple organs in faces. This article explained two kinds of face modeling method which is based on the data driven and based on parameter control, analyzed its content and background, summarized their advantages and disadvantages, and concluded muscle model which is based on the anatomy of the principle has higher veracity and easy to drive.

The relationship of rain-induced cross-polarization discrimination to attenuation for 10 to 30 GHz earth-space radio links

NASA Technical Reports Server (NTRS)

Stutzman, W. L.; Runyon, D. L.

1984-01-01

Rain depolarization is quantified through the cross-polarization discrimination (XPD) versus attenuation relationship. Such a relationship is derived by curve fitting to a rigorous theoretical model (the multiple scattering model) to determine the variation of the parameters involved. This simple isolation model (SIM) is compared to data from several earth-space link experiments and to three other models.

Mitochondria, oligodendrocytes and inflammation in bipolar disorder: evidence from transcriptome studies points to intriguing parallels with multiple sclerosis

PubMed Central

Konradi, Christine; Sillivan, Stephanie E.; Clay, Hayley B.

2011-01-01

Gene expression studies of bipolar disorder (BPD) have shown changes in transcriptome profiles in multiple brain regions. Here we summarize the most consistent findings in the scientific literature, and compare them to data from schizophrenia (SZ) and major depressive disorder (MDD). The transcriptome profiles of all three disorders overlap, making the existence of a BPD-specific profile unlikely. Three groups of functionally related genes are consistently expressed at altered levels in BPD, SZ and MDD. Genes involved in energy metabolism and mitochondrial function are downregulated, genes involved in immune response and inflammation are upregulated, and genes expressed in oligodendrocytes are downregulated. Experimental paradigms for multiple sclerosis demonstrate a tight link between energy metabolism, inflammation and demyelination. These studies also show variabilities in the extent of oligodendrocyte stress, which can vary from a downregulation of oligodendrocyte genes, such as observed in psychiatric disorders, to cell death and brain lesions seen in multiple sclerosis. We conclude that experimental models of multiple sclerosis could be of interest for the research of BPD, SZ and MDD. PMID:21310238

Value Focused Thinking in Developing Aerobatic Aircraft Selection Model for Turkish Air Force

DTIC Science & Technology

2012-03-22

many reasons . Most problems in decision- making involve multiple objectives and uncertainties. The number of alternatives can be significant and make ...and Republic of Turkey all around the world”. This is a clear and concise statement of the most basic reason for decision. After making interview...Hwang, C.-L. (1995). Multiple Attribute Decison Making : An Introduction. California: Sage Publications. 90 Vita First Lieutenant

The Science of Strategic Communication

EPA Science Inventory

The field of Strategic Communication involves a focused effort to identify, develop, and present multiple types of communication media on a given subject. A Strategic Communication program recognizes the limitations of the most common communication models (primarily “one s...

THE AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT TOOL

EPA Science Inventory

A toolkit for distributed hydrologic modeling at multiple scales using a geographic information system is presented. This open-source, freely available software was developed through a collaborative endeavor involving two Universities and two government agencies. Called the Auto...

General Methodology for Designing Spacecraft Trajectories

NASA Technical Reports Server (NTRS)

Condon, Gerald; Ocampo, Cesar; Mathur, Ravishankar; Morcos, Fady; Senent, Juan; Williams, Jacob; Davis, Elizabeth C.

2012-01-01

A methodology for designing spacecraft trajectories in any gravitational environment within the solar system has been developed. The methodology facilitates modeling and optimization for problems ranging from that of a single spacecraft orbiting a single celestial body to that of a mission involving multiple spacecraft and multiple propulsion systems operating in gravitational fields of multiple celestial bodies. The methodology consolidates almost all spacecraft trajectory design and optimization problems into a single conceptual framework requiring solution of either a system of nonlinear equations or a parameter-optimization problem with equality and/or inequality constraints.

The organization of multidisciplinary care teams: modeling internal and external influences on cancer care quality.

PubMed

Fennell, Mary L; Das, Irene Prabhu; Clauser, Steven; Petrelli, Nicholas; Salner, Andrew

2010-01-01

Quality cancer treatment depends upon careful coordination between multiple treatments and treatment providers, the exchange of technical information, and regular communication between all providers and physician disciplines involved in treatment. This article will examine a particular type of organizational structure purported to regularize and streamline the communication between multiple specialists and support services involved in cancer treatment: the multidisciplinary treatment care (MDC) team. We present a targeted review of what is known about various types of MDC team structures and their impact on the quality of treatment care, and we outline a conceptual model of the connections between team context, structure, process, and performance and their subsequent effects on cancer treatment care processes and patient outcomes. Finally, we will discuss future research directions to understand how MDC teams improve patient outcomes and how characteristics of team structure, culture, leadership, and context (organizational setting and local environment) contribute to optimal multidisciplinary cancer care.

A Practical Approach to Address Uncertainty in Stakeholder Deliberations.

PubMed

Gregory, Robin; Keeney, Ralph L

2017-03-01

This article addresses the difficulties of incorporating uncertainty about consequence estimates as part of stakeholder deliberations involving multiple alternatives. Although every prediction of future consequences necessarily involves uncertainty, a large gap exists between common practices for addressing uncertainty in stakeholder deliberations and the procedures of prescriptive decision-aiding models advanced by risk and decision analysts. We review the treatment of uncertainty at four main phases of the deliberative process: with experts asked to describe possible consequences of competing alternatives, with stakeholders who function both as individuals and as members of coalitions, with the stakeholder committee composed of all stakeholders, and with decisionmakers. We develop and recommend a model that uses certainty equivalents as a theoretically robust and practical approach for helping diverse stakeholders to incorporate uncertainties when evaluating multiple-objective alternatives as part of public policy decisions. © 2017 Society for Risk Analysis.

A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network

PubMed Central

Tokumitsu, Masahiro; Ishida, Yoshiteru

2014-01-01

This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing. PMID:24803190

A space weather forecasting system with multiple satellites based on a self-recognizing network.

PubMed

Tokumitsu, Masahiro; Ishida, Yoshiteru

2014-05-05

This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

Customer involvement in greening the supply chain: an interpretive structural modeling methodology

NASA Astrophysics Data System (ADS)

Kumar, Sanjay; Luthra, Sunil; Haleem, Abid

2013-04-01

The role of customers in green supply chain management needs to be identified and recognized as an important research area. This paper is an attempt to explore the involvement aspect of customers towards greening of the supply chain (SC). An empirical research approach has been used to collect primary data to rank different variables for effective customer involvement in green concept implementation in SC. An interpretive structural-based model has been presented, and variables have been classified using matrice d' impacts croises- multiplication appliqué a un classement analysis. Contextual relationships among variables have been established using experts' opinions. The research may help practicing managers to understand the interaction among variables affecting customer involvement. Further, this understanding may be helpful in framing the policies and strategies to green SC. Analyzing interaction among variables for effective customer involvement in greening SC to develop the structural model in the Indian perspective is an effort towards promoting environment consciousness.

Spray combustion model improvement study, 1

NASA Technical Reports Server (NTRS)

Chen, C. P.; Kim, Y. M.; Shang, H. M.

1993-01-01

This study involves the development of numerical and physical modeling in spray combustion. These modeling efforts are mainly motivated to improve the physical submodels of turbulence, combustion, atomization, dense spray effects, and group vaporization. The present mathematical formulation can be easily implemented in any time-marching multiple pressure correction methodologies such as MAST code. A sequence of validation cases includes the nonevaporating, evaporating and_burnin dense_sprays.

Building effective working relationships across culturally and ethnically diverse communities.

PubMed

Hosley, Cheryl A; Gensheimer, Linda; Yang, Mai

2003-01-01

Amherst H. Wilder Foundation's Social Adjustment Program for Southeast Asians is implementing two collaborative, best practice, mental health and substance abuse prevention service models in Minnesota. It faced several issues in effectively bridging multiple cultural groups, including building a diverse collaborative team, involving families and youth, reconciling cultural variation in meeting styles, and making best practice models culturally appropriate. Researchers and program staff used multiple strategies to address these challenges and build successful partnerships. Through shared goals, flexibility, and a willingness to explore and address challenges, collaboratives can promote stronger relationships across cultural communities and improve their service delivery systems.

Simultaneous Excitation of Multiple-Input Multiple-Output CFD-Based Unsteady Aerodynamic Systems

NASA Technical Reports Server (NTRS)

Silva, Walter A.

2008-01-01

A significant improvement to the development of CFD-based unsteady aerodynamic reduced-order models (ROMs) is presented. This improvement involves the simultaneous excitation of the structural modes of the CFD-based unsteady aerodynamic system that enables the computation of the unsteady aerodynamic state-space model using a single CFD execution, independent of the number of structural modes. Four different types of inputs are presented that can be used for the simultaneous excitation of the structural modes. Results are presented for a flexible, supersonic semi-span configuration using the CFL3Dv6.4 code.

Simultaneous Excitation of Multiple-Input Multiple-Output CFD-Based Unsteady Aerodynamic Systems

NASA Technical Reports Server (NTRS)

Silva, Walter A.

2007-01-01

A significant improvement to the development of CFD-based unsteady aerodynamic reduced-order models (ROMs) is presented. This improvement involves the simultaneous excitation of the structural modes of the CFD-based unsteady aerodynamic system that enables the computation of the unsteady aerodynamic state-space model using a single CFD execution, independent of the number of structural modes. Four different types of inputs are presented that can be used for the simultaneous excitation of the structural modes. Results are presented for a flexible, supersonic semi-span configuration using the CFL3Dv6.4 code.

A Matter of Timing: Developmental Theories of Romantic Involvement and Psychosocial Adjustment

PubMed Central

Furman, Wyndol; Collibee, Charlene

2014-01-01

The present study compared two theories of the association between romantic involvement and adjustment—a social timetable theory and a developmental task theory. We examined seven waves of longitudinal data on a community based sample of 200 participants (M age Wave 1 = 15 years, 10 months). In each wave, multiple measures of substance use, externalizing symptoms, and internalizing symptoms were gathered, typically from multiple reporters. Multilevel modeling revealed that greater levels of romantic involvement in adolescence were associated with higher levels of substance use and externalizing symptoms, but became associated with lower levels in adulthood. Similarly, having a romantic partner was associated with greater levels of substance use, externalizing symptoms, and internalizing symptoms in adolescence, but was associated with lower levels in young adulthood. The findings were not consistent with a social timetable theory, which predicts that nonnormative involvement is associated with poor adjustment. Instead, the findings are consistent with a developmental task theory which predicts that precocious romantic involvement undermines development and adaptation, but when romantic involvement becomes a salient developmental task in adulthood, it is associated with positive adjustment. Discussion focuses on the processes that may underlie the changing nature of the association between romantic involvement and adjustment. PMID:24703413

Predicting early adolescent gang involvement from middle school adaptation.

PubMed

Dishion, Thomas J; Nelson, Sarah E; Yasui, Miwa

2005-03-01

This study examined the role of adaptation in the first year of middle school (Grade 6, age 11) to affiliation with gangs by the last year of middle school (Grade 8, age 13). The sample consisted of 714 European American (EA) and African American (AA) boys and girls. Specifically, academic grades, reports of antisocial behavior, and peer relations in 6th grade were used to predict multiple measures of gang involvement by 8th grade. The multiple measures of gang involvement included self-, peer, teacher, and counselor reports. Unexpectedly, self-report measures of gang involvement did not correlate highly with peer and school staff reports. The results, however, were similar for other and self-report measures of gang involvement. Mean level analyses revealed statistically reliable differences in 8th-grade gang involvement as a function of the youth gender and ethnicity. Structural equation prediction models revealed that peer nominations of rejection, acceptance, academic failure, and antisocial behavior were predictive of gang involvement for most youth. These findings suggest that the youth level of problem behavior and the school ecology (e.g., peer rejection, school failure) require attention in the design of interventions to prevent the formation of gangs among high-risk young adolescents.

Correction of the significance level when attempting multiple transformations of an explanatory variable in generalized linear models

PubMed Central

2013-01-01

Background In statistical modeling, finding the most favorable coding for an exploratory quantitative variable involves many tests. This process involves multiple testing problems and requires the correction of the significance level. Methods For each coding, a test on the nullity of the coefficient associated with the new coded variable is computed. The selected coding corresponds to that associated with the largest statistical test (or equivalently the smallest pvalue). In the context of the Generalized Linear Model, Liquet and Commenges (Stat Probability Lett,71:33–38,2005) proposed an asymptotic correction of the significance level. This procedure, based on the score test, has been developed for dichotomous and Box-Cox transformations. In this paper, we suggest the use of resampling methods to estimate the significance level for categorical transformations with more than two levels and, by definition those that involve more than one parameter in the model. The categorical transformation is a more flexible way to explore the unknown shape of the effect between an explanatory and a dependent variable. Results The simulations we ran in this study showed good performances of the proposed methods. These methods were illustrated using the data from a study of the relationship between cholesterol and dementia. Conclusion The algorithms were implemented using R, and the associated CPMCGLM R package is available on the CRAN. PMID:23758852

Multiple Service System Involvement and Later Offending Behavior: Implications for Prevention and Early Intervention.

PubMed

Bright, Charlotte Lyn; Jonson-Reid, Melissa

2015-07-01

We investigated patterns of childhood and adolescent experiences that correspond to later justice system entry, including persistence into adulthood, and explored whether timing of potential supports to the child or onset of family poverty, according to developmental periods and gender, would distinguish among latent classes. We constructed a database containing records for 8587 youths from a Midwestern metropolitan region, born between 1982 and 1991, with outcomes. We used data from multiple publicly funded systems (child welfare, income maintenance, juvenile and criminal justice, mental health, Medicaid, vital statistics). We applied a latent class analysis and interpreted a 7-class model. Classes with higher rates of offending persisting into adulthood were characterized by involvement with multiple publicly funded systems in childhood and adolescence, with the exception of 1 less-urban, predominantly female class that had similarly high system involvement coupled with lower rates of offending. Poverty and maltreatment appear to play a critical role in offending trajectories. Identifying risk factors that cluster together may help program and intervention staff best target those most in need of more intensive intervention.

Detangling Spaghetti: Tracking Deep Ocean Currents in the Gulf of Mexico

ERIC Educational Resources Information Center

Curran, Mary Carla; Bower, Amy S.; Furey, Heather H.

2017-01-01

Creation of physical models can help students learn science by enabling them to be more involved in the scientific process of discovery and to use multiple senses during investigations. This activity achieves these goals by having students model ocean currents in the Gulf of Mexico. In general, oceans play a key role in influencing weather…

Data Modeling Challenges of Advanced Interoperability.

PubMed

Blobel, Bernd; Oemig, Frank; Ruotsalainen, Pekka

2018-01-01

Progressive health paradigms, involving many different disciplines and combining multiple policy domains, requires advanced interoperability solutions. This results in special challenges for modeling health systems. The paper discusses classification systems for data models and enterprise business architectures and compares them with the ISO Reference Architecture. On that basis, existing definitions, specifications and standards of data models for interoperability are evaluated and their limitations are discussed. Amendments to correctly use those models and to better meet the aforementioned challenges are offered.

Mechanism of Amido-Thiourea Catalyzed Enantioselective Imine Hydrocyanation: Transition State Stabilization via Multiple Non-Covalent Interactions

PubMed Central

Zuend, Stephan J.

2009-01-01

An experimental and computational investigation of amido-thiourea promoted imine hydrocyanation has revealed a new and unexpected mechanism of catalysis. Rather than direct activation of the imine by the thiourea, as had been proposed previously in related systems, the data are consistent with a mechanism involving catalyst-promoted proton transfer from hydrogen isocyanide to imine to generate diastereomeric iminium/cyanide ion pairs that are bound to catalyst through multiple non-covalent interactions; these ion pairs collapse to form the enantiomeric α-aminonitrile products. This mechanistic proposal is supported by the observation of a statistically significant correlation between experimental and calculated enantioselectivities induced by eight different catalysts (P ≪ 0.01). The computed models reveal a basis for enantioselectivity that involves multiple stabilizing and destabilizing interactions between substrate and catalyst, including thiourea-cyanide and amide-iminium interactions. PMID:19778044

Managing data from multiple disciplines, scales, and sites to support synthesis and modeling

USGS Publications Warehouse

Olson, R. J.; Briggs, J. M.; Porter, J.H.; Mah, Grant R.; Stafford, S.G.

1999-01-01

The synthesis and modeling of ecological processes at multiple spatial and temporal scales involves bringing together and sharing data from numerous sources. This article describes a data and information system model that facilitates assembling, managing, and sharing diverse data from multiple disciplines, scales, and sites to support integrated ecological studies. Cross-site scientific-domain working groups coordinate the development of data associated with their particular scientific working group, including decisions about data requirements, data to be compiled, data formats, derived data products, and schedules across the sites. The Web-based data and information system consists of nodes for each working group plus a central node that provides data access, project information, data query, and other functionality. The approach incorporates scientists and computer experts in the working groups and provides incentives for individuals to submit documented data to the data and information system.

Crack Damage Detection Method via Multiple Visual Features and Efficient Multi-Task Learning Model.

PubMed

Wang, Baoxian; Zhao, Weigang; Gao, Po; Zhang, Yufeng; Wang, Zhe

2018-06-02

This paper proposes an effective and efficient model for concrete crack detection. The presented work consists of two modules: multi-view image feature extraction and multi-task crack region detection. Specifically, multiple visual features (such as texture, edge, etc.) of image regions are calculated, which can suppress various background noises (such as illumination, pockmark, stripe, blurring, etc.). With the computed multiple visual features, a novel crack region detector is advocated using a multi-task learning framework, which involves restraining the variability for different crack region features and emphasizing the separability between crack region features and complex background ones. Furthermore, the extreme learning machine is utilized to construct this multi-task learning model, thereby leading to high computing efficiency and good generalization. Experimental results of the practical concrete images demonstrate that the developed algorithm can achieve favorable crack detection performance compared with traditional crack detectors.

Electrophysiological models of neural processing.

PubMed

Nelson, Mark E

2011-01-01

The brain is an amazing information processing system that allows organisms to adaptively monitor and control complex dynamic interactions with their environment across multiple spatial and temporal scales. Mathematical modeling and computer simulation techniques have become essential tools in understanding diverse aspects of neural processing ranging from sub-millisecond temporal coding in the sound localization circuity of barn owls to long-term memory storage and retrieval in humans that can span decades. The processing capabilities of individual neurons lie at the core of these models, with the emphasis shifting upward and downward across different levels of biological organization depending on the nature of the questions being addressed. This review provides an introduction to the techniques for constructing biophysically based models of individual neurons and local networks. Topics include Hodgkin-Huxley-type models of macroscopic membrane currents, Markov models of individual ion-channel currents, compartmental models of neuronal morphology, and network models involving synaptic interactions among multiple neurons.

A comparative study of turbulence models for overset grids

NASA Technical Reports Server (NTRS)

Renze, Kevin J.; Buning, Pieter G.; Rajagopalan, R. G.

1992-01-01

The implementation of two different types of turbulence models for a flow solver using the Chimera overset grid method is examined. Various turbulence model characteristics, such as length scale determination and transition modeling, are found to have a significant impact on the computed pressure distribution for a multielement airfoil case. No inherent problem is found with using either algebraic or one-equation turbulence models with an overset grid scheme, but simulation of turbulence for multiple-body or complex geometry flows is very difficult regardless of the gridding method. For complex geometry flowfields, modification of the Baldwin-Lomax turbulence model is necessary to select the appropriate length scale in wall-bounded regions. The overset grid approach presents no obstacle to use of a one- or two-equation turbulence model. Both Baldwin-Lomax and Baldwin-Barth models have problems providing accurate eddy viscosity levels for complex multiple-body flowfields such as those involving the Space Shuttle.

Should multiple imputation be the method of choice for handling missing data in randomized trials?

PubMed Central

Sullivan, Thomas R; White, Ian R; Salter, Amy B; Ryan, Philip; Lee, Katherine J

2016-01-01

The use of multiple imputation has increased markedly in recent years, and journal reviewers may expect to see multiple imputation used to handle missing data. However in randomized trials, where treatment group is always observed and independent of baseline covariates, other approaches may be preferable. Using data simulation we evaluated multiple imputation, performed both overall and separately by randomized group, across a range of commonly encountered scenarios. We considered both missing outcome and missing baseline data, with missing outcome data induced under missing at random mechanisms. Provided the analysis model was correctly specified, multiple imputation produced unbiased treatment effect estimates, but alternative unbiased approaches were often more efficient. When the analysis model overlooked an interaction effect involving randomized group, multiple imputation produced biased estimates of the average treatment effect when applied to missing outcome data, unless imputation was performed separately by randomized group. Based on these results, we conclude that multiple imputation should not be seen as the only acceptable way to handle missing data in randomized trials. In settings where multiple imputation is adopted, we recommend that imputation is carried out separately by randomized group. PMID:28034175

Should multiple imputation be the method of choice for handling missing data in randomized trials?

PubMed

Sullivan, Thomas R; White, Ian R; Salter, Amy B; Ryan, Philip; Lee, Katherine J

2016-01-01

The use of multiple imputation has increased markedly in recent years, and journal reviewers may expect to see multiple imputation used to handle missing data. However in randomized trials, where treatment group is always observed and independent of baseline covariates, other approaches may be preferable. Using data simulation we evaluated multiple imputation, performed both overall and separately by randomized group, across a range of commonly encountered scenarios. We considered both missing outcome and missing baseline data, with missing outcome data induced under missing at random mechanisms. Provided the analysis model was correctly specified, multiple imputation produced unbiased treatment effect estimates, but alternative unbiased approaches were often more efficient. When the analysis model overlooked an interaction effect involving randomized group, multiple imputation produced biased estimates of the average treatment effect when applied to missing outcome data, unless imputation was performed separately by randomized group. Based on these results, we conclude that multiple imputation should not be seen as the only acceptable way to handle missing data in randomized trials. In settings where multiple imputation is adopted, we recommend that imputation is carried out separately by randomized group.

Strategic Communication and its Utility in Ecosystem Service Science

EPA Science Inventory

The field of Strategic Communication involves a focused effort to identify, develop, and present multiple types of communication media on a given subject. A Strategic Communication program recognizes the limitations of the most common communication models (primarily “one s...

Using Gaming To Help Nursing Students Understand Ethics.

ERIC Educational Resources Information Center

Metcalf, Barbara L.; Yankou, Dawn

2003-01-01

An ethics game involves nursing students in defending actions in ethics-based scenarios. Benefits include increased confidence, ability to see multiple perspectives, values clarification, and exposure to decision-making models, professional responsibilities, ethical principles, social expectations, and legal requirements. Difficulties include…

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions

PubMed Central

Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael

2015-01-01

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field. DOI: http://dx.doi.org/10.7554/eLife.08411.001 PMID:26609814

Why do people appear not to extrapolate trajectories during multiple object tracking? A computational investigation

PubMed Central

Zhong, Sheng-hua; Ma, Zheng; Wilson, Colin; Liu, Yan; Flombaum, Jonathan I

2014-01-01

Intuitively, extrapolating object trajectories should make visual tracking more accurate. This has proven to be true in many contexts that involve tracking a single item. But surprisingly, when tracking multiple identical items in what is known as “multiple object tracking,” observers often appear to ignore direction of motion, relying instead on basic spatial memory. We investigated potential reasons for this behavior through probabilistic models that were endowed with perceptual limitations in the range of typical human observers, including noisy spatial perception. When we compared a model that weights its extrapolations relative to other sources of information about object position, and one that does not extrapolate at all, we found no reliable difference in performance, belying the intuition that extrapolation always benefits tracking. In follow-up experiments we found this to be true for a variety of models that weight observations and predictions in different ways; in some cases we even observed worse performance for models that use extrapolations compared to a model that does not at all. Ultimately, the best performing models either did not extrapolate, or extrapolated very conservatively, relying heavily on observations. These results illustrate the difficulty and attendant hazards of using noisy inputs to extrapolate the trajectories of multiple objects simultaneously in situations with targets and featurally confusable nontargets. PMID:25311300

A Macroevolutionary Perspective on Multiple Sexual Traits in the Phasianidae (Galliformes)

PubMed Central

Kimball, Rebecca T.; Mary, Colette M. St.; Braun, Edward L.

2011-01-01

Traits involved in sexual signaling are ubiquitous among animals. Although a single trait appears sufficient to convey information, many sexually dimorphic species exhibit multiple sexual signals, which may be costly to signalers and receivers. Given that one signal may be enough, there are many microevolutionary hypotheses to explain the evolution of multiple signals. Here we extend these hypotheses to a macroevolutionary scale and compare those predictions to the patterns of gains and losses of sexual dimorphism in pheasants and partridges. Among nine dimorphic characters, including six intersexual signals and three indicators of competitive ability, all exhibited both gains and losses of dimorphism within the group. Although theories of intersexual selection emphasize gain and elaboration, those six characters exhibited greater rates of loss than gain; in contrast, the competitive traits showed a slight bias towards gains. The available models, when examined in a macroevolutionary framework, did not yield unique predictions, making it difficult to distinguish among them. Even with this limitation, when the predictions of these alternative models were compared with the heterogeneous patterns of evolution of dimorphism in phasianids, it is clear that many different selective processes have been involved in the evolution of sexual signals in this group. PMID:21716735

The Development of the Speaker Independent ARM Continuous Speech Recognition System

DTIC Science & Technology

1992-01-01

spokeTi airborne reconnaissance reports u-ing a speech recognition system based on phoneme-level hidden Markov models (HMMs). Previous versions of the ARM...will involve automatic selection from multiple model sets, corresponding to different speaker types, and that the most rudimen- tary partition of a...The vocabulary size for the ARM task is 497 words. These words are related to the phoneme-level symbols corresponding to the models in the model set

Developing Cross-Racial Self-Efficacy: A Longitudinal Examination of the Role of Cross-Racial Mastery Experiences

ERIC Educational Resources Information Center

Liang, Christopher T. H.; Prince, Jessica K.

2008-01-01

A social-cognitive model for the development of cross-racial self-efficacy was developed and tested in a longitudinal study involving a racially and culturally diverse sample of undergraduate students (N = 879). Multiple group analyses indicated that the model fit equally well for men and women and for White students and ethnic minority students.…

Modeling Complex Equilibria in ITC Experiments: Thermodynamic Parameters Estimation for a Three Binding Site Model

PubMed Central

Le, Vu H.; Buscaglia, Robert; Chaires, Jonathan B.; Lewis, Edwin A.

2013-01-01

Isothermal Titration Calorimetry, ITC, is a powerful technique that can be used to estimate a complete set of thermodynamic parameters (e.g. Keq (or ΔG), ΔH, ΔS, and n) for a ligand binding interaction described by a thermodynamic model. Thermodynamic models are constructed by combination of equilibrium constant, mass balance, and charge balance equations for the system under study. Commercial ITC instruments are supplied with software that includes a number of simple interaction models, for example one binding site, two binding sites, sequential sites, and n-independent binding sites. More complex models for example, three or more binding sites, one site with multiple binding mechanisms, linked equilibria, or equilibria involving macromolecular conformational selection through ligand binding need to be developed on a case by case basis by the ITC user. In this paper we provide an algorithm (and a link to our MATLAB program) for the non-linear regression analysis of a multiple binding site model with up to four overlapping binding equilibria. Error analysis demonstrates that fitting ITC data for multiple parameters (e.g. up to nine parameters in the three binding site model) yields thermodynamic parameters with acceptable accuracy. PMID:23262283

Promoting Decimal Number Sense and Representational Fluency

ERIC Educational Resources Information Center

Suh, Jennifer M.; Johnston, Chris; Jamieson, Spencer; Mills, Michelle

2008-01-01

The abstract nature of mathematics requires the communication of mathematical ideas through multiple representations, such as words, symbols, pictures, objects, or actions. Building representational fluency involves using mathematical representations flexibly and being able to interpret and translate among these different models and mathematical…

The science of Strategic Communication and its utility in natural resource management

EPA Science Inventory

The field of Strategic Communication involves a focused effort to identify, develop, and present multiple types of communication media on a given subject. A Strategic Communication program recognizes the limitations of the most common communication models (primarily "one si...

MODELING A MIXTURE: PBPK/PD APPROACHES FOR PREDICTING CHEMICAL INTERACTIONS.

EPA Science Inventory

Since environmental chemical exposures generally involve multiple chemicals, there are both regulatory and scientific drivers to develop methods to predict outcomes of these exposures. Even using efficient statistical and experimental designs, it is not possible to test in vivo a...

The Rho Kinases: Critical Mediators of Multiple Profibrotic Processes and Rational Targets for New Therapies for Pulmonary Fibrosis

PubMed Central

Knipe, Rachel S.; Tager, Andrew M.

2015-01-01

Idiopathic pulmonary fibrosis (IPF) is characterized by progressive lung scarring, short median survival, and limited therapeutic options, creating great need for new pharmacologic therapies. IPF is thought to result from repetitive environmental injury to the lung epithelium, in the context of aberrant host wound healing responses. Tissue responses to injury fundamentally involve reorganization of the actin cytoskeleton of participating cells, including epithelial cells, fibroblasts, endothelial cells, and macrophages. Actin filament assembly and actomyosin contraction are directed by the Rho-associated coiled-coil forming protein kinase (ROCK) family of serine/threonine kinases (ROCK1 and ROCK2). As would therefore be expected, lung ROCK activation has been demonstrated in humans with IPF and in animal models of this disease. ROCK inhibitors can prevent fibrosis in these models, and more importantly, induce the regression of already established fibrosis. Here we review ROCK structure and function, upstream activators and downstream targets of ROCKs in pulmonary fibrosis, contributions of ROCKs to profibrotic cellular responses to lung injury, ROCK inhibitors and their efficacy in animal models of pulmonary fibrosis, and potential toxicities of ROCK inhibitors in humans, as well as involvement of ROCKs in fibrosis in other organs. As we discuss, ROCK activation is required for multiple profibrotic responses, in the lung and multiple other organs, suggesting ROCK participation in fundamental pathways that contribute to the pathogenesis of a broad array of fibrotic diseases. Multiple lines of evidence therefore indicate that ROCK inhibition has great potential to be a powerful therapeutic tool in the treatment of fibrosis, both in the lung and beyond. PMID:25395505

Pathways from Racial Discrimination to Multiple Sexual Partners Among Male African American Adolescents

PubMed Central

Kogan, Steven M.; Yu, Tianyi; Allen, Kimberly A.; Pocock, Alexandra M.; Brody, Gene H.

2014-01-01

African American male adolescents’ involvement with multiple sexual partners has important implications for public health as well as for their development of ideas regarding masculinity and sexuality. The purpose of this study was to test hypotheses regarding the pathways through which racial discrimination affects African American adolescents’ involvement with multiple sexual partners. We hypothesized that racial discrimination would engender psychological distress, which would promote attitudes and peer affiliations conducive to multiple sexual partnerships. The study also examined the protective influence of parenting practices in buffering the influence of contextual stressors. Participants were 221 African American male youth who provided data at ages 16 and 18; their parents provided data on family socioeconomic disadvantages. Of these young men, 18.5% reported having 3 or more sexual partners during the past 3 months. Structural equation models indicated that racial discrimination contributed to sexual activity with multiple partners by inducing psychological distress, which in turn affected attitudes and peer affiliations conducive to multiple partners. The experience of protective parenting, which included racial socialization, closeness and harmony in parent-child relationships, and parental monitoring, buffered the influence of racial discrimination on psychological distress. These findings suggest targets for prevention programming and underscore the importance of efforts to reduce young men’s experience with racial discrimination. PMID:25937821

A new statistical method for transfer coefficient calculations in the framework of the general multiple-compartment model of transport for radionuclides in biological systems.

PubMed

Garcia, F; Arruda-Neto, J D; Manso, M V; Helene, O M; Vanin, V R; Rodriguez, O; Mesa, J; Likhachev, V P; Filho, J W; Deppman, A; Perez, G; Guzman, F; de Camargo, S P

1999-10-01

A new and simple statistical procedure (STATFLUX) for the calculation of transfer coefficients of radionuclide transport to animals and plants is proposed. The method is based on the general multiple-compartment model, which uses a system of linear equations involving geometrical volume considerations. By using experimentally available curves of radionuclide concentrations versus time, for each animal compartment (organs), flow parameters were estimated by employing a least-squares procedure, whose consistency is tested. Some numerical results are presented in order to compare the STATFLUX transfer coefficients with those from other works and experimental data.

Statistical hadronization with exclusive channels in e +e - annihilation

DOE PAGES

Ferroni, L.; Becattini, F.

2012-01-01

We present a systematic analysis of exclusive hadronic channels in e +e - collisions at centre-of-mass energies between 2.1 and 2.6 GeV within the statistical hadronization model. Because of the low multiplicities involved, calculations have been carried out in the full microcanonical ensemble, including conservation of energy-momentum, angular momentum, parity, isospin, and all relevant charges. We show that the data is in an overall good agreement with the model for an energy density of about 0.5 GeV/fm 3 and an extra strangeness suppression parameter γ S 0:7, essentially the same values found with fits to inclusive multiplicities at higher energy.

The role of visual imagery in the retention of information from sentences.

PubMed

Drose, G S; Allen, G L

1994-01-01

We conducted two experiments to evaluate a multiple-code model for sentence memory that posits both propositional and visual representational systems. Both sentences involved recognition memory. The results of Experiment 1 indicated that subjects' recognition memory for concrete sentences was superior to their recognition memory for abstract sentences. Instructions to use visual imagery to enhance recognition performance yielded no effects. Experiment 2 tested the prediction that interference by a visual task would differentially affect recognition memory for concrete sentences. Results showed the interference task to have had a detrimental effect on recognition memory for both concrete and abstract sentences. Overall, the evidence provided partial support for both a multiple-code model and a semantic integration model of sentence memory.

A Generic Authentication LoA Derivation Model

NASA Astrophysics Data System (ADS)

Yao, Li; Zhang, Ning

One way of achieving a more fine-grained access control is to link an authentication level of assurance (LoA) derived from a requester’s authentication instance to the authorisation decision made to the requester. To realise this vision, there is a need for designing a LoA derivation model that supports the use and quantification of multiple LoA-effecting attributes, and analyse their composite effect on a given authentication instance. This paper reports the design of such a model, namely a generic LoA derivation model (GEA- LoADM). GEA-LoADM takes into account of multiple authentication attributes along with their relationships, abstracts the composite effect by the multiple attributes into a generic value, authentication LoA, and provides algorithms for the run-time derivation of LoA. The algorithms are tailored to reflect the relationships among the attributes involved in an authentication instance. The model has a number of valuable properties, including flexibility and extensibility; it can be applied to different application contexts and support easy addition of new attributes and removal of obsolete ones.

Multivariate longitudinal data analysis with mixed effects hidden Markov models.

PubMed

Raffa, Jesse D; Dubin, Joel A

2015-09-01

Multiple longitudinal responses are often collected as a means to capture relevant features of the true outcome of interest, which is often hidden and not directly measurable. We outline an approach which models these multivariate longitudinal responses as generated from a hidden disease process. We propose a class of models which uses a hidden Markov model with separate but correlated random effects between multiple longitudinal responses. This approach was motivated by a smoking cessation clinical trial, where a bivariate longitudinal response involving both a continuous and a binomial response was collected for each participant to monitor smoking behavior. A Bayesian method using Markov chain Monte Carlo is used. Comparison of separate univariate response models to the bivariate response models was undertaken. Our methods are demonstrated on the smoking cessation clinical trial dataset, and properties of our approach are examined through extensive simulation studies. © 2015, The International Biometric Society.

Organizational Commitment and Nurses' Characteristics as Predictors of Job Involvement.

PubMed

Alammar, Kamila; Alamrani, Mashael; Alqahtani, Sara; Ahmad, Muayyad

2016-01-01

To predict nurses' job involvement on the basis of their organizational commitment and personal characteristics at a large tertiary hospital in Saudi Arabia. Data were collected in 2015 from a convenience sample of 558 nurses working at a large tertiary hospital in Riyadh, Saudi Arabia. A cross-sectional correlational design was used in this study. Data were collected using a structured questionnaire. All commitment scales had significant relationships. Multiple linear regression analysis revealed that the model predicted a sizeable proportion of variance in nurses' job involvement (p < 0.001). High organizational commitment enhances job involvement, which may lead to more organizational stability and effectiveness.

Temperature Stratification in a Cryogenic Fuel Tank

NASA Technical Reports Server (NTRS)

Daigle, Matthew John; Smelyanskiy, Vadim; Boschee, Jacob; Foygel, Michael Gregory

2013-01-01

A reduced dynamical model describing temperature stratification effects driven by natural convection in a liquid hydrogen cryogenic fuel tank has been developed. It accounts for cryogenic propellant loading, storage, and unloading in the conditions of normal, increased, and micro- gravity. The model involves multiple horizontal control volumes in both liquid and ullage spaces. Temperature and velocity boundary layers at the tank walls are taken into account by using correlation relations. Heat exchange involving the tank wall is considered by means of the lumped-parameter method. By employing basic conservation laws, the model takes into consideration the major multi-phase mass and energy exchange processes involved, such as condensation-evaporation of the hydrogen, as well as flows of hydrogen liquid and vapor in the presence of pressurizing helium gas. The model involves a liquid hydrogen feed line and a tank ullage vent valve for pressure control. The temperature stratification effects are investigated, including in the presence of vent valve oscillations. A simulation of temperature stratification effects in a generic cryogenic tank has been implemented in Matlab and results are presented for various tank conditions.

Models of Sector Flows Under Local, Regional and Airport Weather Constraints

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak

2017-01-01

Recently, the ATM community has made important progress in collaborative trajectory management through the introduction of a new FAA traffic management initiative called a Collaborative Trajectory Options Program (CTOP). FAA can use CTOPs to manage air traffic under multiple constraints (manifested as flow constrained areas or FCAs) in the system, and it allows flight operators to indicate their preferences for routing and delay options. CTOPs also permits better management of the overall trajectory of flights by considering both routing and departure delay options simultaneously. However, adoption of CTOPs in airspace has been hampered by many factors that include challenges in how to identify constrained areas and how to set rates for the FCAs. Decision support tools providing assistance would be particularly helpful in effective use of CTOPs. Such DSTs tools would need models of demand and capacity in the presence of multiple constraints. This study examines different approaches to using historical data to create and validate models of maximum flows in sectors and other airspace regions in the presence of multiple constraints. A challenge in creating an empirical model of flows under multiple constraints is a lack of sufficient historical data that captures diverse situations involving combinations of multiple constraints especially those with severe weather. The approach taken here to deal with this is two-fold. First, we create a generalized sector model encompassing multiple sectors rather than individual sectors in order to increase the amount of data used for creating the model by an order of magnitude. Secondly, we decompose the problem so that the amount of data needed is reduced. This involves creating a baseline demand model plus a separate weather constrained flow reduction model and then composing these into a single integrated model. A nominal demand model is a flow model (gdem) in the presence of clear local weather. This defines the flow as a function of weather constraints in neighboring regions, airport constraints and weather in locations that can cause re-routes to the location of interest. A weather constrained flow reduction model (fwx-red) is a model of reduction in baseline counts as a function of local weather. Because the number of independent variables associated with each of the two decomposed models is smaller than that with a single model, need for amount of data is reduced. Finally, a composite model that combines these two can be represented as fwx-red (gdem(e), l) where e represents non-local constraints and l represents local weather. The approaches studied to developing these models are divided into three categories: (1) Point estimation models (2) Empirical models (3) Theoretical models. Errors in predictions of these different types of models have been estimated. In situations when there is abundant data, point estimation models tend to be very accurate. In contrast, empirical models do better than theoretical models when there is some data available. The biggest benefit of theoretical models is their general applicability in wider range situations once the degree of accuracy of these has been established.

Models of Sector Aircraft Counts in the Presence of Local, Regional and Airport Constraints

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak

2017-01-01

Recently, the ATM community has made important progress in collaborative trajectory management through the introduction of a new FAA traffic management initiative called a Collaborative Trajectory Options Program (CTOP). FAA can use CTOPs to manage air traffic under multiple constraints (manifested as flow constrained areas or FCAs) in the system, and it allows flight operators to indicate their preferences for routing and delay options. CTOPs also permits better management of the overall trajectory of flights by considering both routing and departure delay options simultaneously. However, adoption of CTOPs in airspace has been hampered by many factors that include challenges in how to identify constrained areas and how to set rates for the FCAs. Decision support tools providing assistance would be particularly helpful in effective use of CTOPs. Such DSTs tools would need models of demand and capacity in the presence of multiple constraints. This study examines different approaches to using historical data to create and validate models of maximum flows in sectors and other airspace regions in the presence of multiple constraints. A challenge in creating an empirical model of flows under multiple constraints is a lack of sufficient historical data that captures diverse situations involving combinations of multiple constraints especially those with severe weather. The approach taken here to deal with this is two-fold. First, we create a generalized sector model encompassing multiple sectors rather than individual sectors in order to increase the amount of data used for creating the model by an order of magnitude. Secondly, we decompose the problem so that the amount of data needed is reduced. This involves creating a baseline demand model plus a separate weather constrained flow reduction model and then composing these into a single integrated model. A nominal demand model is a flow model (gdem) in the presence of clear local weather. This defines the flow as a function of weather constraints in neighboring regions, airport constraints and weather in locations that can cause re-routes to the location of interest. A weather constrained flow reduction model (fwx-red) is a model of reduction in baseline counts as a function of local weather. Because the number of independent variables associated with each of the two decomposed models is smaller than that with a single model, need for amount of data is reduced. Finally, a composite model that combines these two can be represented as fwx-red (gdem(e), l) where e represents non-local constraints and l represents local weather. The approaches studied to developing these models are divided into three categories: (1) Point estimation models (2) Empirical models (3) Theoretical models. Errors in predictions of these different types of models have been estimated. In situations when there is abundant data, point estimation models tend to be very accurate. In contrast, empirical models do better than theoretical models when there is some data available. The biggest benefit of theoretical models is their general applicability in wider range situations once the degree of accuracy of these has been established.

USING REMORE SENSING AND LANDSCAPE ECOLOGY TO ASSESS THE CONDITION OF GREAT LAKES WETLANDS

EPA Science Inventory

Geospatial modeling approaches are being used to locate and assess the condition of natural resources (particularly wetland ecosystems) in the Great Lakes Basin. These assessments involve measuring landscape characteristics at multiple scales, primarily focusing

on surface...

Proteomic analysis of lung tissue by DIGE

USDA-ARS?s Scientific Manuscript database

Lungs perform an essential physiological function, mediated by a complex series of events that involve the coordination of multiple cell types to support not only gaseous exchange, but homeostasis and protection from infection. Guinea pigs are an important animal disease model for a number of infect...

Gravitational decoupling and the Picard-Lefschetz approach

NASA Astrophysics Data System (ADS)

Brown, Jon; Cole, Alex; Shiu, Gary; Cottrell, William

2018-01-01

In this work, we consider tunneling between nonmetastable states in gravitational theories. Such processes arise in various contexts, e.g., in inflationary scenarios where the inflaton potential involves multiple fields or multiple branches. They are also relevant for bubble wall nucleation in some cosmological settings. However, we show that the transition amplitudes computed using the Euclidean method generally do not approach the corresponding field theory limit as Mp→∞ . This implies that in the Euclidean framework, there is no systematic expansion in powers of GN for such processes. Such considerations also carry over directly to no-boundary scenarios involving Hawking-Turok instantons. In this note, we illustrate this failure of decoupling in the Euclidean approach with a simple model of axion monodromy and then argue that the situation can be remedied with a Lorentzian prescription such as the Picard-Lefschetz theory. As a proof of concept, we illustrate with a simple model how tunneling transition amplitudes can be calculated using the Picard-Lefschetz approach.

An integrative model of auditory phantom perception: tinnitus as a unified percept of interacting separable subnetworks.

PubMed

De Ridder, Dirk; Vanneste, Sven; Weisz, Nathan; Londero, Alain; Schlee, Winnie; Elgoyhen, Ana Belen; Langguth, Berthold

2014-07-01

Tinnitus is a considered to be an auditory phantom phenomenon, a persistent conscious percept of a salient memory trace, externally attributed, in the absence of a sound source. It is perceived as a phenomenological unified coherent percept, binding multiple separable clinical characteristics, such as its loudness, the sidedness, the type (pure tone, noise), the associated distress and so on. A theoretical pathophysiological framework capable of explaining all these aspects in one model is highly needed. The model must incorporate both the deafferentation based neurophysiological models and the dysfunctional noise canceling model, and propose a 'tinnitus core' subnetwork. The tinnitus core can be defined as the minimal set of brain areas that needs to be jointly activated (=subnetwork) for tinnitus to be consciously perceived, devoid of its affective components. The brain areas involved in the other separable characteristics of tinnitus can be retrieved by studies on spontaneous resting state magnetic and electrical activity in people with tinnitus, evaluated for the specific aspect investigated and controlled for other factors. By combining these functional imaging studies with neuromodulation techniques some of the correlations are turned into causal relationships. Thereof, a heuristic pathophysiological framework is constructed, integrating the tinnitus perceptual core with the other tinnitus related aspects. This phenomenological unified percept of tinnitus can be considered an emergent property of multiple, parallel, dynamically changing and partially overlapping subnetworks, each with a specific spontaneous oscillatory pattern and functional connectivity signature. Communication between these different subnetworks is proposed to occur at hubs, brain areas that are involved in multiple subnetworks simultaneously. These hubs can take part in each separable subnetwork at different frequencies. Communication between the subnetworks is proposed to occur at discrete oscillatory frequencies. As such, the brain uses multiple nonspecific networks in parallel, each with their own oscillatory signature, that adapt to the context to construct a unified percept possibly by synchronized activation integrated at hubs at discrete oscillatory frequencies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Analyzing latent state-trait and multiple-indicator latent growth curve models as multilevel structural equation models

PubMed Central

Geiser, Christian; Bishop, Jacob; Lockhart, Ginger; Shiffman, Saul; Grenard, Jerry L.

2013-01-01

Latent state-trait (LST) and latent growth curve (LGC) models are frequently used in the analysis of longitudinal data. Although it is well-known that standard single-indicator LGC models can be analyzed within either the structural equation modeling (SEM) or multilevel (ML; hierarchical linear modeling) frameworks, few researchers realize that LST and multivariate LGC models, which use multiple indicators at each time point, can also be specified as ML models. In the present paper, we demonstrate that using the ML-SEM rather than the SL-SEM framework to estimate the parameters of these models can be practical when the study involves (1) a large number of time points, (2) individually-varying times of observation, (3) unequally spaced time intervals, and/or (4) incomplete data. Despite the practical advantages of the ML-SEM approach under these circumstances, there are also some limitations that researchers should consider. We present an application to an ecological momentary assessment study (N = 158 youths with an average of 23.49 observations of positive mood per person) using the software Mplus (Muthén and Muthén, 1998–2012) and discuss advantages and disadvantages of using the ML-SEM approach to estimate the parameters of LST and multiple-indicator LGC models. PMID:24416023

Using the Context, Input, Process, and Product Evaluation Model (CIPP) as a Comprehensive Framework to Guide the Planning, Implementation, and Assessment of Service-Learning Programs

ERIC Educational Resources Information Center

Zhang, Guili; Zeller, Nancy; Griffith, Robin; Metcalf, Debbie; Williams, Jennifer; Shea, Christine; Misulis, Katherine

2011-01-01

Planning, implementing, and assessing a service-learning project can be a complex task because service-learning projects often involve multiple constituencies and aim to meet both the needs of service providers and community partners. In this article, Stufflebeam's Context, Input, Process, and Product (CIPP) evaluation model is recommended as a…

Perturbation Theory/Machine Learning Model of ChEMBL Data for Dopamine Targets: Docking, Synthesis, and Assay of New l-Prolyl-l-leucyl-glycinamide Peptidomimetics.

PubMed

Ferreira da Costa, Joana; Silva, David; Caamaño, Olga; Brea, José M; Loza, Maria Isabel; Munteanu, Cristian R; Pazos, Alejandro; García-Mera, Xerardo; González-Díaz, Humbert

2018-06-25

Predicting drug-protein interactions (DPIs) for target proteins involved in dopamine pathways is a very important goal in medicinal chemistry. We can tackle this problem using Molecular Docking or Machine Learning (ML) models for one specific protein. Unfortunately, these models fail to account for large and complex big data sets of preclinical assays reported in public databases. This includes multiple conditions of assays, such as different experimental parameters, biological assays, target proteins, cell lines, organism of the target, or organism of assay. On the other hand, perturbation theory (PT) models allow us to predict the properties of a query compound or molecular system in experimental assays with multiple boundary conditions based on a previously known case of reference. In this work, we report the first PTML (PT + ML) study of a large ChEMBL data set of preclinical assays of compounds targeting dopamine pathway proteins. The best PTML model found predicts 50000 cases with accuracy of 70-91% in training and external validation series. We also compared the linear PTML model with alternative PTML models trained with multiple nonlinear methods (artificial neural network (ANN), Random Forest, Deep Learning, etc.). Some of the nonlinear methods outperform the linear model but at the cost of a notable increment of the complexity of the model. We illustrated the practical use of the new model with a proof-of-concept theoretical-experimental study. We reported for the first time the organic synthesis, chemical characterization, and pharmacological assay of a new series of l-prolyl-l-leucyl-glycinamide (PLG) peptidomimetic compounds. In addition, we performed a molecular docking study for some of these compounds with the software Vina AutoDock. The work ends with a PTML model predictive study of the outcomes of the new compounds in a large number of assays. Therefore, this study offers a new computational methodology for predicting the outcome for any compound in new assays. This PTML method focuses on the prediction with a simple linear model of multiple pharmacological parameters (IC 50 , EC 50 , K i , etc.) for compounds in assays involving different cell lines used, organisms of the protein target, or organism of assay for proteins in the dopamine pathway.

The multiple imputation method: a case study involving secondary data analysis.

PubMed

Walani, Salimah R; Cleland, Charles M

2015-05-01

To illustrate with the example of a secondary data analysis study the use of the multiple imputation method to replace missing data. Most large public datasets have missing data, which need to be handled by researchers conducting secondary data analysis studies. Multiple imputation is a technique widely used to replace missing values while preserving the sample size and sampling variability of the data. The 2004 National Sample Survey of Registered Nurses. The authors created a model to impute missing values using the chained equation method. They used imputation diagnostics procedures and conducted regression analysis of imputed data to determine the differences between the log hourly wages of internationally educated and US-educated registered nurses. The authors used multiple imputation procedures to replace missing values in a large dataset with 29,059 observations. Five multiple imputed datasets were created. Imputation diagnostics using time series and density plots showed that imputation was successful. The authors also present an example of the use of multiple imputed datasets to conduct regression analysis to answer a substantive research question. Multiple imputation is a powerful technique for imputing missing values in large datasets while preserving the sample size and variance of the data. Even though the chained equation method involves complex statistical computations, recent innovations in software and computation have made it possible for researchers to conduct this technique on large datasets. The authors recommend nurse researchers use multiple imputation methods for handling missing data to improve the statistical power and external validity of their studies.

Validation and calibration of structural models that combine information from multiple sources.

PubMed

Dahabreh, Issa J; Wong, John B; Trikalinos, Thomas A

2017-02-01

Mathematical models that attempt to capture structural relationships between their components and combine information from multiple sources are increasingly used in medicine. Areas covered: We provide an overview of methods for model validation and calibration and survey studies comparing alternative approaches. Expert commentary: Model validation entails a confrontation of models with data, background knowledge, and other models, and can inform judgments about model credibility. Calibration involves selecting parameter values to improve the agreement of model outputs with data. When the goal of modeling is quantitative inference on the effects of interventions or forecasting, calibration can be viewed as estimation. This view clarifies issues related to parameter identifiability and facilitates formal model validation and the examination of consistency among different sources of information. In contrast, when the goal of modeling is the generation of qualitative insights about the modeled phenomenon, calibration is a rather informal process for selecting inputs that result in model behavior that roughly reproduces select aspects of the modeled phenomenon and cannot be equated to an estimation procedure. Current empirical research on validation and calibration methods consists primarily of methodological appraisals or case-studies of alternative techniques and cannot address the numerous complex and multifaceted methodological decisions that modelers must make. Further research is needed on different approaches for developing and validating complex models that combine evidence from multiple sources.

Evaluation of metabolites extraction strategies for identifying different brain regions and their relationship with alcohol preference and gender difference using NMR metabolomics.

PubMed

Wang, Jie; Zeng, Hao-Long; Du, Hongying; Liu, Zeyuan; Cheng, Ji; Liu, Taotao; Hu, Ting; Kamal, Ghulam Mustafa; Li, Xihai; Liu, Huili; Xu, Fuqiang

2018-03-01

Metabolomics generate a profile of small molecules from cellular/tissue metabolism, which could directly reflect the mechanisms of complex networks of biochemical reactions. Traditional metabolomics methods, such as OPLS-DA, PLS-DA are mainly used for binary class discrimination. Multiple groups are always involved in the biological system, especially for brain research. Multiple brain regions are involved in the neuronal study of brain metabolic dysfunctions such as alcoholism, Alzheimer's disease, etc. In the current study, 10 different brain regions were utilized for comparative studies between alcohol preferring and non-preferring rats, male and female rats respectively. As many classes are involved (ten different regions and four types of animals), traditional metabolomics methods are no longer efficient for showing differentiation. Here, a novel strategy based on the decision tree algorithm was employed for successfully constructing different classification models to screen out the major characteristics of ten brain regions at the same time. Subsequently, this method was also utilized to select the major effective brain regions related to alcohol preference and gender difference. Compared with the traditional multivariate statistical methods, the decision tree could construct acceptable and understandable classification models for multi-class data analysis. Therefore, the current technology could also be applied to other general metabolomics studies involving multi class data. Copyright © 2017 Elsevier B.V. All rights reserved.

Social Ecology, Genomics, and African American Health: A Nonlinear Dynamical Perspective

PubMed Central

Madhere, Serge; Harrell, Jules; Royal, Charmaine D. M.

2009-01-01

This article offers a model that clarifies the degree of interdependence between social ecology and genomic processes. Drawing on principles from nonlinear dynamics, the model delineates major lines of bifurcation involving people's habitat, their family health history, and collective catastrophes experienced by their community. It shows how mechanisms of resource acquisition, depletion, and preservation can lead to disruptions in basic metabolism and in the activity of cytokines, neurotransmitters, and protein kinases, thus giving impetus to epigenetic changes. The hypotheses generated from the model are discussed throughout the article for their relevance to health problems among African Americans. Where appropriate, they are examined in light of data from the National Vital Statistics System. Multiple health outcomes are considered. For any one of them, the model makes clear the unique and converging contributions of multiple antecedent factors. PMID:19672481

A regenerative approach to the treatment of multiple sclerosis.

PubMed

Deshmukh, Vishal A; Tardif, Virginie; Lyssiotis, Costas A; Green, Chelsea C; Kerman, Bilal; Kim, Hyung Joon; Padmanabhan, Krishnan; Swoboda, Jonathan G; Ahmad, Insha; Kondo, Toru; Gage, Fred H; Theofilopoulos, Argyrios N; Lawson, Brian R; Schultz, Peter G; Lairson, Luke L

2013-10-17

Progressive phases of multiple sclerosis are associated with inhibited differentiation of the progenitor cell population that generates the mature oligodendrocytes required for remyelination and disease remission. To identify selective inducers of oligodendrocyte differentiation, we performed an image-based screen for myelin basic protein (MBP) expression using primary rat optic-nerve-derived progenitor cells. Here we show that among the most effective compounds identifed was benztropine, which significantly decreases clinical severity in the experimental autoimmune encephalomyelitis (EAE) model of relapsing-remitting multiple sclerosis when administered alone or in combination with approved immunosuppressive treatments for multiple sclerosis. Evidence from a cuprizone-induced model of demyelination, in vitro and in vivo T-cell assays and EAE adoptive transfer experiments indicated that the observed efficacy of this drug results directly from an enhancement of remyelination rather than immune suppression. Pharmacological studies indicate that benztropine functions by a mechanism that involves direct antagonism of M1 and/or M3 muscarinic receptors. These studies should facilitate the development of effective new therapies for the treatment of multiple sclerosis that complement established immunosuppressive approaches.

Statechart Analysis with Symbolic PathFinder

NASA Technical Reports Server (NTRS)

Pasareanu, Corina S.

2012-01-01

We report here on our on-going work that addresses the automated analysis and test case generation for software systems modeled using multiple Statechart formalisms. The work is motivated by large programs such as NASA Exploration, that involve multiple systems that interact via safety-critical protocols and are designed with different Statechart variants. To verify these safety-critical systems, we have developed Polyglot, a framework for modeling and analysis of model-based software written using different Statechart formalisms. Polyglot uses a common intermediate representation with customizable Statechart semantics and leverages the analysis and test generation capabilities of the Symbolic PathFinder tool. Polyglot is used as follows: First, the structure of the Statechart model (expressed in Matlab Stateflow or Rational Rhapsody) is translated into a common intermediate representation (IR). The IR is then translated into Java code that represents the structure of the model. The semantics are provided as "pluggable" modules.

Protective factors associated with fewer multiple problem behaviors among homeless/runaway youth.

PubMed

Lightfoot, Marguerita; Stein, Judith A; Tevendale, Heather; Preston, Kathleen

2011-01-01

Although homeless youth exhibit numerous problem behaviors, protective factors that can be targeted and modified by prevention programs to decrease the likelihood of involvement in risky behaviors are less apparent. The current study tested a model of protective factors for multiple problem behavior in a sample of 474 homeless youth (42% girls; 83% minority) ages 12 to 24 years. Higher levels of problem solving and planning skills were strongly related to lower levels of multiple problem behaviors in homeless youth, suggesting both the positive impact of preexisting personal assets of these youth and important programmatic targets for further building their resilience and decreasing problem behaviors. Indirect relationships between the background factors of self-esteem and social support and multiple problem behaviors were significantly mediated through protective skills. The model suggests that helping youth enhance their skills in goal setting, decision making, and self-reliant coping could lessen a variety of problem behaviors commonly found among homeless youth.

Protective Factors Associated with Fewer Multiple Problem Behaviors Among Homeless/Runaway Youth

PubMed Central

Lightfoot, Marguerita; Stein, Judith A.; Tevendale, Heather; Preston, Kathleen

2015-01-01

Although homeless youth exhibit numerous problem behaviors, protective factors that can be targeted and modified by prevention programs to decrease the likelihood of involvement in risky behaviors are less apparent. The current study tested a model of protective factors for multiple problem behavior in a sample of 474 homeless youth (42% girls; 83% minority) ages 12 to 24 years. Higher levels of problem solving and planning skills were strongly related to lower levels of multiple problem behaviors in homeless youth, suggesting both the positive impact of preexisting personal assets of these youth and important programmatic targets for further building their resilience and decreasing problem behaviors. Indirect relationships between the background factors of self-esteem and social support and multiple problem behaviors were significantly mediated through protective skills. The model suggests that helping youth enhance their skills in goal setting, decision making, and self-reliant coping could lessen a variety of problem behaviors commonly found among homeless youth. PMID:22023279

Software forecasting as it is really done: A study of JPL software engineers

NASA Technical Reports Server (NTRS)

Griesel, Martha Ann; Hihn, Jairus M.; Bruno, Kristin J.; Fouser, Thomas J.; Tausworthe, Robert C.

1993-01-01

This paper presents a summary of the results to date of a Jet Propulsion Laboratory internally funded research task to study the costing process and parameters used by internally recognized software cost estimating experts. Protocol Analysis and Markov process modeling were used to capture software engineer's forecasting mental models. While there is significant variation between the mental models that were studied, it was nevertheless possible to identify a core set of cost forecasting activities, and it was also found that the mental models cluster around three forecasting techniques. Further partitioning of the mental models revealed clustering of activities, that is very suggestive of a forecasting lifecycle. The different forecasting methods identified were based on the use of multiple-decomposition steps or multiple forecasting steps. The multiple forecasting steps involved either forecasting software size or an additional effort forecast. Virtually no subject used risk reduction steps in combination. The results of the analysis include: the identification of a core set of well defined costing activities, a proposed software forecasting life cycle, and the identification of several basic software forecasting mental models. The paper concludes with a discussion of the implications of the results for current individual and institutional practices.

Semantic Structures of One-Step Word Problems Involving Multiplication or Division.

ERIC Educational Resources Information Center

Schmidt, Siegbert; Weiser, Werner

1995-01-01

Proposes a four-category classification of semantic structures of one-step word problems involving multiplication and division: forming the n-th multiple of measures, combinatorial multiplication, composition of operators, and multiplication by formula. This classification is compatible with semantic structures of addition and subtraction word…

User needs for propagation data

NASA Technical Reports Server (NTRS)

Sullivan, Thomas M.

1993-01-01

New and refined models of radio signal propagation phenomena are needed to support studies of evolving satellite services and systems. Taking an engineering perspective, applications for propagation measurements and models in the context of various types of analyses that are of ongoing interest are reviewed. Problems that were encountered in the signal propagation aspects of these analyses are reviewed, and potential solutions to these problems are discussed. The focus is on propagation measurements and models needed to support design and performance analyses of systems in the Mobile-Satellite Service (MSS) operating in the 1-3 GHz range. These systems may use geostationary or non-geostationary satellites and Frequency Division Multiple Access (FDMA), Time Division Multiple Access Digital (TDMA), or Code Division Multiple Access (CDMA) techniques. Many of the propagation issues raised in relation to MSS are also pertinent to other services such as broadcasting-satellite (sound) at 2310-2360 MHz. In particular, services involving mobile terminals or terminals with low gain antennas are of concern.

Inference of emission rates from multiple sources using Bayesian probability theory.

PubMed

Yee, Eugene; Flesch, Thomas K

2010-03-01

The determination of atmospheric emission rates from multiple sources using inversion (regularized least-squares or best-fit technique) is known to be very susceptible to measurement and model errors in the problem, rendering the solution unusable. In this paper, a new perspective is offered for this problem: namely, it is argued that the problem should be addressed as one of inference rather than inversion. Towards this objective, Bayesian probability theory is used to estimate the emission rates from multiple sources. The posterior probability distribution for the emission rates is derived, accounting fully for the measurement errors in the concentration data and the model errors in the dispersion model used to interpret the data. The Bayesian inferential methodology for emission rate recovery is validated against real dispersion data, obtained from a field experiment involving various source-sensor geometries (scenarios) consisting of four synthetic area sources and eight concentration sensors. The recovery of discrete emission rates from three different scenarios obtained using Bayesian inference and singular value decomposition inversion are compared and contrasted.

Load forecasting via suboptimal seasonal autoregressive models and iteratively reweighted least squares estimation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mbamalu, G.A.N.; El-Hawary, M.E.

The authors propose suboptimal least squares or IRWLS procedures for estimating the parameters of a seasonal multiplicative AR model encountered during power system load forecasting. The proposed method involves using an interactive computer environment to estimate the parameters of a seasonal multiplicative AR process. The method comprises five major computational steps. The first determines the order of the seasonal multiplicative AR process, and the second uses the least squares or the IRWLS to estimate the optimal nonseasonal AR model parameters. In the third step one obtains the intermediate series by back forecast, which is followed by using the least squaresmore » or the IRWLS to estimate the optimal season AR parameters. The final step uses the estimated parameters to forecast future load. The method is applied to predict the Nova Scotia Power Corporation's 168 lead time hourly load. The results obtained are documented and compared with results based on the Box and Jenkins method.« less

Genomic and Coexpression Analyses Predict Multiple Genes Involved in Triterpene Saponin Biosynthesis in Medicago truncatula[C][W

PubMed Central

Naoumkina, Marina A.; Modolo, Luzia V.; Huhman, David V.; Urbanczyk-Wochniak, Ewa; Tang, Yuhong; Sumner, Lloyd W.; Dixon, Richard A.

2010-01-01

Saponins, an important group of bioactive plant natural products, are glycosides of triterpenoid or steroidal aglycones (sapogenins). Saponins possess many biological activities, including conferring potential health benefits for humans. However, most of the steps specific for the biosynthesis of triterpene saponins remain uncharacterized at the molecular level. Here, we use comprehensive gene expression clustering analysis to identify candidate genes involved in the elaboration, hydroxylation, and glycosylation of the triterpene skeleton in the model legume Medicago truncatula. Four candidate uridine diphosphate glycosyltransferases were expressed in Escherichia coli, one of which (UGT73F3) showed specificity for multiple sapogenins and was confirmed to glucosylate hederagenin at the C28 position. Genetic loss-of-function studies in M. truncatula confirmed the in vivo function of UGT73F3 in saponin biosynthesis. This report provides a basis for future studies to define genetically the roles of multiple cytochromes P450 and glycosyltransferases in triterpene saponin biosynthesis in Medicago. PMID:20348429

High-resolution imaging using a wideband MIMO radar system with two distributed arrays.

PubMed

Wang, Dang-wei; Ma, Xiao-yan; Chen, A-Lei; Su, Yi

2010-05-01

Imaging a fast maneuvering target has been an active research area in past decades. Usually, an array antenna with multiple elements is implemented to avoid the motion compensations involved in the inverse synthetic aperture radar (ISAR) imaging. Nevertheless, there is a price dilemma due to the high level of hardware complexity compared to complex algorithm implemented in the ISAR imaging system with only one antenna. In this paper, a wideband multiple-input multiple-output (MIMO) radar system with two distributed arrays is proposed to reduce the hardware complexity of the system. Furthermore, the system model, the equivalent array production method and the imaging procedure are presented. As compared with the classical real aperture radar (RAR) imaging system, there is a very important contribution in our method that the lower hardware complexity can be involved in the imaging system since many additive virtual array elements can be obtained. Numerical simulations are provided for testing our system and imaging method.

An investigation of multidisciplinary complex health care interventions - steps towards an integrative treatment model in the rehabilitation of People with Multiple Sclerosis

PubMed Central

2012-01-01

Background The Danish Multiple Sclerosis Society initiated a large-scale bridge building and integrative treatment project to take place from 2004–2010 at a specialized Multiple Sclerosis (MS) hospital. In this project, a team of five conventional health care practitioners and five alternative practitioners was set up to work together in developing and offering individualized treatments to 200 people with MS. The purpose of this paper is to present results from the six year treatment collaboration process regarding the development of an integrative treatment model. Discussion The collaborative work towards an integrative treatment model for people with MS, involved six steps: 1) Working with an initial model 2) Unfolding the different treatment philosophies 3) Discussing the elements of the Intervention-Mechanism-Context-Outcome-scheme (the IMCO-scheme) 4) Phrasing the common assumptions for an integrative MS program theory 5) Developing the integrative MS program theory 6) Building the integrative MS treatment model. The model includes important elements of the different treatment philosophies represented in the team and thereby describes a common understanding of the complexity of the courses of treatment. Summary An integrative team of practitioners has developed an integrative model for combined treatments of People with Multiple Sclerosis. The model unites different treatment philosophies and focuses on process-oriented factors and the strengthening of the patients’ resources and competences on a physical, an emotional and a cognitive level. PMID:22524586

Group-oriented coordination models for distributed client-server computing

NASA Technical Reports Server (NTRS)

Adler, Richard M.; Hughes, Craig S.

1994-01-01

This paper describes group-oriented control models for distributed client-server interactions. These models transparently coordinate requests for services that involve multiple servers, such as queries across distributed databases. Specific capabilities include: decomposing and replicating client requests; dispatching request subtasks or copies to independent, networked servers; and combining server results into a single response for the client. The control models were implemented by combining request broker and process group technologies with an object-oriented communication middleware tool. The models are illustrated in the context of a distributed operations support application for space-based systems.

Waste generated in high-rise buildings construction: a quantification model based on statistical multiple regression.

PubMed

Parisi Kern, Andrea; Ferreira Dias, Michele; Piva Kulakowski, Marlova; Paulo Gomes, Luciana

2015-05-01

Reducing construction waste is becoming a key environmental issue in the construction industry. The quantification of waste generation rates in the construction sector is an invaluable management tool in supporting mitigation actions. However, the quantification of waste can be a difficult process because of the specific characteristics and the wide range of materials used in different construction projects. Large variations are observed in the methods used to predict the amount of waste generated because of the range of variables involved in construction processes and the different contexts in which these methods are employed. This paper proposes a statistical model to determine the amount of waste generated in the construction of high-rise buildings by assessing the influence of design process and production system, often mentioned as the major culprits behind the generation of waste in construction. Multiple regression was used to conduct a case study based on multiple sources of data of eighteen residential buildings. The resulting statistical model produced dependent (i.e. amount of waste generated) and independent variables associated with the design and the production system used. The best regression model obtained from the sample data resulted in an adjusted R(2) value of 0.694, which means that it predicts approximately 69% of the factors involved in the generation of waste in similar constructions. Most independent variables showed a low determination coefficient when assessed in isolation, which emphasizes the importance of assessing their joint influence on the response (dependent) variable. Copyright © 2015 Elsevier Ltd. All rights reserved.

One size does not fit all: Adapting mark-recapture and occupancy models for state uncertainty

USGS Publications Warehouse

Kendall, W.L.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

2009-01-01

Multistate capture?recapture models continue to be employed with greater frequency to test hypotheses about metapopulation dynamics and life history, and more recently disease dynamics. In recent years efforts have begun to adjust these models for cases where there is uncertainty about an animal?s state upon capture. These efforts can be categorized into models that permit misclassification between two states to occur in either direction or one direction, where state is certain for a subset of individuals or is always uncertain, and where estimation is based on one sampling occasion per period of interest or multiple sampling occasions per period. State uncertainty also arises in modeling patch occupancy dynamics. I consider several case studies involving bird and marine mammal studies that illustrate how misclassified states can arise, and outline model structures for properly utilizing the data that are produced. In each case misclassification occurs in only one direction (thus there is a subset of individuals or patches where state is known with certainty), and there are multiple sampling occasions per period of interest. For the cases involving capture?recapture data I allude to a general model structure that could include each example as a special case. However, this collection of cases also illustrates how difficult it is to develop a model structure that can be directly useful for answering every ecological question of interest and account for every type of data from the field.

Interacting multiple model forward filtering and backward smoothing for maneuvering target tracking

NASA Astrophysics Data System (ADS)

Nandakumaran, N.; Sutharsan, S.; Tharmarasa, R.; Lang, Tom; McDonald, Mike; Kirubarajan, T.

2009-08-01

The Interacting Multiple Model (IMM) estimator has been proven to be effective in tracking agile targets. Smoothing or retrodiction, which uses measurements beyond the current estimation time, provides better estimates of target states. Various methods have been proposed for multiple model smoothing in the literature. In this paper, a new smoothing method, which involves forward filtering followed by backward smoothing while maintaining the fundamental spirit of the IMM, is proposed. The forward filtering is performed using the standard IMM recursion, while the backward smoothing is performed using a novel interacting smoothing recursion. This backward recursion mimics the IMM estimator in the backward direction, where each mode conditioned smoother uses standard Kalman smoothing recursion. Resulting algorithm provides improved but delayed estimates of target states. Simulation studies are performed to demonstrate the improved performance with a maneuvering target scenario. The comparison with existing methods confirms the improved smoothing accuracy. This improvement results from avoiding the augmented state vector used by other algorithms. In addition, the new technique to account for model switching in smoothing is a key in improving the performance.

Probability analysis of multiple-tank-car release incidents in railway hazardous materials transportation.

PubMed

Liu, Xiang; Saat, Mohd Rapik; Barkan, Christopher P L

2014-07-15

Railroads play a key role in the transportation of hazardous materials in North America. Rail transport differs from highway transport in several aspects, an important one being that rail transport involves trains in which many railcars carrying hazardous materials travel together. By contrast to truck accidents, it is possible that a train accident may involve multiple hazardous materials cars derailing and releasing contents with consequently greater potential impact on human health, property and the environment. In this paper, a probabilistic model is developed to estimate the probability distribution of the number of tank cars releasing contents in a train derailment. Principal operational characteristics considered include train length, derailment speed, accident cause, position of the first car derailed, number and placement of tank cars in a train and tank car safety design. The effect of train speed, tank car safety design and tank car positions in a train were evaluated regarding the number of cars that release their contents in a derailment. This research provides insights regarding the circumstances affecting multiple-tank-car release incidents and potential strategies to reduce their occurrences. The model can be incorporated into a larger risk management framework to enable better local, regional and national safety management of hazardous materials transportation by rail. Copyright © 2014 Elsevier B.V. All rights reserved.

Therapeutic Efficacy of Suppressing the JAK/STAT Pathway in Multiple Models of EAE1

PubMed Central

Liu, Yudong; Holdbrooks, Andrew T.; De Sarno, Patrizia; Rowse, Amber L.; Yanagisawa, Lora L.; McFarland, Braden C.; Harrington, Laurie E.; Raman, Chander; Sabbaj, Steffanie; Benveniste, Etty N.; Qin, Hongwei

2014-01-01

Pathogenic T helper cells and myeloid cells are involved in the pathogenesis of Multiple Sclerosis (MS) and Experimental Autoimmune Encephalomyelitis (EAE), an animal model of MS. The JAK/STAT pathway is utilized by numerous cytokines for signaling, and is critical for development, regulation and termination of immune responses. Dysregulation of the JAK/STAT pathway has pathological implications in autoimmune and neuroinflammatory diseases. Many of the cytokines involved in MS/EAE, including IL-6, IL-12, IL-23, IFN-γ and GM-CSF, use the JAK/STAT pathway to induce biological responses. Thus, targeting JAKs has implications for treating autoimmune inflammation of the brain. We have utilized AZD1480, a JAK1/2 inhibitor, to investigate the therapeutic potential of inhibiting the JAK/STAT pathway in models of EAE. AZD1480 treatment inhibits disease severity in MOG-induced classical and atypical EAE models by preventing entry of immune cells into the brain, suppressing differentiation of Th1 and Th17 cells, deactivating myeloid cells, inhibiting STAT activation in the brain, and reducing expression of pro-inflammatory cytokines and chemokines. Treatment of SJL/J mice with AZD1480 delays disease onset of PLP-induced relapsing-remitting disease, reduces relapses and diminishes clinical severity. AZD1480 treatment was also effective in reducing ongoing paralysis induced by adoptive transfer of either pathogenic Th1 or Th17 cells. In vivo AZD1480 treatment impairs both the priming and expansion of T-cells, and attenuates antigen-presentation functions of myeloid cells. Inhibition of the JAK/STAT pathway has clinical efficacy in multiple pre-clinical models of MS, suggesting the feasibility of the JAK/STAT pathway as a target for neuroinflammatory diseases. PMID:24323580

Multiple scales in metapopulations of public goods producers

NASA Astrophysics Data System (ADS)

Bauer, Marianne; Frey, Erwin

2018-04-01

Multiple scales in metapopulations can give rise to paradoxical behavior: in a conceptual model for a public goods game, the species associated with a fitness cost due to the public good production can be stabilized in the well-mixed limit due to the mere existence of these scales. The scales in this model involve a length scale corresponding to separate patches, coupled by mobility, and separate time scales for reproduction and interaction with a local environment. Contrary to the well-mixed high mobility limit, we find that for low mobilities, the interaction rate progressively stabilizes this species due to stochastic effects, and that the formation of spatial patterns is not crucial for this stabilization.

Estimating and Visualizing Nonlinear Relations among Latent Variables: A Semiparametric Approach

ERIC Educational Resources Information Center

Pek, Jolynn; Sterba, Sonya K.; Kok, Bethany E.; Bauer, Daniel J.

2009-01-01

The graphical presentation of any scientific finding enhances its description, interpretation, and evaluation. Research involving latent variables is no exception, especially when potential nonlinear effects are suspect. This article has multiple aims. First, it provides a nontechnical overview of a semiparametric approach to modeling nonlinear…

Articulating the Resources for Business Process Analysis and Design

ERIC Educational Resources Information Center

Jin, Yulong

2012-01-01

Effective process analysis and modeling are important phases of the business process management lifecycle. When many activities and multiple resources are involved, it is very difficult to build a correct business process specification. This dissertation provides a resource perspective of business processes. It aims at a better process analysis…

ASSESSMENT OF LAKE ECOSYSTEM RESPONSE TO TOXIC EVENTS WITH THE AQUATOX MODEL

EPA Science Inventory

An attack involving a toxic chemical added to a water resource could have multiple effects on the aquatic ecosystem of that resource. This is particularly significant for systems such as lakes and reservoirs, where the residence time of water is long and there is more opportunit...

Averaging and Adding in Children's Worth Judgements

ERIC Educational Resources Information Center

Schlottmann, Anne; Harman, Rachel M.; Paine, Julie

2012-01-01

Under the normative Expected Value (EV) model, multiple outcomes are additive, but in everyday worth judgement intuitive averaging prevails. Young children also use averaging in EV judgements, leading to a disordinal, crossover violation of utility when children average the part worths of simple gambles involving independent events (Schlottmann,…

US EPA'S LANDSCAPE ECOLOGY RESEARCH: ASSESSING TRENDS FOR WETLANDS AND SURFACE WATERS USING REMORE SENSING, GIS, AND FIELD-BASED TECHNIQUES

EPA Science Inventory

The US EPA, Environmental Sciences Division-Las Vegas is using a variety of geopspatical and statistical modeling approaches to locate and assess the complex functions of wetland ecosystems. These assessments involve measuring landscape characteristrics and change, at multiple s...

Development of a QSAR Model for Thyroperoxidase Inhbition and Screening of 72,524 REACH substances - (Eurotox 2016)

EPA Science Inventory

hyroid hormones (THs) are involved in multiple biological processes and are critical modulators of fetal development. Even moderate changes in maternal or fetal TH levels can produce irreversible neurological deficits in children, such as lower IQ. The enzyme thyroperoxidase (TPO...

Person-Oriented Approaches to Profiling Learners in Technology-Rich Learning Environments for Ecological Learner Modeling

ERIC Educational Resources Information Center

Jang, Eunice Eunhee; Lajoie, Susanne P.; Wagner, Maryam; Xu, Zhenhua; Poitras, Eric; Naismith, Laura

2017-01-01

Technology-rich learning environments (TREs) provide opportunities for learners to engage in complex interactions involving a multitude of cognitive, metacognitive, and affective states. Understanding learners' distinct learning progressions in TREs demand inquiry approaches that employ well-conceived theoretical accounts of these multiple facets.…

Religious Influences on the Risk of Marital Dissolution

ERIC Educational Resources Information Center

Vaaler, Margaret L.; Ellison, Christopher G.; Powers, Daniel A.

2009-01-01

This study examined multiple dimensions of religious involvement and the risk of divorce among a nationwide sample of 2,979 first-time married couples. Multivariate proportional hazards modeling was used to analyze two waves of the National Survey of Families and Households. Results indicated that although each partner's religious attendance bore…

Immunoglobulin A multiple myeloma with cutaneous involvement in a dog.

PubMed

Mayer, Monique N; Kerr, Moira E; Grier, Candace K; Macdonald, Valerie S

2008-07-01

An 8-year-old rottweiler, diagnosed with multiple myeloma and multiple sites of cutaneous involvement, was treated with chemotherapy and radiation therapy. The diagnostic criteria for canine multiple myeloma, limitations of diagnostic testing for light chain proteinuria in dogs, and the role of radiation therapy in multiple myeloma patients is discussed.

Immunoglobulin A multiple myeloma with cutaneous involvement in a dog

PubMed Central

Mayer, Monique N.; Kerr, Moira E.; Grier, Candace K.; MacDonald, Valerie S.

2008-01-01

An 8-year-old rottweiler, diagnosed with multiple myeloma and multiple sites of cutaneous involvement, was treated with chemotherapy and radiation therapy. The diagnostic criteria for canine multiple myeloma, limitations of diagnostic testing for light chain proteinuria in dogs, and the role of radiation therapy in multiple myeloma patients is discussed. PMID:18827847

A Comparison of Approximation Modeling Techniques: Polynomial Versus Interpolating Models

NASA Technical Reports Server (NTRS)

Giunta, Anthony A.; Watson, Layne T.

1998-01-01

Two methods of creating approximation models are compared through the calculation of the modeling accuracy on test problems involving one, five, and ten independent variables. Here, the test problems are representative of the modeling challenges typically encountered in realistic engineering optimization problems. The first approximation model is a quadratic polynomial created using the method of least squares. This type of polynomial model has seen considerable use in recent engineering optimization studies due to its computational simplicity and ease of use. However, quadratic polynomial models may be of limited accuracy when the response data to be modeled have multiple local extrema. The second approximation model employs an interpolation scheme known as kriging developed in the fields of spatial statistics and geostatistics. This class of interpolating model has the flexibility to model response data with multiple local extrema. However, this flexibility is obtained at an increase in computational expense and a decrease in ease of use. The intent of this study is to provide an initial exploration of the accuracy and modeling capabilities of these two approximation methods.

Least-squares deconvolution of evoked potentials and sequence optimization for multiple stimuli under low-jitter conditions.

PubMed

Bardy, Fabrice; Dillon, Harvey; Van Dun, Bram

2014-04-01

Rapid presentation of stimuli in an evoked response paradigm can lead to overlap of multiple responses and consequently difficulties interpreting waveform morphology. This paper presents a deconvolution method allowing overlapping multiple responses to be disentangled. The deconvolution technique uses a least-squared error approach. A methodology is proposed to optimize the stimulus sequence associated with the deconvolution technique under low-jitter conditions. It controls the condition number of the matrices involved in recovering the responses. Simulations were performed using the proposed deconvolution technique. Multiple overlapping responses can be recovered perfectly in noiseless conditions. In the presence of noise, the amount of error introduced by the technique can be controlled a priori by the condition number of the matrix associated with the used stimulus sequence. The simulation results indicate the need for a minimum amount of jitter, as well as a sufficient number of overlap combinations to obtain optimum results. An aperiodic model is recommended to improve reconstruction. We propose a deconvolution technique allowing multiple overlapping responses to be extracted and a method of choosing the stimulus sequence optimal for response recovery. This technique may allow audiologists, psychologists, and electrophysiologists to optimize their experimental designs involving rapidly presented stimuli, and to recover evoked overlapping responses. Copyright © 2013 International Federation of Clinical Neurophysiology. All rights reserved.

Simultaneous Helmert transformations among multiple frames considering all relevant measurements

NASA Astrophysics Data System (ADS)

Chang, Guobin; Lin, Peng; Bian, Hefang; Gao, Jingxiang

2018-03-01

Helmert or similarity models are widely employed to relate different coordinate frames. It is often encountered in practice to transform coordinates from more than one old frame into a new one. One may perform separate Helmert transformations for each old frame. However, although each transformation is locally optimal, this is not globally optimal. Transformations among three frames, namely one new and two old, are studied as an example. Simultaneous Helmert transformations among all frames are also studied. Least-squares estimation of the transformation parameters and the coordinates in the new frame of all stations involved is performed. A functional model for the transformations among multiple frames is developed. A realistic stochastic model is followed, in which not only non-common stations are taken into consideration, but also errors in all measurements are addressed. An algorithm of iterative linearizations and estimations is derived in detail. The proposed method is globally optimal, and, perhaps more importantly, it produces a unified network of the new frame providing coordinate estimates for all involved stations and the associated covariance matrix, with the latter being consistent with the true errors of the former. Simulations are conducted, and the results validate the superiority of the proposed combined method over separate approaches.

Research on efficiency evaluation model of integrated energy system based on hybrid multi-attribute decision-making.

PubMed

Li, Yan

2017-05-25

The efficiency evaluation model of integrated energy system, involving many influencing factors, and the attribute values are heterogeneous and non-deterministic, usually cannot give specific numerical or accurate probability distribution characteristics, making the final evaluation result deviation. According to the characteristics of the integrated energy system, a hybrid multi-attribute decision-making model is constructed. The evaluation model considers the decision maker's risk preference. In the evaluation of the efficiency of the integrated energy system, the evaluation value of some evaluation indexes is linguistic value, or the evaluation value of the evaluation experts is not consistent. These reasons lead to ambiguity in the decision information, usually in the form of uncertain linguistic values and numerical interval values. In this paper, the risk preference of decision maker is considered when constructing the evaluation model. Interval-valued multiple-attribute decision-making method and fuzzy linguistic multiple-attribute decision-making model are proposed. Finally, the mathematical model of efficiency evaluation of integrated energy system is constructed.

Two methods for parameter estimation using multiple-trait models and beef cattle field data.

PubMed

Bertrand, J K; Kriese, L A

1990-08-01

Two methods are presented for estimating variances and covariances from beef cattle field data using multiple-trait sire models. Both methods require that the first trait have no missing records and that the contemporary groups for the second trait be subsets of the contemporary groups for the first trait; however, the second trait may have missing records. One method uses pseudo expectations involving quadratics composed of the solutions and the right-hand sides of the mixed model equations. The other method is an extension of Henderson's Simple Method to the multiple trait case. Neither of these methods requires any inversions of large matrices in the computation of the parameters; therefore, both methods can handle very large sets of data. Four simulated data sets were generated to evaluate the methods. In general, both methods estimated genetic correlations and heritabilities that were close to the Restricted Maximum Likelihood estimates and the true data set values, even when selection within contemporary groups was practiced. The estimates of residual correlations by both methods, however, were biased by selection. These two methods can be useful in estimating variances and covariances from multiple-trait models in large populations that have undergone a minimal amount of selection within contemporary groups.

Multiple role adaptation among women who have children and re-enter nursing school in Taiwan.

PubMed

Lin, Li-Ling

2005-03-01

This study assessed multiple role adaptation within maternal and student roles among female RNs who had children and returned to school for baccalaureate degrees in Taiwan. Using Roy's Adaptation Model as the theoretical framework, relationships were explored among demographic (number of children, age of youngest child, employment status), physical (sleep quality, health perception, activity), and psychosocial factors (self-identity, role expectation, role involvement, social support) and multiple role adaptation (role accumulation). The sample included 118 mother-students who had at least one child younger than age 18 and who were studying in nursing programs in Taiwan. The highest correlation was found between activity and role accumulation followed by significant correlations between sleep quality, health perception, maternal role expectation, and age of youngest child and role accumulation. In regression analyses, the complete model explained 46% of the variance in role accumulation. Implications for education and future research are identified.

Isolation with Migration Models for More Than Two Populations

PubMed Central

Hey, Jody

2010-01-01

A method for studying the divergence of multiple closely related populations is described and assessed. The approach of Hey and Nielsen (2007, Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics. Proc Natl Acad Sci USA. 104:2785–2790) for fitting an isolation-with-migration model was extended to the case of multiple populations with a known phylogeny. Analysis of simulated data sets reveals the kinds of history that are accessible with a multipopulation analysis. Necessarily, processes associated with older time periods in a phylogeny are more difficult to estimate; and histories with high levels of gene flow are particularly difficult with more than two populations. However, for histories with modest levels of gene flow, or for very large data sets, it is possible to study large complex divergence problems that involve multiple closely related populations or species. PMID:19955477

Isolation with migration models for more than two populations.

PubMed

Hey, Jody

2010-04-01

A method for studying the divergence of multiple closely related populations is described and assessed. The approach of Hey and Nielsen (2007, Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics. Proc Natl Acad Sci USA. 104:2785-2790) for fitting an isolation-with-migration model was extended to the case of multiple populations with a known phylogeny. Analysis of simulated data sets reveals the kinds of history that are accessible with a multipopulation analysis. Necessarily, processes associated with older time periods in a phylogeny are more difficult to estimate; and histories with high levels of gene flow are particularly difficult with more than two populations. However, for histories with modest levels of gene flow, or for very large data sets, it is possible to study large complex divergence problems that involve multiple closely related populations or species.

Fluid-Structure Interaction Modeling of Parachutes with Disreefing and Modified Geometric Porosity and Separation Aerodynamics of a Cover Jettisoned to the Spacecraft Wake

NASA Astrophysics Data System (ADS)

Fritze, Matthew D.

Fluid-structure interaction (FSI) modeling of spacecraft parachutes involves a number of computational challenges. The canopy complexity created by the hundreds of gaps and slits and design-related modification of that geometric porosity by removal of some of the sails and panels are among the formidable challenges. Disreefing from one stage to another when the parachute is used in multiple stages is another formidable challenge. This thesis addresses the computational challenges involved in disreefing of spacecraft parachutes and fully-open and reefed stages of the parachutes with modified geometric porosity. The special techniques developed to address these challenges are described and the FSI computations are be reported. The thesis also addresses the modeling and computation challenges involved in very early stages, where the sudden separation of a cover jettisoned to the spacecraft wake needs to be modeled. Higher-order temporal representations used in modeling the separation motion are described, and the computed separation and wake-induced forces acting on the cover are reported.

Identification and Correction of Additive and Multiplicative Spatial Biases in Experimental High-Throughput Screening.

PubMed

Mazoure, Bogdan; Caraus, Iurie; Nadon, Robert; Makarenkov, Vladimir

2018-06-01

Data generated by high-throughput screening (HTS) technologies are prone to spatial bias. Traditionally, bias correction methods used in HTS assume either a simple additive or, more recently, a simple multiplicative spatial bias model. These models do not, however, always provide an accurate correction of measurements in wells located at the intersection of rows and columns affected by spatial bias. The measurements in these wells depend on the nature of interaction between the involved biases. Here, we propose two novel additive and two novel multiplicative spatial bias models accounting for different types of bias interactions. We describe a statistical procedure that allows for detecting and removing different types of additive and multiplicative spatial biases from multiwell plates. We show how this procedure can be applied by analyzing data generated by the four HTS technologies (homogeneous, microorganism, cell-based, and gene expression HTS), the three high-content screening (HCS) technologies (area, intensity, and cell-count HCS), and the only small-molecule microarray technology available in the ChemBank small-molecule screening database. The proposed methods are included in the AssayCorrector program, implemented in R, and available on CRAN.

A View on Future Building System Modeling and Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wetter, Michael

This chapter presents what a future environment for building system modeling and simulation may look like. As buildings continue to require increased performance and better comfort, their energy and control systems are becoming more integrated and complex. We therefore focus in this chapter on the modeling, simulation and analysis of building energy and control systems. Such systems can be classified as heterogeneous systems because they involve multiple domains, such as thermodynamics, fluid dynamics, heat and mass transfer, electrical systems, control systems and communication systems. Also, they typically involve multiple temporal and spatial scales, and their evolution can be described bymore » coupled differential equations, discrete equations and events. Modeling and simulating such systems requires a higher level of abstraction and modularisation to manage the increased complexity compared to what is used in today's building simulation programs. Therefore, the trend towards more integrated building systems is likely to be a driving force for changing the status quo of today's building simulation programs. Thischapter discusses evolving modeling requirements and outlines a path toward a future environment for modeling and simulation of heterogeneous building systems.A range of topics that would require many additional pages of discussion has been omitted. Examples include computational fluid dynamics for air and particle flow in and around buildings, people movement, daylight simulation, uncertainty propagation and optimisation methods for building design and controls. For different discussions and perspectives on the future of building modeling and simulation, we refer to Sahlin (2000), Augenbroe (2001) and Malkawi and Augenbroe (2004).« less

Visual Foraging With Fingers and Eye Gaze

PubMed Central

Thornton, Ian M.; Smith, Irene J.; Chetverikov, Andrey; Kristjánsson, Árni

2016-01-01

A popular model of the function of selective visual attention involves search where a single target is to be found among distractors. For many scenarios, a more realistic model involves search for multiple targets of various types, since natural tasks typically do not involve a single target. Here we present results from a novel multiple-target foraging paradigm. We compare finger foraging where observers cancel a set of predesignated targets by tapping them, to gaze foraging where observers cancel items by fixating them for 100 ms. During finger foraging, for most observers, there was a large difference between foraging based on a single feature, where observers switch easily between target types, and foraging based on a conjunction of features where observers tended to stick to one target type. The pattern was notably different during gaze foraging where these condition differences were smaller. Two conclusions follow: (a) The fact that a sizeable number of observers (in particular during gaze foraging) had little trouble switching between different target types raises challenges for many prominent theoretical accounts of visual attention and working memory. (b) While caveats must be noted for the comparison of gaze and finger foraging, the results suggest that selection mechanisms for gaze and pointing have different operational constraints. PMID:27433323

A Research Framework for Understanding the Practical Impact of Family Involvement in the Juvenile Justice System: The Juvenile Justice Family Involvement Model.

PubMed

Walker, Sarah Cusworth; Bishop, Asia S; Pullmann, Michael D; Bauer, Grace

2015-12-01

Family involvement is recognized as a critical element of service planning for children's mental health, welfare and education. For the juvenile justice system, however, parents' roles in this system are complex due to youths' legal rights, public safety, a process which can legally position parents as plaintiffs, and a historical legacy of blaming parents for youth indiscretions. Three recent national surveys of juvenile justice-involved parents reveal that the current paradigm elicits feelings of stress, shame and distrust among parents and is likely leading to worse outcomes for youth, families and communities. While research on the impact of family involvement in the justice system is starting to emerge, the field currently has no organizing framework to guide a research agenda, interpret outcomes or translate findings for practitioners. We propose a research framework for family involvement that is informed by a comprehensive review and content analysis of current, published arguments for family involvement in juvenile justice along with a synthesis of family involvement efforts in other child-serving systems. In this model, family involvement is presented as an ascending, ordinal concept beginning with (1) exclusion, and moving toward climates characterized by (2) information-giving, (3) information-eliciting and (4) full, decision-making partnerships. Specific examples of how courts and facilities might align with these levels are described. Further, the model makes predictions for how involvement will impact outcomes at multiple levels with applications for other child-serving systems.

Multiple Regression Analysis of mRNA-miRNA Associations in Colorectal Cancer Pathway

PubMed Central

Wang, Fengfeng; Wong, S. C. Cesar; Chan, Lawrence W. C.; Cho, William C. S.; Yip, S. P.; Yung, Benjamin Y. M.

2014-01-01

Background. MicroRNA (miRNA) is a short and endogenous RNA molecule that regulates posttranscriptional gene expression. It is an important factor for tumorigenesis of colorectal cancer (CRC), and a potential biomarker for diagnosis, prognosis, and therapy of CRC. Our objective is to identify the related miRNAs and their associations with genes frequently involved in CRC microsatellite instability (MSI) and chromosomal instability (CIN) signaling pathways. Results. A regression model was adopted to identify the significantly associated miRNAs targeting a set of candidate genes frequently involved in colorectal cancer MSI and CIN pathways. Multiple linear regression analysis was used to construct the model and find the significant mRNA-miRNA associations. We identified three significantly associated mRNA-miRNA pairs: BCL2 was positively associated with miR-16 and SMAD4 was positively associated with miR-567 in the CRC tissue, while MSH6 was positively associated with miR-142-5p in the normal tissue. As for the whole model, BCL2 and SMAD4 models were not significant, and MSH6 model was significant. The significant associations were different in the normal and the CRC tissues. Conclusion. Our results have laid down a solid foundation in exploration of novel CRC mechanisms, and identification of miRNA roles as oncomirs or tumor suppressor mirs in CRC. PMID:24895601

Empowering Prospective Teachers to Become Active Sense-Makers: Multimodal Modeling of the Seasons

NASA Astrophysics Data System (ADS)

Kim, Mi Song

2015-10-01

Situating science concepts in concrete and authentic contexts, using information and communications technologies, including multimodal modeling tools, is important for promoting the development of higher-order thinking skills in learners. However, teachers often struggle to integrate emergent multimodal models into a technology-rich informal learning environment. Our design-based research co-designs and develops engaging, immersive, and interactive informal learning activities called "Embodied Modeling-Mediated Activities" (EMMA) to support not only Singaporean learners' deep learning of astronomy but also the capacity of teachers. As part of the research on EMMA, this case study describes two prospective teachers' co-design processes involving multimodal models for teaching and learning the concept of the seasons in a technology-rich informal learning setting. Our study uncovers four prominent themes emerging from our data concerning the contextualized nature of learning and teaching involving multimodal models in informal learning contexts: (1) promoting communication and emerging questions, (2) offering affordances through limitations, (3) explaining one concept involving multiple concepts, and (4) integrating teaching and learning experiences. This study has an implication for the development of a pedagogical framework for teaching and learning in technology-enhanced learning environments—that is empowering teachers to become active sense-makers using multimodal models.

Water Isotopes in the GISS GCM: History, Applications and Potential

NASA Astrophysics Data System (ADS)

Schmidt, G. A.; LeGrande, A. N.; Field, R. D.; Nusbaumer, J. M.

2017-12-01

Water isotopes have been incorporated in the GISS GCMs since the pioneering work of Jean Jouzel in the 1980s. Since 2005, this functionality has been maintained within the master branch of the development code and has been usable (and used) in all subsequent versions. This has allowed a wide variety of applications, across multiple time-scales and interests, to be tackled coherently. Water isotope tracers have been used to debug the atmospheric model code, tune parameterisations of moist processes, assess the isotopic fingerprints of multiple climate drivers, produce forward models for remotely sensed isotope products, and validate paleo-climate interpretations from the last millennium to the Eocene. We will present an overview of recent results involving isotope tracers, including improvements in models for the isotopic fractionation processes themselves, and demonstrate the potential for using these tracers and models more systematically in paleo-climate reconstructions and investigations of the modern hydrological cycle.

Galantamine improves olfactory learning in the Ts65Dn mouse model of Down syndrome

PubMed Central

Simoes de Souza, Fabio M.; Busquet, Nicolas; Blatner, Megan; Maclean, Kenneth N.; Restrepo, Diego

2011-01-01

Down syndrome (DS) is the most common form of congenital intellectual disability. Although DS involves multiple disturbances in various tissues, there is little doubt that in terms of quality of life cognitive impairment is the most serious facet and there is no effective treatment for this aspect of the syndrome. The Ts65Dn mouse model of DS recapitulates multiple aspects of DS including cognitive impairment. Here the Ts65Dn mouse model of DS was evaluated in an associative learning paradigm based on olfactory cues. In contrast to disomic controls, trisomic mice exhibited significant deficits in olfactory learning. Treatment of trisomic mice with the acetylcholinesterase inhibitor galantamine resulted in a significant improvement in olfactory learning. Collectively, our study indicates that olfactory learning can be a sensitive tool for evaluating deficits in associative learning in mouse models of DS and that galantamine has therapeutic potential for improving cognitive abilities. PMID:22355654

Galantamine improves olfactory learning in the Ts65Dn mouse model of Down syndrome.

PubMed

de Souza, Fabio M Simoes; Busquet, Nicolas; Blatner, Megan; Maclean, Kenneth N; Restrepo, Diego

2011-01-01

Down syndrome (DS) is the most common form of congenital intellectual disability. Although DS involves multiple disturbances in various tissues, there is little doubt that in terms of quality of life cognitive impairment is the most serious facet and there is no effective treatment for this aspect of the syndrome. The Ts65Dn mouse model of DS recapitulates multiple aspects of DS including cognitive impairment. Here the Ts65Dn mouse model of DS was evaluated in an associative learning paradigm based on olfactory cues. In contrast to disomic controls, trisomic mice exhibited significant deficits in olfactory learning. Treatment of trisomic mice with the acetylcholinesterase inhibitor galantamine resulted in a significant improvement in olfactory learning. Collectively, our study indicates that olfactory learning can be a sensitive tool for evaluating deficits in associative learning in mouse models of DS and that galantamine has therapeutic potential for improving cognitive abilities.

Bayesian function-on-function regression for multilevel functional data.

PubMed

Meyer, Mark J; Coull, Brent A; Versace, Francesco; Cinciripini, Paul; Morris, Jeffrey S

2015-09-01

Medical and public health research increasingly involves the collection of complex and high dimensional data. In particular, functional data-where the unit of observation is a curve or set of curves that are finely sampled over a grid-is frequently obtained. Moreover, researchers often sample multiple curves per person resulting in repeated functional measures. A common question is how to analyze the relationship between two functional variables. We propose a general function-on-function regression model for repeatedly sampled functional data on a fine grid, presenting a simple model as well as a more extensive mixed model framework, and introducing various functional Bayesian inferential procedures that account for multiple testing. We examine these models via simulation and a data analysis with data from a study that used event-related potentials to examine how the brain processes various types of images. © 2015, The International Biometric Society.

A management and optimisation model for water supply planning in water deficit areas

NASA Astrophysics Data System (ADS)

Molinos-Senante, María; Hernández-Sancho, Francesc; Mocholí-Arce, Manuel; Sala-Garrido, Ramón

2014-07-01

The integrated water resources management approach has proven to be a suitable option for efficient, equitable and sustainable water management. In water-poor regions experiencing acute and/or chronic shortages, optimisation techniques are a useful tool for supporting the decision process of water allocation. In order to maximise the value of water use, an optimisation model was developed which involves multiple supply sources (conventional and non-conventional) and multiple users. Penalties, representing monetary losses in the event of an unfulfilled water demand, have been incorporated into the objective function. This model represents a novel approach which considers water distribution efficiency and the physical connections between water supply and demand points. Subsequent empirical testing using data from a Spanish Mediterranean river basin demonstrated the usefulness of the global optimisation model to solve existing water imbalances at the river basin level.

Maternal depression in association with fathers' involvement with their infants: spillover or compensation/buffering?

PubMed

Goodman, Sherryl H; Lusby, Cara M; Thompson, Katina; Newport, D Jeffrey; Stowe, Zachary N

2014-01-01

Both concurrent and prospective associations between maternal depression and father involvement were tested to evaluate support for the spillover model (higher depressive symptom levels associated with lower father involvement) and the compensatory/buffering model (higher depressive symptom levels associated with higher father involvement). Participants in this longitudinal study were women at risk for perinatal depression in association with their histories of mood or anxiety disorders, their husbands/partners, and their infants at 3, 6, and 12 months of age. Maternal depressive symptoms were measured with depression rating scales at multiple times over the infants' first year. Paternal involvement was measured with a questionnaire (relative perceived responsibility) and a time diary (accessibility and engagement) inquiring about a recent weekday and a recent weekend, completed in a telephone interview, at infant ages 3, 6, and 12 months. Findings consistently supported the compensatory/buffering model for depression in the first 6 months' postpartum, along with an indication of spillover regarding maternal depressive symptoms that persist into the second half of the infants' first year. Findings are discussed in terms of implications for clinical practice and policy as well as suggestions for future research. © 2014 Michigan Association for Infant Mental Health.

Understanding the psychology of bullying: Moving toward a social-ecological diathesis-stress model.

PubMed

Swearer, Susan M; Hymel, Shelley

2015-01-01

With growing recognition that bullying is a complex phenomenon, influenced by multiple factors, research findings to date have been understood within a social-ecological framework. Consistent with this model, we review research on the known correlates and contributing factors in bullying/victimization within the individual, family, peer group, school and community. Recognizing the fluid and dynamic nature of involvement in bullying, we then expand on this model and consider research on the consequences of bullying involvement, as either victim or bully or both, and propose a social-ecological, diathesis-stress model for understanding the bullying dynamic and its impact. Specifically, we frame involvement in bullying as a stressful life event for both children who bully and those who are victimized, serving as a catalyst for a diathesis-stress connection between bullying, victimization, and psychosocial difficulties. Against this backdrop, we suggest that effective bullying prevention and intervention efforts must take into account the complexities of the human experience, addressing both individual characteristics and history of involvement in bullying, risk and protective factors, and the contexts in which bullying occurs, in order to promote healthier social relationships. (c) 2015 APA, all rights reserved).

A Software Toolkit to Study Systematic Uncertainties of the Physics Models of the Geant4 Simulation Package

DOE Office of Scientific and Technical Information (OSTI.GOV)

Genser, Krzysztof; Hatcher, Robert; Perdue, Gabriel

2016-11-10

The Geant4 toolkit is used to model interactions between particles and matter. Geant4 employs a set of validated physics models that span a wide range of interaction energies. These models are tuned to cover a large variety of possible applications. This raises the critical question of what uncertainties are associated with the Geant4 physics model, or group of models, involved in a simulation project. To address the challenge, we have designed and implemented a comprehen- sive, modular, user-friendly software toolkit that allows the variation of one or more parameters of one or more Geant4 physics models involved in simulation studies.more » It also enables analysis of multiple variants of the resulting physics observables of interest in order to estimate the uncertain- ties associated with the simulation model choices. Key functionalities of the toolkit are presented in this paper and are illustrated with selected results.« less

Escaping the snare of chronological growth and launching a free curve alternative: general deviance as latent growth model.

PubMed

Wood, Phillip Karl; Jackson, Kristina M

2013-08-01

Researchers studying longitudinal relationships among multiple problem behaviors sometimes characterize autoregressive relationships across constructs as indicating "protective" or "launch" factors or as "developmental snares." These terms are used to indicate that initial or intermediary states of one problem behavior subsequently inhibit or promote some other problem behavior. Such models are contrasted with models of "general deviance" over time in which all problem behaviors are viewed as indicators of a common linear trajectory. When fit of the "general deviance" model is poor and fit of one or more autoregressive models is good, this is taken as support for the inhibitory or enhancing effect of one construct on another. In this paper, we argue that researchers consider competing models of growth before comparing deviance and time-bound models. Specifically, we propose use of the free curve slope intercept (FCSI) growth model (Meredith & Tisak, 1990) as a general model to typify change in a construct over time. The FCSI model includes, as nested special cases, several statistical models often used for prospective data, such as linear slope intercept models, repeated measures multivariate analysis of variance, various one-factor models, and hierarchical linear models. When considering models involving multiple constructs, we argue the construct of "general deviance" can be expressed as a single-trait multimethod model, permitting a characterization of the deviance construct over time without requiring restrictive assumptions about the form of growth over time. As an example, prospective assessments of problem behaviors from the Dunedin Multidisciplinary Health and Development Study (Silva & Stanton, 1996) are considered and contrasted with earlier analyses of Hussong, Curran, Moffitt, and Caspi (2008), which supported launch and snare hypotheses. For antisocial behavior, the FCSI model fit better than other models, including the linear chronometric growth curve model used by Hussong et al. For models including multiple constructs, a general deviance model involving a single trait and multimethod factors (or a corresponding hierarchical factor model) fit the data better than either the "snares" alternatives or the general deviance model previously considered by Hussong et al. Taken together, the analyses support the view that linkages and turning points cannot be contrasted with general deviance models absent additional experimental intervention or control.

Escaping the snare of chronological growth and launching a free curve alternative: General deviance as latent growth model

PubMed Central

WOOD, PHILLIP KARL; JACKSON, KRISTINA M.

2014-01-01

Researchers studying longitudinal relationships among multiple problem behaviors sometimes characterize autoregressive relationships across constructs as indicating “protective” or “launch” factors or as “developmental snares.” These terms are used to indicate that initial or intermediary states of one problem behavior subsequently inhibit or promote some other problem behavior. Such models are contrasted with models of “general deviance” over time in which all problem behaviors are viewed as indicators of a common linear trajectory. When fit of the “general deviance” model is poor and fit of one or more autoregressive models is good, this is taken as support for the inhibitory or enhancing effect of one construct on another. In this paper, we argue that researchers consider competing models of growth before comparing deviance and time-bound models. Specifically, we propose use of the free curve slope intercept (FCSI) growth model (Meredith & Tisak, 1990) as a general model to typify change in a construct over time. The FCSI model includes, as nested special cases, several statistical models often used for prospective data, such as linear slope intercept models, repeated measures multivariate analysis of variance, various one-factor models, and hierarchical linear models. When considering models involving multiple constructs, we argue the construct of “general deviance” can be expressed as a single-trait multimethod model, permitting a characterization of the deviance construct over time without requiring restrictive assumptions about the form of growth over time. As an example, prospective assessments of problem behaviors from the Dunedin Multidisciplinary Health and Development Study (Silva & Stanton, 1996) are considered and contrasted with earlier analyses of Hussong, Curran, Moffitt, and Caspi (2008), which supported launch and snare hypotheses. For antisocial behavior, the FCSI model fit better than other models, including the linear chronometric growth curve model used by Hussong et al. For models including multiple constructs, a general deviance model involving a single trait and multimethod factors (or a corresponding hierarchical factor model) fit the data better than either the “snares” alternatives or the general deviance model previously considered by Hussong et al. Taken together, the analyses support the view that linkages and turning points cannot be contrasted with general deviance models absent additional experimental intervention or control. PMID:23880389

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

PubMed

Dolan, James G

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare

PubMed Central

Dolan, James G.

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers. Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine “hard data” with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings. The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP) PMID:21394218

Progressive Elaboration and Cross-Validation of a Latent Class Typology of Adolescent Alcohol Involvement in a National Sample

PubMed Central

Donovan, John E.; Chung, Tammy

2015-01-01

Objective: Most studies of adolescent drinking focus on single alcohol use behaviors (e.g., high-volume drinking, drunkenness) and ignore the patterning of adolescents’ involvement across multiple alcohol behaviors. The present latent class analyses (LCAs) examined a procedure for empirically determining multiple cut points on the alcohol use behaviors in order to establish a typology of adolescent alcohol involvement. Method: LCA was carried out on six alcohol use behavior indicators collected from 6,504 7th through 12th graders who participated in Wave I of the National Longitudinal Study of Adolescent Health (AddHealth). To move beyond dichotomous indicators, a “progressive elaboration” strategy was used, starting with six dichotomous indicators and then evaluating a series of models testing additional cut points on the ordinal indicators at progressively higher points for one indicator at a time. Analyses were performed on one random half-sample, and confirmatory LCAs were performed on the second random half-sample and in the Wave II data. Results: The final model consisted of four latent classes (never or non–current drinkers, low-intake drinkers, non–problem drinkers, and problem drinkers). Confirmatory LCAs in the second random half-sample from Wave I and in Wave II support this four-class solution. The means on the four latent classes were also generally ordered on an array of measures reflecting psychosocial risk for problem behavior. Conclusions: These analyses suggest that there may be four different classes or types of alcohol involvement among adolescents, and, more importantly, they illustrate the utility of the progressive elaboration strategy for moving beyond dichotomous indicators in latent class models. PMID:25978828

A devolved model for public involvement in the field of mental health research: case study learning.

PubMed

Moule, Pam; Davies, Rosie

2016-12-01

Patient and public involvement in all aspects of research is espoused and there is a continued interest in understanding its wider impact. Existing investigations have identified both beneficial outcomes and remaining issues. This paper presents the impact of public involvement in one case study led by a mental health charity conducted as part of a larger research project. The case study used a devolved model of working, contracting with service user-led organizations to maximize the benefits of local knowledge on the implementation of personalized budgets, support recruitment and local user-led organizations. To understand the processes and impact of public involvement in a devolved model of working with user-led organizations. Multiple data collection methods were employed throughout 2012. These included interviews with the researchers (n = 10) and research partners (n = 5), observation of two case study meetings and the review of key case study documentation. Analysis was conducted in NVivo10 using a coding framework developed following a literature review. Five key themes emerged from the data; Devolved model, Nature of involvement, Enabling factors, Implementation challenges and Impact. While there were some challenges of implementing the devolved model it is clear that our findings add to the growing understanding of the positive benefits research partners can bring to complex research. A devolved model can support the involvement of user-led organizations in research if there is a clear understanding of the underpinning philosophy and support mechanisms are in place. © 2015 The Authors. Health Expectations Published by John Wiley & Sons Ltd.

Positive or negative involvement of heat shock proteins in multiple sclerosis pathogenesis: an overview.

PubMed

Turturici, Giuseppina; Tinnirello, Rosaria; Sconzo, Gabriella; Asea, Alexzander; Savettieri, Giovanni; Ragonese, Paolo; Geraci, Fabiana

2014-12-01

Multiple sclerosis (MS) is the most diffuse chronic inflammatory disease of the central nervous system. Both immune-mediated and neurodegenerative processes apparently play roles in the pathogenesis of this disease. Heat shock proteins (HSPs) are a family of highly evolutionarily conserved proteins; their expression in the nervous system is induced in a variety of pathologic states, including cerebral ischemia, neurodegenerative diseases, epilepsy, and trauma. To date, investigators have observed protective effects of HSPs in a variety of brain disease models (e.g. of Alzheimer disease and Parkinson disease). In contrast, unequivocal data have been obtained for their roles in MS that depend on the HSP family and particularly on their localization (i.e. intracellular or extracellular). This article reviews our current understanding of the involvement of the principal HSP families in MS.

A Language Training Strategy for Teaching Young Language-Delayed Children a Functional Syntactical Form.

ERIC Educational Resources Information Center

Hester, Peggy; Hendrickson, Jo

A modeling procedure involving dynamic interactions was used to train three language-delayed preschool children to emit five-element syntactic responses. A single-subject multiple baseline design using within- and across-subject replication was employed to study the acquisition of expanded "agent-action-object" sentences and the…

Further Understanding of Complex Information Processing in Verbal Adolescents and Adults with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Williams, Diane L.; Minshew, Nancy J.; Goldstein, Gerald

2015-01-01

More than 20?years ago, Minshew and colleagues proposed the Complex Information Processing model of autism in which the impairment is characterized as a generalized deficit involving multiple modalities and cognitive domains that depend on distributed cortical systems responsible for higher order abilities. Subsequent behavioral work revealed a…

Weighing conservation objectives: maximum expected coverage versus endangered species protection

Treesearch

Jeffrey L. Arthur; Jeffrey D. Camm; Robert G. Haight; Claire A. Montgomery; Stephen Polasky

2004-01-01

Decision makers involved in land acquisition and protection often have multiple conservation objectives and are uncertain about the occurrence of species or other features in candidate sites. Model informing decisions on selection of sites for reserves need to provide information about cost-efficient trade-offs between objectives and account for incidence uncertainty...

Bisubstrate Kinetics of Glutathione S-Transferase: A Colorimetric Experiment for the Introductory Biochemistry Laboratory

ERIC Educational Resources Information Center

Stefanidis, Lazaros; Scinto, Krystal V.; Strada, Monica I.; Alper, Benjamin J.

2018-01-01

Most biochemical transformations involve more than one substrate. Bisubstrate enzymes catalyze multiple chemical reactions in living systems and include members of the transferase, oxidoreductase, and ligase enzyme classes. Working knowledge of bisubstrate enzyme kinetic models is thus of clear importance to the practicing biochemist. However,…

Addressing Pediatric Health Concerns through School-Based Consultation

ERIC Educational Resources Information Center

Truscott, Stephen D.; Albritton, Kizzy

2011-01-01

In schools, the term "consultation" has multiple meanings. Often it is used to describe a quick, informal process of advice giving between teachers and/or school specialists. As a formal discipline, School-Based Consultation (SBC) is an indirect service delivery model that involves two or more parties working together to benefit students. Most…

Managing the University Campus: Exploring Models for the Future and Supporting Today's Decisions

ERIC Educational Resources Information Center

den Heijer, Alexandra

2012-01-01

Managing contemporary campuses and taking decisions that will impact on those of tomorrow is a complex task for universities worldwide. It involves strategic, financial, functional and physical aspects as well as multiple stakeholders. This article summarises the conclusions of a comprehensive PhD research project which was enriched with lessons…

Evaluating Quality of Students' Support Services in Open Distance Learning

ERIC Educational Resources Information Center

Nsamba, Asteria; Makoe, Mpine

2017-01-01

Evaluating the quality of students' support services in distance education institutions is vital because by nature Open Distance Learning (ODL) is a high-involvement service industry, with multiple student support service encounters. Most quality evaluation models tend to view quality from the institutional perspective. As a result, little is…

Identifying Aspects of Parental Involvement that Affect the Academic Achievement of High School Students

ERIC Educational Resources Information Center

Roulette-McIntyre, Ovella; Bagaka's, Joshua G.; Drake, Daniel D.

2005-01-01

This study identified parental practices that relate positively to high school students' academic performance. Parents of 643 high school students participated in the study. Data analysis, using a multiple linear regression model, shows parent-school connection, student gender, and race are significant predictors of student academic performance.…

The Effects of a Multiyear Universal Social-Emotional Learning Program: The Role of Student and School Characteristics

ERIC Educational Resources Information Center

Bierman, Karen L.; Coie, John D.; Dodge, Kenneth A.; Greenberg, Mark T.; Lochman, John E.; McMahon, Robert J.; Pinderhughes, Ellen

2010-01-01

Objective: This article examines the impact of a universal social-emotional learning program, the Fast Track PATHS (Promoting Alternative Thinking Strategies) curriculum and teacher consultation, embedded within the Fast Track selective prevention model. Method: The longitudinal analysis involved 2,937 children of multiple ethnicities who remained…

"Bringing It All Back Home": An Interdisciplinary Model for Community-Based Learning

ERIC Educational Resources Information Center

Schwartz, Earl

2015-01-01

Leaders of community-based learning programs must prove the worth of their programs to community hosts, while engaging students at appropriate levels of learning. Pitfalls multiply when programs are interdisciplinary, involve multiple sites, and/or deal with questions of social equity. Such programs must effectively match and prepare students and…

Developing AN Emergency Response Model for Offshore Oil Spill Disaster Management Using Spatial Decision Support System (sdss)

NASA Astrophysics Data System (ADS)

Balogun, Abdul-Lateef; Matori, Abdul-Nasir; Wong Toh Kiak, Kelvin

2018-04-01

Environmental resources face severe risks during offshore oil spill disasters and Geographic Information System (GIS) Environmental Sensitivity Index (ESI) maps are increasingly being used as response tools to minimize the huge impacts of these spills. However, ESI maps are generally unable to independently harmonize the diverse preferences of the multiple stakeholders' involved in the response process, causing rancour and delay in response time. This paper's Spatial Decision Support System (SDSS) utilizes the Analytic Hierarchy Process (AHP) model to perform tradeoffs in determining the most significant resources to be secured considering the limited resources and time available to perform the response operation. The AHP approach is used to aggregate the diverse preferences of the stakeholders and reach a consensus. These preferences, represented as priority weights, are incorporated in a GIS platform to generate Environmental sensitivity risk (ESR) maps. The ESR maps provide a common operational platform and consistent situational awareness for the multiple parties involved in the emergency response operation thereby minimizing discord among the response teams and saving the most valuable resources.

A numerical approach to controller design for the ACES facility

NASA Technical Reports Server (NTRS)

Frazier, W. Garth; Irwin, R. Dennis

1993-01-01

In recent years the employment of active control techniques for improving the performance of systems involving highly flexible structures has become a topic of considerable research interest. Most of these systems are quite complicated, using multiple actuators and sensors, and possessing high order models. The majority of analytical controller synthesis procedures capable of handling multivariable systems in a systematic way require considerable insight into the underlying mathematical theory to achieve a successful design. This insight is needed in selecting the proper weighting matrices or weighting functions to cast what is naturally a multiple constraint satisfaction problem into an unconstrained optimization problem. Although designers possessing considerable experience with these techniques have a feel for the proper choice of weights, others may spend a significant amount of time attempting to find an acceptable solution. Another disadvantage of such procedures is that the resulting controller has an order greater than or equal to that of the model used for the design. Of course, the order of these controllers can often be reduced, but again this requires a good understanding of the theory involved.

Patient involvement in research programming and implementation: A responsive evaluation of the Dialogue Model for research agenda setting.

PubMed

Abma, Tineke A; Pittens, Carina A C M; Visse, Merel; Elberse, Janneke E; Broerse, Jacqueline E W

2015-12-01

The Dialogue Model for research agenda-setting, involving multiple stakeholders including patients, was developed and validated in the Netherlands. However, there is little insight into whether and how patient involvement is sustained during the programming and implementation of research agendas. To understand how the Dialogue Model can be optimised by focusing on programming and implementation, in order to stimulate the inclusion of (the perspectives of) patients in research. A responsive evaluation of the programming and implementation phases of nine agenda-setting projects that had used the Dialogue Model for agenda-setting was conducted. Fifty-four semi-structured interviews were held with different stakeholders (patients, researchers, funding agencies). Three focus groups with patients, funding agencies and researchers (16 participants) were organized to validate the findings. Patient involvement in programming and implementation of the research agendas was limited. This was partly related to poor programming and implementation, partly to pitfalls in earlier phases of the agenda-setting. Optimization of the Dialogue Model is possible by attending to the nature of the agenda and its intended use in earlier phases. Attention should also be given to the ambassadors and intended users of agenda topics. Support is needed during programming and implementation to organize patient involvement and adapt organizational structures like review procedures. In all phases the attitude to patient involvement, stakeholder participation, especially of researchers, and formal and informal relationships between parties need to be addressed to build a strong relationship with a shared goal. Patient involvement in agenda-setting is not automatically followed by patient involvement in programming and implementation. More attention should be paid, in earlier stages, to the attitude and engagement of researchers and funding agencies. © 2014 John Wiley & Sons Ltd.

Multiple non-syndromic odontogenic keratocysts in three siblings

PubMed Central

Nirwan, Amit; Wanjari, Sangeeta Panjab; Saikhedkar, Rashmi; Karun, Vinayak

2013-01-01

Occurrence of multiple cysts (MC) involving the jaw is rare. When multiple, it is usually associated with a syndrome. Occurrence of MC without syndromic association is extremely rare. Multiple odontogenic cysts mostly could be odontogenic keratocysts or dentigerous cysts. Odontogenic keratocyst shows involvement of mandible over maxilla, with peak incidence in second and third decade and it is exceedingly rare before 10 years of age. However multiple odontogenic keratocysts found in children are often reflective of nevoid basal cell carcinoma syndrome. Here is a case report which documents multiple jaw cysts involving both the jaws, in three siblings of ages 10, 13 and 17 years with negative parental history. All three reported cases were free of any systemic involvement. As odontogenic keratocyst spreads through bone marrow, destruction is more before any clinical manifestation. Therefore, early detection and intervention are essential in preventing extensive destruction. PMID:23505078

Multi-objective optimization of GENIE Earth system models.

PubMed

Price, Andrew R; Myerscough, Richard J; Voutchkov, Ivan I; Marsh, Robert; Cox, Simon J

2009-07-13

The tuning of parameters in climate models is essential to provide reliable long-term forecasts of Earth system behaviour. We apply a multi-objective optimization algorithm to the problem of parameter estimation in climate models. This optimization process involves the iterative evaluation of response surface models (RSMs), followed by the execution of multiple Earth system simulations. These computations require an infrastructure that provides high-performance computing for building and searching the RSMs and high-throughput computing for the concurrent evaluation of a large number of models. Grid computing technology is therefore essential to make this algorithm practical for members of the GENIE project.

A conceptual model to empower software requirements conflict detection and resolution with rule-based reasoning

NASA Astrophysics Data System (ADS)

Ahmad, Sabrina; Jalil, Intan Ermahani A.; Ahmad, Sharifah Sakinah Syed

2016-08-01

It is seldom technical issues which impede the process of eliciting software requirements. The involvement of multiple stakeholders usually leads to conflicts and therefore the need of conflict detection and resolution effort is crucial. This paper presents a conceptual model to further improve current efforts. Hence, this paper forwards an improved conceptual model to assist the conflict detection and resolution effort which extends the model ability and improves overall performance. The significant of the new model is to empower the automation of conflicts detection and its severity level with rule-based reasoning.

Fostering Emotion Expression and Affective Involvement with Communication Partners in People with Congenital Deafblindness and Intellectual Disabilities.

PubMed

Martens, Marga A W; Janssen, Marleen J; Ruijssenaars, Wied A J J M; Huisman, Mark; Riksen-Walraven, J Marianne

2017-09-01

Recent studies have shown that it is possible to foster affective involvement between people with congenital deafblindness and their communication partners. Affective involvement is crucial for well-being, and it is important to know whether it can also be fostered with people who have congenital deafblindness and intellectual disabilities. This study used a multiple-baseline design to examine whether an intervention based on the Intervention Model for Affective Involvement would (i) increase affective involvement between four participants with congenital deafblindness and intellectual disabilities and their 13 communication partners and (ii) increase the participants' positive emotions and decrease their negative emotions. In all cases, dyadic affective involvement increased, the participants' very positive emotions also increased and the participants' negative emotions decreased. The results indicate that communication partners of persons with congenital deafblindness and intellectual disabilities can be successfully trained to foster affective involvement. © 2016 John Wiley & Sons Ltd.

Effect of electronic stability control on automobile crash risk.

PubMed

Farmer, Charles

2004-12-01

Per vehicle crash involvement rates were compared for otherwise identical vehicle models with and without electronic stability control (ESC) systems. ESC was found to affect single-vehicle crashes to a greater extent than multiple-vehicle crashes, and crashes with fatal injuries to a greater extent than less severe crashes. Based on all police-reported crashes in 7 states over 2 years, ESC reduced single-vehicle crash involvement risk by approximately 41 percent (95 percent confidence limits 3348) and single-vehicle injury crash involvement risk by 41 percent (2752). This translates to an estimated 7 percent reduction in overall crash involvement risk (310) and a 9 percent reduction in overall injury crash involvement risk (314). Based on all fatal crashes in the United States over 3 years, ESC was found to have reduced single-vehicle fatal crash involvement risk by 56 percent (3968). This translates to an estimated 34 percent reduction in overall fatal crash involvement risk (2145).

Decision-making for foot-and-mouth disease control: Objectives matter

USGS Publications Warehouse

Probert, William J. M.; Shea, Katriona; Fonnesbeck, Christopher J.; Runge, Michael C.; Carpenter, Tim E.; Durr, Salome; Garner, M. Graeme; Harvey, Neil; Stevenson, Mark A.; Webb, Colleen T.; Werkman, Marleen; Tildesley, Michael J.; Ferrari, Matthew J.

2016-01-01

Formal decision-analytic methods can be used to frame disease control problems, the first step of which is to define a clear and specific objective. We demonstrate the imperative of framing clearly-defined management objectives in finding optimal control actions for control of disease outbreaks. We illustrate an analysis that can be applied rapidly at the start of an outbreak when there are multiple stakeholders involved with potentially multiple objectives, and when there are also multiple disease models upon which to compare control actions. The output of our analysis frames subsequent discourse between policy-makers, modellers and other stakeholders, by highlighting areas of discord among different management objectives and also among different models used in the analysis. We illustrate this approach in the context of a hypothetical foot-and-mouth disease (FMD) outbreak in Cumbria, UK using outputs from five rigorously-studied simulation models of FMD spread. We present both relative rankings and relative performance of controls within each model and across a range of objectives. Results illustrate how control actions change across both the base metric used to measure management success and across the statistic used to rank control actions according to said metric. This work represents a first step towards reconciling the extensive modelling work on disease control problems with frameworks for structured decision making.

Omics analysis of mouse brain models of human diseases.

PubMed

Paban, Véronique; Loriod, Béatrice; Villard, Claude; Buee, Luc; Blum, David; Pietropaolo, Susanna; Cho, Yoon H; Gory-Faure, Sylvie; Mansour, Elodie; Gharbi, Ali; Alescio-Lautier, Béatrice

2017-02-05

The identification of common gene/protein profiles related to brain alterations, if they exist, may indicate the convergence of the pathogenic mechanisms driving brain disorders. Six genetically engineered mouse lines modelling neurodegenerative diseases and neuropsychiatric disorders were considered. Omics approaches, including transcriptomic and proteomic methods, were used. The gene/protein lists were used for inter-disease comparisons and further functional and network investigations. When the inter-disease comparison was performed using the gene symbol identifiers, the number of genes/proteins involved in multiple diseases decreased rapidly. Thus, no genes/proteins were shared by all 6 mouse models. Only one gene/protein (Gfap) was shared among 4 disorders, providing strong evidence that a common molecular signature does not exist among brain diseases. The inter-disease comparison of functional processes showed the involvement of a few major biological processes indicating that brain diseases of diverse aetiologies might utilize common biological pathways in the nervous system, without necessarily involving similar molecules. Copyright © 2016 Elsevier B.V. All rights reserved.

A note on the use of the generalized odds ratio in meta-analysis of association studies involving bi- and tri-allelic polymorphisms.

PubMed

Pereira, Tiago V; Mingroni-Netto, Regina C

2011-06-06

The generalized odds ratio (GOR) was recently suggested as a genetic model-free measure for association studies. However, its properties were not extensively investigated. We used Monte Carlo simulations to investigate type-I error rates, power and bias in both effect size and between-study variance estimates of meta-analyses using the GOR as a summary effect, and compared these results to those obtained by usual approaches of model specification. We further applied the GOR in a real meta-analysis of three genome-wide association studies in Alzheimer's disease. For bi-allelic polymorphisms, the GOR performs virtually identical to a standard multiplicative model of analysis (e.g. per-allele odds ratio) for variants acting multiplicatively, but augments slightly the power to detect variants with a dominant mode of action, while reducing the probability to detect recessive variants. Although there were differences among the GOR and usual approaches in terms of bias and type-I error rates, both simulation- and real data-based results provided little indication that these differences will be substantial in practice for meta-analyses involving bi-allelic polymorphisms. However, the use of the GOR may be slightly more powerful for the synthesis of data from tri-allelic variants, particularly when susceptibility alleles are less common in the populations (≤10%). This gain in power may depend on knowledge of the direction of the effects. For the synthesis of data from bi-allelic variants, the GOR may be regarded as a multiplicative-like model of analysis. The use of the GOR may be slightly more powerful in the tri-allelic case, particularly when susceptibility alleles are less common in the populations.

Neuroprotective effect of lurasidone via antagonist activities on histamine in a rat model of cranial nerve involvement.

PubMed

He, Baoming; Yu, Liang; Li, Suping; Xu, Fei; Yang, Lili; Ma, Shuai; Guo, Yi

2018-04-01

Cranial nerve involvement frequently involves neuron damage and often leads to psychiatric disorder caused by multiple inducements. Lurasidone is a novel antipsychotic agent approved for the treatment of cranial nerve involvement and a number of mental health conditions in several countries. In the present study, the neuroprotective effect of lurasidone by antagonist activities on histamine was investigated in a rat model of cranial nerve involvement. The antagonist activities of lurasidone on serotonin 5‑HT7, serotonin 5‑HT2A, serotonin 5‑HT1A and serotonin 5‑HT6 were analyzed, and the preclinical therapeutic effects of lurasidone were examined in a rat model of cranial nerve involvement. The safety, maximum tolerated dose (MTD) and preliminary antitumor activity of lurasidone were also assessed in the cranial nerve involvement model. The therapeutic dose of lurasidone was 0.32 mg once daily, administered continuously in 14‑day cycles. The results of the present study found that the preclinical prescriptions induced positive behavioral responses following treatment with lurasidone. The MTD was identified as a once daily administration of 0.32 mg lurasidone. Long‑term treatment with lurasidone for cranial nerve involvement was shown to improve the therapeutic effects and reduce anxiety in the experimental rats. In addition, treatment with lurasidone did not affect body weight. The expression of the language competence protein, Forkhead‑BOX P2, was increased, and the levels of neuroprotective SxIP motif and microtubule end‑binding protein were increased in the hippocampal cells of rats with cranial nerve involvement treated with lurasidone. Lurasidone therapy reinforced memory capability and decreased anxiety. Taken together, lurasidone treatment appeared to protect against language disturbances associated with negative and cognitive impairment in the rat model of cranial nerve involvement, providing a basis for its use in the clinical treatment of patients with cranial nerve involvement.

Multiple imputation for handling missing outcome data when estimating the relative risk.

PubMed

Sullivan, Thomas R; Lee, Katherine J; Ryan, Philip; Salter, Amy B

2017-09-06

Multiple imputation is a popular approach to handling missing data in medical research, yet little is known about its applicability for estimating the relative risk. Standard methods for imputing incomplete binary outcomes involve logistic regression or an assumption of multivariate normality, whereas relative risks are typically estimated using log binomial models. It is unclear whether misspecification of the imputation model in this setting could lead to biased parameter estimates. Using simulated data, we evaluated the performance of multiple imputation for handling missing data prior to estimating adjusted relative risks from a correctly specified multivariable log binomial model. We considered an arbitrary pattern of missing data in both outcome and exposure variables, with missing data induced under missing at random mechanisms. Focusing on standard model-based methods of multiple imputation, missing data were imputed using multivariate normal imputation or fully conditional specification with a logistic imputation model for the outcome. Multivariate normal imputation performed poorly in the simulation study, consistently producing estimates of the relative risk that were biased towards the null. Despite outperforming multivariate normal imputation, fully conditional specification also produced somewhat biased estimates, with greater bias observed for higher outcome prevalences and larger relative risks. Deleting imputed outcomes from analysis datasets did not improve the performance of fully conditional specification. Both multivariate normal imputation and fully conditional specification produced biased estimates of the relative risk, presumably since both use a misspecified imputation model. Based on simulation results, we recommend researchers use fully conditional specification rather than multivariate normal imputation and retain imputed outcomes in the analysis when estimating relative risks. However fully conditional specification is not without its shortcomings, and so further research is needed to identify optimal approaches for relative risk estimation within the multiple imputation framework.

Astrostatistical Analysis in Solar and Stellar Physics

NASA Astrophysics Data System (ADS)

Stenning, David Craig

This dissertation focuses on developing statistical models and methods to address data-analytic challenges in astrostatistics---a growing interdisciplinary field fostering collaborations between statisticians and astrophysicists. The astrostatistics projects we tackle can be divided into two main categories: modeling solar activity and Bayesian analysis of stellar evolution. These categories from Part I and Part II of this dissertation, respectively. The first line of research we pursue involves classification and modeling of evolving solar features. Advances in space-based observatories are increasing both the quality and quantity of solar data, primarily in the form of high-resolution images. To analyze massive streams of solar image data, we develop a science-driven dimension reduction methodology to extract scientifically meaningful features from images. This methodology utilizes mathematical morphology to produce a concise numerical summary of the magnetic flux distribution in solar "active regions'' that (i) is far easier to work with than the source images, (ii) encapsulates scientifically relevant information in a more informative manner than existing schemes (i.e., manual classification schemes), and (iii) is amenable to sophisticated statistical analyses. In a related line of research, we perform a Bayesian analysis of the solar cycle using multiple proxy variables, such as sunspot numbers. We take advantage of patterns and correlations among the proxy variables to model solar activity using data from proxies that have become available more recently, while also taking advantage of the long history of observations of sunspot numbers. This model is an extension of the Yu et al. (2012) Bayesian hierarchical model for the solar cycle that used the sunspot numbers alone. Since proxies have different temporal coverage, we devise a multiple imputation scheme to account for missing data. We find that incorporating multiple proxies reveals important features of the solar cycle that are missed when the model is fit using only the sunspot numbers. In Part II of this dissertation we focus on two related lines of research involving Bayesian analysis of stellar evolution. We first focus on modeling multiple stellar populations in star clusters. It has long been assumed that all star clusters are comprised of single stellar populations---stars that formed at roughly the same time from a common molecular cloud. However, recent studies have produced evidence that some clusters host multiple populations, which has far-reaching scientific implications. We develop a Bayesian hierarchical model for multiple-population star clusters, extending earlier statistical models of stellar evolution (e.g., van Dyk et al. 2009, Stein et al. 2013). We also devise an adaptive Markov chain Monte Carlo algorithm to explore the complex posterior distribution. We use numerical studies to demonstrate that our method can recover parameters of multiple-population clusters, and also show how model misspecification can be diagnosed. Our model and computational tools are incorporated into an open-source software suite known as BASE-9. We also explore statistical properties of the estimators and determine that the influence of the prior distribution does not diminish with larger sample sizes, leading to non-standard asymptotics. In a final line of research, we present the first-ever attempt to estimate the carbon fraction of white dwarfs. This quantity has important implications for both astrophysics and fundamental nuclear physics, but is currently unknown. We use a numerical study to demonstrate that assuming an incorrect value for the carbon fraction leads to incorrect white-dwarf ages of star clusters. Finally, we present our attempt to estimate the carbon fraction of the white dwarfs in the well-studied star cluster 47 Tucanae.

An integrated modelling framework for neural circuits with multiple neuromodulators.

PubMed

Joshi, Alok; Youssofzadeh, Vahab; Vemana, Vinith; McGinnity, T M; Prasad, Girijesh; Wong-Lin, KongFatt

2017-01-01

Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. © 2017 The Authors.

An integrated modelling framework for neural circuits with multiple neuromodulators

PubMed Central

Vemana, Vinith

2017-01-01

Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. PMID:28100828

Multiple Family Groups for Child Behavior Difficulties Retention Among Child Welfare–Involved Caregivers

PubMed Central

Gopalan, Geetha; Fuss, Ashley; Wisdom, Jennifer P.

2013-01-01

Among children who remain at home with their permanent caregivers following a child welfare investigation, few who manifest emotional and behavioral difficulties actually engage in mental health treatment. The Multiple Family Group service delivery model to reduce childhood disruptive behavior disorders (MFG) has shown promise in engaging child welfare-involved families. This qualitative study examines caregiver perceptions of factors that influence retention in MFGs among child welfare-involved families. Methods Twenty-five predominantly Black and Hispanic adult (ages 26–57) female caregivers with child welfare services involvement participated in individual, in-depth interviews about their experience with MFGs. Transcribed interview data were thematically coded guided by grounded theory methodology. Emergent themes were subsequently organized into a conceptual framework. Results Within the overarching influence of child welfare services involvement, specific components of MFGs influencing retention included the quality of interaction among group members, group facilitators’ attentive approach with caregivers, supports designed to overcome logistical barriers (i.e., child care, transportation expenses, meals), and perceptions of MFG content and activities as fun and helpful. Caregiver factors, including their mental health and personal characteristics, as well as children’s behavior, (i.e., observed changes in behavioral difficulties) were also associated with retention. Conclusions High acceptability suggest utility for implementing MFGs within settings serving child welfare involved families, with additional modifications to tailor to setting and client features. PMID:26527856

Pairwise Force SPH Model for Real-Time Multi-Interaction Applications.

PubMed

Yang, Tao; Martin, Ralph R; Lin, Ming C; Chang, Jian; Hu, Shi-Min

2017-10-01

In this paper, we present a novel pairwise-force smoothed particle hydrodynamics (PF-SPH) model to enable simulation of various interactions at interfaces in real time. Realistic capture of interactions at interfaces is a challenging problem for SPH-based simulations, especially for scenarios involving multiple interactions at different interfaces. Our PF-SPH model can readily handle multiple types of interactions simultaneously in a single simulation; its basis is to use a larger support radius than that used in standard SPH. We adopt a novel anisotropic filtering term to further improve the performance of interaction forces. The proposed model is stable; furthermore, it avoids the particle clustering problem which commonly occurs at the free surface. We show how our model can be used to capture various interactions. We also consider the close connection between droplets and bubbles, and show how to animate bubbles rising in liquid as well as bubbles in air. Our method is versatile, physically plausible and easy-to-implement. Examples are provided to demonstrate the capabilities and effectiveness of our approach.

The Effect of Orem’s Self-Care Model on Fatigue in Patients With Multiple Sclerosis: A Single Blind Randomized Clinical Trial Study

PubMed Central

Afrasiabifar, Ardashir; Mehri, Zahra; Javad Sadat, Saied; Ghaffarian Shirazi, Hamid Reza

2016-01-01

Background Orem’s self-care model is a nursing model that was introduced with the purpose of improving the self-care of individuals, especially patients suffering from chronic diseases. Objectives To determining the effect of Orem’s self-care model on fatigue in multiple sclerosis patients. Patients and Methods This research involved a clinical trial. Sixty-three multiple sclerosis patients at the vice-chancellor in treatment affairs of Yasuj University of Medical Sciences were selected based on nonrandom sampling, but they were allocated to the two groups based on random allocation. In the intervention group, Orem’s model was applied during six sessions of 45 - 60 minutes in length, and the process continued for 1 month. The data were collected 1 week before and 7 weeks after the end of the intervention using the Orem’s self-care model-based assessment form and fatigue severity scale, the validity and reliability of which have been Results Before the intervention, 11.11% of the participants had a good knowledge of self-care. In addition, self-care willingness and skills were observed in 76.19% and 4.76% of participants, respectively. The mean difference in fatigue reduced significantly in the intervention group after the intervention (P < 0.05). After the intervention, a statistically significant difference was observed in the mean difference of fatigue between the two groups (P < 0.05). Conclusions Orem’s self-care model is significantly effective in reducing the fatigue of multiple sclerosis patients. PMID:27781119

Multiple transmitter performance with appropriate amplitude modulation for free-space optical communication.

PubMed

Tellez, Jason A; Schmidt, Jason D

2011-08-20

The propagation of a free-space optical communications signal through atmospheric turbulence experiences random fluctuations in intensity, including signal fades, which negatively impact the performance of the communications link. The gamma-gamma probability density function is commonly used to model the scintillation of a single beam. One proposed method to reduce the occurrence of scintillation-induced fades at the receiver plane involves the use of multiple beams propagating through independent paths, resulting in a sum of independent gamma-gamma random variables. Recently an analytical model for the probability distribution of irradiance from the sum of multiple independent beams was developed. Because truly independent beams are practically impossible to create, we present here a more general but approximate model for the distribution of beams traveling through partially correlated paths. This model compares favorably with wave-optics simulations and highlights the reduced scintillation as the number of transmitted beams is increased. Additionally, a pulse-position modulation scheme is used to reduce the impact of signal fades when they occur. Analytical and simulated results showed significantly improved performance when compared to fixed threshold on/off keying. © 2011 Optical Society of America

Low Dose Radiation Cancer Risks: Epidemiological and Toxicological Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

David G. Hoel, PhD

2012-04-19

The basic purpose of this one year research grant was to extend the two stage clonal expansion model (TSCE) of carcinogenesis to exposures other than the usual single acute exposure. The two-stage clonal expansion model of carcinogenesis incorporates the biological process of carcinogenesis, which involves two mutations and the clonal proliferation of the intermediate cells, in a stochastic, mathematical way. The current TSCE model serves a general purpose of acute exposure models but requires numerical computation of both the survival and hazard functions. The primary objective of this research project was to develop the analytical expressions for the survival functionmore » and the hazard function of the occurrence of the first cancer cell for acute, continuous and multiple exposure cases within the framework of the piece-wise constant parameter two-stage clonal expansion model of carcinogenesis. For acute exposure and multiple exposures of acute series, it is either only allowed to have the first mutation rate vary with the dose, or to have all the parameters be dose dependent; for multiple exposures of continuous exposures, all the parameters are allowed to vary with the dose. With these analytical functions, it becomes easy to evaluate the risks of cancer and allows one to deal with the various exposure patterns in cancer risk assessment. A second objective was to apply the TSCE model with varing continuous exposures from the cancer studies of inhaled plutonium in beagle dogs. Using step functions to estimate the retention functions of the pulmonary exposure of plutonium the multiple exposure versions of the TSCE model was to be used to estimate the beagle dog lung cancer risks. The mathematical equations of the multiple exposure versions of the TSCE model were developed. A draft manuscript which is attached provides the results of this mathematical work. The application work using the beagle dog data from plutonium exposure has not been completed due to the fact that the research project did not continue beyond its first year.« less

[Burning mouth syndrome - a joint biopsychosocial approach].

PubMed

Arpone, Francesca; Combremont, Florian; Weber, Kerstin; Scolozzi, Paolo

2016-02-10

Burning mouth syndrome (BMS) is a medical condition that is often refractory to conventional diagnostic and therapeutic methods. Patients suffering from BMS can benefit from a biopsychosocial approach in a joint, medical-psychological consultation model. Such a consultation exists at Geneva University Hospitals, involving the collaboration of the maxillo-facial and oral surgery division and the division of liaison psychiatry and crisis intervention, in order to take into account the multiple factors involved in BMS onset and persistence. This article will describe BMS clinical presentation, and present an integrate approach to treat these patients.

Treatment of anorexia nervosa in children and adolescents.

PubMed

Weaver, Laurel; Sit, Lydia; Liebman, Ronald

2012-04-01

In this review, we discuss the treatment of anorexia nervosa (AN) in children and adolescents, highlighting inpatient and outpatient psychiatric treatment. AN is an illness that involves medical and psychological issues; hence, treatment often requires the seamless integration of several medical professionals. It is important that the treatment model be unified and consistent as patients transition from inpatient to outpatient treatment. We briefly describe the therapeutic principles involved in treatment of AN and then give examples of how we employ these principles across treatment settings and with multiple medical professionals.

Circuit to Construct Mapping: A Mathematical Tool for Assisting the Diagnosis and Treatment in Major Depressive Disorder

PubMed Central

Bielczyk, Natalia Z.; Buitelaar, Jan K.; Glennon, Jeffrey C.; Tiesinga, Paul H. E.

2015-01-01

Major depressive disorder (MDD) is a serious condition with a lifetime prevalence exceeding 16% worldwide. MDD is a heterogeneous disorder that involves multiple behavioral symptoms on the one hand and multiple neuronal circuits on the other hand. In this review, we integrate the literature on cognitive and physiological biomarkers of MDD with the insights derived from mathematical models of brain networks, especially models that can be used for fMRI datasets. We refer to the recent NIH research domain criteria initiative, in which a concept of “constructs” as functional units of mental disorders is introduced. Constructs are biomarkers present at multiple levels of brain functioning – cognition, genetics, brain anatomy, and neurophysiology. In this review, we propose a new approach which we called circuit to construct mapping (CCM), which aims to characterize causal relations between the underlying network dynamics (as the cause) and the constructs referring to the clinical symptoms of MDD (as the effect). CCM involves extracting diagnostic categories from behavioral data, linking circuits that are causal to these categories with use of clinical neuroimaging data, and modeling the dynamics of the emerging circuits with attractor dynamics in order to provide new, neuroimaging-related biomarkers for MDD. The CCM approach optimizes the clinical diagnosis and patient stratification. It also addresses the recent demand for linking circuits to behavior, and provides a new insight into clinical treatment by investigating the dynamics of neuronal circuits underneath cognitive dimensions of MDD. CCM can serve as a new regime toward personalized medicine, assisting the diagnosis and treatment of MDD. PMID:25767450

Hypergraph partitioning implementation for parallelizing matrix-vector multiplication using CUDA GPU-based parallel computing

NASA Astrophysics Data System (ADS)

Murni, Bustamam, A.; Ernastuti, Handhika, T.; Kerami, D.

2017-07-01

Calculation of the matrix-vector multiplication in the real-world problems often involves large matrix with arbitrary size. Therefore, parallelization is needed to speed up the calculation process that usually takes a long time. Graph partitioning techniques that have been discussed in the previous studies cannot be used to complete the parallelized calculation of matrix-vector multiplication with arbitrary size. This is due to the assumption of graph partitioning techniques that can only solve the square and symmetric matrix. Hypergraph partitioning techniques will overcome the shortcomings of the graph partitioning technique. This paper addresses the efficient parallelization of matrix-vector multiplication through hypergraph partitioning techniques using CUDA GPU-based parallel computing. CUDA (compute unified device architecture) is a parallel computing platform and programming model that was created by NVIDIA and implemented by the GPU (graphics processing unit).

Alternatives for jet engine control

NASA Technical Reports Server (NTRS)

Leake, R. J.; Sain, M. K.

1978-01-01

General goals of the research were classified into two categories. The first category involves the use of modern multivariable frequency domain methods for control of engine models in the neighborhood of a quiescent point. The second category involves the use of nonlinear modelling and optimization techniques for control of engine models over a more extensive part of the flight envelope. In the frequency domain category, works were published in the areas of low-interaction design, polynomial design, and multiple setpoint studies. A number of these ideas progressed to the point at which they are starting to attract practical interest. In the nonlinear category, advances were made both in engine modelling and in the details associated with software for determination of time optimal controls. Nonlinear models for a two spool turbofan engine were expanded and refined; and a promising new approach to automatic model generation was placed under study. A two time scale scheme was developed to do two-dimensional dynamic programming, and an outward spiral sweep technique has greatly speeded convergence times in time optimal calculations.

Agent based modeling of the effects of potential treatments over the blood-brain barrier in multiple sclerosis.

PubMed

Pennisi, Marzio; Russo, Giulia; Motta, Santo; Pappalardo, Francesco

2015-12-01

Multiple sclerosis is a disease of the central nervous system that involves the destruction of the insulating sheath of axons, causing severe disabilities. Since the etiology of the disease is not yet fully understood, the use of novel techniques that may help to understand the disease, to suggest potential therapies and to test the effects of candidate treatments is highly advisable. To this end we developed an agent based model that demonstrated its ability to reproduce the typical oscillatory behavior observed in the most common form of multiple sclerosis, relapsing-remitting multiple sclerosis. The model has then been used to test the potential beneficial effects of vitamin D over the disease. Many scientific studies underlined the importance of the blood-brain barrier and of the mechanisms that influence its permeability on the development of the disease. In the present paper we further extend our previously developed model with a mechanism that mimics the blood-brain barrier behavior. The goal of our work is to suggest the best strategies to follow for developing new potential treatments that intervene in the blood-brain barrier. Results suggest that the best treatments should potentially prevent the opening of the blood-brain barrier, as treatments that help in recovering the blood-brain barrier functionality could be less effective. Copyright © 2015 Elsevier B.V. All rights reserved.

Patterns of evolution at the gametophytic self-incompatibility Sorbus aucuparia (Pyrinae) S pollen genes support the non-self recognition by multiple factors model.

PubMed

Aguiar, Bruno; Vieira, Jorge; Cunha, Ana E; Fonseca, Nuno A; Reboiro-Jato, David; Reboiro-Jato, Miguel; Fdez-Riverola, Florentino; Raspé, Olivier; Vieira, Cristina P

2013-05-01

S-RNase-based gametophytic self-incompatibility evolved once before the split of the Asteridae and Rosidae. In Prunus (tribe Amygdaloideae of Rosaceae), the self-incompatibility S-pollen is a single F-box gene that presents the expected evolutionary signatures. In Malus and Pyrus (subtribe Pyrinae of Rosaceae), however, clusters of F-box genes (called SFBBs) have been described that are expressed in pollen only and are linked to the S-RNase gene. Although polymorphic, SFBB genes present levels of diversity lower than those of the S-RNase gene. They have been suggested as putative S-pollen genes, in a system of non-self recognition by multiple factors. Subsets of allelic products of the different SFBB genes interact with non-self S-RNases, marking them for degradation, and allowing compatible pollinations. This study performed a detailed characterization of SFBB genes in Sorbus aucuparia (Pyrinae) to address three predictions of the non-self recognition by multiple factors model. As predicted, the number of SFBB genes was large to account for the many S-RNase specificities. Secondly, like the S-RNase gene, the SFBB genes were old. Thirdly, amino acids under positive selection-those that could be involved in specificity determination-were identified when intra-haplotype SFBB genes were analysed using codon models. Overall, the findings reported here support the non-self recognition by multiple factors model.

Examining the Links between Challenging Behaviors in Youth with ASD and Parental Stress, Mental Health, and Involvement: Applying an Adaptation of the Family Stress Model to Families of Youth with ASD

ERIC Educational Resources Information Center

Schiltz, Hillary K.; McVey, Alana J.; Magnus, Brooke; Dolan, Bridget K.; Willar, Kirsten S.; Pleiss, Sheryl; Karst, Jeffrey; Carson, Audrey M.; Caiozzo, Christina; Vogt, Elisabeth; Van Hecke, Amy Vaughan

2018-01-01

Raising a child with autism spectrum disorder (ASD) poses unique challenges that may impact parents' mental health and parenting experiences. The current study analyzed self-report data from 77 parents of youth with ASD. A serial multiple mediation model revealed that parenting stress (SIPA) and parental mental health (BAI and BDI-II) appears to…

The hearing ear is always found close to the speaking tongue: Review of the role of the motor system in speech perception.

PubMed

Skipper, Jeremy I; Devlin, Joseph T; Lametti, Daniel R

2017-01-01

Does "the motor system" play "a role" in speech perception? If so, where, how, and when? We conducted a systematic review that addresses these questions using both qualitative and quantitative methods. The qualitative review of behavioural, computational modelling, non-human animal, brain damage/disorder, electrical stimulation/recording, and neuroimaging research suggests that distributed brain regions involved in producing speech play specific, dynamic, and contextually determined roles in speech perception. The quantitative review employed region and network based neuroimaging meta-analyses and a novel text mining method to describe relative contributions of nodes in distributed brain networks. Supporting the qualitative review, results show a specific functional correspondence between regions involved in non-linguistic movement of the articulators, covertly and overtly producing speech, and the perception of both nonword and word sounds. This distributed set of cortical and subcortical speech production regions are ubiquitously active and form multiple networks whose topologies dynamically change with listening context. Results are inconsistent with motor and acoustic only models of speech perception and classical and contemporary dual-stream models of the organization of language and the brain. Instead, results are more consistent with complex network models in which multiple speech production related networks and subnetworks dynamically self-organize to constrain interpretation of indeterminant acoustic patterns as listening context requires. Copyright © 2016. Published by Elsevier Inc.

Research activities at the Center for Modeling of Turbulence and Transition

NASA Technical Reports Server (NTRS)

Shih, Tsan-Hsing

1993-01-01

The main research activities at the Center for Modeling of Turbulence and Transition (CMOTT) are described. The research objective of CMOTT is to improve and/or develop turbulence and transition models for propulsion systems. The flows of interest in propulsion systems can be both compressible and incompressible, three dimensional, bounded by complex wall geometries, chemically reacting, and involve 'bypass' transition. The most relevant turbulence and transition models for the above flows are one- and two-equation eddy viscosity models, Reynolds stress algebraic- and transport-equation models, pdf models, and multiple-scale models. All these models are classified as one-point closure schemes since only one-point (in time and space) turbulent correlations, such as second moments (Reynolds stresses and turbulent heat fluxes) and third moments, are involved. In computational fluid dynamics, all turbulent quantities are one-point correlations. Therefore, the study of one-point turbulent closure schemes is the focus of our turbulence research. However, other research, such as the renormalization group theory, the direct interaction approximation method, and numerical simulations are also pursued to support the development of turbulence modeling.

Nonadiabatic excited-state molecular dynamics: modeling photophysics in organic conjugated materials.

PubMed

Nelson, Tammie; Fernandez-Alberti, Sebastian; Roitberg, Adrian E; Tretiak, Sergei

2014-04-15

To design functional photoactive materials for a variety of technological applications, researchers need to understand their electronic properties in detail and have ways to control their photoinduced pathways. When excited by photons of light, organic conjugated materials (OCMs) show dynamics that are often characterized by large nonadiabatic (NA) couplings between multiple excited states through a breakdown of the Born-Oppenheimer (BO) approximation. Following photoexcitation, various nonradiative intraband relaxation pathways can lead to a number of complex processes. Therefore, computational simulation of nonadiabatic molecular dynamics is an indispensable tool for understanding complex photoinduced processes such as internal conversion, energy transfer, charge separation, and spatial localization of excitons. Over the years, we have developed a nonadiabatic excited-state molecular dynamics (NA-ESMD) framework that efficiently and accurately describes photoinduced phenomena in extended conjugated molecular systems. We use the fewest-switches surface hopping (FSSH) algorithm to treat quantum transitions among multiple adiabatic excited state potential energy surfaces (PESs). Extended molecular systems often contain hundreds of atoms and involve large densities of excited states that participate in the photoinduced dynamics. We can achieve an accurate description of the multiple excited states using the configuration interaction single (CIS) formalism with a semiempirical model Hamiltonian. Analytical techniques allow the trajectory to be propagated "on the fly" using the complete set of NA coupling terms and remove computational bottlenecks in the evaluation of excited-state gradients and NA couplings. Furthermore, the use of state-specific gradients for propagation of nuclei on the native excited-state PES eliminates the need for simplifications such as the classical path approximation (CPA), which only uses ground-state gradients. Thus, the NA-ESMD methodology offers a computationally tractable route for simulating hundreds of atoms on ~10 ps time scales where multiple coupled excited states are involved. In this Account, we review recent developments in the NA-ESMD modeling of photoinduced dynamics in extended conjugated molecules involving multiple coupled electronic states. We have successfully applied the outlined NA-ESMD framework to study ultrafast conformational planarization in polyfluorenes where the rate of torsional relaxation can be controlled based on the initial excitation. With the addition of the state reassignment algorithm to identify instances of unavoided crossings between noninteracting PESs, NA-ESMD can now be used to study systems in which these so-called trivial unavoided crossings are expected to predominate. We employ this technique to analyze the energy transfer between poly(phenylene vinylene) (PPV) segments where conformational fluctuations give rise to numerous instances of unavoided crossings leading to multiple pathways and complex energy transfer dynamics that cannot be described using a simple Förster model. In addition, we have investigated the mechanism of ultrafast unidirectional energy transfer in dendrimers composed of poly(phenylene ethynylene) (PPE) chromophores and have demonstrated that differential nuclear motion favors downhill energy transfer in dendrimers. The use of native excited-state gradients allows us to observe this feature.

Features in visual search combine linearly

PubMed Central

Pramod, R. T.; Arun, S. P.

2014-01-01

Single features such as line orientation and length are known to guide visual search, but relatively little is known about how multiple features combine in search. To address this question, we investigated how search for targets differing in multiple features (intensity, length, orientation) from the distracters is related to searches for targets differing in each of the individual features. We tested race models (based on reaction times) and co-activation models (based on reciprocal of reaction times) for their ability to predict multiple feature searches. Multiple feature searches were best accounted for by a co-activation model in which feature information combined linearly (r = 0.95). This result agrees with the classic finding that these features are separable i.e., subjective dissimilarity ratings sum linearly. We then replicated the classical finding that the length and width of a rectangle are integral features—in other words, they combine nonlinearly in visual search. However, to our surprise, upon including aspect ratio as an additional feature, length and width combined linearly and this model outperformed all other models. Thus, length and width of a rectangle became separable when considered together with aspect ratio. This finding predicts that searches involving shapes with identical aspect ratio should be more difficult than searches where shapes differ in aspect ratio. We confirmed this prediction on a variety of shapes. We conclude that features in visual search co-activate linearly and demonstrate for the first time that aspect ratio is a novel feature that guides visual search. PMID:24715328

Teaching Multiplication with Regrouping Using the Concrete-Representational-Abstract Sequence and the Strategic Instruction Model

ERIC Educational Resources Information Center

Flores, Margaret M.; Franklin, Toni M.

2014-01-01

The Common Core State Standards (2010) involve the demonstration of conceptual knowledge of numbers and operations. For students who struggle with mathematics and have not responded to instruction, it is important that interventions emphasize this understanding. In order to address conceptual understanding of numbers and operations in meeting the…

Fiber length - fiber strength interrelationship for slash pine and its effect on pulp-sheet properties

Treesearch

F.F. Wangaard; George E. Woodson

1972-01-01

Based on a model developed for hardwood fiber strength-pulp property relationships, multiple-regression equations involving fiber strength, fiber length, and sheet density were determined to predict the properties of kraft pulps of slash pine (Pinus elliottii). Regressions for breaking length and burst factor accounted for 88 and 90 percent,...

Fiber length strength interrelationship for slash pine and its effect on pulp-sheet properties

Treesearch

F. G. Wangaard; G. E. Woodson

1973-01-01

Based on a model developed for hardwood fiber strength-pulp property relationships, multiple-regression equations involving fiber strength, fiber length, and sheet density were determined to predict the properties of kraft pulps of slash pine (Pinus elliottii). Regressions for breaking length and burst factor accounted for 88 and 90 percent,...

Process Writing and the Internet: Blogs and Ning Networks in the Classroom

ERIC Educational Resources Information Center

Boas, Isabela Villas

2011-01-01

In contrast to the product approach to writing, which is based on studying and replicating textual models, the process approach involves multiple and repeated steps that compel the writer to closely consider the topic, language, purpose for writing, and social reality of an audience. In addition to discussing the benefits of the process approach…

Using Mouse Models to Explore Genotype-Phenotype Relationship in Down Syndrome

ERIC Educational Resources Information Center

Salehi, Ahmad; Faizi, Mehrdad; Belichenko, Pavel V.; Mobley, William C.

2007-01-01

Down Syndrome (DS) caused by trisomy 21 is characterized by a variety of phenotypes and involves multiple organs. Sequencing of human chromosome 21 (HSA21) and subsequently of its orthologues on mouse chromosome 16 have created an unprecedented opportunity to explore the complex relationship between various DS phenotypes and the extra copy of…

Video-Based Intervention in Teaching Fraction Problem-Solving to Students with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Yakubova, Gulnoza; Hughes, Elizabeth M.; Hornberger, Erin

2015-01-01

The purpose of this study was to determine the effectiveness of a point-of-view video modeling intervention to teach mathematics problem-solving when working on word problems involving subtracting mixed fractions with uncommon denominators. Using a multiple-probe across students design of single-case methodology, three high school students with…

A Competency Model for Determining the Professional Profiles of Faculty at Teacher Preparation Schools in Southern Mexico

ERIC Educational Resources Information Center

Mijangos-Noh, Juan Carlos; Canto-Herrera, Pedro J.; Cisneros-Cohernour, Edith J.

2006-01-01

In this paper we present the preliminary findings of a study focused on determining the demographic and professional profiles and competencies of professors teaching at the Normal Schools that prepare elementary school teachers in the Southeast of Mexico. Data collection involves multiple methods of data collection including focus group…

Predicting Negative Discipline in Traditional Families: A Multi-Dimensional Stress Model.

ERIC Educational Resources Information Center

Fisher, Philip A.

An attempt is made to integrate existing theories of family violence by introducing the concept of family role stress. Role stressors may be defined as factors inhibiting the enactment of family roles. Multiple regression analyses were performed on data from 190 families to test a hypothesis involving the prediction of negative discipline at…

ViSA: A Neurodynamic Model for Visuo-Spatial Working Memory, Attentional Blink, and Conscious Access

ERIC Educational Resources Information Center

Simione, Luca; Raffone, Antonino; Wolters, Gezinus; Salmas, Paola; Nakatani, Chie; Belardinelli, Marta Olivetti; van Leeuwen, Cees

2012-01-01

Two separate lines of study have clarified the role of selectivity in conscious access to visual information. Both involve presenting multiple targets and distracters: one "simultaneously" in a spatially distributed fashion, the other "sequentially" at a single location. To understand their findings in a unified framework, we propose a…

Benefits and Drawbacks of Using Multiple Instructors to Teach Single Courses

ERIC Educational Resources Information Center

Jones, Francis; Harris, Sara

2012-01-01

We set out to identify the benefits and drawbacks of using more than one instructor to teach single section science courses at a large research university. Nine courses were investigated involving widely differing subjects and levels. Teaching models included: sequential teaching with two to six instructors each covering only their own modules,…

Mapping fuels at multiple scales: landscape application of the fuel characteristic classification system.

Treesearch

D. McKenzie; C.L. Raymond; L.-K.B. Kellogg; R.A. Norheim; A.G. Andreu; A.C. Bayard; K.E. Kopper; E. Elman

2007-01-01

Fuel mapping is a complex and often multidisciplinary process, involving remote sensing, ground-based validation, statistical modeling, and knowledge-based systems. The scale and resolution of fuel mapping depend both on objectives and availability of spatial data layers. We demonstrate use of the Fuel Characteristic Classification System (FCCS) for fuel mapping at two...

A single-index threshold Cox proportional hazard model for identifying a treatment-sensitive subset based on multiple biomarkers.

PubMed

He, Ye; Lin, Huazhen; Tu, Dongsheng

2018-06-04

In this paper, we introduce a single-index threshold Cox proportional hazard model to select and combine biomarkers to identify patients who may be sensitive to a specific treatment. A penalized smoothed partial likelihood is proposed to estimate the parameters in the model. A simple, efficient, and unified algorithm is presented to maximize this likelihood function. The estimators based on this likelihood function are shown to be consistent and asymptotically normal. Under mild conditions, the proposed estimators also achieve the oracle property. The proposed approach is evaluated through simulation analyses and application to the analysis of data from two clinical trials, one involving patients with locally advanced or metastatic pancreatic cancer and one involving patients with resectable lung cancer. Copyright © 2018 John Wiley & Sons, Ltd.

Why Quantify Uncertainty in Ecosystem Studies: Obligation versus Discovery Tool?

NASA Astrophysics Data System (ADS)

Harmon, M. E.

2016-12-01

There are multiple motivations for quantifying uncertainty in ecosystem studies. One is as an obligation; the other is as a tool useful in moving ecosystem science toward discovery. While reporting uncertainty should become a routine expectation, a more convincing motivation involves discovery. By clarifying what is known and to what degree it is known, uncertainty analyses can point the way toward improvements in measurements, sampling designs, and models. While some of these improvements (e.g., better sampling designs) may lead to incremental gains, those involving models (particularly model selection) may require large gains in knowledge. To be fully harnessed as a discovery tool, attitudes toward uncertainty may have to change: rather than viewing uncertainty as a negative assessment of what was done, it should be viewed as positive, helpful assessment of what remains to be done.

Occupational stress and psychopathology in health professionals: an explorative study with the multiple indicators multiple causes (MIMIC) model approach.

PubMed

Iliceto, Paolo; Pompili, Maurizio; Spencer-Thomas, Sally; Ferracuti, Stefano; Erbuto, Denise; Lester, David; Candilera, Gabriella; Girardi, Paolo

2013-03-01

Occupational stress is a multivariate process involving sources of pressure, psycho-physiological distress, locus of control, work dissatisfaction, depression, anxiety, mental health disorders, hopelessness, and suicide ideation. Healthcare professionals are known for higher rates of occupational-related distress (burnout and compassion fatigue) and higher rates of suicide. The purpose of this study was to explain the relationships between occupational stress and some psychopathological dimensions in a sample of health professionals. We investigated 156 nurses and physicians, 62 males and 94 females, who were administered self-report questionnaires to assess occupational stress [occupational stress inventory (OSI)], temperament (temperament evaluation of Memphis, Pisa, Paris, and San Diego autoquestionnaire), and hopelessness (Beck hopelessness scale). The best Multiple Indicators Multiple Causes model with five OSI predictors yielded the following results: χ2(9) = 14.47 (p = 0.11); χ2/df = 1.60; comparative fit index = 0.99; root mean square error of approximation = 0.05. This model provided a good fit to the empirical data, showing a strong direct influence of casual variables such as work dissatisfaction, absence of type A behavior, and especially external locus of control, psychological and physiological distress on latent variable psychopathology. Occupational stress is in a complex relationship with temperament and hopelessness and also common among healthcare professionals.

Multiple Regions of a Cortical Network Commonly Encode the Meaning of Words in Multiple Grammatical Positions of Read Sentences.

PubMed

Anderson, Andrew James; Lalor, Edmund C; Lin, Feng; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Raizada, Rajeev D S; Grimm, Scott; Wang, Xixi

2018-05-16

Deciphering how sentence meaning is represented in the brain remains a major challenge to science. Semantically related neural activity has recently been shown to arise concurrently in distributed brain regions as successive words in a sentence are read. However, what semantic content is represented by different regions, what is common across them, and how this relates to words in different grammatical positions of sentences is weakly understood. To address these questions, we apply a semantic model of word meaning to interpret brain activation patterns elicited in sentence reading. The model is based on human ratings of 65 sensory/motor/emotional and cognitive features of experience with words (and their referents). Through a process of mapping functional Magnetic Resonance Imaging activation back into model space we test: which brain regions semantically encode content words in different grammatical positions (e.g., subject/verb/object); and what semantic features are encoded by different regions. In left temporal, inferior parietal, and inferior/superior frontal regions we detect the semantic encoding of words in all grammatical positions tested and reveal multiple common components of semantic representation. This suggests that sentence comprehension involves a common core representation of multiple words' meaning being encoded in a network of regions distributed across the brain.

Classification of Multiple Seizure-Like States in Three Different Rodent Models of Epileptogenesis.

PubMed

Guirgis, Mirna; Serletis, Demitre; Zhang, Jane; Florez, Carlos; Dian, Joshua A; Carlen, Peter L; Bardakjian, Berj L

2014-01-01

Epilepsy is a dynamical disease and its effects are evident in over fifty million people worldwide. This study focused on objective classification of the multiple states involved in the brain's epileptiform activity. Four datasets from three different rodent hippocampal preparations were explored, wherein seizure-like-events (SLE) were induced by the perfusion of a low - Mg(2+) /high-K(+) solution or 4-Aminopyridine. Local field potentials were recorded from CA3 pyramidal neurons and interneurons and modeled as Markov processes. Specifically, hidden Markov models (HMM) were used to determine the nature of the states present. Properties of the Hilbert transform were used to construct the feature spaces for HMM training. By sequentially applying the HMM training algorithm, multiple states were identified both in episodes of SLE and nonSLE activity. Specifically, preSLE and postSLE states were differentiated and multiple inner SLE states were identified. This was accomplished using features extracted from the lower frequencies (1-4 Hz, 4-8 Hz) alongside those of both the low- (40-100 Hz) and high-gamma (100-200 Hz) of the recorded electrical activity. The learning paradigm of this HMM-based system eliminates the inherent bias associated with other learning algorithms that depend on predetermined state segmentation and renders it an appropriate candidate for SLE classification.

A critical examination of the numerology of antigen-binding cells: evidence for multiple receptor specificities on single cells.

PubMed

Miller, A

1977-01-01

The data available from other laboratories as well as our own on the frequency of cells recognizing major histocompatibility antigens or conventional protein and hapten antigens is critically evaluated. The frequency of specific binding for a large number of antigens is sufficiently high to support the idea that at least part of the antigen-binding cell population must have multiple specificities. Our results suggest that these multiple specific cells result from single cells synthesizing and displaying as many as 50-100 species of receptor, each at a frequency of 10(4) per cell. A model involving gene expansion of constant-region genes is suggested and some auxilliary evidence consistent with such C-gene expansion is presented.

Modeling multiple time series annotations as noisy distortions of the ground truth: An Expectation-Maximization approach.

PubMed

Gupta, Rahul; Audhkhasi, Kartik; Jacokes, Zach; Rozga, Agata; Narayanan, Shrikanth

2018-01-01

Studies of time-continuous human behavioral phenomena often rely on ratings from multiple annotators. Since the ground truth of the target construct is often latent, the standard practice is to use ad-hoc metrics (such as averaging annotator ratings). Despite being easy to compute, such metrics may not provide accurate representations of the underlying construct. In this paper, we present a novel method for modeling multiple time series annotations over a continuous variable that computes the ground truth by modeling annotator specific distortions. We condition the ground truth on a set of features extracted from the data and further assume that the annotators provide their ratings as modification of the ground truth, with each annotator having specific distortion tendencies. We train the model using an Expectation-Maximization based algorithm and evaluate it on a study involving natural interaction between a child and a psychologist, to predict confidence ratings of the children's smiles. We compare and analyze the model against two baselines where: (i) the ground truth in considered to be framewise mean of ratings from various annotators and, (ii) each annotator is assumed to bear a distinct time delay in annotation and their annotations are aligned before computing the framewise mean.

Development of the Complex General Linear Model in the Fourier Domain: Application to fMRI Multiple Input-Output Evoked Responses for Single Subjects

PubMed Central

Rio, Daniel E.; Rawlings, Robert R.; Woltz, Lawrence A.; Gilman, Jodi; Hommer, Daniel W.

2013-01-01

A linear time-invariant model based on statistical time series analysis in the Fourier domain for single subjects is further developed and applied to functional MRI (fMRI) blood-oxygen level-dependent (BOLD) multivariate data. This methodology was originally developed to analyze multiple stimulus input evoked response BOLD data. However, to analyze clinical data generated using a repeated measures experimental design, the model has been extended to handle multivariate time series data and demonstrated on control and alcoholic subjects taken from data previously analyzed in the temporal domain. Analysis of BOLD data is typically carried out in the time domain where the data has a high temporal correlation. These analyses generally employ parametric models of the hemodynamic response function (HRF) where prewhitening of the data is attempted using autoregressive (AR) models for the noise. However, this data can be analyzed in the Fourier domain. Here, assumptions made on the noise structure are less restrictive, and hypothesis tests can be constructed based on voxel-specific nonparametric estimates of the hemodynamic transfer function (HRF in the Fourier domain). This is especially important for experimental designs involving multiple states (either stimulus or drug induced) that may alter the form of the response function. PMID:23840281

Development of the complex general linear model in the Fourier domain: application to fMRI multiple input-output evoked responses for single subjects.

PubMed

Rio, Daniel E; Rawlings, Robert R; Woltz, Lawrence A; Gilman, Jodi; Hommer, Daniel W

2013-01-01

A linear time-invariant model based on statistical time series analysis in the Fourier domain for single subjects is further developed and applied to functional MRI (fMRI) blood-oxygen level-dependent (BOLD) multivariate data. This methodology was originally developed to analyze multiple stimulus input evoked response BOLD data. However, to analyze clinical data generated using a repeated measures experimental design, the model has been extended to handle multivariate time series data and demonstrated on control and alcoholic subjects taken from data previously analyzed in the temporal domain. Analysis of BOLD data is typically carried out in the time domain where the data has a high temporal correlation. These analyses generally employ parametric models of the hemodynamic response function (HRF) where prewhitening of the data is attempted using autoregressive (AR) models for the noise. However, this data can be analyzed in the Fourier domain. Here, assumptions made on the noise structure are less restrictive, and hypothesis tests can be constructed based on voxel-specific nonparametric estimates of the hemodynamic transfer function (HRF in the Fourier domain). This is especially important for experimental designs involving multiple states (either stimulus or drug induced) that may alter the form of the response function.

Multifocal pigmented villonodular synovitis in a child. A case report.

PubMed

Kay, R M; Eckardt, J J; Mirra, J M

1996-01-01

Pigmented villonodular synovitis is a well-described disease that almost universally involves a single site. This is a report of an unusual case of multiple site involvement of pigmented villonodular synovitis in a child. In addition to multiple site involvement, the case is unusual for several reasons: asymmetric involvement, involvement of both upper and lower extremities, involvement of the pes anserine tendons, and the patient is an otherwise healthy child.

Stochastic determination of matrix determinants

NASA Astrophysics Data System (ADS)

Dorn, Sebastian; Enßlin, Torsten A.

2015-07-01

Matrix determinants play an important role in data analysis, in particular when Gaussian processes are involved. Due to currently exploding data volumes, linear operations—matrices—acting on the data are often not accessible directly but are only represented indirectly in form of a computer routine. Such a routine implements the transformation a data vector undergoes under matrix multiplication. While efficient probing routines to estimate a matrix's diagonal or trace, based solely on such computationally affordable matrix-vector multiplications, are well known and frequently used in signal inference, there is no stochastic estimate for its determinant. We introduce a probing method for the logarithm of a determinant of a linear operator. Our method rests upon a reformulation of the log-determinant by an integral representation and the transformation of the involved terms into stochastic expressions. This stochastic determinant determination enables large-size applications in Bayesian inference, in particular evidence calculations, model comparison, and posterior determination.

Stochastic determination of matrix determinants.

PubMed

Dorn, Sebastian; Ensslin, Torsten A

2015-07-01

Matrix determinants play an important role in data analysis, in particular when Gaussian processes are involved. Due to currently exploding data volumes, linear operations-matrices-acting on the data are often not accessible directly but are only represented indirectly in form of a computer routine. Such a routine implements the transformation a data vector undergoes under matrix multiplication. While efficient probing routines to estimate a matrix's diagonal or trace, based solely on such computationally affordable matrix-vector multiplications, are well known and frequently used in signal inference, there is no stochastic estimate for its determinant. We introduce a probing method for the logarithm of a determinant of a linear operator. Our method rests upon a reformulation of the log-determinant by an integral representation and the transformation of the involved terms into stochastic expressions. This stochastic determinant determination enables large-size applications in Bayesian inference, in particular evidence calculations, model comparison, and posterior determination.

On two diffusion neuronal models with multiplicative noise: The mean first-passage time properties

NASA Astrophysics Data System (ADS)

D'Onofrio, G.; Lansky, P.; Pirozzi, E.

2018-04-01

Two diffusion processes with multiplicative noise, able to model the changes in the neuronal membrane depolarization between two consecutive spikes of a single neuron, are considered and compared. The processes have the same deterministic part but different stochastic components. The differences in the state-dependent variabilities, their asymptotic distributions, and the properties of the first-passage time across a constant threshold are investigated. Closed form expressions for the mean of the first-passage time of both processes are derived and applied to determine the role played by the parameters involved in the model. It is shown that for some values of the input parameters, the higher variability, given by the second moment, does not imply shorter mean first-passage time. The reason for that can be found in the complete shape of the stationary distribution of the two processes. Applications outside neuroscience are also mentioned.

Explanation Constraint Programming for Model-based Diagnosis of Engineered Systems

NASA Technical Reports Server (NTRS)

Narasimhan, Sriram; Brownston, Lee; Burrows, Daniel

2004-01-01

We can expect to see an increase in the deployment of unmanned air and land vehicles for autonomous exploration of space. In order to maintain autonomous control of such systems, it is essential to track the current state of the system. When the system includes safety-critical components, failures or faults in the system must be diagnosed as quickly as possible, and their effects compensated for so that control and safety are maintained under a variety of fault conditions. The Livingstone fault diagnosis and recovery kernel and its temporal extension L2 are examples of model-based reasoning engines for health management. Livingstone has been shown to be effective, it is in demand, and it is being further developed. It was part of the successful Remote Agent demonstration on Deep Space One in 1999. It has been and is being utilized by several projects involving groups from various NASA centers, including the In Situ Propellant Production (ISPP) simulation at Kennedy Space Center, the X-34 and X-37 experimental reusable launch vehicle missions, Techsat-21, and advanced life support projects. Model-based and consistency-based diagnostic systems like Livingstone work only with discrete and finite domain models. When quantitative and continuous behaviors are involved, these are abstracted to discrete form using some mapping. This mapping from the quantitative domain to the qualitative domain is sometimes very involved and requires the design of highly sophisticated and complex monitors. We propose a diagnostic methodology that deals directly with quantitative models and behaviors, thereby mitigating the need for these sophisticated mappings. Our work brings together ideas from model-based diagnosis systems like Livingstone and concurrent constraint programming concepts. The system uses explanations derived from the propagation of quantitative constraints to generate conflicts. Fast conflict generation algorithms are used to generate and maintain multiple candidates whose consistency can be tracked across multiple time steps.

Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.

PubMed

Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study.

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

PubMed Central

Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. PMID:24415945

Lithological and Surface Geometry Joint Inversions Using Multi-Objective Global Optimization Methods

NASA Astrophysics Data System (ADS)

Lelièvre, Peter; Bijani, Rodrigo; Farquharson, Colin

2016-04-01

Geologists' interpretations about the Earth typically involve distinct rock units with contacts (interfaces) between them. In contrast, standard minimum-structure geophysical inversions are performed on meshes of space-filling cells (typically prisms or tetrahedra) and recover smoothly varying physical property distributions that are inconsistent with typical geological interpretations. There are several approaches through which mesh-based minimum-structure geophysical inversion can help recover models with some of the desired characteristics. However, a more effective strategy may be to consider two fundamentally different types of inversions: lithological and surface geometry inversions. A major advantage of these two inversion approaches is that joint inversion of multiple types of geophysical data is greatly simplified. In a lithological inversion, the subsurface is discretized into a mesh and each cell contains a particular rock type. A lithological model must be translated to a physical property model before geophysical data simulation. Each lithology may map to discrete property values or there may be some a priori probability density function associated with the mapping. Through this mapping, lithological inverse problems limit the parameter domain and consequently reduce the non-uniqueness from that presented by standard mesh-based inversions that allow physical property values on continuous ranges. Furthermore, joint inversion is greatly simplified because no additional mathematical coupling measure is required in the objective function to link multiple physical property models. In a surface geometry inversion, the model comprises wireframe surfaces representing contacts between rock units. This parameterization is then fully consistent with Earth models built by geologists, which in 3D typically comprise wireframe contact surfaces of tessellated triangles. As for the lithological case, the physical properties of the units lying between the contact surfaces are set to a priori values. The inversion is tasked with calculating the geometry of the contact surfaces instead of some piecewise distribution of properties in a mesh. Again, no coupling measure is required and joint inversion is simplified. Both of these inverse problems involve high nonlinearity and discontinuous or non-obtainable derivatives. They can also involve the existence of multiple minima. Hence, one can not apply the standard descent-based local minimization methods used to solve typical minimum-structure inversions. Instead, we are applying Pareto multi-objective global optimization (PMOGO) methods, which generate a suite of solutions that minimize multiple objectives (e.g. data misfits and regularization terms) in a Pareto-optimal sense. Providing a suite of models, as opposed to a single model that minimizes a weighted sum of objectives, allows a more complete assessment of the possibilities and avoids the often difficult choice of how to weight each objective. While there are definite advantages to PMOGO joint inversion approaches, the methods come with significantly increased computational requirements. We are researching various strategies to ameliorate these computational issues including parallelization and problem dimension reduction.

Improving Measures via Examining the Behavior of Distractors in Multiple-Choice Tests

PubMed Central

Sideridis, Georgios; Tsaousis, Ioannis; Al Harbi, Khaleel

2017-01-01

The purpose of the present article was to illustrate, using an example from a national assessment, the value from analyzing the behavior of distractors in measures that engage the multiple-choice format. A secondary purpose of the present article was to illustrate four remedial actions that can potentially improve the measurement of the construct(s) under study. Participants were 2,248 individuals who took a national examination of chemistry. The behavior of the distractors was analyzed by modeling their behavior within the Rasch model. Potentially informative distractors were (a) further modeled using the partial credit model, (b) split onto separate items and retested for model fit and parsimony, (c) combined to form a “super” item or testlet, and (d) reexamined after deleting low-ability individuals who likely guessed on those informative, albeit erroneous, distractors. Results indicated that all but the item split strategies were associated with better model fit compared with the original model. The best fitted model, however, involved modeling and crediting informative distractors via the partial credit model or eliminating the responses of low-ability individuals who likely guessed on informative distractors. The implications, advantages, and disadvantages of modeling informative distractors for measurement purposes are discussed. PMID:29795904

Multisource passive acoustic tracking: an application of random finite set data fusion

NASA Astrophysics Data System (ADS)

Ali, Andreas M.; Hudson, Ralph E.; Lorenzelli, Flavio; Yao, Kung

2010-04-01

Multisource passive acoustic tracking is useful in animal bio-behavioral study by replacing or enhancing human involvement during and after field data collection. Multiple simultaneous vocalizations are a common occurrence in a forest or a jungle, where many species are encountered. Given a set of nodes that are capable of producing multiple direction-of-arrivals (DOAs), such data needs to be combined into meaningful estimates. Random Finite Set provides the mathematical probabilistic model, which is suitable for analysis and optimal estimation algorithm synthesis. Then the proposed algorithm has been verified using a simulation and a controlled test experiment.

Growth models and the expected distribution of fluctuating asymmetry

USGS Publications Warehouse

Graham, John H.; Shimizu, Kunio; Emlen, John M.; Freeman, D. Carl; Merkel, John

2003-01-01

Multiplicative error accounts for much of the size-scaling and leptokurtosis in fluctuating asymmetry. It arises when growth involves the addition of tissue to that which is already present. Such errors are lognormally distributed. The distribution of the difference between two lognormal variates is leptokurtic. If those two variates are correlated, then the asymmetry variance will scale with size. Inert tissues typically exhibit additive error and have a gamma distribution. Although their asymmetry variance does not exhibit size-scaling, the distribution of the difference between two gamma variates is nevertheless leptokurtic. Measurement error is also additive, but has a normal distribution. Thus, the measurement of fluctuating asymmetry may involve the mixing of additive and multiplicative error. When errors are multiplicative, we recommend computing log E(l) − log E(r), the difference between the logarithms of the expected values of left and right sides, even when size-scaling is not obvious. If l and r are lognormally distributed, and measurement error is nil, the resulting distribution will be normal, and multiplicative error will not confound size-related changes in asymmetry. When errors are additive, such a transformation to remove size-scaling is unnecessary. Nevertheless, the distribution of l − r may still be leptokurtic.

Multiple-Strain Approach and Probabilistic Modeling of Consumer Habits in Quantitative Microbial Risk Assessment: A Quantitative Assessment of Exposure to Staphylococcal Enterotoxin A in Raw Milk.

PubMed

Crotta, Matteo; Rizzi, Rita; Varisco, Giorgio; Daminelli, Paolo; Cunico, Elena Cosciani; Luini, Mario; Graber, Hans Ulrich; Paterlini, Franco; Guitian, Javier

2016-03-01

Quantitative microbial risk assessment (QMRA) models are extensively applied to inform management of a broad range of food safety risks. Inevitably, QMRA modeling involves an element of simplification of the biological process of interest. Two features that are frequently simplified or disregarded are the pathogenicity of multiple strains of a single pathogen and consumer behavior at the household level. In this study, we developed a QMRA model with a multiple-strain approach and a consumer phase module (CPM) based on uncertainty distributions fitted from field data. We modeled exposure to staphylococcal enterotoxin A in raw milk in Lombardy; a specific enterotoxin production module was thus included. The model is adaptable and could be used to assess the risk related to other pathogens in raw milk as well as other staphylococcal enterotoxins. The multiplestrain approach, implemented as a multinomial process, allowed the inclusion of variability and uncertainty with regard to pathogenicity at the bacterial level. Data from 301 questionnaires submitted to raw milk consumers were used to obtain uncertainty distributions for the CPM. The distributions were modeled to be easily updatable with further data or evidence. The sources of uncertainty due to the multiple-strain approach and the CPM were identified, and their impact on the output was assessed by comparing specific scenarios to the baseline. When the distributions reflecting the uncertainty in consumer behavior were fixed to the 95th percentile, the risk of exposure increased up to 160 times. This reflects the importance of taking into consideration the diversity of consumers' habits at the household level and the impact that the lack of knowledge about variables in the CPM can have on the final QMRA estimates. The multiple-strain approach lends itself to use in other food matrices besides raw milk and allows the model to better capture the complexity of the real world and to be capable of geographical specificity.

Dynamic and impact contact mechanics of geologic materials: Grain-scale experiments and modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cole, David M.; Hopkins, Mark A.; Ketcham, Stephen A.

2013-06-18

High fidelity treatments of the generation and propagation of seismic waves in naturally occurring granular materials is becoming more practical given recent advancements in our ability to model complex particle shapes and their mechanical interaction. Of particular interest are the grain-scale processes that are activated by impact events and the characteristics of force transmission through grain contacts. To address this issue, we have developed a physics based approach that involves laboratory experiments to quantify the dynamic contact and impact behavior of granular materials and incorporation of the observed behavior indiscrete element models. The dynamic experiments do not involve particle damagemore » and emphasis is placed on measured values of contact stiffness and frictional loss. The normal stiffness observed in dynamic contact experiments at low frequencies (e.g., 10 Hz) are shown to be in good agreement with quasistatic experiments on quartz sand. The results of impact experiments - which involve moderate to extensive levels of particle damage - are presented for several types of naturally occurring granular materials (several quartz sands, magnesite and calcium carbonate ooids). Implementation of the experimental findings in discrete element models is discussed and the results of impact simulations involving up to 5 Multiplication-Sign 105 grains are presented.« less

A Factor Analytic Model of Drug-Related Behavior in Adolescence and Its Impact on Arrests at Multiple Stages of the Life Course

PubMed Central

2016-01-01

Objectives Recognizing the inherent variability of drug-related behaviors, this study develops an empirically-driven and holistic model of drug-related behavior during adolescence using factor analysis to simultaneously model multiple drug behaviors. Methods The factor analytic model uncovers latent dimensions of drug-related behaviors, rather than patterns of individuals. These latent dimensions are treated as empirical typologies which are then used to predict an individual’s number of arrests accrued at multiple phases of the life course. The data are robust enough to simultaneously capture drug behavior measures typically considered in isolation in the literature, and to allow for behavior to change and evolve over the period of adolescence. Results Results show that factor analysis is capable of developing highly descriptive patterns of drug offending, and that these patterns have great utility in predicting arrests. Results further demonstrate that while drug behavior patterns are predictive of arrests at the end of adolescence for both males and females, the impacts on arrests are longer lasting for females. Conclusions The various facets of drug behaviors have been a long-time concern of criminological research. However, the ability to model multiple behaviors simultaneously is often constrained by data that do not measure the constructs fully. Factor analysis is shown to be a useful technique for modeling adolescent drug involvement patterns in a way that accounts for the multitude and variability of possible behaviors, and in predicting future negative life outcomes, such as arrests. PMID:28435183

Determination of optimal self-drive tourism route using the orienteering problem method

NASA Astrophysics Data System (ADS)

Hashim, Zakiah; Ismail, Wan Rosmanira; Ahmad, Norfaieqah

2013-04-01

This paper was conducted to determine the optimal travel routes for self-drive tourism based on the allocation of time and expense by maximizing the amount of attraction scores assigned to each city involved. Self-drive tourism represents a type of tourism where tourists hire or travel by their own vehicle. It only involves a tourist destination which can be linked with a network of roads. Normally, the traveling salesman problem (TSP) and multiple traveling salesman problems (MTSP) method were used in the minimization problem such as determination the shortest time or distance traveled. This paper involved an alternative approach for maximization method which is maximize the attraction scores and tested on tourism data for ten cities in Kedah. A set of priority scores are used to set the attraction score at each city. The classical approach of the orienteering problem was used to determine the optimal travel route. This approach is extended to the team orienteering problem and the two methods were compared. These two models have been solved by using LINGO12.0 software. The results indicate that the model involving the team orienteering problem provides a more appropriate solution compared to the orienteering problem model.

Statistical mechanical model of coupled transcription from multiple promoters due to transcription factor titration

PubMed Central

Rydenfelt, Mattias; Cox, Robert Sidney; Garcia, Hernan; Phillips, Rob

2014-01-01

Transcription factors (TFs) with regulatory action at multiple promoter targets is the rule rather than the exception, with examples ranging from the cAMP receptor protein (CRP) in E. coli that regulates hundreds of different genes simultaneously to situations involving multiple copies of the same gene, such as plasmids, retrotransposons, or highly replicated viral DNA. When the number of TFs heavily exceeds the number of binding sites, TF binding to each promoter can be regarded as independent. However, when the number of TF molecules is comparable to the number of binding sites, TF titration will result in correlation (“promoter entanglement”) between transcription of different genes. We develop a statistical mechanical model which takes the TF titration effect into account and use it to predict both the level of gene expression for a general set of promoters and the resulting correlation in transcription rates of different genes. Our results show that the TF titration effect could be important for understanding gene expression in many regulatory settings. PMID:24580252

Estimating Interaction Effects With Incomplete Predictor Variables

PubMed Central

Enders, Craig K.; Baraldi, Amanda N.; Cham, Heining

2014-01-01

The existing missing data literature does not provide a clear prescription for estimating interaction effects with missing data, particularly when the interaction involves a pair of continuous variables. In this article, we describe maximum likelihood and multiple imputation procedures for this common analysis problem. We outline 3 latent variable model specifications for interaction analyses with missing data. These models apply procedures from the latent variable interaction literature to analyses with a single indicator per construct (e.g., a regression analysis with scale scores). We also discuss multiple imputation for interaction effects, emphasizing an approach that applies standard imputation procedures to the product of 2 raw score predictors. We thoroughly describe the process of probing interaction effects with maximum likelihood and multiple imputation. For both missing data handling techniques, we outline centering and transformation strategies that researchers can implement in popular software packages, and we use a series of real data analyses to illustrate these methods. Finally, we use computer simulations to evaluate the performance of the proposed techniques. PMID:24707955

Technical note: Simultaneous fully dynamic characterization of multiple input–output relationships in climate models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kravitz, Ben; MacMartin, Douglas G.; Rasch, Philip J.

We introduce system identification techniques to climate science wherein multiple dynamic input–output relationships can be simultaneously characterized in a single simulation. This method, involving multiple small perturbations (in space and time) of an input field while monitoring output fields to quantify responses, allows for identification of different timescales of climate response to forcing without substantially pushing the climate far away from a steady state. We use this technique to determine the steady-state responses of low cloud fraction and latent heat flux to heating perturbations over 22 regions spanning Earth's oceans. We show that the response characteristics are similar to thosemore » of step-change simulations, but in this new method the responses for 22 regions can be characterized simultaneously. Moreover, we can estimate the timescale over which the steady-state response emerges. The proposed methodology could be useful for a wide variety of purposes in climate science, including characterization of teleconnections and uncertainty quantification to identify the effects of climate model tuning parameters.« less

Mass media in health promotion: an analysis using an extended information-processing model.

PubMed

Flay, B R; DiTecco, D; Schlegel, R P

1980-01-01

The information-processing model of the attitude and behavior change process was critically examined and extended from six to 12 levels for a better analysis of change due to mass media campaigns. Findings from social psychology and communications research, and from evaluations of mass media health promotion programs, were reviewed to determine how source, message, channel, receiver, and destination variables affect each of the levels of change of major interest (knowledge, beliefs, attitudes, intentions and behavior). Factors found to most likely induce permanent attitude and behavior change (most important in health promotion) were: presentation and repetition over long time periods, via multiple sources, at different times (including "prime" or high-exposure times), by multiple sources, in novel and involving ways, with appeals to multiple motives, development of social support, and provisions of appropriate behavioral skills, alternatives, and reinforcement (preferably in ways that get the active participation of the audience). Suggestions for evaluation of mass media programs that take account of this complexity were advanced.

Technical note: Simultaneous fully dynamic characterization of multiple input–output relationships in climate models

DOE PAGES

Kravitz, Ben; MacMartin, Douglas G.; Rasch, Philip J.; ...

2017-02-17

We introduce system identification techniques to climate science wherein multiple dynamic input–output relationships can be simultaneously characterized in a single simulation. This method, involving multiple small perturbations (in space and time) of an input field while monitoring output fields to quantify responses, allows for identification of different timescales of climate response to forcing without substantially pushing the climate far away from a steady state. We use this technique to determine the steady-state responses of low cloud fraction and latent heat flux to heating perturbations over 22 regions spanning Earth's oceans. We show that the response characteristics are similar to thosemore » of step-change simulations, but in this new method the responses for 22 regions can be characterized simultaneously. Moreover, we can estimate the timescale over which the steady-state response emerges. The proposed methodology could be useful for a wide variety of purposes in climate science, including characterization of teleconnections and uncertainty quantification to identify the effects of climate model tuning parameters.« less

Sudden multiple fractures in a patient with sarcoidosis in multiple organs.

PubMed

Sada, Mitsuru; Saraya, Takeshi; Ishii, Haruyuki; Goto, Hajime

2014-04-07

A 30-year-old man who incidentally fractured his right olecranon and other multiple phalanges was admitted to our hospital. He had a 2-year history of uveitis and bilateral hilar lymphadenopathy (BHL), and pulmonary sarcoidosis was diagnosed from transbronchial lung biopsy. Right elbow arthrodesis was performed, and biopsied specimens showed non-caseating epithelioid cell granuloma, suggesting osseous sarcoidosis. He was discharged uneventfully without further treatment, but BHL had progressed with the appearance of lung parenchymal lesions 3 months later. At that time, involvement of other organs was also noted on Gallium-67 scintigraphy, showing accumulations in BHL, axillary and inguinal lymph nodes, enlarged liver and spleen and subcutaneous areas. After initiation of steroid therapy, multiple organ involvement improved, and no further bone involvement has been recognised to date. Osseous sarcoidosis complicated by bone fracture is an extremely rare presentation, but should be considered in patients with sarcoidosis, especially when multiple organs are involved.

Editorial: Introduction to the Special Section on Causal Inference in Cross Sectional and Longitudinal Mediational Models

PubMed Central

West, Stephen G.

2016-01-01

Psychologists have long had interest in the processes through which antecedent variables produce their effects on the outcomes of ultimate interest (e.g., Wood-worth's Stimulus-Organism-Response model). Models involving such meditational processes have characterized many of the important psychological theories of the 20th century and continue to the present day. However, it was not until Judd and Kenny (1981) and Baron and Kenny (1986) combined ideas from experimental design and structural equation modeling that statistical methods for directly testing such models, now known as mediation analysis, began to be developed. Methodologists have improved these statistical methods, developing new, more efficient estimators for mediated effects. They have also extended mediation analysis to multilevel data structures, models involving multiple mediators, models in which interactions occur, and an array of noncontinuous outcome measures (see MacKinnon, 2008). This work nicely maps on to key questions of applied researchers and has led to an outpouring of research testing meditational models (As of August, 2011, Baron and Kenny's article has had over 24,000 citations according to Google Scholar). PMID:26736046

Models of Temporal Discounting 1937-2000: An Interdisciplinary Exchange between Economics and Psychology.

PubMed

Grüne-Yanoff, Till

2015-12-01

Today's models of temporal discounting are the result of multiple interdisciplinary exchanges between psychology and economics. Although these exchanges did not result in an integrated discipline, they had important effects on all disciplines involved. The paper describes these exchanges from the 1930s onwards, focusing on two episodes in particular: an attempted synthesis by psychiatrist George Ainslie and others in the 1970s; and the attempted application of this new discounting model by a generation of economists and psychologists in the 1980s, which ultimately ended in the diversity of measurements disappointment. I draw four main conclusions. First, multiple notions of temporal discounting must be conceptually distinguished. Second, behavioral economics is not an integration or unification of psychology and economics. Third, the analysis identifies some central disciplinary markers that distinguish modeling strategies in economics and psychology. Finally, it offers a case of interdisciplinary success that does not fit the currently dominant account of interdisciplinarity as integration.

Longitudinal Trajectories of Parental Involvement in Type 1 Diabetes and Adolescents’ Adherence

PubMed Central

King, Pamela S.; Berg, Cynthia A.; Butner, Jonathan; Butler, Jorie M.; Wiebe, Deborah J.

2016-01-01

Objective The purpose of this study was to examine longitudinal trajectories of parental involvement and adolescent adherence to the Type 1 diabetes regimen, to determine whether changes in multiple facets of parental involvement over time predicted subsequent changes in adolescents’ adherence, and to examine whether adolescent self-efficacy mediated the effect of parental involvement on adherence. Method Two hundred fifty-two adolescents (M age = 12.49 years, SD = 1.53; 53.6% females) diagnosed with Type 1 diabetes mellitus, their mothers, and 188 fathers were enrolled in a 2.5-year longitudinal study. Across 5 time points, up to 252 adolescents and their parents completed measures of adherence, parental involvement (diabetes monitoring, behavioral involvement in diabetes management, and acceptance), and adolescent diabetes self-efficacy. Results Using multilevel modeling, analyses indicated significant average declines over time in adherence and most indicators of parental involvement. Lagged multilevel models indicated that declines in mothers’ and fathers’ acceptance and diabetes monitoring predicted subsequent declines in adolescents’ adherence. Additional analyses revealed that longitudinal associations between both maternal acceptance and diabetes monitoring and subsequent adolescent adherence were mediated by adolescents’ self-efficacy. Conclusions Results of this study, which were largely consistent across reporters, highlight the importance of maintaining parental involvement in diabetes across adolescence and suggest that parental involvement is beneficial for adolescents’ adherence, in part, because it contributes to higher self-efficacy for diabetes management among adolescents. PMID:23795709

Overlapping Networks Engaged during Spoken Language Production and Its Cognitive Control

PubMed Central

Wise, Richard J.S.; Mehta, Amrish; Leech, Robert

2014-01-01

Spoken language production is a complex brain function that relies on large-scale networks. These include domain-specific networks that mediate language-specific processes, as well as domain-general networks mediating top-down and bottom-up attentional control. Language control is thought to involve a left-lateralized fronto-temporal-parietal (FTP) system. However, these regions do not always activate for language tasks and similar regions have been implicated in nonlinguistic cognitive processes. These inconsistent findings suggest that either the left FTP is involved in multidomain cognitive control or that there are multiple spatially overlapping FTP systems. We present evidence from an fMRI study using multivariate analysis to identify spatiotemporal networks involved in spoken language production in humans. We compared spoken language production (Speech) with multiple baselines, counting (Count), nonverbal decision (Decision), and “rest,” to pull apart the multiple partially overlapping networks that are involved in speech production. A left-lateralized FTP network was activated during Speech and deactivated during Count and nonverbal Decision trials, implicating it in cognitive control specific to sentential spoken language production. A mirror right-lateralized FTP network was activated in the Count and Decision trials, but not Speech. Importantly, a second overlapping left FTP network showed relative deactivation in Speech. These three networks, with distinct time courses, overlapped in the left parietal lobe. Contrary to the standard model of the left FTP as being dominant for speech, we revealed a more complex pattern within the left FTP, including at least two left FTP networks with competing functional roles, only one of which was activated in speech production. PMID:24966373

Overlapping networks engaged during spoken language production and its cognitive control.

PubMed

Geranmayeh, Fatemeh; Wise, Richard J S; Mehta, Amrish; Leech, Robert

2014-06-25

Spoken language production is a complex brain function that relies on large-scale networks. These include domain-specific networks that mediate language-specific processes, as well as domain-general networks mediating top-down and bottom-up attentional control. Language control is thought to involve a left-lateralized fronto-temporal-parietal (FTP) system. However, these regions do not always activate for language tasks and similar regions have been implicated in nonlinguistic cognitive processes. These inconsistent findings suggest that either the left FTP is involved in multidomain cognitive control or that there are multiple spatially overlapping FTP systems. We present evidence from an fMRI study using multivariate analysis to identify spatiotemporal networks involved in spoken language production in humans. We compared spoken language production (Speech) with multiple baselines, counting (Count), nonverbal decision (Decision), and "rest," to pull apart the multiple partially overlapping networks that are involved in speech production. A left-lateralized FTP network was activated during Speech and deactivated during Count and nonverbal Decision trials, implicating it in cognitive control specific to sentential spoken language production. A mirror right-lateralized FTP network was activated in the Count and Decision trials, but not Speech. Importantly, a second overlapping left FTP network showed relative deactivation in Speech. These three networks, with distinct time courses, overlapped in the left parietal lobe. Contrary to the standard model of the left FTP as being dominant for speech, we revealed a more complex pattern within the left FTP, including at least two left FTP networks with competing functional roles, only one of which was activated in speech production. Copyright © 2014 Geranmayeh et al.

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages.

PubMed

Kim, Yoonsang; Choi, Young-Ku; Emery, Sherry

2013-08-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods' performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages-SAS GLIMMIX Laplace and SuperMix Gaussian quadrature-perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes.

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages

PubMed Central

Kim, Yoonsang; Emery, Sherry

2013-01-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods’ performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages—SAS GLIMMIX Laplace and SuperMix Gaussian quadrature—perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes. PMID:24288415

Mixed linear-non-linear inversion of crustal deformation data: Bayesian inference of model, weighting and regularization parameters

NASA Astrophysics Data System (ADS)

Fukuda, Jun'ichi; Johnson, Kaj M.

2010-06-01

We present a unified theoretical framework and solution method for probabilistic, Bayesian inversions of crustal deformation data. The inversions involve multiple data sets with unknown relative weights, model parameters that are related linearly or non-linearly through theoretic models to observations, prior information on model parameters and regularization priors to stabilize underdetermined problems. To efficiently handle non-linear inversions in which some of the model parameters are linearly related to the observations, this method combines both analytical least-squares solutions and a Monte Carlo sampling technique. In this method, model parameters that are linearly and non-linearly related to observations, relative weights of multiple data sets and relative weights of prior information and regularization priors are determined in a unified Bayesian framework. In this paper, we define the mixed linear-non-linear inverse problem, outline the theoretical basis for the method, provide a step-by-step algorithm for the inversion, validate the inversion method using synthetic data and apply the method to two real data sets. We apply the method to inversions of multiple geodetic data sets with unknown relative data weights for interseismic fault slip and locking depth. We also apply the method to the problem of estimating the spatial distribution of coseismic slip on faults with unknown fault geometry, relative data weights and smoothing regularization weight.

AgMIP: Next Generation Models and Assessments

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2014-12-01

Next steps in developing next-generation crop models fall into several categories: significant improvements in simulation of important crop processes and responses to stress; extension from simplified crop models to complex cropping systems models; and scaling up from site-based models to landscape, national, continental, and global scales. Crop processes that require major leaps in understanding and simulation in order to narrow uncertainties around how crops will respond to changing atmospheric conditions include genetics; carbon, temperature, water, and nitrogen; ozone; and nutrition. The field of crop modeling has been built on a single crop-by-crop approach. It is now time to create a new paradigm, moving from 'crop' to 'cropping system.' A first step is to set up the simulation technology so that modelers can rapidly incorporate multiple crops within fields, and multiple crops over time. Then the response of these more complex cropping systems can be tested under different sustainable intensification management strategies utilizing the updated simulation environments. Model improvements for diseases, pests, and weeds include developing process-based models for important diseases, frameworks for coupling air-borne diseases to crop models, gathering significantly more data on crop impacts, and enabling the evaluation of pest management strategies. Most smallholder farming in the world involves integrated crop-livestock systems that cannot be represented by crop modeling alone. Thus, next-generation cropping system models need to include key linkages to livestock. Livestock linkages to be incorporated include growth and productivity models for grasslands and rangelands as well as the usual annual crops. There are several approaches for scaling up, including use of gridded models and development of simpler quasi-empirical models for landscape-scale analysis. On the assessment side, AgMIP is leading a community process for coordinated contributions to IPCC AR6 that involves the key modeling groups from around the world including North America, Europe, South America, Sub-Saharan Africa, South Asia, East Asia, and Australia and Oceania. This community process will lead to mutually agreed protocols for coordinated global and regional assessments.

Identifying Opportunities for Decision Support Systems in Support of Regional Resource Use Planning: An Approach Through Soft Systems Methodology.

PubMed

Zhu; Dale

2000-10-01

/ Regional resource use planning relies on key regional stakeholder groups using and having equitable access to appropriate social, economic, and environmental information and assessment tools. Decision support systems (DSS) can improve stakeholder access to such information and analysis tools. Regional resource use planning, however, is a complex process involving multiple issues, multiple assessment criteria, multiple stakeholders, and multiple values. There is a need for an approach to DSS development that can assist in understanding and modeling complex problem situations in regional resource use so that areas where DSSs could provide effective support can be identified, and the user requirements can be well established. This paper presents an approach based on the soft systems methodology for identifying DSS opportunities for regional resource use planning, taking the Central Highlands Region of Queensland, Australia, as a case study.

A comparative study of Conroy and Monte Carlo methods applied to multiple quadratures and multiple scattering

NASA Technical Reports Server (NTRS)

Deepak, A.; Fluellen, A.

1978-01-01

An efficient numerical method of multiple quadratures, the Conroy method, is applied to the problem of computing multiple scattering contributions in the radiative transfer through realistic planetary atmospheres. A brief error analysis of the method is given and comparisons are drawn with the more familiar Monte Carlo method. Both methods are stochastic problem-solving models of a physical or mathematical process and utilize the sampling scheme for points distributed over a definite region. In the Monte Carlo scheme the sample points are distributed randomly over the integration region. In the Conroy method, the sample points are distributed systematically, such that the point distribution forms a unique, closed, symmetrical pattern which effectively fills the region of the multidimensional integration. The methods are illustrated by two simple examples: one, of multidimensional integration involving two independent variables, and the other, of computing the second order scattering contribution to the sky radiance.

Children's representations of multiple family relationships: organizational structure and development in early childhood.

PubMed

Schermerhorn, Alice C; Cummings, E Mark; Davies, Patrick T

2008-02-01

The authors examine mutual family influence processes at the level of children's representations of multiple family relationships, as well as the structure of those representations. From a community sample with 3 waves, each spaced 1 year apart, kindergarten-age children (105 boys and 127 girls) completed a story-stem completion task, tapping representations of multiple family relationships. Structural equation modeling with autoregressive controls indicated that representational processes involving different family relationships were interrelated over time, including links between children's representations of marital conflict and reactions to conflict, between representations of security about marital conflict and parent-child relationships, and between representations of security in father-child and mother-child relationships. Mixed support was found for notions of increasing stability in representations during this developmental period. Results are discussed in terms of notions of transactional family dynamics, including family-wide perspectives on mutual influence processes attributable to multiple family relationships.

Multiple meanings of "gift" and its value for organ donation.

PubMed

Shaw, Rhonda M; Webb, Robert

2015-05-01

The "gift of life" metaphor is used to promote organ donation where commercialization is prohibited. In this article, we explore how multiple parties involved in organ transfer procedures think of gift terminology by drawing on interview data with transplantation specialists, organ transplant recipients, living directed donors and living nondirected donors. The interviews took place across New Zealand between October 2008 and May 2012, in participants' homes and hospital workplaces. The interviews were transcribed verbatim, coded manually, and thematically analyzed. Although gift language is often viewed as clear-cut, the gift trope has multiple meanings for different constituent and cultural groups, ranging from positive descriptors to obscuring and romanticizing the complexities of transplantation processes. To account for these multiple perspectives, we suggest new ethical models to capture the nuanced phenomenon of organ transfer in ways that recognize the full range of donation and reception experiences. © The Author(s) 2014.

Multiple cranial neuropathy: a common diagnostic problem.

PubMed

Garg, R K; Karak, B

1999-10-01

Syndrome of multiple cranial palsies is a common clinical problem routinely encountered in neurological practice. Anatomical patterns of cranial nerves involvement help in localizing the lesion. Various infections, malignant neoplasms and autoimmune vasculitis are common disorders leading to various syndromes of multiple cranial nerve palsies. A large number of diffuse neurological disorders (e.g. Gullian-Barre syndrome, myopathies) may also present with syndrome of multiple cranial nerve palsies. Despite extensive biochemical and radiological work-up the accurate diagnosis may not be established. Few such patients represent "idiopathic" variety of multiple cranial nerve involvement and show good response to corticosteroids. Widespread and sequential involvements of cranial nerves frequently suggest possibility of malignant infiltration of meninges, however, confirmation of diagnosis may not be possible before autopsy.

More Than Just Accuracy: A Novel Method to Incorporate Multiple Test Attributes in Evaluating Diagnostic Tests Including Point of Care Tests.

PubMed

Thompson, Matthew; Weigl, Bernhard; Fitzpatrick, Annette; Ide, Nicole

2016-01-01

Current frameworks for evaluating diagnostic tests are constrained by a focus on diagnostic accuracy, and assume that all aspects of the testing process and test attributes are discrete and equally important. Determining the balance between the benefits and harms associated with new or existing tests has been overlooked. Yet, this is critically important information for stakeholders involved in developing, testing, and implementing tests. This is particularly important for point of care tests (POCTs) where tradeoffs exist between numerous aspects of the testing process and test attributes. We developed a new model that multiple stakeholders (e.g., clinicians, patients, researchers, test developers, industry, regulators, and health care funders) can use to visualize the multiple attributes of tests, the interactions that occur between these attributes, and their impacts on health outcomes. We use multiple examples to illustrate interactions between test attributes (test availability, test experience, and test results) and outcomes, including several POCTs. The model could be used to prioritize research and development efforts, and inform regulatory submissions for new diagnostics. It could potentially provide a way to incorporate the relative weights that various subgroups or clinical settings might place on different test attributes. Our model provides a novel way that multiple stakeholders can use to visualize test attributes, their interactions, and impacts on individual and population outcomes. We anticipate that this will facilitate more informed decision making around diagnostic tests.

Race, gender, class, and sexual orientation: intersecting axes of inequality and self-rated health in Canada

PubMed Central

2011-01-01

Background Intersectionality theory, a way of understanding social inequalities by race, gender, class, and sexuality that emphasizes their mutually constitutive natures, possesses potential to uncover and explicate previously unknown health inequalities. In this paper, the intersectionality principles of "directionality," "simultaneity," "multiplicativity," and "multiple jeopardy" are applied to inequalities in self-rated health by race, gender, class, and sexual orientation in a Canadian sample. Methods The Canadian Community Health Survey 2.1 (N = 90,310) provided nationally representative data that enabled binary logistic regression modeling on fair/poor self-rated health in two analytical stages. The additive stage involved regressing self-rated health on race, gender, class, and sexual orientation singly and then as a set. The intersectional stage involved consideration of two-way and three-way interaction terms between the inequality variables added to the full additive model created in the previous stage. Results From an additive perspective, poor self-rated health outcomes were reported by respondents claiming Aboriginal, Asian, or South Asian affiliations, lower class respondents, and bisexual respondents. However, each axis of inequality interacted significantly with at least one other: multiple jeopardy pertained to poor homosexuals and to South Asian women who were at unexpectedly high risks of fair/poor self-rated health and mitigating effects were experienced by poor women and by poor Asian Canadians who were less likely than expected to report fair/poor health. Conclusions Although a variety of intersections between race, gender, class, and sexual orientation were associated with especially high risks of fair/poor self-rated health, they were not all consistent with the predictions of intersectionality theory. I conclude that an intersectionality theory well suited for explicating health inequalities in Canada should be capable of accommodating axis intersections of multiple kinds and qualities. PMID:21241506

The Contributions of Working Memory and Executive Functioning to Problem Representation and Solution Generation in Algebraic Word Problems

ERIC Educational Resources Information Center

Lee, Kerry; Ng, Ee Lynn; Ng, Swee Fong

2009-01-01

Solving algebraic word problems involves multiple cognitive phases. The authors used a multitask approach to examine the extent to which working memory and executive functioning are associated with generating problem models and producing solutions. They tested 255 11-year-olds on working memory (Counting Recall, Letter Memory, and Keep Track),…

Therapeutic Guidance for Infants and Families: Using Multi-Family Groups as an Extension of Child-Parent Psychotherapy

ERIC Educational Resources Information Center

Frame, Laura; Ivins, Barbara; Wong, Lynette; Cantrell, Sally

2015-01-01

Treatment of very young children in foster care involves the complex dynamics of a child's trauma history, multiple relationships, and caregivers' and providers' feelings about working with the child welfare system. Through the story of a toddler removed from his parents and placed in foster care, the authors illustrate a model of combined group…

Current and future molecular approaches to investigate the white pine blister rust pathosystem

Treesearch

B. A. Richardson; A. K. M. Ekramoddoulah; J.-J. Liu; M.-S. Kim; N. B. Klopfenstein

2010-01-01

Molecular genetics is proving to be especially useful for addressing a wide variety of research and management questions on the white pine blister rust pathosystem. White pine blister rust, caused by Cronartium ribicola, is an ideal model for studying biogeography, genetics, and evolution because: (1) it involves an introduced pathogen; (2) it includes multiple primary...

Positive Youth Development in a School-Based Setting: A Study of the Los Angeles Police Academy Magnet School Program. PRGS Dissertation

ERIC Educational Resources Information Center

Maloney, Shannon

2014-01-01

Positive youth development (PYD) orients youth toward pro-social and forward-looking behavior through programs that emphasize youth empowerment and involvement, focus on skill development and character building, incorporate community collaboration at multiple levels, and include positive adult role models and mentors that interact with youth in…

Glycogen synthase kinase 3: more than a namesake.

PubMed

Rayasam, Geetha Vani; Tulasi, Vamshi Krishna; Sodhi, Reena; Davis, Joseph Alex; Ray, Abhijit

2009-03-01

Glycogen synthase kinase 3 (GSK3), a constitutively acting multi-functional serine threonine kinase is involved in diverse physiological pathways ranging from metabolism, cell cycle, gene expression, development and oncogenesis to neuroprotection. These diverse multiple functions attributed to GSK3 can be explained by variety of substrates like glycogen synthase, tau protein and beta catenin that are phosphorylated leading to their inactivation. GSK3 has been implicated in various diseases such as diabetes, inflammation, cancer, Alzheimer's and bipolar disorder. GSK3 negatively regulates insulin-mediated glycogen synthesis and glucose homeostasis, and increased expression and activity of GSK3 has been reported in type II diabetics and obese animal models. Consequently, inhibitors of GSK3 have been demonstrated to have anti-diabetic effects in vitro and in animal models. However, inhibition of GSK3 poses a challenge as achieving selectivity of an over achieving kinase involved in various pathways with multiple substrates may lead to side effects and toxicity. The primary concern is developing inhibitors of GSK3 that are anti-diabetic but do not lead to up-regulation of oncogenes. The focus of this review is the recent advances and the challenges surrounding GSK3 as an anti-diabetic therapeutic target.

Monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM): novel biological insights and development of early treatment strategies

PubMed Central

Kristinsson, Sigurdur Y.

2011-01-01

Monoclonal gammopathy of unknown significance (MGUS) and smoldering multiple myeloma (SMM) are asymptomatic plasma cell dyscrasias, with a propensity to progress to symptomatic MM. In recent years there have been improvements in risk stratification models (involving molecular markers) of both disorders, which have led to better understanding of the biology and probability of progression of MGUS and SMM. In the context of numerous molecular events and heterogeneous risk of progression, developing individualized risk profiles for patients with MGUS and SMM represents an ongoing challenge that has to be addressed by prospective clinical monitoring and extensive correlative science. In this review we discuss the current standard of care of patients with MGUS and SMM, the use of risk models, including flow cytometry and free-light chain analyses, for predicting risk of progression. Emerging evidence from molecular studies on MGUS and SMM, involving cytogenetics, gene-expression profiling, and microRNA as well as molecular imaging is described. Finally, future directions for improving individualized management of MGUS and SMM patients, as well as the potential for developing early treatment strategies designed to delay and prevent development of MM are discussed. PMID:21441462

Monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM): novel biological insights and development of early treatment strategies.

PubMed

Korde, Neha; Kristinsson, Sigurdur Y; Landgren, Ola

2011-05-26

Monoclonal gammopathy of unknown significance (MGUS) and smoldering multiple myeloma (SMM) are asymptomatic plasma cell dyscrasias, with a propensity to progress to symptomatic MM. In recent years there have been improvements in risk stratification models (involving molecular markers) of both disorders, which have led to better understanding of the biology and probability of progression of MGUS and SMM. In the context of numerous molecular events and heterogeneous risk of progression, developing individualized risk profiles for patients with MGUS and SMM represents an ongoing challenge that has to be addressed by prospective clinical monitoring and extensive correlative science. In this review we discuss the current standard of care of patients with MGUS and SMM, the use of risk models, including flow cytometry and free-light chain analyses, for predicting risk of progression. Emerging evidence from molecular studies on MGUS and SMM, involving cytogenetics, gene-expression profiling, and microRNA as well as molecular imaging is described. Finally, future directions for improving individualized management of MGUS and SMM patients, as well as the potential for developing early treatment strategies designed to delay and prevent development of MM are discussed.

Interleukin 35 and Hepatocyte Growth Factor; as a novel combined immune gene therapy for Multiple Sclerosis disease.

PubMed

Moghadam, Samira; Erfanmanesh, Maryam; Esmaeilzadeh, Abdolreza

2017-11-01

An autoimmune demyelination disease of the Central Nervous System, Multiple Sclerosis, is a chronic inflammation which mostly involves young adults. Suffering people face functional loss with a severe pain. Most current MS treatments are focused on the immune response suppression. Approved drugs suppress the inflammatory process, but factually, there is no definite cure for Multiple Sclerosis. Recently developed knowledge has demonstrated that gene and cell therapy as a hopeful approach in tissue regeneration. The authors propose a novel combined immune gene therapy for Multiple Sclerosis treatment using anti-inflammatory and remyelination of Interleukine-35 and Hepatocyte Growth Factor properties, respectively. In this hypothesis Interleukine-35 and Hepatocyte Growth Factor introduce to Mesenchymal Stem Cells of EAE mouse model via an adenovirus based vector. It is expected that Interleukine-35 and Hepatocyte Growth Factor genes expressed from MSCs could effectively perform in immunotherapy of Multiple Sclerosis. Copyright © 2017. Published by Elsevier Ltd.

Multiple testing and power calculations in genetic association studies.

PubMed

So, Hon-Cheong; Sham, Pak C

2011-01-01

Modern genetic association studies typically involve multiple single-nucleotide polymorphisms (SNPs) and/or multiple genes. With the development of high-throughput genotyping technologies and the reduction in genotyping cost, investigators can now assay up to a million SNPs for direct or indirect association with disease phenotypes. In addition, some studies involve multiple disease or related phenotypes and use multiple methods of statistical analysis. The combination of multiple genetic loci, multiple phenotypes, and multiple methods of evaluating associations between genotype and phenotype means that modern genetic studies often involve the testing of an enormous number of hypotheses. When multiple hypothesis tests are performed in a study, there is a risk of inflation of the type I error rate (i.e., the chance of falsely claiming an association when there is none). Several methods for multiple-testing correction are in popular use, and they all have strengths and weaknesses. Because no single method is universally adopted or always appropriate, it is important to understand the principles, strengths, and weaknesses of the methods so that they can be applied appropriately in practice. In this article, we review the three principle methods for multiple-testing correction and provide guidance for calculating statistical power.

A quantitative systems physiology model of renal function and blood pressure regulation: Model description.

PubMed

Hallow, K M; Gebremichael, Y

2017-06-01

Renal function plays a central role in cardiovascular, kidney, and multiple other diseases, and many existing and novel therapies act through renal mechanisms. Even with decades of accumulated knowledge of renal physiology, pathophysiology, and pharmacology, the dynamics of renal function remain difficult to understand and predict, often resulting in unexpected or counterintuitive therapy responses. Quantitative systems pharmacology modeling of renal function integrates this accumulated knowledge into a quantitative framework, allowing evaluation of competing hypotheses, identification of knowledge gaps, and generation of new experimentally testable hypotheses. Here we present a model of renal physiology and control mechanisms involved in maintaining sodium and water homeostasis. This model represents the core renal physiological processes involved in many research questions in drug development. The model runs in R and the code is made available. In a companion article, we present a case study using the model to explore mechanisms and pharmacology of salt-sensitive hypertension. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Drosophila nemo is an essential gene involved in the regulation of programmed cell death.

PubMed

Mirkovic, Ivana; Charish, Kristi; Gorski, Sharon M; McKnight, Kristen; Verheyen, Esther M

2002-11-01

Nemo-like kinases define a novel family of serine/threonine kinases that are involved in integrating multiple signaling pathways. They are conserved regulators of Wnt/Wingless pathways, which may coordinate Wnt with TGFbeta-mediated signaling. Drosophila nemo was identified through its involvement in epithelial planar polarity, a process regulated by a non-canonical Wnt pathway. We have previously found that ectopic expression of Nemo using the Gal4-UAS system resulted in embryonic lethality associated with defects in patterning and head development. In this study we present our analyses of the phenotypes of germline clone-derived embryos. We observe lethality associated with head defects and reduction of programmed cell death and conclude that nmo is an essential gene. We also present data showing that nmo is involved in regulating apoptosis during eye development, based on both loss of function phenotypes and on genetic interactions with the pro-apoptotic gene reaper. Finally, we present genetic data from the adult wing that suggest the activity of ectopically expressed Nemo can be modulated by Jun N-terminal kinase (JNK) signaling. Such an observation supports the model that there is cross-talk between Wnt, TGFbeta and JNK signaling at multiple stages of development. Copyright 2002 Elsevier Science Ireland Ltd.

An Ontology for Modeling Complex Inter-relational Organizations

NASA Astrophysics Data System (ADS)

Wautelet, Yves; Neysen, Nicolas; Kolp, Manuel

This paper presents an ontology for organizational modeling through multiple complementary aspects. The primary goal of the ontology is to dispose of an adequate set of related concepts for studying complex organizations involved in a lot of relationships at the same time. In this paper, we define complex organizations as networked organizations involved in a market eco-system that are playing several roles simultaneously. In such a context, traditional approaches focus on the macro analytic level of transactions; this is supplemented here with a micro analytic study of the actors' rationale. At first, the paper overviews enterprise ontologies literature to position our proposal and exposes its contributions and limitations. The ontology is then brought to an advanced level of formalization: a meta-model in the form of a UML class diagram allows to overview the ontology concepts and their relationships which are formally defined. Finally, the paper presents the case study on which the ontology has been validated.

Quantitative prediction of solvation free energy in octanol of organic compounds.

PubMed

Delgado, Eduardo J; Jaña, Gonzalo A

2009-03-01

The free energy of solvation, DeltaGS0, in octanol of organic compounds is quantitatively predicted from the molecular structure. The model, involving only three molecular descriptors, is obtained by multiple linear regression analysis from a data set of 147 compounds containing diverse organic functions, namely, halogenated and non-halogenated alkanes, alkenes, alkynes, aromatics, alcohols, aldehydes, ketones, amines, ethers and esters; covering a DeltaGS0 range from about -50 to 0 kJ.mol(-1). The model predicts the free energy of solvation with a squared correlation coefficient of 0.93 and a standard deviation, 2.4 kJ.mol(-1), just marginally larger than the generally accepted value of experimental uncertainty. The involved molecular descriptors have definite physical meaning corresponding to the different intermolecular interactions occurring in the bulk liquid phase. The model is validated with an external set of 36 compounds not included in the training set.

Quantitative Prediction of Solvation Free Energy in Octanol of Organic Compounds

PubMed Central

Delgado, Eduardo J.; Jaña, Gonzalo A.

2009-01-01

The free energy of solvation, ΔGS0, in octanol of organic compunds is quantitatively predicted from the molecular structure. The model, involving only three molecular descriptors, is obtained by multiple linear regression analysis from a data set of 147 compounds containing diverse organic functions, namely, halogenated and non-halogenated alkanes, alkenes, alkynes, aromatics, alcohols, aldehydes, ketones, amines, ethers and esters; covering a ΔGS0 range from about −50 to 0 kJ·mol−1. The model predicts the free energy of solvation with a squared correlation coefficient of 0.93 and a standard deviation, 2.4 kJ·mol−1, just marginally larger than the generally accepted value of experimental uncertainty. The involved molecular descriptors have definite physical meaning corresponding to the different intermolecular interactions occurring in the bulk liquid phase. The model is validated with an external set of 36 compounds not included in the training set. PMID:19399236

Quantifying Recycling and Losses of Cr and Ni in Steel Throughout Multiple Life Cycles Using MaTrace-Alloy.

PubMed

Nakamura, Shinichiro; Kondo, Yasushi; Nakajima, Kenichi; Ohno, Hajime; Pauliuk, Stefan

2017-09-05

Alloying metals are indispensable ingredients of high quality alloy steel such as austenitic stainless steel, the cyclical use of which is vital for sustainable resource management. Under the current practice of recycling, however, different metals are likely to be mixed in an uncontrolled manner, resulting in function losses and dissipation of metals with distinctive functions, and in the contamination of recycled steels. The latter could result in dilution loss, if metal scrap needed dilution with virgin iron to reduce the contamination below critical levels. Management of these losses resulting from mixing in repeated recycling of metals requires tracking of metals over multiple life cycles of products with compositional details. A new model (MaTrace-alloy) was developed that tracks the fate of metals embodied in each of products over multiple life cycles of products, involving accumulation, discard, and recycling, with compositional details at the level of both alloys and products. The model was implemented for the flow of Cr and Ni in the Japanese steel cycle involving 27 steel species and 115 final products. It was found that, under a high level of scrap sorting, greater than 70% of the initial functionality of Cr and Ni could be retained over a period of 100 years, whereas under a poor level of sorting, it could plunge to less than 30%, demonstrating the relevance of waste management technology in circular economy policies.

Bone matrix, cellularity, and structural changes in a rat model with high-turnover osteoporosis induced by combined ovariectomy and a multiple-deficient diet.

PubMed

Govindarajan, Parameswari; Böcker, Wolfgang; El Khassawna, Thaqif; Kampschulte, Marian; Schlewitz, Gudrun; Huerter, Britta; Sommer, Ursula; Dürselen, Lutz; Ignatius, Anita; Bauer, Natali; Szalay, Gabor; Wenisch, Sabine; Lips, Katrin S; Schnettler, Reinhard; Langheinrich, Alexander; Heiss, Christian

2014-03-01

In estrogen-deficient, postmenopausal women, vitamin D and calcium deficiency increase osteoporotic fracture risk. Therefore, a new rat model of combined ovariectomy and multiple-deficient diet was established to mimic human postmenopausal osteoporotic conditions under nutrient deficiency. Sprague-Dawley rats were untreated (control), laparatomized (sham), or ovariectomized and received a deficient diet (OVX-Diet). Multiple analyses involving structure (micro-computed tomography and biomechanics), cellularity (osteoblasts and osteoclasts), bone matrix (mRNA expression and IHC), and mineralization were investigated for a detailed characterization of osteoporosis. The study involved long-term observation up to 14 months (M14) after laparotomy or after OVX-Diet, with intermediate time points at M3 and M12. OVX-Diet rats showed enhanced osteoblastogenesis and osteoclastogenesis. Bone matrix markers (biglycan, COL1A1, tenascin C, and fibronectin) and low-density lipoprotein-5 (bone mass marker) were down-regulated at M12 in OVX-Diet rats. However, up-regulation of matrix markers and existence of unmineralized osteoid were seen at M3 and M14. Osteoclast markers (matrix metallopeptidase 9 and cathepsin K) were up-regulated at M14. Micro-computed tomography and biomechanics confirmed bone fragility of OVX-Diet rats, and quantitative RT-PCR revealed a higher turnover rate in the humerus than in lumbar vertebrae, suggesting enhanced bone formation and resorption in OVX-Diet rats. Such bone remodeling caused disturbed bone mineralization and severe bone loss, as reported in patients with high-turnover, postmenopausal osteoporosis. Therefore, this rat model may serve as a suitable tool to evaluate osteoporotic drugs and new biomaterials or fracture implants. Copyright © 2014 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Search for supersymmetry in pp collisions at $$\\sqrt{s}$$=8 TeV in events with a single lepton, large jet multiplicity, and multiple b jets

DOE PAGES

Chatrchyan, Serguei

2014-04-18

Results are reported from a search for supersymmetry in pp collisions at a center-of-mass energy of 8 TeV, based on events with a single isolated lepton (electron or muon) and multiple jets, at least two of which are identified as b jets. The data sample corresponds to an integrated luminosity of 19.3 inverse femtobarns recorded by the CMS experiment at the LHC in 2012. The search is motivated by supersymmetric models that involve strong-production processes and cascade decays of new particles. The resulting final states contain multiple jets as well as missing transverse momentum from weakly interacting particles. The eventmore » yields, observed across several kinematic regions, are consistent with the expectations from standard model processes. Thus the results are interpreted in the context of simplified supersymmetric scenarios with pair production of gluinos, where each gluino decays to a top quark-antiquark pair and the lightest neutralino. For the case of decays via virtual top squarks, gluinos with a mass smaller than 1.26 TeV are excluded for low neutralino masses.« less

Modelling multiple sources of dissemination bias in meta-analysis.

PubMed

Bowden, Jack; Jackson, Dan; Thompson, Simon G

2010-03-30

Asymmetry in the funnel plot for a meta-analysis suggests the presence of dissemination bias. This may be caused by publication bias through the decisions of journal editors, by selective reporting of research results by authors or by a combination of both. Typically, study results that are statistically significant or have larger estimated effect sizes are more likely to appear in the published literature, hence giving a biased picture of the evidence-base. Previous statistical approaches for addressing dissemination bias have assumed only a single selection mechanism. Here we consider a more realistic scenario in which multiple dissemination processes, involving both the publishing authors and journals, are operating. In practical applications, the methods can be used to provide sensitivity analyses for the potential effects of multiple dissemination biases operating in meta-analysis.

Multiple-solution problems in a statistics classroom: an example

NASA Astrophysics Data System (ADS)

Chu, Chi Wing; Chan, Kevin L. T.; Chan, Wai-Sum; Kwong, Koon-Shing

2017-11-01

The mathematics education literature shows that encouraging students to develop multiple solutions for given problems has a positive effect on students' understanding and creativity. In this paper, we present an example of multiple-solution problems in statistics involving a set of non-traditional dice. In particular, we consider the exact probability mass distribution for the sum of face values. Four different ways of solving the problem are discussed. The solutions span various basic concepts in different mathematical disciplines (sample space in probability theory, the probability generating function in statistics, integer partition in basic combinatorics and individual risk model in actuarial science) and thus promotes upper undergraduate students' awareness of knowledge connections between their courses. All solutions of the example are implemented using the R statistical software package.

Patterns of evolution at the gametophytic self-incompatibility Sorbus aucuparia (Pyrinae) S pollen genes support the non-self recognition by multiple factors model

PubMed Central

Aguiar, Bruno; Vieira, Jorge; Cunha, Ana E.; Fonseca, Nuno A.; Reboiro-Jato, David; Reboiro-Jato, Miguel; Fdez-Riverola, Florentino; Raspé, Olivier; Vieira, Cristina P.

2013-01-01

S-RNase-based gametophytic self-incompatibility evolved once before the split of the Asteridae and Rosidae. In Prunus (tribe Amygdaloideae of Rosaceae), the self-incompatibility S-pollen is a single F-box gene that presents the expected evolutionary signatures. In Malus and Pyrus (subtribe Pyrinae of Rosaceae), however, clusters of F-box genes (called SFBBs) have been described that are expressed in pollen only and are linked to the S-RNase gene. Although polymorphic, SFBB genes present levels of diversity lower than those of the S-RNase gene. They have been suggested as putative S-pollen genes, in a system of non-self recognition by multiple factors. Subsets of allelic products of the different SFBB genes interact with non-self S-RNases, marking them for degradation, and allowing compatible pollinations. This study performed a detailed characterization of SFBB genes in Sorbus aucuparia (Pyrinae) to address three predictions of the non-self recognition by multiple factors model. As predicted, the number of SFBB genes was large to account for the many S-RNase specificities. Secondly, like the S-RNase gene, the SFBB genes were old. Thirdly, amino acids under positive selection—those that could be involved in specificity determination—were identified when intra-haplotype SFBB genes were analysed using codon models. Overall, the findings reported here support the non-self recognition by multiple factors model. PMID:23606363

An Optimization of Manufacturing Systems using a Feedback Control Scheduling Model

NASA Astrophysics Data System (ADS)

Ikome, John M.; Kanakana, Grace M.

2018-03-01

In complex production system that involves multiple process, unplanned disruption often turn to make the entire production system vulnerable to a number of problems which leads to customer’s dissatisfaction. However, this problem has been an ongoing problem that requires a research and methods to streamline the entire process or develop a model that will address it, in contrast to this, we have developed a feedback scheduling model that can minimize some of this problem and after a number of experiment, it shows that some of this problems can be eliminated if the correct remedial actions are implemented on time.

Efficient computation of the joint sample frequency spectra for multiple populations.

PubMed

Kamm, John A; Terhorst, Jonathan; Song, Yun S

2017-01-01

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity.

Efficient computation of the joint sample frequency spectra for multiple populations

PubMed Central

Kamm, John A.; Terhorst, Jonathan; Song, Yun S.

2016-01-01

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity. PMID:28239248

Multiple-try differential evolution adaptive Metropolis for efficient solution of highly parameterized models

NASA Astrophysics Data System (ADS)

Eric, L.; Vrugt, J. A.

2010-12-01

Spatially distributed hydrologic models potentially contain hundreds of parameters that need to be derived by calibration against a historical record of input-output data. The quality of this calibration strongly determines the predictive capability of the model and thus its usefulness for science-based decision making and forecasting. Unfortunately, high-dimensional optimization problems are typically difficult to solve. Here we present our recent developments to the Differential Evolution Adaptive Metropolis (DREAM) algorithm (Vrugt et al., 2009) to warrant efficient solution of high-dimensional parameter estimation problems. The algorithm samples from an archive of past states (Ter Braak and Vrugt, 2008), and uses multiple-try Metropolis sampling (Liu et al., 2000) to decrease the required burn-in time for each individual chain and increase efficiency of posterior sampling. This approach is hereafter referred to as MT-DREAM. We present results for 2 synthetic mathematical case studies, and 2 real-world examples involving from 10 to 240 parameters. Results for those cases show that our multiple-try sampler, MT-DREAM, can consistently find better solutions than other Bayesian MCMC methods. Moreover, MT-DREAM is admirably suited to be implemented and ran on a parallel machine and is therefore a powerful method for posterior inference.

Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

PubMed Central

Tsai, Yu-Shuen; Aguan, Kripamoy; Pal, Nikhil R.; Chung, I-Fang

2011-01-01

Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases. PMID:21909426

Numerically accurate computational techniques for optimal estimator analyses of multi-parameter models

NASA Astrophysics Data System (ADS)

Berger, Lukas; Kleinheinz, Konstantin; Attili, Antonio; Bisetti, Fabrizio; Pitsch, Heinz; Mueller, Michael E.

2018-05-01

Modelling unclosed terms in partial differential equations typically involves two steps: First, a set of known quantities needs to be specified as input parameters for a model, and second, a specific functional form needs to be defined to model the unclosed terms by the input parameters. Both steps involve a certain modelling error, with the former known as the irreducible error and the latter referred to as the functional error. Typically, only the total modelling error, which is the sum of functional and irreducible error, is assessed, but the concept of the optimal estimator enables the separate analysis of the total and the irreducible errors, yielding a systematic modelling error decomposition. In this work, attention is paid to the techniques themselves required for the practical computation of irreducible errors. Typically, histograms are used for optimal estimator analyses, but this technique is found to add a non-negligible spurious contribution to the irreducible error if models with multiple input parameters are assessed. Thus, the error decomposition of an optimal estimator analysis becomes inaccurate, and misleading conclusions concerning modelling errors may be drawn. In this work, numerically accurate techniques for optimal estimator analyses are identified and a suitable evaluation of irreducible errors is presented. Four different computational techniques are considered: a histogram technique, artificial neural networks, multivariate adaptive regression splines, and an additive model based on a kernel method. For multiple input parameter models, only artificial neural networks and multivariate adaptive regression splines are found to yield satisfactorily accurate results. Beyond a certain number of input parameters, the assessment of models in an optimal estimator analysis even becomes practically infeasible if histograms are used. The optimal estimator analysis in this paper is applied to modelling the filtered soot intermittency in large eddy simulations using a dataset of a direct numerical simulation of a non-premixed sooting turbulent flame.

Differences between Homicides Committed by Lone and Multiple Offenders in Korea.

PubMed

Park, Jisun; Cho, Joon Tag

2018-05-16

The aim of this study was to differentiate between homicides committed by multiple offenders and homicides committed by lone offenders. Using data on homicide incidents that occurred in South Korea between 1985 and 2008, we compared 134 homicides committed by multiple offenders, with 369 homicides committed by lone offenders. A greater proportion of homicides committed by multiple offenders involved injuries to the victim's head compared to homicides by lone offenders. Homicides committed by multiple offenders were more likely to involve blunt instruments and ligatures, whereas homicides by lone offenders were more likely to involve sharp instruments. In addition, a majority of the homicides committed by multiple offenders were planned. The results of this study have practical implications for homicide investigations, as well as theoretical implications for homicide research on the difference in offense behaviors based on the number of offenders. © 2018 American Academy of Forensic Sciences.

Modelling CO2 flow in naturally fractured geological media using MINC and multiple subregion upscaling procedure

NASA Astrophysics Data System (ADS)

Tatomir, Alexandru Bogdan A. C.; Flemisch, Bernd; Class, Holger; Helmig, Rainer; Sauter, Martin

2017-04-01

Geological storage of CO2 represents one viable solution to reduce greenhouse gas emission in the atmosphere. Potential leakage of CO2 storage can occur through networks of interconnected fractures. The geometrical complexity of these networks is often very high involving fractures occurring at various scales and having hierarchical structures. Such multiphase flow systems are usually hard to solve with a discrete fracture modelling (DFM) approach. Therefore, continuum fracture models assuming average properties are usually preferred. The multiple interacting continua (MINC) model is an extension of the classic double porosity model (Warren and Root, 1963) which accounts for the non-linear behaviour of the matrix-fracture interactions. For CO2 storage applications the transient representation of the inter-porosity two phase flow plays an important role. This study tests the accuracy and computational efficiency of the MINC method complemented with the multiple sub-region (MSR) upscaling procedure versus the DFM. The two phase flow MINC simulator is implemented in the free-open source numerical toolbox DuMux (www.dumux.org). The MSR (Gong et al., 2009) determines the inter-porosity terms by solving simplified local single-phase flow problems. The DFM is considered as the reference solution. The numerical examples consider a quasi-1D reservoir with a quadratic fracture system , a five-spot radial symmetric reservoir, and a completely random generated fracture system. Keywords: MINC, upscaling, two-phase flow, fractured porous media, discrete fracture model, continuum fracture model

A physical layer perspective on access network sharing

NASA Astrophysics Data System (ADS)

Pfeiffer, Thomas

2015-12-01

Unlike in copper or wireless networks, there is no sharing of resources in fiber access networks yet, other than bit stream access or cable sharing, in which the fibers of a cable are let to one or multiple operators. Sharing optical resources on a single fiber among multiple operators or different services has not yet been applied. While this would allow for a better exploitation of installed infrastructures, there are operational issues which still need to be resolved, before this sharing model can be implemented in networks. Operating multiple optical systems and services over a common fiber plant, autonomously and independently from each other, can result in mutual distortions on the physical layer. These distortions will degrade the performance of the involved systems, unless precautions are taken in the infrastructure hardware to eliminate or to reduce them to an acceptable level. Moreover, the infrastructure needs to be designed such as to support different system technologies and to ensure a guaranteed quality of the end-to-end connections. In this paper, suitable means are proposed to be introduced in fiber access infrastructures that will allow for shared utilization of the fibers while safeguarding the operational needs and business interests of the involved parties.

Involvement of Working Memory in Mental Multiplication in Chinese Elementary Students

ERIC Educational Resources Information Center

Liu, Ru-De; Ding, Yi; Xu, Le; Wang, Jia

2017-01-01

The authors' aim was to examine the relation between two-digit mental multiplication and working memory. In Study 1, involving 30 fifth-grade students, we used digit span backward as an abbreviated measure of working memory. In Study 2, involving 41 fourth-grade students, working memory comprised measures of phonological loop, visuospatial…

The intricate mechanisms of neurodegeneration in prion diseases

PubMed Central

Soto, Claudio; Satani, Nikunj

2010-01-01

Prion diseases are a group of infectious neurodegenerative diseases with an entirely novel mechanism of transmission, involving a protein-only infectious agent that propagates the disease by transmitting protein conformational changes. The disease results from extensive and progressive brain degeneration. The molecular mechanisms involved in neurodegeneration are not entirely known but involve multiple processes operating simultaneously and synergistically in the brain, including spongiform degeneration, synaptic alterations, brain inflammation, neuronal death and the accumulation of protein aggregates. Here, we review the pathways implicated in prion-induced brain damage and put the pieces together into a possible model of neurodegeneration in prion disorders. A more comprehensive understanding of the molecular basis of brain degeneration is essential to develop a much needed therapy for these devastating diseases. PMID:20889378

Sustaining self-management in diabetes mellitus.

PubMed

Mitchell-Brown, Fay

2014-01-01

Successful management of diabetes depends on the individual's ability to manage and control symptoms. Self-management of diabetes is believed to play a significant role in achieving positive outcomes for patients. Adherence to self-management behaviors supports high-quality care, which reduces and delays disease complications, resulting in improved quality of life. Because self-management is so important to diabetes management and involves a lifelong commitment for all patients, health care providers should actively promote ways to maintain and sustain behavior change that support adherence to self-management. A social ecological model of behavior change (McLeroy, Bibeau, Steckler, & Glanz, 1988) helps practitioners provide evidence-based care and optimizes patients' clinical outcomes. This model supports self-management behaviors through multiple interacting interventions that can help sustain behavior change. Diabetes is a complex chronic disease; successful management must use multiple-level interventions.

A multiple-point geostatistical approach to quantifying uncertainty for flow and transport simulation in geologically complex environments

NASA Astrophysics Data System (ADS)

Cronkite-Ratcliff, C.; Phelps, G. A.; Boucher, A.

2011-12-01

In many geologic settings, the pathways of groundwater flow are controlled by geologic heterogeneities which have complex geometries. Models of these geologic heterogeneities, and consequently, their effects on the simulated pathways of groundwater flow, are characterized by uncertainty. Multiple-point geostatistics, which uses a training image to represent complex geometric descriptions of geologic heterogeneity, provides a stochastic approach to the analysis of geologic uncertainty. Incorporating multiple-point geostatistics into numerical models provides a way to extend this analysis to the effects of geologic uncertainty on the results of flow simulations. We present two case studies to demonstrate the application of multiple-point geostatistics to numerical flow simulation in complex geologic settings with both static and dynamic conditioning data. Both cases involve the development of a training image from a complex geometric description of the geologic environment. Geologic heterogeneity is modeled stochastically by generating multiple equally-probable realizations, all consistent with the training image. Numerical flow simulation for each stochastic realization provides the basis for analyzing the effects of geologic uncertainty on simulated hydraulic response. The first case study is a hypothetical geologic scenario developed using data from the alluvial deposits in Yucca Flat, Nevada. The SNESIM algorithm is used to stochastically model geologic heterogeneity conditioned to the mapped surface geology as well as vertical drill-hole data. Numerical simulation of groundwater flow and contaminant transport through geologic models produces a distribution of hydraulic responses and contaminant concentration results. From this distribution of results, the probability of exceeding a given contaminant concentration threshold can be used as an indicator of uncertainty about the location of the contaminant plume boundary. The second case study considers a characteristic lava-flow aquifer system in Pahute Mesa, Nevada. A 3D training image is developed by using object-based simulation of parametric shapes to represent the key morphologic features of rhyolite lava flows embedded within ash-flow tuffs. In addition to vertical drill-hole data, transient pressure head data from aquifer tests can be used to constrain the stochastic model outcomes. The use of both static and dynamic conditioning data allows the identification of potential geologic structures that control hydraulic response. These case studies demonstrate the flexibility of the multiple-point geostatistics approach for considering multiple types of data and for developing sophisticated models of geologic heterogeneities that can be incorporated into numerical flow simulations.

Multiple sclerosis pathogenesis: missing pieces of an old puzzle.

PubMed

Rahmanzadeh, Reza; Brück, Wolfgang; Minagar, Alireza; Sahraian, Mohammad Ali

2018-06-08

Traditionally, multiple sclerosis (MS) was considered to be a CD4 T cell-mediated CNS autoimmunity, compatible with experimental autoimmune encephalitis model, which can be characterized by focal lesions in the white matter. However, studies of recent decades revealed several missing pieces of MS puzzle and showed that MS pathogenesis is more complex than the traditional view and may include the following: a primary degenerative process (e.g. oligodendroglial pathology), generalized abnormality of normal-appearing brain tissue, pronounced gray matter pathology, involvement of innate immunity, and CD8 T cells and B cells. Here, we review these findings and discuss their implications in MS pathogenesis.

A Multiple-Item Scale for Assessing E-Government Service Quality

NASA Astrophysics Data System (ADS)

Papadomichelaki, Xenia; Mentzas, Gregoris

A critical element in the evolution of e-governmental services is the development of sites that better serve the citizens’ needs. To deliver superior service quality, we must first understand how citizens perceive and evaluate online citizen service. This involves defining what e-government service quality is, identifying its underlying dimensions, and determining how it can be conceptualized and measured. In this article we conceptualise an e-government service quality model (e-GovQual) and then we develop, refine, validate, confirm and test a multiple-item scale for measuring e-government service quality for public administration sites where citizens seek either information or services.

Forecasting models for sugi (Cryptomeria japonica D. Don) pollen count showing an alternate dispersal rhythm.

PubMed

Ito, Yukiko; Hattori, Reiko; Mase, Hiroki; Watanabe, Masako; Shiotani, Itaru

2008-12-01

Pollen information is indispensable for allergic individuals and clinicians. This study aimed to develop forecasting models for the total annual count of airborne pollen grains based on data monitored over the last 20 years at the Mie Chuo Medical Center, Tsu, Mie, Japan. Airborne pollen grains were collected using a Durham sampler. Total annual pollen count and pollen count from October to December (OD pollen count) of the previous year were transformed to logarithms. Regression analysis of the total pollen count was performed using variables such as the OD pollen count and the maximum temperature for mid-July of the previous year. Time series analysis revealed an alternate rhythm of the series of total pollen count. The alternate rhythm consisted of a cyclic alternation of an "on" year (high pollen count) and an "off" year (low pollen count). This rhythm was used as a dummy variable in regression equations. Of the three models involving the OD pollen count, a multiple regression equation that included the alternate rhythm variable and the interaction of this rhythm with OD pollen count showed a high coefficient of determination (0.844). Of the three models involving the maximum temperature for mid-July, those including the alternate rhythm variable and the interaction of this rhythm with maximum temperature had the highest coefficient of determination (0.925). An alternate pollen dispersal rhythm represented by a dummy variable in the multiple regression analysis plays a key role in improving forecasting models for the total annual sugi pollen count.

Mediators of Stress and Role Satisfaction in Multiple Role Women.

ERIC Educational Resources Information Center

Hammond, Laura A.

Women involved in multiple life roles comprise a large segment of society, yet little is known about how stressful and satisfying they find this lifestyle, or about what characteristics are related to feeling stressed or satisfied. The purpose of this study was to examine role and life satisfaction and stress in women involved in multiple life…

Real-Time Optimal Flood Control Decision Making and Risk Propagation Under Multiple Uncertainties

NASA Astrophysics Data System (ADS)

Zhu, Feilin; Zhong, Ping-An; Sun, Yimeng; Yeh, William W.-G.

2017-12-01

Multiple uncertainties exist in the optimal flood control decision-making process, presenting risks involving flood control decisions. This paper defines the main steps in optimal flood control decision making that constitute the Forecast-Optimization-Decision Making (FODM) chain. We propose a framework for supporting optimal flood control decision making under multiple uncertainties and evaluate risk propagation along the FODM chain from a holistic perspective. To deal with uncertainties, we employ stochastic models at each link of the FODM chain. We generate synthetic ensemble flood forecasts via the martingale model of forecast evolution. We then establish a multiobjective stochastic programming with recourse model for optimal flood control operation. The Pareto front under uncertainty is derived via the constraint method coupled with a two-step process. We propose a novel SMAA-TOPSIS model for stochastic multicriteria decision making. Then we propose the risk assessment model, the risk of decision-making errors and rank uncertainty degree to quantify the risk propagation process along the FODM chain. We conduct numerical experiments to investigate the effects of flood forecast uncertainty on optimal flood control decision making and risk propagation. We apply the proposed methodology to a flood control system in the Daduhe River basin in China. The results indicate that the proposed method can provide valuable risk information in each link of the FODM chain and enable risk-informed decisions with higher reliability.

Deciphering Epithelial–Mesenchymal Transition Regulatory Networks in Cancer through Computational Approaches

PubMed Central

Burger, Gerhard A.; Danen, Erik H. J.; Beltman, Joost B.

2017-01-01

Epithelial–mesenchymal transition (EMT), the process by which epithelial cells can convert into motile mesenchymal cells, plays an important role in development and wound healing but is also involved in cancer progression. It is increasingly recognized that EMT is a dynamic process involving multiple intermediate or “hybrid” phenotypes rather than an “all-or-none” process. However, the role of EMT in various cancer hallmarks, including metastasis, is debated. Given the complexity of EMT regulation, computational modeling has proven to be an invaluable tool for cancer research, i.e., to resolve apparent conflicts in experimental data and to guide experiments by generating testable hypotheses. In this review, we provide an overview of computational modeling efforts that have been applied to regulation of EMT in the context of cancer progression and its associated tumor characteristics. Moreover, we identify possibilities to bridge different modeling approaches and point out outstanding questions in which computational modeling can contribute to advance our understanding of pathological EMT. PMID:28824874

Complex index of refraction estimation from degree of polarization with diffuse scattering consideration.

PubMed

Zhan, Hanyu; Voelz, David G; Cho, Sang-Yeon; Xiao, Xifeng

2015-11-20

The estimation of the refractive index from optical scattering off a target's surface is an important task for remote sensing applications. Optical polarimetry is an approach that shows promise for refractive index estimation. However, this estimation often relies on polarimetric models that are limited to specular targets involving single surface scattering. Here, an analytic model is developed for the degree of polarization (DOP) associated with reflection from a rough surface that includes the effect of diffuse scattering. A multiplicative factor is derived to account for the diffuse component and evaluation of the model indicates that diffuse scattering can significantly affect the DOP values. The scattering model is used in a new approach for refractive index estimation from a series of DOP values that involves jointly estimating n, k, and ρ(d)with a nonlinear equation solver. The approach is shown to work well with simulation data and additive noise. When applied to laboratory-measured DOP values, the approach produces significantly improved index estimation results relative to reference values.

Degenerative joint disease: multiple joint involvement in young and mature dogs.

PubMed

Olsewski, J M; Lust, G; Rendano, V T; Summers, B A

1983-07-01

Radiologic, pathologic, and ancillary methods were used to determine the occurrence of degenerative joint disease involving multiple joints of immature and adult dogs. Animals were selected for the development of hip joint dysplasia and chronic degenerative joint disease. Of disease-prone dogs, 82% (45 of 55 dogs) had radiologic changes, indicative of hip dysplasia, by 1 year of age. At necropsy, more abnormal joints were identified than by radiographic examination. Among 92 dogs between 3 to 11 months of age that had joint abnormalities, 71% had hip joint involvement; 38%, shoulder joint involvement; 22%, stifle joint involvement; and 40% had multiple joint involvement. Polyarthritis was asymptomatic and unexpected. Radiographic examination of older dogs also revealed evidence of degenerative joint disease in many joints. Multiple joint involvement was substantiated at necropsy of young and mature dogs. A similar pattern of polyarticular osteoarthritis was revealed in a survey (computer search) of necropsy reports from medical case records of 100 adult and elderly dogs. Usually, the joint disease was an incidental observation, unrelated to the clinical disease or to the cause of death. The frequent occurrence of degenerative changes in several joints of dogs aged 6 months to 17 years indicated that osteoarthritis may be progressive in these joints and raises the possibility that systemic factors are involved in the disease process.

An Integrated Crustal Dynamics Simulator

NASA Astrophysics Data System (ADS)

Xing, H. L.; Mora, P.

2007-12-01

Numerical modelling offers an outstanding opportunity to gain an understanding of the crustal dynamics and complex crustal system behaviour. This presentation provides our long-term and ongoing effort on finite element based computational model and software development to simulate the interacting fault system for earthquake forecasting. A R-minimum strategy based finite-element computational model and software tool, PANDAS, for modelling 3-dimensional nonlinear frictional contact behaviour between multiple deformable bodies with the arbitrarily-shaped contact element strategy has been developed by the authors, which builds up a virtual laboratory to simulate interacting fault systems including crustal boundary conditions and various nonlinearities (e.g. from frictional contact, materials, geometry and thermal coupling). It has been successfully applied to large scale computing of the complex nonlinear phenomena in the non-continuum media involving the nonlinear frictional instability, multiple material properties and complex geometries on supercomputers, such as the South Australia (SA) interacting fault system, South California fault model and Sumatra subduction model. It has been also extended and to simulate the hot fractured rock (HFR) geothermal reservoir system in collaboration of Geodynamics Ltd which is constructing the first geothermal reservoir system in Australia and to model the tsunami generation induced by earthquakes. Both are supported by Australian Research Council.

An Illustrative Guide to the Minerva Framework

NASA Astrophysics Data System (ADS)

Flom, Erik; Leonard, Patrick; Hoeffel, Udo; Kwak, Sehyun; Pavone, Andrea; Svensson, Jakob; Krychowiak, Maciej; Wendelstein 7-X Team Collaboration

2017-10-01

Modern phsyics experiments require tracking and modelling data and their associated uncertainties on a large scale, as well as the combined implementation of multiple independent data streams for sophisticated modelling and analysis. The Minerva Framework offers a centralized, user-friendly method of large-scale physics modelling and scientific inference. Currently used by teams at multiple large-scale fusion experiments including the Joint European Torus (JET) and Wendelstein 7-X (W7-X), the Minerva framework provides a forward-model friendly architecture for developing and implementing models for large-scale experiments. One aspect of the framework involves so-called data sources, which are nodes in the graphical model. These nodes are supplied with engineering and physics parameters. When end-user level code calls a node, it is checked network-wide against its dependent nodes for changes since its last implementation and returns version-specific data. Here, a filterscope data node is used as an illustrative example of the Minerva Framework's data management structure and its further application to Bayesian modelling of complex systems. This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014-2018 under Grant Agreement No. 633053.

A Blended Learning Approach to Teaching Project Management: A Model for Active Participation and Involvement--Insights from Norway

ERIC Educational Resources Information Center

Hussein, Bassam A.

2015-01-01

The paper demonstrates and evaluates the effectiveness of a blended learning approach to create a meaningful learning environment. We use the term blended learning approach in this paper to refer to the use of multiple or hybrid instructional methods that emphasize the role of learners as contributors to the learning process rather than recipients…

Learning to Look beyond the Boundaries of Representation: Using Technology to Examine Teaching (Overview for a Digital Exhibition: Learning from the Practice of Teaching)

ERIC Educational Resources Information Center

Hatch, Thomas; Grossman, Pam

2009-01-01

Leading a classroom discussion involves multiple components, including establishing norms for participation, assisting students in engaging in careful readings of text ahead of time, and modeling features of academic discourse. In other work, Grossman and her colleagues refer to this as the "decomposition" of practice--breaking down complex…

Challenges to Providing End-of-Life Care to Low-Income Elders with Advanced Chronic Disease: Lessons Learned from a Model Program

ERIC Educational Resources Information Center

Kramer, Betty J.; Auer, Casey

2005-01-01

Purpose: This study explored the challenges in providing end-of-life care to low-income elders with multiple comorbid chronic conditions in a fully "integrated" managed care program, and it highlighted essential recommendations. Design and Methods: A case-study design was used that involved an extensive analysis of qualitative data from five focus…

Evaluation of a Technology for Teaching Complex Social Skills to Young Adults with Visual and Cognitive Impairments.

ERIC Educational Resources Information Center

Gumpel, Thomas P.; Nativ-Ari-Am, Hagit

2001-01-01

Two multiple baseline designs were used to evaluate a two-stage model for training four young adults with visual and cognitive impairments to grocery shop. A task-analytical flow chart of the behavioral skills involved in grocery shopping was used to increase completed skill steps and the number of correct items purchased. (Contains references.)…

Preclinical evaluation of the PI3K/Akt/mTOR pathway in animal models of multiple sclerosis

PubMed Central

Mammana, Santa; Bramanti, Placido; Mazzon, Emanuela; Cavalli, Eugenio; Basile, Maria Sofia; Fagone, Paolo; Petralia, Maria Cristina; McCubrey, James Andrew; Nicoletti, Ferdinando; Mangano, Katia

2018-01-01

The PI3K/AKT/mTOR pathway is an intracellular signalling pathway that regulates cell activation. proliferation, metabolism and apoptosis. Increasing body of data suggests that alterations in the PI3K/AKT/mTOR pathway may result in an enhanced susceptibility to autoimmunity. Multiple Sclerosis (MS) is one of the most common chronic inflammatory diseases of the central nervous system leading to demyelination and neurodegeneration. In the current study, we have firstly evaluated in silico the involvement of the mTOR network on the generation and progression of MS and on oligodendrocyte function, making use of currently available whole-genome transcriptomic data. Then, the data generated in silico were subjected to an ex-vivo evaluation. To this aim, the involvement of mTOR was validated on a well-known animal model of MS and in vitro on Th17 cells. Our data indicate that there is a significant involvement of the mTOR network in the etiopathogenesis of MS and that Rapamycin treatment may represent a useful therapeutic approach in this clinical setting. On the other hand, our data showed that a significant involvement of the mTOR network could be observed only in the early phases of oligodendrocyte maturation, but not in the maturation process of adult oligodendrocytes and in the process of remyelination following demyelinating injury. Overall, our study suggests that targeting the PI3K/mTOR pathway, although it may not be a useful therapeutic approach to promote remyelination in MS patients, it can be exploited to exert immunomodulation, preventing/delaying relapses, and to treat MS patients in order to slow down the progression of disability. PMID:29492193

Reinforcement Learning of Two-Joint Virtual Arm Reaching in a Computer Model of Sensorimotor Cortex

PubMed Central

Neymotin, Samuel A.; Chadderdon, George L.; Kerr, Cliff C.; Francis, Joseph T.; Lytton, William W.

2014-01-01

Neocortical mechanisms of learning sensorimotor control involve a complex series of interactions at multiple levels, from synaptic mechanisms to cellular dynamics to network connectomics. We developed a model of sensory and motor neocortex consisting of 704 spiking model neurons. Sensory and motor populations included excitatory cells and two types of interneurons. Neurons were interconnected with AMPA/NMDA and GABAA synapses. We trained our model using spike-timing-dependent reinforcement learning to control a two-joint virtual arm to reach to a fixed target. For each of 125 trained networks, we used 200 training sessions, each involving 15 s reaches to the target from 16 starting positions. Learning altered network dynamics, with enhancements to neuronal synchrony and behaviorally relevant information flow between neurons. After learning, networks demonstrated retention of behaviorally relevant memories by using proprioceptive information to perform reach-to-target from multiple starting positions. Networks dynamically controlled which joint rotations to use to reach a target, depending on current arm position. Learning-dependent network reorganization was evident in both sensory and motor populations: learned synaptic weights showed target-specific patterning optimized for particular reach movements. Our model embodies an integrative hypothesis of sensorimotor cortical learning that could be used to interpret future electrophysiological data recorded in vivo from sensorimotor learning experiments. We used our model to make the following predictions: learning enhances synchrony in neuronal populations and behaviorally relevant information flow across neuronal populations, enhanced sensory processing aids task-relevant motor performance and the relative ease of a particular movement in vivo depends on the amount of sensory information required to complete the movement. PMID:24047323

Family Matters: Examining Child Abuse and Neglect as Family Dysfunction for Minority Youth Living in Extreme Poverty.

PubMed

Spano, Richard; David, Michael A; Jeffries, Sara R; Bolland, John M

2017-12-01

Two competing models of child abuse and neglect (scapegoat vs. family dysfunction) are used to illustrate how the specification of victims ("index" victim vs. all children in household) from incidents of child abuse and neglect can be used to improve estimates of maltreatment for at-risk minority youth. Child Protection Services records were searched in 2005 for 366 "index" victims who were surveyed for 5 consecutive years (from 1998 to 2002) for the Mobile Youth Survey as well as other siblings in the household. The findings indicate that the baseline estimate of any maltreatment, sexual abuse, physical abuse, and neglect increased by 68%, 26%, 33%, and 74%, respectively, after adjusting for incidents that involved multiple victims (i.e., maltreatment as family dysfunction). In addition, the baseline estimate of more severe (indicated) incidents of physical abuse and neglect increased by 67% and 64%, respectively, after accounting for incidents that involved multiple victims, but there were no incidents of more severe (indicated) sexual abuse that involved multiple victims. Similarly, baseline estimates of age of onset (or chronicity) of maltreatment during childhood and adolescence increased by 62% and 26%, respectively. Baseline estimates for youth with 3 or more years of maltreatment and youth with 3 or more incidents of maltreatment both increased by about 71%. The implications of these findings for policy and practice as well as areas for future research are also discussed.

Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks

PubMed Central

Jung, Sungmo; Kim, Jong Hyun; Kim, Seoksoo

2012-01-01

Wireless machine-to-machine sensor networks with multiple radio interfaces are expected to have several advantages, including high spatial scalability, low event detection latency, and low energy consumption. Here, we propose a network model design method involving network approximation and an optimized multi-tiered clustering algorithm that maximizes node lifespan by minimizing energy consumption in a non-uniformly distributed network. Simulation results show that the cluster scales and network parameters determined with the proposed method facilitate a more efficient performance compared to existing methods. PMID:23202190

Multiple kinetic k-essence, phantom barrier crossing and stability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sur, Sourav; Das, Saurya, E-mail: sourav.sur@uleth.ca

We investigate models of dark energy with purely kinetic multiple k-essence sources that allow for the crossing of the phantom divide line, without violating the conditions of stability. It is known that with more than one kinetic k-field one can possibly construct dark energy models whose equation of state parameter w{sub X} crosses -1 (the phantom barrier) at recent red-shifts, as indicated by the Supernova Ia and other observational probes. However, such models may suffer from cosmological instabilities, as the effective speed of propagation c{sub X} of the dark energy density perturbations may become imaginary while the w{sub X} =more » -1 barrier is crossed. Working out the expression for c{sub X} we show that multiple kinetic k-essence fields do indeed lead to a w{sub X} = -1 crossing dark energy model, satisfying the stability criterion c{sub X}{sup 2} {>=} 0 as well as the condition c{sub X} {<=} 1 (in natural units), which implies that the dark energy is not super-luminal. As a specific example, we construct a phantom barrier crossing model involving three k-fields for which c{sub X} is a constant, lying between 0 and 1. The model fits well with the latest Supernova Ia Union data, and the best fit shows that w{sub X} crosses -1 at red-shift z {approx} 0.2, whereas the dark energy density nearly tracks the matter density at higher red-shifts.« less

Factors influencing recruitment of walleye and white bass to three distinct early ontogenetic stages

USGS Publications Warehouse

DeBoer, Jason A.; Pope, Kevin L.

2015-01-01

Determining the factors that influence recruitment to sequential ontogenetic stages is critical for understanding recruitment dynamics of fish and for effective management of sportfish, particularly in dynamic and unpredictable environments. We sampled walleye (Sander vitreus) and white bass (Morone chrysops) at 3 ontogenetic stages (age 0 during spring: ‘age-0 larval’; age 0 during autumn: ‘age-0 juvenile’; and age 1 during autumn: ‘age-1 juvenile’) from 3 reservoirs. We developed multiple linear regression models to describe factors influencing age-0 larval, age-0 juvenile and age-1 juvenile walleye and white bass abundance indices. Our models explained 40–80% (68 ± 9%; mean ± SE) and 71%–97% (81 ± 6%) of the variability in catch for walleye and white bass respectively. For walleye, gizzard shad were present in the candidate model sets for all three ontogenetic stages we assessed. For white bass, there was no unifying variable in all three stage-specific candidate model sets, although walleye abundance was present in two of the three white bass candidate model sets. We were able to determine several factors affecting walleye and white bass year-class strength at multiple ontogenetic stages; comprehensive analyses of factors influencing recruitment to multiple early ontogenetic stages are seemingly rare in the literature. Our models demonstrate the interdependency among early ontogenetic stages and the complexities involved with sportfish recruitment.

A Component Approach to Collaborative Scientific Software Development: Tools and Techniques Utilized by the Quantum Chemistry Science Application Partnership

DOE PAGES

Kenny, Joseph P.; Janssen, Curtis L.; Gordon, Mark S.; ...

2008-01-01

Cutting-edge scientific computing software is complex, increasingly involving the coupling of multiple packages to combine advanced algorithms or simulations at multiple physical scales. Component-based software engineering (CBSE) has been advanced as a technique for managing this complexity, and complex component applications have been created in the quantum chemistry domain, as well as several other simulation areas, using the component model advocated by the Common Component Architecture (CCA) Forum. While programming models do indeed enable sound software engineering practices, the selection of programming model is just one building block in a comprehensive approach to large-scale collaborative development which must also addressmore » interface and data standardization, and language and package interoperability. We provide an overview of the development approach utilized within the Quantum Chemistry Science Application Partnership, identifying design challenges, describing the techniques which we have adopted to address these challenges and highlighting the advantages which the CCA approach offers for collaborative development.« less

Dry wind tunnel system

NASA Technical Reports Server (NTRS)

Chen, Ping-Chih (Inventor)

2013-01-01

This invention is a ground flutter testing system without a wind tunnel, called Dry Wind Tunnel (DWT) System. The DWT system consists of a Ground Vibration Test (GVT) hardware system, a multiple input multiple output (MIMO) force controller software, and a real-time unsteady aerodynamic force generation software, that is developed from an aerodynamic reduced order model (ROM). The ground flutter test using the DWT System operates on a real structural model, therefore no scaled-down structural model, which is required by the conventional wind tunnel flutter test, is involved. Furthermore, the impact of the structural nonlinearities on the aeroelastic stability can be included automatically. Moreover, the aeroservoelastic characteristics of the aircraft can be easily measured by simply including the flight control system in-the-loop. In addition, the unsteady aerodynamics generated computationally is interference-free from the wind tunnel walls. Finally, the DWT System can be conveniently and inexpensively carried out as a post GVT test with the same hardware, only with some possible rearrangement of the shakers and the inclusion of additional sensors.

Dissecting Embryonic Stem Cell Self-Renewal and Differentiation Commitment from Quantitative Models.

PubMed

Hu, Rong; Dai, Xianhua; Dai, Zhiming; Xiang, Qian; Cai, Yanning

2016-10-01

To model quantitatively embryonic stem cell (ESC) self-renewal and differentiation by computational approaches, we developed a unified mathematical model for gene expression involved in cell fate choices. Our quantitative model comprised ESC master regulators and lineage-specific pivotal genes. It took the factors of multiple pathways as input and computed expression as a function of intrinsic transcription factors, extrinsic cues, epigenetic modifications, and antagonism between ESC master regulators and lineage-specific pivotal genes. In the model, the differential equations of expression of genes involved in cell fate choices from regulation relationship were established according to the transcription and degradation rates. We applied this model to the Murine ESC self-renewal and differentiation commitment and found that it modeled the expression patterns with good accuracy. Our model analysis revealed that Murine ESC was an attractor state in culture and differentiation was predominantly caused by antagonism between ESC master regulators and lineage-specific pivotal genes. Moreover, antagonism among lineages played a critical role in lineage reprogramming. Our results also uncovered that the ordered expression alteration of ESC master regulators over time had a central role in ESC differentiation fates. Our computational framework was generally applicable to most cell-type maintenance and lineage reprogramming.

Assessing interactions between HLA-DRB1*15 and infectious mononucleosis on the risk of multiple sclerosis.

PubMed

Disanto, Giulio; Hall, Carolina; Lucas, Robyn; Ponsonby, Anne-Louise; Berlanga-Taylor, Antonio J; Giovannoni, Gavin; Ramagopalan, Sreeram V

2013-09-01

Gene-environment interactions may shed light on the mechanisms underlying multiple sclerosis (MS). We pooled data from two case-control studies on incident demyelination and used different methods to assess interaction between HLA-DRB1*15 (DRB1-15) and history of infectious mononucleosis (IM). Individuals exposed to both factors were at substantially increased risk of disease (OR=7.32, 95% CI=4.92-10.90). In logistic regression models, DRB1-15 and IM status were independent predictors of disease while their interaction term was not (DRB1-15*IM: OR=1.35, 95% CI=0.79-2.23). However, interaction on an additive scale was evident (Synergy index=2.09, 95% CI=1.59-2.59; excess risk due to interaction=3.30, 95%CI=0.47-6.12; attributable proportion due to interaction=45%, 95% CI=22-68%). This suggests, if the additive model is appropriate, the DRB1-15 and IM may be involved in the same causal process leading to MS and highlights the benefit of reporting gene-environment interactions on both a multiplicative and additive scale.

The extraction of simple relationships in growth factor-specific multiple-input and multiple-output systems in cell-fate decisions by backward elimination PLS regression.

PubMed

Akimoto, Yuki; Yugi, Katsuyuki; Uda, Shinsuke; Kudo, Takamasa; Komori, Yasunori; Kubota, Hiroyuki; Kuroda, Shinya

2013-01-01

Cells use common signaling molecules for the selective control of downstream gene expression and cell-fate decisions. The relationship between signaling molecules and downstream gene expression and cellular phenotypes is a multiple-input and multiple-output (MIMO) system and is difficult to understand due to its complexity. For example, it has been reported that, in PC12 cells, different types of growth factors activate MAP kinases (MAPKs) including ERK, JNK, and p38, and CREB, for selective protein expression of immediate early genes (IEGs) such as c-FOS, c-JUN, EGR1, JUNB, and FOSB, leading to cell differentiation, proliferation and cell death; however, how multiple-inputs such as MAPKs and CREB regulate multiple-outputs such as expression of the IEGs and cellular phenotypes remains unclear. To address this issue, we employed a statistical method called partial least squares (PLS) regression, which involves a reduction of the dimensionality of the inputs and outputs into latent variables and a linear regression between these latent variables. We measured 1,200 data points for MAPKs and CREB as the inputs and 1,900 data points for IEGs and cellular phenotypes as the outputs, and we constructed the PLS model from these data. The PLS model highlighted the complexity of the MIMO system and growth factor-specific input-output relationships of cell-fate decisions in PC12 cells. Furthermore, to reduce the complexity, we applied a backward elimination method to the PLS regression, in which 60 input variables were reduced to 5 variables, including the phosphorylation of ERK at 10 min, CREB at 5 min and 60 min, AKT at 5 min and JNK at 30 min. The simple PLS model with only 5 input variables demonstrated a predictive ability comparable to that of the full PLS model. The 5 input variables effectively extracted the growth factor-specific simple relationships within the MIMO system in cell-fate decisions in PC12 cells.

Multiple spatially localized dynamical states in friction-excited oscillator chains

NASA Astrophysics Data System (ADS)

Papangelo, A.; Hoffmann, N.; Grolet, A.; Stender, M.; Ciavarella, M.

2018-03-01

Friction-induced vibrations are known to affect many engineering applications. Here, we study a chain of friction-excited oscillators with nearest neighbor elastic coupling. The excitation is provided by a moving belt which moves at a certain velocity vd while friction is modelled with an exponentially decaying friction law. It is shown that in a certain range of driving velocities, multiple stable spatially localized solutions exist whose dynamical behavior (i.e. regular or irregular) depends on the number of oscillators involved in the vibration. The classical non-repeatability of friction-induced vibration problems can be interpreted in light of those multiple stable dynamical states. These states are found within a "snaking-like" bifurcation pattern. Contrary to the classical Anderson localization phenomenon, here the underlying linear system is perfectly homogeneous and localization is solely triggered by the friction nonlinearity.

Causal models of attention-deficit/hyperactivity disorder: from common simple deficits to multiple developmental pathways.

PubMed

Sonuga-Barke, Edmund J S

2005-06-01

Until recently, causal models of attention-deficit/hyperactivity disorder (ADHD) have tended to focus on the role of common, simple, core deficits. One such model highlights the role of executive dysfunction due to deficient inhibitory control resulting from disturbances in the frontodorsal striatal circuit and associated mesocortical dopaminergic branches. An alternative model presents ADHD as resulting from impaired signaling of delayed rewards arising from disturbances in motivational processes, involving frontoventral striatal reward circuits and mesolimbic branches terminating in the ventral striatum, particularly the nucleus accumbens. In the present article, these models are elaborated in two ways. First, they are each placed within their developmental context by consideration of the role of person x environment correlation and interaction and individual adaptation to developmental constraint. Second, their relationship to one another is reviewed in the light of recent data suggesting that delay aversion and executive functions might each make distinctive contributions to the development of the disorder. This provides an impetus for theoretical models built around the idea of multiple neurodevelopmental pathways. The possibility of neuropathologic heterogeneity in ADHD is likely to have important implications for the clinical management of the condition, potentially impacting on both diagnostic strategies and treatment options.

A clustering-based fuzzy wavelet neural network model for short-term load forecasting.

PubMed

Kodogiannis, Vassilis S; Amina, Mahdi; Petrounias, Ilias

2013-10-01

Load forecasting is a critical element of power system operation, involving prediction of the future level of demand to serve as the basis for supply and demand planning. This paper presents the development of a novel clustering-based fuzzy wavelet neural network (CB-FWNN) model and validates its prediction on the short-term electric load forecasting of the Power System of the Greek Island of Crete. The proposed model is obtained from the traditional Takagi-Sugeno-Kang fuzzy system by replacing the THEN part of fuzzy rules with a "multiplication" wavelet neural network (MWNN). Multidimensional Gaussian type of activation functions have been used in the IF part of the fuzzyrules. A Fuzzy Subtractive Clustering scheme is employed as a pre-processing technique to find out the initial set and adequate number of clusters and ultimately the number of multiplication nodes in MWNN, while Gaussian Mixture Models with the Expectation Maximization algorithm are utilized for the definition of the multidimensional Gaussians. The results corresponding to the minimum and maximum power load indicate that the proposed load forecasting model provides significantly accurate forecasts, compared to conventional neural networks models.

Multiple Lower Extremity Mononeuropathies by Segmental Schwannomatosis: A Case Report

PubMed Central

Kwon, Na Yeon; Oh, Hyun-Mi

2015-01-01

Schwannoma is an encapsulated nerve sheath tumor that is distinct from neurofibromatosis. It is defined as the occurrence of multiple schwannomas without any bilateral vestibular schwannomas. A 46-year-old man with multiple schwannomas involving peripheral nerves of the ipsilateral lower extremity presented with neurologic symptoms. Electrodiagnostic studies revealed multiple mononeuropathies involving the left sciatic, common peroneal, tibial, femoral and superior gluteal nerves. Histologic findings confirmed the diagnosis of schwannoma. We reported this rare case of segmental schwannomatosis that presented with neurologic symptoms including motor weakness, which was confirmed as multiple mononeuropathies by electrodiagnostic studies. PMID:26605183

Multiple Lower Extremity Mononeuropathies by Segmental Schwannomatosis: A Case Report.

PubMed

Kwon, Na Yeon; Oh, Hyun-Mi; Ko, Young Jin

2015-10-01

Schwannoma is an encapsulated nerve sheath tumor that is distinct from neurofibromatosis. It is defined as the occurrence of multiple schwannomas without any bilateral vestibular schwannomas. A 46-year-old man with multiple schwannomas involving peripheral nerves of the ipsilateral lower extremity presented with neurologic symptoms. Electrodiagnostic studies revealed multiple mononeuropathies involving the left sciatic, common peroneal, tibial, femoral and superior gluteal nerves. Histologic findings confirmed the diagnosis of schwannoma. We reported this rare case of segmental schwannomatosis that presented with neurologic symptoms including motor weakness, which was confirmed as multiple mononeuropathies by electrodiagnostic studies.

Applications of numerical methods to simulate the movement of contaminants in groundwater.

PubMed Central

Sun, N Z

1989-01-01

This paper reviews mathematical models and numerical methods that have been extensively used to simulate the movement of contaminants through the subsurface. The major emphasis is placed on the numerical methods of advection-dominated transport problems and inverse problems. Several mathematical models that are commonly used in field problems are listed. A variety of numerical solutions for three-dimensional models are introduced, including the multiple cell balance method that can be considered a variation of the finite element method. The multiple cell balance method is easy to understand and convenient for solving field problems. When the advection transport dominates the dispersion transport, two kinds of numerical difficulties, overshoot and numerical dispersion, are always involved in solving standard, finite difference methods and finite element methods. To overcome these numerical difficulties, various numerical techniques are developed, such as upstream weighting methods and moving point methods. A complete review of these methods is given and we also mention the problems of parameter identification, reliability analysis, and optimal-experiment design that are absolutely necessary for constructing a practical model. PMID:2695327

Thermal regulation in multiple-source arc welding involving material transformations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doumanidis, C.C.

1995-06-01

This article addresses regulation of the thermal field generated during arc welding, as the cause of solidification, heat-affected zone and cooling rate related metallurgical transformations affecting the final microstructure and mechanical properties of various welded materials. This temperature field is described by a dynamic real-time process model, consisting of an analytical composite conduction expression for the solid region, and a lumped-state, double-stream circulation model in the weld pool, integrated with a Gaussian heat input and calibrated experimentally through butt joint GMAW tests on plain steel plates. This model serves as the basis of an in-process thermal control system employing feedbackmore » of part surface temperatures measured by infrared pyrometry; and real-time identification of the model parameters with a multivariable adaptive control strategy. Multiple heat inputs and continuous power distributions are implemented by a single time-multiplexed torch, scanning the weld surface to ensure independent, decoupled control of several thermal characteristics. Their regulation is experimentally obtained in longitudinal GTAW of stainless steel pipes, despite the presence of several geometrical, thermal and process condition disturbances of arc welding.« less

NAViGaTing the Micronome – Using Multiple MicroRNA Prediction Databases to Identify Signalling Pathway-Associated MicroRNAs

PubMed Central

Shirdel, Elize A.; Xie, Wing; Mak, Tak W.; Jurisica, Igor

2011-01-01

Background MicroRNAs are a class of small RNAs known to regulate gene expression at the transcript level, the protein level, or both. Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms. We integrate prediction databases, compare predictions to in vitro data, and use cross-database predictions to model the microRNA:transcript interactome – referred to as the micronome – to study microRNA involvement in well-known signalling pathways as well as associations with disease. We make this data freely available with a flexible user interface as our microRNA Data Integration Portal — mirDIP (http://ophid.utoronto.ca/mirDIP). Results mirDIP integrates prediction databases to elucidate accurate microRNA:target relationships. Using NAViGaTOR to produce interaction networks implicating microRNAs in literature-based, KEGG-based and Reactome-based pathways, we find these signalling pathway networks have significantly more microRNA involvement compared to chance (p<0.05), suggesting microRNAs co-target many genes in a given pathway. Further examination of the micronome shows two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets (p<0.0001), to be more studied (p<0.0002), and to have higher degree in the KEGG cancer pathway (p<0.0001), compared to intra-pathway microRNAs. Conclusions Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling. We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level. PMID:21364759

Analysing and correcting the differences between multi-source and multi-scale spatial remote sensing observations.

PubMed

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation.

Analysing and Correcting the Differences between Multi-Source and Multi-Scale Spatial Remote Sensing Observations

PubMed Central

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation. PMID:25405760

Design Requirements for Communication-Intensive Interactive Applications

NASA Astrophysics Data System (ADS)

Bolchini, Davide; Garzotto, Franca; Paolini, Paolo

Online interactive applications call for new requirements paradigms to capture the growing complexity of computer-mediated communication. Crafting successful interactive applications (such as websites and multimedia) involves modeling the requirements for the user experience, including those leading to content design, usable information architecture and interaction, in profound coordination with the communication goals of all stakeholders involved, ranging from persuasion to social engagement, to call for action. To face this grand challenge, we propose a methodology for modeling communication requirements and provide a set of operational conceptual tools to be used in complex projects with multiple stakeholders. Through examples from real-life projects and lessons-learned from direct experience, we draw on the concepts of brand, value, communication goals, information and persuasion requirements to systematically guide analysts to master the multifaceted connections of these elements as drivers to inform successful communication designs.

Estimation of Causal Mediation Effects for a Dichotomous Outcome in Multiple-Mediator Models using the Mediation Formula

PubMed Central

Nelson, Suchitra; Albert, Jeffrey M.

2013-01-01

Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets of mediators using the potential outcomes framework. We formulate a model of joint distribution (probit-normal) using continuous latent variables for any binary mediators to account for correlations among multiple mediators. A mediation formula approach is proposed to estimate the total mediation effect and decomposed mediation effects based on this parametric model. Estimation of mediation effects through individual or subsets of mediators requires an assumption involving the joint distribution of multiple counterfactuals. We conduct a simulation study that demonstrates low bias of mediation effect estimators for two-mediator models with various combinations of mediator types. The results also show that the power to detect a non-zero total mediation effect increases as the correlation coefficient between two mediators increases, while power for individual mediation effects reaches a maximum when the mediators are uncorrelated. We illustrate our approach by applying it to a retrospective cohort study of dental caries in adolescents with low and high socioeconomic status. Sensitivity analysis is performed to assess the robustness of conclusions regarding mediation effects when the assumption of no unmeasured mediator-outcome confounders is violated. PMID:23650048

Estimation of causal mediation effects for a dichotomous outcome in multiple-mediator models using the mediation formula.

PubMed

Wang, Wei; Nelson, Suchitra; Albert, Jeffrey M

2013-10-30

Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets of mediators using the potential outcomes framework. We formulate a model of joint distribution (probit-normal) using continuous latent variables for any binary mediators to account for correlations among multiple mediators. A mediation formula approach is proposed to estimate the total mediation effect and decomposed mediation effects based on this parametric model. Estimation of mediation effects through individual or subsets of mediators requires an assumption involving the joint distribution of multiple counterfactuals. We conduct a simulation study that demonstrates low bias of mediation effect estimators for two-mediator models with various combinations of mediator types. The results also show that the power to detect a nonzero total mediation effect increases as the correlation coefficient between two mediators increases, whereas power for individual mediation effects reaches a maximum when the mediators are uncorrelated. We illustrate our approach by applying it to a retrospective cohort study of dental caries in adolescents with low and high socioeconomic status. Sensitivity analysis is performed to assess the robustness of conclusions regarding mediation effects when the assumption of no unmeasured mediator-outcome confounders is violated. Copyright © 2013 John Wiley & Sons, Ltd.

Modeling the Impact of Motivation, Personality, and Emotion on Social Behavior

NASA Astrophysics Data System (ADS)

Miller, Lynn C.; Read, Stephen J.; Zachary, Wayne; Rosoff, Andrew

Models seeking to predict human social behavior must contend with multiple sources of individual and group variability that underlie social behavior. One set of interrelated factors that strongly contribute to that variability - motivations, personality, and emotions - has been only minimally incorporated in previous computational models of social behavior. The Personality, Affect, Culture (PAC) framework is a theory-based computational model that addresses this gap. PAC is used to simulate social agents whose social behavior varies according to their personalities and emotions, which, in turn, vary according to their motivations and underlying motive control parameters. Examples involving disease spread and counter-insurgency operations show how PAC can be used to study behavioral variability in different social contexts.

Business process modeling in healthcare.

PubMed

Ruiz, Francisco; Garcia, Felix; Calahorra, Luis; Llorente, César; Gonçalves, Luis; Daniel, Christel; Blobel, Bernd

2012-01-01

The importance of the process point of view is not restricted to a specific enterprise sector. In the field of health, as a result of the nature of the service offered, health institutions' processes are also the basis for decision making which is focused on achieving their objective of providing quality medical assistance. In this chapter the application of business process modelling - using the Business Process Modelling Notation (BPMN) standard is described. Main challenges of business process modelling in healthcare are the definition of healthcare processes, the multi-disciplinary nature of healthcare, the flexibility and variability of the activities involved in health care processes, the need of interoperability between multiple information systems, and the continuous updating of scientific knowledge in healthcare.

Improved Algorithms for Blending Dam Releases to Meet Downstream Water-Temperature Targets in the CE-QUAL-W2 Water-Quality Model

NASA Astrophysics Data System (ADS)

Rounds, S. A.; Buccola, N. L.

2014-12-01

The two-dimensional (longitudinal, vertical) water-quality model CE-QUAL-W2, version 3.7, was enhanced with new features to help dam operators and managers efficiently explore and optimize potential solutions for temperature management downstream of thermally stratified reservoirs. Such temperature management often is accomplished by blending releases from multiple dam outlets that access water of different temperatures at different depths in the reservoir. The original blending algorithm in this version of the model was limited to mixing releases from two outlets at a time, and few constraints could be imposed. The new enhanced blending algorithm allows the user to (1) specify a time-series of target release temperatures, (2) designate from 2 to 10 floating or fixed-elevation outlets for blending, (3) impose maximum head constraints as well as minimum and maximum flow constraints for any blended outlet, and (4) set a priority designation for each outlet that allows the model to choose which outlets to use and how to balance releases among them. The modified model was tested against a previously calibrated model of Detroit Lake on the North Santiam River in northwestern Oregon, and the results compared well. The enhanced model code is being used to evaluate operational and structural scenarios at multiple dam/reservoir systems in the Willamette River basin in Oregon, where downstream temperature management for endangered fish is a high priority for resource managers and dam operators. These updates to the CE-QUAL-W2 blending algorithm allow scenarios involving complicated dam operations and/or hypothetical outlet structures to be evaluated more efficiently with the model, with decreased need for multiple/iterative model runs or preprocessing of model inputs to fully characterize the operational constraints.

Force-Manipulation Single-Molecule Spectroscopy Studies of Enzymatic Dynamics

NASA Astrophysics Data System (ADS)

Lu, H. Peter; He, Yufan; Lu, Maolin; Cao, Jin; Guo, Qing

2014-03-01

Subtle conformational changes play a crucial role in protein functions, especially in enzymatic reactions involving complex substrate-enzyme interactions and chemical reactions. We applied AFM-enhanced and magnetic tweezers-correlated single-molecule spectroscopy to study the mechanisms and dynamics of enzymatic reactions involved with kinase and lysozyme proteins. Enzymatic reaction turnovers and the associated structure changes of individual protein molecules were observed simultaneously in real-time by single-molecule FRET detections. Our single-molecule spectroscopy measurements of enzymatic conformational dynamics have revealed time bunching effect and intermittent coherence in conformational state change dynamics involving in enzymatic reaction cycles. The coherent conformational state dynamics suggests that the enzymatic catalysis involves a multi-step conformational motion along the coordinates of substrate-enzyme complex formation and product releasing. Our results support a multiple-conformational state model, being consistent with a complementary conformation selection and induced-fit enzymatic loop-gated conformational change mechanism in substrate-enzyme active complex formation.

Testing of Environmental Satellite Bus-Instrument Interfaces Using Engineering Models

NASA Technical Reports Server (NTRS)

Gagnier, Donald; Hayner, Rick; Nosek, Thomas; Roza, Michael; Hendershot, James E.; Razzaghi, Andrea I.

2004-01-01

This paper discusses the formulation and execution of a laboratory test of the electrical interfaces between multiple atmospheric scientific instruments and the spacecraft bus that carries them. The testing, performed in 2002, used engineering models of the instruments and the Aura spacecraft bus electronics. Aura is one of NASA s Earth Observatory System missions. The test was designed to evaluate the complex interfaces in the command and data handling subsystems prior to integration of the complete flight instruments on the spacecraft. A problem discovered during the flight integration phase of the observatory can cause significant cost and schedule impacts. The tests successfully revealed problems and led to their resolution before the full-up integration phase, saving significant cost and schedule. This approach could be beneficial for future environmental satellite programs involving the integration of multiple, complex scientific instruments onto a spacecraft bus.

Dynamical correlation effects on photoisomerization: Ab initio multiple spawning dynamics with MS-CASPT2 for a model trans-protonated Schiff base

DOE PAGES

Liu, Lihong; Liu, Jian; Martinez, Todd J.

2015-12-17

Here, we investigate the photoisomerization of a model retinal protonated Schiff base (trans-PSB3) using ab initio multiple spawning (AIMS) based on multi-state second order perturbation theory (MSPT2). Discrepancies between the photodynamical mechanism computed with three-root state-averaged complete active space self-consistent field (SA-3-CASSCF, which does not include dynamic electron correlation effects) and MSPT2 show that dynamic correlation is critical in this photoisomerization reaction. Furthermore, we show that the photodynamics of trans-PSB3 is not well described by predictions based on minimum energy conical intersections (MECIs) or minimum energy conical intersection (CI) seam paths. Instead, most of the CIs involved in the photoisomerizationmore » are far from MECIs and minimum energy CI seam paths. Thus, both dynamical nuclear effects and dynamic electron correlation are critical to understanding the photochemical mechanism.« less

Social Identity in People with Multiple Sclerosis: An Examination of Family Identity and Mood.

PubMed

Barker, Alex B; Lincoln, Nadina B; Hunt, Nigel; dasNair, Roshan

2018-01-01

Mood disorders are highly prevalent in people with multiple sclerosis (MS). MS causes changes to a person's sense of self. The Social Identity Model of Identity Change posits that group membership can have a positive effect on mood during identity change. The family is a social group implicated in adjustment to MS. The objectives of this study were to investigate whether family identity can predict mood in people with MS and to test whether this prediction was mediated by social support and connectedness to others. This cross-sectional survey of 195 participants comprised measures of family identity, family social support, connectedness to others, and mood. Family identity predicted mood both directly and indirectly through parallel mediators of family social support and connectedness to others. Family identity predicted mood as posited by the Social Identity Model of Identity Change. Involving the family in adjustment to MS could reduce low mood.

Methods for understanding super-efficient data envelopment analysis results with an application to hospital inpatient surgery.

PubMed

O'Neill, Liam; Dexter, Franklin

2005-11-01

We compare two techniques for increasing the transparency and face validity of Data Envelopment Analysis (DEA) results for managers at a single decision-making unit: multifactor efficiency (MFE) and non-radial super-efficiency (NRSE). Both methods incorporate the slack values from the super-efficient DEA model to provide a more robust performance measure than radial super-efficiency scores. MFE and NRSE are equivalent for unique optimal solutions and a single output. MFE incorporates the slack values from multiple output variables, whereas NRSE does not. MFE can be more transparent to managers since it involves no additional optimization steps beyond the DEA, whereas NRSE requires several. We compare results for operating room managers at an Iowa hospital evaluating its growth potential for multiple surgical specialties. In addition, we address the problem of upward bias of the slack values of the super-efficient DEA model.

Matching multiple rigid domain decompositions of proteins

PubMed Central

Flynn, Emily; Streinu, Ileana

2017-01-01

We describe efficient methods for consistently coloring and visualizing collections of rigid cluster decompositions obtained from variations of a protein structure, and lay the foundation for more complex setups that may involve different computational and experimental methods. The focus here is on three biological applications: the conceptually simpler problems of visualizing results of dilution and mutation analyses, and the more complex task of matching decompositions of multiple NMR models of the same protein. Implemented into the KINARI web server application, the improved visualization techniques give useful information about protein folding cores, help examining the effect of mutations on protein flexibility and function, and provide insights into the structural motions of PDB proteins solved with solution NMR. These tools have been developed with the goal of improving and validating rigidity analysis as a credible coarse-grained model capturing essential information about a protein’s slow motions near the native state. PMID:28141528

EG-VEGF Maintenance Over Early Gestation to Develop a Pregnancy-Induced Hypertensive Animal Model.

PubMed

Reynaud, Déborah; Sergent, Frédéric; Abi Nahed, Roland; Brouillet, Sophie; Benharouga, Mohamed; Alfaidy, Nadia

2018-01-01

During the last decade, multiple animal models have been developed to mimic hallmarks of pregnancy-induced hypertension (PIH) diseases, which include gestational hypertension, preeclampsia (PE), or eclampsia. Converging in vitro, ex vivo, and clinical studies from our group strongly suggested the potential involvement of the new angiogenic factor EG-VEGF (endocrine gland-derived-VEGF) in the development of PIH. Here, we described the protocol that served to demonstrate that maintenance of EG-VEGF production over 11.5 days post coitus (dpc) in the gravid mice caused the development of PIH. The developed model exhibited most hallmarks of preeclampsia.

The origin of mass

NASA Astrophysics Data System (ADS)

Froggatt*, C. D.

2003-01-01

The quark-lepton mass problem and the ideas of mass protection are reviewed. The hierarchy problem and suggestions for its resolution, including Little Higgs models, are discussed. The Multiple Point Principle (MPP) is introduced and used within the Standard Model (SM) to predict the top quark and Higgs particle masses. Mass matrix ansätze are considered; in particular we discuss the lightest family mass generation model, in which all the quark mixing angles are successfully expressed in terms of simple expressions involving quark mass ratios. It is argued that an underlying chiral flavour symmetry is responsible for the hierarchical texture of the fermion mass matrices. The phenomenology of neutrino mass matrices is briefly discussed.

FIRE Science Results 1989

NASA Technical Reports Server (NTRS)

Mcdougal, David S. (Editor)

1990-01-01

FIRE (First ISCCP Regional Experiment) is a U.S. cloud-radiation research program formed in 1984 to increase the basic understanding of cirrus and marine stratocumulus cloud systems, to develop realistic parameterizations for these systems, and to validate and improve ISCCP cloud product retrievals. Presentations of results culminating the first 5 years of FIRE research activities were highlighted. The 1986 Cirrus Intensive Field Observations (IFO), the 1987 Marine Stratocumulus IFO, the Extended Time Observations (ETO), and modeling activities are described. Collaborative efforts involving the comparison of multiple data sets, incorporation of data measurements into modeling activities, validation of ISCCP cloud parameters, and development of parameterization schemes for General Circulation Models (GCMs) are described.

Memory interface simulator: A computer design aid

NASA Technical Reports Server (NTRS)

Taylor, D. S.; Williams, T.; Weatherbee, J. E.

1972-01-01

Results are presented of a study conducted with a digital simulation model being used in the design of the Automatically Reconfigurable Modular Multiprocessor System (ARMMS), a candidate computer system for future manned and unmanned space missions. The model simulates the activity involved as instructions are fetched from random access memory for execution in one of the system central processing units. A series of model runs measured instruction execution time under various assumptions pertaining to the CPU's and the interface between the CPU's and RAM. Design tradeoffs are presented in the following areas: Bus widths, CPU microprogram read only memory cycle time, multiple instruction fetch, and instruction mix.

Inter-organizational network in Indonesia during disasters: Examples and research agenda on disaster management

NASA Astrophysics Data System (ADS)

Bisri, M. B. F.

2017-02-01

Indonesia is facing various type of disaster risks, each with its own nature (sudden or slow onset, purely natural or man-made) and coverage of affected areas. Whereas science, technology and engineering intervention requires different modalities for each hazard, little has been known on whether the institutional setup and organizations involvement requires a different or similar types of intervention. Under a decentralized disaster management system, potential involvement of international organizations in response and growing diversified organizations involved in responding to disaster, it is important to understand the nature of inter-organizational network during various type of disasters in Indonesia. This paper is mixture of in-depth literature review and multiple case studies on utilization of social network analysis (SNA) in modelling inter-organizational network during various disasters in Indonesia.

Distinct representations of subtraction and multiplication in the neural systems for numerosity and language

PubMed Central

Prado, Jérôme; Mutreja, Rachna; Zhang, Hongchuan; Mehta, Rucha; Desroches, Amy S.; Minas, Jennifer E.; Booth, James R.

2010-01-01

It has been proposed that recent cultural inventions such as symbolic arithmetic recycle evolutionary older neural mechanisms. A central assumption of this hypothesis is that the degree to which a pre-existing mechanism is recycled depends upon the degree of similarity between its initial function and the novel task. To test this assumption, we investigated whether the brain region involved in magnitude comparison in the intraparietal sulcus (IPS), localized by a numerosity comparison task, is recruited to a greater degree by arithmetic problems that involve number comparison (single-digit subtractions) than by problems that involve retrieving facts from memory (single-digit multiplications). Our results confirmed that subtractions are associated with greater activity in the IPS than multiplications, whereas multiplications elicit greater activity than subtractions in regions involved in verbal processing including the middle temporal gyrus and inferior frontal gyrus that were localized by a phonological processing task. Pattern analyses further indicated that the neural mechanisms more active for subtraction than multiplication in the IPS overlap with those involved in numerosity comparison, and that the strength of this overlap predicts inter-individual performance in the subtraction task. These findings provide novel evidence that elementary arithmetic relies on the co-option of evolutionary older neural circuits. PMID:21246667

Vestibular evoked myogenic potentials and MRI in early multiple sclerosis: Validation of the VEMP score.

PubMed

Crnošija, Luka; Krbot Skorić, Magdalena; Gabelić, Tereza; Adamec, Ivan; Habek, Mario

2017-01-15

To validate the VEMP score as a measure of brainstem dysfunction in patients with the first symptom of multiple sclerosis (MS) (clinically isolated syndrome (CIS)) and to investigate the correlation between VEMP and brainstem MRI results. 121 consecutive CIS patients were enrolled and brainstem functional system score (BSFS) was determined. Ocular VEMP (oVEMP) and cervical VEMP (cVEMP) were analyzed for latencies, conduction block and amplitude asymmetry ratio and the VEMP score was calculated. MRI was analyzed for the presence of brainstem lesions as a whole and separately for the presence of pontine, midbrain and medulla oblongata lesions. Patients with signs of brainstem involvement during the neurological examination (with BSFS ≥1) had a higher oVEMP score compared to patients with no signs of brainstem involvement. A binary logistic regression model showed that patients with brainstem lesion on the MRI are 6.780 times more likely to have BSFS ≥1 (p=0.001); and also, a higher VEMP score is associated with BSFS ≥1 (p=0.042). Furthermore, significant correlations were found between clinical brainstem involvement and brainstem and pontine MRI lesions, and prolonged latencies and/or absent VEMP responses. The VEMP score is a valuable tool in evaluation of brainstem involvement in patients with early MS. Copyright © 2016 Elsevier B.V. All rights reserved.

Angular intensity and polarization dependence of diffuse transmission through random media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eliyahu, D.; Rosenbluh, M.; Feund, I.

1993-03-01

A simple theoretical model involving only a single sample parameter, the depolarization ratio [rho] for linearly polarized normally incident and normally scattered light, is developed to describe the angular intensity and all other polarization-dependent properties of diffuse transmission through multiple-scattering media. Initial experimental results that tend to support the theory are presented. Results for diffuse reflection are also described. 63 refs., 15 figs.

A one-dimensional peridynamic model of defect propagation and its relation to certain other continuum models

NASA Astrophysics Data System (ADS)

Wang, Linjuan; Abeyaratne, Rohan

2018-07-01

The peridynamic model of a solid does not involve spatial gradients of the displacement field and is therefore well suited for studying defect propagation. Here, bond-based peridynamic theory is used to study the equilibrium and steady propagation of a lattice defect - a kink - in one dimension. The material transforms locally, from one state to another, as the kink passes through. The kink is in equilibrium if the applied force is less than a certain critical value that is calculated, and propagates if it exceeds that value. The kinetic relation giving the propagation speed as a function of the applied force is also derived. In addition, it is shown that the dynamical solutions of certain differential-equation-based models of a continuum are the same as those of the peridynamic model provided the micromodulus function is chosen suitably. A formula for calculating the micromodulus function of the equivalent peridynamic model is derived and illustrated. This ability to replace a differential-equation-based model with a peridynamic one may prove useful when numerically studying more complicated problems such as those involving multiple and interacting defects.

An intermolecular binding mechanism involving multiple LysM domains mediates carbohydrate recognition by an endopeptidase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wong, Jaslyn E. M. M.; Midtgaard, Søren Roi; Gysel, Kira

The crystal and solution structures of the T. thermophilus NlpC/P60 d, l-endopeptidase as well as the co-crystal structure of its N-terminal LysM domains bound to chitohexaose allow a proposal to be made regarding how the enzyme recognizes peptidoglycan. LysM domains, which are frequently present as repetitive entities in both bacterial and plant proteins, are known to interact with carbohydrates containing N-acetylglucosamine (GlcNAc) moieties, such as chitin and peptidoglycan. In bacteria, the functional significance of the involvement of multiple LysM domains in substrate binding has so far lacked support from high-resolution structures of ligand-bound complexes. Here, a structural study of themore » Thermus thermophilus NlpC/P60 endopeptidase containing two LysM domains is presented. The crystal structure and small-angle X-ray scattering solution studies of this endopeptidase revealed the presence of a homodimer. The structure of the two LysM domains co-crystallized with N-acetyl-chitohexaose revealed a new intermolecular binding mode that may explain the differential interaction between LysM domains and short or long chitin oligomers. By combining the structural information with the three-dimensional model of peptidoglycan, a model suggesting how protein dimerization enhances the recognition of peptidoglycan is proposed.« less

Glycogen synthase kinase 3: more than a namesake

PubMed Central

Rayasam, Geetha Vani; Tulasi, Vamshi Krishna; Sodhi, Reena; Davis, Joseph Alex; Ray, Abhijit

2009-01-01

Glycogen synthase kinase 3 (GSK3), a constitutively acting multi-functional serine threonine kinase is involved in diverse physiological pathways ranging from metabolism, cell cycle, gene expression, development and oncogenesis to neuroprotection. These diverse multiple functions attributed to GSK3 can be explained by variety of substrates like glycogen synthase, τ protein and β catenin that are phosphorylated leading to their inactivation. GSK3 has been implicated in various diseases such as diabetes, inflammation, cancer, Alzheimer's and bipolar disorder. GSK3 negatively regulates insulin-mediated glycogen synthesis and glucose homeostasis, and increased expression and activity of GSK3 has been reported in type II diabetics and obese animal models. Consequently, inhibitors of GSK3 have been demonstrated to have anti-diabetic effects in vitro and in animal models. However, inhibition of GSK3 poses a challenge as achieving selectivity of an over achieving kinase involved in various pathways with multiple substrates may lead to side effects and toxicity. The primary concern is developing inhibitors of GSK3 that are anti-diabetic but do not lead to up-regulation of oncogenes. The focus of this review is the recent advances and the challenges surrounding GSK3 as an anti-diabetic therapeutic target. British Journal of Pharmacology (2009) doi:10.1111/j.1476-5381.2008.00085.x PMID:19366350

Dissecting DNA repair in adult high grade gliomas for patient stratification in the post-genomic era

PubMed Central

Perry, Christina; Agarwal, Devika; Abdel-Fatah, Tarek M.A.; Lourdusamy, Anbarasu; Grundy, Richard; Auer, Dorothee T.; Walker, David; Lakhani, Ravi; Scott, Ian S.; Chan, Stephen; Ball, Graham; Madhusudan, Srinivasan

2014-01-01

Deregulation of multiple DNA repair pathways may contribute to aggressive biology and therapy resistance in gliomas. We evaluated transcript levels of 157 genes involved in DNA repair in an adult glioblastoma Test set (n=191) and validated in ‘The Cancer Genome Atlas’ (TCGA) cohort (n=508). A DNA repair prognostic index model was generated. Artificial neural network analysis (ANN) was conducted to investigate global gene interactions. Protein expression by immunohistochemistry was conducted in 61 tumours. A fourteen DNA repair gene expression panel was associated with poor survival in Test and TCGA cohorts. A Cox multivariate model revealed APE1, NBN, PMS2, MGMT and PTEN as independently associated with poor prognosis. A DNA repair prognostic index incorporating APE1, NBN, PMS2, MGMT and PTEN stratified patients in to three prognostic sub-groups with worsening survival. APE1, NBN, PMS2, MGMT and PTEN also have predictive significance in patients who received chemotherapy and/or radiotherapy. ANN analysis of APE1, NBN, PMS2, MGMT and PTEN revealed interactions with genes involved in transcription, hypoxia and metabolic regulation. At the protein level, low APE1 and low PTEN remain associated with poor prognosis. In conclusion, multiple DNA repair pathways operate to influence biology and clinical outcomes in adult high grade gliomas. PMID:25026297

An integrated GIS-based data model for multimodal urban public transportation analysis and management

NASA Astrophysics Data System (ADS)

Chen, Shaopei; Tan, Jianjun; Ray, C.; Claramunt, C.; Sun, Qinqin

2008-10-01

Diversity is one of the main characteristics of transportation data collected from multiple sources or formats, which can be extremely complex and disparate. Moreover, these multimodal transportation data are usually characterised by spatial and temporal properties. Multimodal transportation network data modelling involves both an engineering and research domain that has attracted the design of a number of spatio-temporal data models in the geographic information system (GIS). However, the application of these specific models to multimodal transportation network is still a challenging task. This research addresses this challenge from both integrated multimodal data organization and object-oriented modelling perspectives, that is, how a complex urban transportation network should be organized, represented and modeled appropriately when considering a multimodal point of view, and using object-oriented modelling method. We proposed an integrated GIS-based data model for multimodal urban transportation network that lays a foundation to enhance the multimodal transportation network analysis and management. This modelling method organizes and integrates multimodal transit network data, and supports multiple representations for spatio-temporal objects and relationship as both visual and graphic views. The data model is expressed by using a spatio-temporal object-oriented modelling method, i.e., the unified modelling language (UML) extended to spatial and temporal plug-in for visual languages (PVLs), which provides an essential support to the spatio-temporal data modelling for transportation GIS.

Automated platform for designing multiple robot work cells

NASA Astrophysics Data System (ADS)

Osman, N. S.; Rahman, M. A. A.; Rahman, A. A. Abdul; Kamsani, S. H.; Bali Mohamad, B. M.; Mohamad, E.; Zaini, Z. A.; Rahman, M. F. Ab; Mohamad Hatta, M. N. H.

2017-06-01

Designing the multiple robot work cells is very knowledge-intensive, intricate, and time-consuming process. This paper elaborates the development process of a computer-aided design program for generating the multiple robot work cells which offer a user-friendly interface. The primary purpose of this work is to provide a fast and easy platform for less cost and human involvement with minimum trial and errors adjustments. The automated platform is constructed based on the variant-shaped configuration concept with its mathematical model. A robot work cell layout, system components, and construction procedure of the automated platform are discussed in this paper where integration of these items will be able to automatically provide the optimum robot work cell design according to the information set by the user. This system is implemented on top of CATIA V5 software and utilises its Part Design, Assembly Design, and Macro tool. The current outcomes of this work provide a basis for future investigation in developing a flexible configuration system for the multiple robot work cells.

Safinamide and flecainide protect axons and reduce microglial activation in models of multiple sclerosis.

PubMed

Morsali, Damineh; Bechtold, David; Lee, Woojin; Chauhdry, Summen; Palchaudhuri, Upayan; Hassoon, Paula; Snell, Daniel M; Malpass, Katy; Piers, Thomas; Pocock, Jennifer; Roach, Arthur; Smith, Kenneth J

2013-04-01

Axonal degeneration is a major cause of permanent disability in the inflammatory demyelinating disease multiple sclerosis, but no therapies are known to be effective in axonal protection. Sodium channel blocking agents can provide effective protection of axons in the white matter in experimental models of multiple sclerosis, but the mechanism of action (directly on axons or indirectly via immune modulation) remains uncertain. Here we have examined the efficacy of two sodium channel blocking agents to protect white matter axons in two forms of experimental autoimmune encephalomyelitis, a common model of multiple sclerosis. Safinamide is currently in phase III development for use in Parkinson's disease based on its inhibition of monoamine oxidase B, but the drug is also a potent state-dependent inhibitor of sodium channels. Safinamide provided significant protection against neurological deficit and axonal degeneration in experimental autoimmune encephalomyelitis, even when administration was delayed until after the onset of neurological deficit. Protection of axons was associated with a significant reduction in the activation of microglia/macrophages within the central nervous system. To clarify which property of safinamide was likely to be involved in the suppression of the innate immune cells, the action of safinamide on microglia/macrophages was compared with that of the classical sodium channel blocking agent, flecainide, which has no recognized monoamine oxidase B activity, and which has previously been shown to protect the white matter in experimental autoimmune encephalomyelitis. Flecainide was also potent in suppressing microglial activation in experimental autoimmune encephalomyelitis. To distinguish whether the suppression of microglia was an indirect consequence of the reduction in axonal damage, or possibly instrumental in the axonal protection, the action of safinamide was examined in separate experiments in vitro. In cultured primary rat microglial cells activated by lipopolysaccharide, safinamide potently suppressed microglial superoxide production and enhanced the production of the anti-oxidant glutathione. The findings show that safinamide is effective in protecting axons from degeneration in experimental autoimmune encephalomyelitis, and that this effect is likely to involve a direct effect on microglia that can result in a less activated phenotype. Together, this work highlights the potential of safinamide as an effective neuroprotective agent in multiple sclerosis, and implicates microglia in the protective mechanism.

Model observer design for multi-signal detection in the presence of anatomical noise

NASA Astrophysics Data System (ADS)

Wen, Gezheng; Markey, Mia K.; Park, Subok

2017-02-01

As psychophysical studies are resource-intensive to conduct, model observers are commonly used to assess and optimize medical imaging quality. Model observers are typically designed to detect at most one signal. However, in clinical practice, there may be multiple abnormalities in a single image set (e.g. multifocal multicentric (MFMC) breast cancer), which can impact treatment planning. Prevalence of signals can be different across anatomical regions, and human observers do not know the number or location of signals a priori. As new imaging techniques have the potential to improve multiple-signal detection (e.g. digital breast tomosynthesis may be more effective for diagnosis of MFMC than mammography), image quality assessment approaches addressing such tasks are needed. In this study, we present a model observer to detect multiple signals in an image dataset. A novel implementation of partial least squares (PLS) was developed to estimate different sets of efficient channels directly from the images. The PLS channels are adaptive to the characteristics of signals and the background, and they capture the interactions among signal locations. Corresponding linear decision templates are employed to generate both image-level and location-specific scores on the presence of signals. Our results show that: (1) the model observer can achieve high performance with a reasonably small number of channels; (2) the model observer with PLS channels outperforms that with benchmark modified Laguerre-Gauss channels, especially when realistic signal shapes and complex background statistics are involved; (3) the tasks of clinical interest, and other constraints such as sample size would alter the optimal design of the model observer.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adam, J. C.; Stephens, J. C.; Chung, Serena

As managers of agricultural and natural resources are confronted with uncertainties in global change impacts, the complexities associated with the interconnected cycling of nitrogen, carbon, and water present daunting management challenges. Existing models provide detailed information on specific sub-systems (land, air, water, economics, etc). An increasing awareness of the unintended consequences of management decisions resulting from interconnectedness of these sub-systems, however, necessitates coupled regional earth system models (EaSMs). Decision makers’ needs and priorities can be integrated into the model design and development processes to enhance decision-making relevance and "usability" of EaSMs. BioEarth is a current research initiative with a focusmore » on the U.S. Pacific Northwest region that explores the coupling of multiple stand-alone EaSMs to generate usable information for resource decision-making. Direct engagement between model developers and non-academic stakeholders involved in resource and environmental management decisions throughout the model development process is a critical component of this effort. BioEarth utilizes a "bottom-up" approach, upscaling a catchment-scale model to basin and regional scales, as opposed to the "top-down" approach of downscaling global models utilized by most other EaSM efforts. This paper describes the BioEarth initiative and highlights opportunities and challenges associated with coupling multiple stand-alone models to generate usable information for agricultural and natural resource decision-making.« less

Applications of the BIOPHYS Algorithm for Physically-Based Retrieval of Biophysical, Structural and Forest Disturbance Information

NASA Technical Reports Server (NTRS)

Peddle, Derek R.; Huemmrich, K. Fred; Hall, Forrest G.; Masek, Jeffrey G.; Soenen, Scott A.; Jackson, Chris D.

2011-01-01

Canopy reflectance model inversion using look-up table approaches provides powerful and flexible options for deriving improved forest biophysical structural information (BSI) compared with traditional statistical empirical methods. The BIOPHYS algorithm is an improved, physically-based inversion approach for deriving BSI for independent use and validation and for monitoring, inventory and quantifying forest disturbance as well as input to ecosystem, climate and carbon models. Based on the multiple-forward mode (MFM) inversion approach, BIOPHYS results were summarized from different studies (Minnesota/NASA COVER; Virginia/LEDAPS; Saskatchewan/BOREAS), sensors (airborne MMR; Landsat; MODIS) and models (GeoSail; GOMS). Applications output included forest density, height, crown dimension, branch and green leaf area, canopy cover, disturbance estimates based on multi-temporal chronosequences, and structural change following recovery from forest fires over the last century. Good correspondences with validation field data were obtained. Integrated analyses of multiple solar and view angle imagery further improved retrievals compared with single pass data. Quantifying ecosystem dynamics such as the area and percent of forest disturbance, early regrowth and succession provide essential inputs to process-driven models of carbon flux. BIOPHYS is well suited for large-area, multi-temporal applications involving multiple image sets and mosaics for assessing vegetation disturbance and quantifying biophysical structural dynamics and change. It is also suitable for integration with forest inventory, monitoring, updating, and other programs.

Antimicrobial combinations: Bliss independence and Loewe additivity derived from mechanistic multi-hit models

PubMed Central

Yu, Guozhi; Hozé, Nathanaël; Rolff, Jens

2016-01-01

Antimicrobial peptides (AMPs) and antibiotics reduce the net growth rate of bacterial populations they target. It is relevant to understand if effects of multiple antimicrobials are synergistic or antagonistic, in particular for AMP responses, because naturally occurring responses involve multiple AMPs. There are several competing proposals describing how multiple types of antimicrobials add up when applied in combination, such as Loewe additivity or Bliss independence. These additivity terms are defined ad hoc from abstract principles explaining the supposed interaction between the antimicrobials. Here, we link these ad hoc combination terms to a mathematical model that represents the dynamics of antimicrobial molecules hitting targets on bacterial cells. In this multi-hit model, bacteria are killed when a certain number of targets are hit by antimicrobials. Using this bottom-up approach reveals that Bliss independence should be the model of choice if no interaction between antimicrobial molecules is expected. Loewe additivity, on the other hand, describes scenarios in which antimicrobials affect the same components of the cell, i.e. are not acting independently. While our approach idealizes the dynamics of antimicrobials, it provides a conceptual underpinning of the additivity terms. The choice of the additivity term is essential to determine synergy or antagonism of antimicrobials. This article is part of the themed issue ‘Evolutionary ecology of arthropod antimicrobial peptides’. PMID:27160596

Motor correlates of models of secondary bilateral synchrony and multiple epileptic foci.

PubMed

Jiruska, Premysl; Proks, Jan; Otáhal, Jakub; Mares, Pavel

2007-10-01

Bilateral synchronous epileptiform discharges registered in patients with partial epilepsies may be generated by different pathophysiological mechanisms. Differentiation between underlying mechanisms is often crucial for correct diagnosis and adequate treatment in clinical epileptology. The aim of this study was to model in rats two possible mechanisms--secondary bilateral sychrony and interaction between multiple epilepic foci. Furthermore, to describe in detail semiology, laterality and differences in motor phenomena. Secondary bilateral synchrony was modeled by unilateral topical application of bicuculline methiodide (BMI) over the sensorimotor cortex. Bilateral symmetric application of BMI was used as a model of multiple epileptic foci. Electrographic and behavioural phenomena were recorded for 1h following the application of BMI. Electroencephalogram in both groups was characterized by presence of bilateral synchronous discharges. Myoclonic and clonic seizures involving forelimb and head muscles represented the most common motor seizure pattern in both groups. Significant differences were found in the laterality of motor phenomena. Motor seizures in unilateral foci always started in the contralateral limbs whereas symmetrical foci exhibited bilateral independent onset of convulsions. Similar lateralization was observed in interictal motor phenomena (myoclonic jerks). An important influence of posture on epileptic motor phenomena was demonstrated. Active or passive changes in animal posture (verticalization to bipedal posture) caused conversion from unilateral myoclonic jerks or clonic seizures to bilaterally synchronous (generalized) motor phenomena in both groups.

Introduction to bioinformatics.

PubMed

Can, Tolga

2014-01-01

Bioinformatics is an interdisciplinary field mainly involving molecular biology and genetics, computer science, mathematics, and statistics. Data intensive, large-scale biological problems are addressed from a computational point of view. The most common problems are modeling biological processes at the molecular level and making inferences from collected data. A bioinformatics solution usually involves the following steps: Collect statistics from biological data. Build a computational model. Solve a computational modeling problem. Test and evaluate a computational algorithm. This chapter gives a brief introduction to bioinformatics by first providing an introduction to biological terminology and then discussing some classical bioinformatics problems organized by the types of data sources. Sequence analysis is the analysis of DNA and protein sequences for clues regarding function and includes subproblems such as identification of homologs, multiple sequence alignment, searching sequence patterns, and evolutionary analyses. Protein structures are three-dimensional data and the associated problems are structure prediction (secondary and tertiary), analysis of protein structures for clues regarding function, and structural alignment. Gene expression data is usually represented as matrices and analysis of microarray data mostly involves statistics analysis, classification, and clustering approaches. Biological networks such as gene regulatory networks, metabolic pathways, and protein-protein interaction networks are usually modeled as graphs and graph theoretic approaches are used to solve associated problems such as construction and analysis of large-scale networks.

System Dynamics Modeling for Public Health: Background and Opportunities

PubMed Central

Homer, Jack B.; Hirsch, Gary B.

2006-01-01

The systems modeling methodology of system dynamics is well suited to address the dynamic complexity that characterizes many public health issues. The system dynamics approach involves the development of computer simulation models that portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance. System dynamics modeling of chronic disease prevention should seek to incorporate all the basic elements of a modern ecological approach, including disease outcomes, health and risk behaviors, environmental factors, and health-related resources and delivery systems. System dynamics shows promise as a means of modeling multiple interacting diseases and risks, the interaction of delivery systems and diseased populations, and matters of national and state policy. PMID:16449591

Multiple Correlation versus Multiple Regression.

ERIC Educational Resources Information Center

Huberty, Carl J.

2003-01-01

Describes differences between multiple correlation analysis (MCA) and multiple regression analysis (MRA), showing how these approaches involve different research questions and study designs, different inferential approaches, different analysis strategies, and different reported information. (SLD)

Comparing multiple statistical methods for inverse prediction in nuclear forensics applications

DOE PAGES

Lewis, John R.; Zhang, Adah; Anderson-Cook, Christine Michaela

2017-10-29

Forensic science seeks to predict source characteristics using measured observables. Statistically, this objective can be thought of as an inverse problem where interest is in the unknown source characteristics or factors ( X) of some underlying causal model producing the observables or responses (Y = g ( X) + error). Here, this paper reviews several statistical methods for use in inverse problems and demonstrates that comparing results from multiple methods can be used to assess predictive capability. Motivation for assessing inverse predictions comes from the desired application to historical and future experiments involving nuclear material production for forensics research inmore » which inverse predictions, along with an assessment of predictive capability, are desired.« less

Comparing multiple statistical methods for inverse prediction in nuclear forensics applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewis, John R.; Zhang, Adah; Anderson-Cook, Christine Michaela

Forensic science seeks to predict source characteristics using measured observables. Statistically, this objective can be thought of as an inverse problem where interest is in the unknown source characteristics or factors ( X) of some underlying causal model producing the observables or responses (Y = g ( X) + error). Here, this paper reviews several statistical methods for use in inverse problems and demonstrates that comparing results from multiple methods can be used to assess predictive capability. Motivation for assessing inverse predictions comes from the desired application to historical and future experiments involving nuclear material production for forensics research inmore » which inverse predictions, along with an assessment of predictive capability, are desired.« less

Interaction dynamics of multiple autonomous mobile robots in bounded spatial domains

NASA Technical Reports Server (NTRS)

Wang, P. K. C.

1989-01-01

A general navigation strategy for multiple autonomous robots in a bounded domain is developed analytically. Each robot is modeled as a spherical particle (i.e., an effective spatial domain about the center of mass); its interactions with other robots or with obstacles and domain boundaries are described in terms of the classical many-body problem; and a collision-avoidance strategy is derived and combined with homing, robot-robot, and robot-obstacle collision-avoidance strategies. Results from homing simulations involving (1) a single robot in a circular domain, (2) two robots in a circular domain, and (3) one robot in a domain with an obstacle are presented in graphs and briefly characterized.

The impact of design-based modeling instruction on seventh graders' spatial abilities and model-based argumentation

NASA Astrophysics Data System (ADS)

McConnell, William J.

Due to the call of current science education reform for the integration of engineering practices within science classrooms, design-based instruction is receiving much attention in science education literature. Although some aspect of modeling is often included in well-known design-based instructional methods, it is not always a primary focus. The purpose of this study was to better understand how design-based instruction with an emphasis on scientific modeling might impact students' spatial abilities and their model-based argumentation abilities. In the following mixed-method multiple case study, seven seventh grade students attending a secular private school in the Mid-Atlantic region of the United States underwent an instructional intervention involving design-based instruction, modeling and argumentation. Through the course of a lesson involving students in exploring the interrelatedness of the environment and an animal's form and function, students created and used multiple forms of expressed models to assist them in model-based scientific argument. Pre/post data were collected through the use of The Purdue Spatial Visualization Test: Rotation, the Mental Rotation Test and interviews. Other data included a spatial activities survey, student artifacts in the form of models, notes, exit tickets, and video recordings of students throughout the intervention. Spatial abilities tests were analyzed using descriptive statistics while students' arguments were analyzed using the Instrument for the Analysis of Scientific Curricular Arguments and a behavior protocol. Models were analyzed using content analysis and interviews and all other data were coded and analyzed for emergent themes. Findings in the area of spatial abilities included increases in spatial reasoning for six out of seven participants, and an immense difference in the spatial challenges encountered by students when using CAD software instead of paper drawings to create models. Students perceived 3D printed models to better assist them in scientific argumentation over paper drawing models. In fact, when given a choice, students rarely used paper drawing to assist in argument. There was also a difference in model utility between the two different model types. Participants explicitly used 3D printed models to complete gestural modeling, while participants rarely looked at 2D models when involved in gestural modeling. This study's findings added to current theory dealing with the varied spatial challenges involved in different modes of expressed models. This study found that depth, symmetry and the manipulation of perspectives are typically spatial challenges students will attend to using CAD while they will typically ignore them when drawing using paper and pencil. This study also revealed a major difference in model-based argument in a design-based instruction context as opposed to model-based argument in a typical science classroom context. In the context of design-based instruction, data revealed that design process is an important part of model-based argument. Due to the importance of design process in model-based argumentation in this context, trusted methods of argument analysis, like the coding system of the IASCA, was found lacking in many respects. Limitations and recommendations for further research were also presented.

75 FR 43144 - Certain Steel Grating from the People's Republic of China: Countervailing Duty Order

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-23

... been slit and expanded, and does not involve welding or joining of multiple pieces of steel. The scope... formed, and does not involve welding or joining of multiple pieces of steel. Certain steel grating that...

Improving Baseline Model Assumptions: Evaluating the Impacts of Typical Methodological Approaches in Watershed Models

NASA Astrophysics Data System (ADS)

Muenich, R. L.; Kalcic, M. M.; Teshager, A. D.; Long, C. M.; Wang, Y. C.; Scavia, D.

2017-12-01

Thanks to the availability of open-source software, online tutorials, and advanced software capabilities, watershed modeling has expanded its user-base and applications significantly in the past thirty years. Even complicated models like the Soil and Water Assessment Tool (SWAT) are being used and documented in hundreds of peer-reviewed publications each year, and likely more applied in practice. These models can help improve our understanding of present, past, and future conditions, or analyze important "what-if" management scenarios. However, baseline data and methods are often adopted and applied without rigorous testing. In multiple collaborative projects, we have evaluated the influence of some of these common approaches on model results. Specifically, we examined impacts of baseline data and assumptions involved in manure application, combined sewer overflows, and climate data incorporation across multiple watersheds in the Western Lake Erie Basin. In these efforts, we seek to understand the impact of using typical modeling data and assumptions, versus using improved data and enhanced assumptions on model outcomes and thus ultimately, study conclusions. We provide guidance for modelers as they adopt and apply data and models for their specific study region. While it is difficult to quantitatively assess the full uncertainty surrounding model input data and assumptions, recognizing the impacts of model input choices is important when considering actions at the both the field and watershed scales.

Integrating Engineering Data Systems for NASA Spaceflight Projects

NASA Technical Reports Server (NTRS)

Carvalho, Robert E.; Tollinger, Irene; Bell, David G.; Berrios, Daniel C.

2012-01-01

NASA has a large range of custom-built and commercial data systems to support spaceflight programs. Some of the systems are re-used by many programs and projects over time. Management and systems engineering processes require integration of data across many of these systems, a difficult problem given the widely diverse nature of system interfaces and data models. This paper describes an ongoing project to use a central data model with a web services architecture to support the integration and access of linked data across engineering functions for multiple NASA programs. The work involves the implementation of a web service-based middleware system called Data Aggregator to bring together data from a variety of systems to support space exploration. Data Aggregator includes a central data model registry for storing and managing links between the data in disparate systems. Initially developed for NASA's Constellation Program needs, Data Aggregator is currently being repurposed to support the International Space Station Program and new NASA projects with processes that involve significant aggregating and linking of data. This change in user needs led to development of a more streamlined data model registry for Data Aggregator in order to simplify adding new project application data as well as standardization of the Data Aggregator query syntax to facilitate cross-application querying by client applications. This paper documents the approach from a set of stand-alone engineering systems from which data are manually retrieved and integrated, to a web of engineering data systems from which the latest data are automatically retrieved and more quickly and accurately integrated. This paper includes the lessons learned through these efforts, including the design and development of a service-oriented architecture and the evolution of the data model registry approaches as the effort continues to evolve and adapt to support multiple NASA programs and priorities.

Quantifying Hydro-biogeochemical Model Sensitivity in Assessment of Climate Change Effect on Hyporheic Zone Processes

NASA Astrophysics Data System (ADS)

Song, X.; Chen, X.; Dai, H.; Hammond, G. E.; Song, H. S.; Stegen, J.

2016-12-01

The hyporheic zone is an active region for biogeochemical processes such as carbon and nitrogen cycling, where the groundwater and surface water mix and interact with each other with distinct biogeochemical and thermal properties. The biogeochemical dynamics within the hyporheic zone are driven by both river water and groundwater hydraulic dynamics, which are directly affected by climate change scenarios. Besides that, the hydraulic and thermal properties of local sediments and microbial and chemical processes also play important roles in biogeochemical dynamics. Thus for a comprehensive understanding of the biogeochemical processes in the hyporheic zone, a coupled thermo-hydro-biogeochemical model is needed. As multiple uncertainty sources are involved in the integrated model, it is important to identify its key modules/parameters through sensitivity analysis. In this study, we develop a 2D cross-section model in the hyporheic zone at the DOE Hanford site adjacent to Columbia River and use this model to quantify module and parametric sensitivity on assessment of climate change. To achieve this purpose, We 1) develop a facies-based groundwater flow and heat transfer model that incorporates facies geometry and heterogeneity characterized from a field data set, 2) derive multiple reaction networks/pathways from batch experiments with in-situ samples and integrate temperate dependent reactive transport modules to the flow model, 3) assign multiple climate change scenarios to the coupled model by analyzing historical river stage data, 4) apply a variance-based global sensitivity analysis to quantify scenario/module/parameter uncertainty in hierarchy level. The objectives of the research include: 1) identifing the key control factors of the coupled thermo-hydro-biogeochemical model in the assessment of climate change, and 2) quantify the carbon consumption in different climate change scenarios in the hyporheic zone.

Vision and vision-related outcome measures in multiple sclerosis

PubMed Central

Balcer, Laura J.; Miller, David H.; Reingold, Stephen C.

2015-01-01

Visual impairment is a key manifestation of multiple sclerosis. Acute optic neuritis is a common, often presenting manifestation, but visual deficits and structural loss of retinal axonal and neuronal integrity can occur even without a history of optic neuritis. Interest in vision in multiple sclerosis is growing, partially in response to the development of sensitive visual function tests, structural markers such as optical coherence tomography and magnetic resonance imaging, and quality of life measures that give clinical meaning to the structure-function correlations that are unique to the afferent visual pathway. Abnormal eye movements also are common in multiple sclerosis, but quantitative assessment methods that can be applied in practice and clinical trials are not readily available. We summarize here a comprehensive literature search and the discussion at a recent international meeting of investigators involved in the development and study of visual outcomes in multiple sclerosis, which had, as its overriding goals, to review the state of the field and identify areas for future research. We review data and principles to help us understand the importance of vision as a model for outcomes assessment in clinical practice and therapeutic trials in multiple sclerosis. PMID:25433914

The Availability and Utility of Services to Address Risk Factors for Recidivism among Justice-Involved Veterans

PubMed Central

Blonigen, Daniel M.; Rodriguez, Allison L.; Manfredi, Luisa; Britt, Jessica; Nevedal, Andrea; Finlay, Andrea K.; Rosenthal, Joel; Smelson, David; Timko, Christine

2016-01-01

The availability and utility of services to address recidivism risk factors among justice-involved veterans is unknown. We explored these issues through qualitative interviews with 63 Specialists from the Department of Veterans Affairs’ (VA) Veterans Justice Programs. To guide the interviews, we utilized the Risk-Need-Responsivity (RNR) model of offender rehabilitation. Specialists reported that justice-involved veterans generally have access to services to address most RNR-based risk factors (substance abuse; lack of positive school/work involvement; family/marital dysfunction; lack of prosocial activities/interests), but have less access to services targeting risk factors of antisocial tendencies and associates and empirically-based treatments for recidivism in VA. Peer-based services, motivational interviewing/cognitive-behavioral therapy, and Veterans Treatment Courts were perceived as useful to address multiple risk factors. These findings highlight potential gaps in provision of evidence-based care to address recidivism among justice-involved veterans, as well as promising policy-based solutions that may have widespread impact on reducing recidivism in this population. PMID:26924887

Significant blockade of multiple receptor tyrosine kinases by MGCD516 (Sitravatinib), a novel small molecule inhibitor, shows potent anti-tumor activity in preclinical models of sarcoma.

PubMed

Patwardhan, Parag P; Ivy, Kathryn S; Musi, Elgilda; de Stanchina, Elisa; Schwartz, Gary K

2016-01-26

Sarcomas are rare but highly aggressive mesenchymal tumors with a median survival of 10-18 months for metastatic disease. Mutation and/or overexpression of many receptor tyrosine kinases (RTKs) including c-Met, PDGFR, c-Kit and IGF1-R drive defective signaling pathways in sarcomas. MGCD516 (Sitravatinib) is a novel small molecule inhibitor targeting multiple RTKs involved in driving sarcoma cell growth. In the present study, we evaluated the efficacy of MGCD516 both in vitro and in mouse xenograft models in vivo. MGCD516 treatment resulted in significant blockade of phosphorylation of potential driver RTKs and induced potent anti-proliferative effects in vitro. Furthermore, MGCD516 treatment of tumor xenografts in vivo resulted in significant suppression of tumor growth. Efficacy of MGCD516 was superior to imatinib and crizotinib, two other well-studied multi-kinase inhibitors with overlapping target specificities, both in vitro and in vivo. This is the first report describing MGCD516 as a potent multi-kinase inhibitor in different models of sarcoma, superior to imatinib and crizotinib. Results from this study showing blockade of multiple driver signaling pathways provides a rationale for further clinical development of MGCD516 for the treatment of patients with soft-tissue sarcoma.

Significant blockade of multiple receptor tyrosine kinases by MGCD516 (Sitravatinib), a novel small molecule inhibitor, shows potent anti-tumor activity in preclinical models of sarcoma

PubMed Central

Musi, Elgilda; de Stanchina, Elisa; Schwartz, Gary K.

2016-01-01

Sarcomas are rare but highly aggressive mesenchymal tumors with a median survival of 10–18 months for metastatic disease. Mutation and/or overexpression of many receptor tyrosine kinases (RTKs) including c-Met, PDGFR, c-Kit and IGF1-R drive defective signaling pathways in sarcomas. MGCD516 (Sitravatinib) is a novel small molecule inhibitor targeting multiple RTKs involved in driving sarcoma cell growth. In the present study, we evaluated the efficacy of MGCD516 both in vitro and in mouse xenograft models in vivo. MGCD516 treatment resulted in significant blockade of phosphorylation of potential driver RTKs and induced potent anti-proliferative effects in vitro. Furthermore, MGCD516 treatment of tumor xenografts in vivo resulted in significant suppression of tumor growth. Efficacy of MGCD516 was superior to imatinib and crizotinib, two other well-studied multi-kinase inhibitors with overlapping target specificities, both in vitro and in vivo. This is the first report describing MGCD516 as a potent multi-kinase inhibitor in different models of sarcoma, superior to imatinib and crizotinib. Results from this study showing blockade of multiple driver signaling pathways provides a rationale for further clinical development of MGCD516 for the treatment of patients with soft-tissue sarcoma. PMID:26675259

A Data Parallel Multizone Navier-Stokes Code

NASA Technical Reports Server (NTRS)

Jespersen, Dennis C.; Levit, Creon; Kwak, Dochan (Technical Monitor)

1995-01-01

We have developed a data parallel multizone compressible Navier-Stokes code on the Connection Machine CM-5. The code is set up for implicit time-stepping on single or multiple structured grids. For multiple grids and geometrically complex problems, we follow the "chimera" approach, where flow data on one zone is interpolated onto another in the region of overlap. We will describe our design philosophy and give some timing results for the current code. The design choices can be summarized as: 1. finite differences on structured grids; 2. implicit time-stepping with either distributed solves or data motion and local solves; 3. sequential stepping through multiple zones with interzone data transfer via a distributed data structure. We have implemented these ideas on the CM-5 using CMF (Connection Machine Fortran), a data parallel language which combines elements of Fortran 90 and certain extensions, and which bears a strong similarity to High Performance Fortran (HPF). One interesting feature is the issue of turbulence modeling, where the architecture of a parallel machine makes the use of an algebraic turbulence model awkward, whereas models based on transport equations are more natural. We will present some performance figures for the code on the CM-5, and consider the issues involved in transitioning the code to HPF for portability to other parallel platforms.

Understanding large multiprotein complexes: applying a multiple allosteric networks model to explain the function of the Mediator transcription complex.

PubMed

Lewis, Brian A

2010-01-15

The regulation of transcription and of many other cellular processes involves large multi-subunit protein complexes. In the context of transcription, it is known that these complexes serve as regulatory platforms that connect activator DNA-binding proteins to a target promoter. However, there is still a lack of understanding regarding the function of these complexes. Why do multi-subunit complexes exist? What is the molecular basis of the function of their constituent subunits, and how are these subunits organized within a complex? What is the reason for physical connections between certain subunits and not others? In this article, I address these issues through a model of network allostery and its application to the eukaryotic RNA polymerase II Mediator transcription complex. The multiple allosteric networks model (MANM) suggests that protein complexes such as Mediator exist not only as physical but also as functional networks of interconnected proteins through which information is transferred from subunit to subunit by the propagation of an allosteric state known as conformational spread. Additionally, there are multiple distinct sub-networks within the Mediator complex that can be defined by their connections to different subunits; these sub-networks have discrete functions that are activated when specific subunits interact with other activator proteins.

Earth Versus Neutrinos: Measuring the Total Muon-Neutrino-to-Nucleon Cross Section at Ultra-High Energies through Differential Earth Absorption of Muon Neutrinos from Cosmic Rays Using the IceCube Detector

NASA Astrophysics Data System (ADS)

Miarecki, Sandra Christine

The IceCube Neutrino Detector at the South Pole was constructed to measure the flux of high-energy neutrinos and to try to identify their cosmic sources. In addition to these astrophysical neutrinos, IceCube also detects the neutrinos that result from cosmic ray interactions with the atmosphere. These atmospheric neutrinos can be used to measure the total muon neutrino-to-nucleon cross section by measuring neutrino absorption in the Earth. The measurement involves isolating a sample of 10,784 Earth-transiting muons detected by IceCube in its 79-string configuration. The cross-section is determined using a two-dimensional fit in measured muon energy and zenith angle and is presented as a multiple of the Standard Model expectation as calculated by Cooper-Sarkar, Mertsch, and Sarkar in 2011. A multiple of 1.0 would indicate agreement with the Standard Model. The results of this analysis find the multiple to be 1.30 (+0.21 -0.19 statistical) (+0.40 -0.44 systematic) for the neutrino energy range of 6.3 to 980 TeV, which is in agreement with the Standard Model expectation.

Mission Concepts and Operations for Asteroid Mitigation Involving Multiple Gravity Tractors

NASA Technical Reports Server (NTRS)

Foster, Cyrus; Bellerose, Julie; Jaroux, Belgacem; Mauro, David

2012-01-01

The gravity tractor concept is a proposed method to deflect an imminent asteroid impact through gravitational tugging over a time scale of years. In this study, we present mission scenarios and operational considerations for asteroid mitigation efforts involving multiple gravity tractors. We quantify the deflection performance improvement provided by a multiple gravity tractor campaign and assess its sensitivity to staggered launches. We next explore several proximity operation strategies to accommodate multiple gravity tractors at a single asteroid including formation-flying and mechanically-docked configurations. Finally, we utilize 99942 Apophis as an illustrative example to assess the performance of a multiple gravity tractor campaign.

The Impact of Prophage on the Equilibria and Stability of Phage and Host

NASA Astrophysics Data System (ADS)

Yu, Pei; Nadeem, Alina; Wahl, Lindi M.

2017-06-01

In this paper, we present a bacteriophage model that includes prophage, that is, phage genomes that are incorporated into the host cell genome. The general model is described by an 18-dimensional system of ordinary differential equations. This study focuses on asymptotic behaviour of the model, and thus the system is reduced to a simple six-dimensional model, involving uninfected host cells, infected host cells and phage. We use dynamical system theory to explore the dynamic behaviour of the model, studying in particular the impact of prophage on the equilibria and stability of phage and host. We employ bifurcation and stability theory, centre manifold and normal form theory to show that the system has multiple equilibrium solutions which undergo a series of bifurcations, finally leading to oscillating motions. Numerical simulations are presented to illustrate and confirm the analytical predictions. The results of this study indicate that in some parameter regimes, the host cell population may drive the phage to extinction through diversification, that is, if multiple types of host emerge; this prediction holds even if the phage population is likewise diverse. This parameter regime is restricted, however, if infecting phage are able to recombine with prophage sequences in the host cell genome.

Are You Talking to Me? Dialogue Systems Supporting Mixed Teams of Humans and Robots

NASA Technical Reports Server (NTRS)

Dowding, John; Clancey, William J.; Graham, Jeffrey

2006-01-01

This position paper describes an approach to building spoken dialogue systems for environments containing multiple human speakers and hearers, and multiple robotic speakers and hearers. We address the issue, for robotic hearers, of whether the speech they hear is intended for them, or more likely to be intended for some other hearer. We will describe data collected during a series of experiments involving teams of multiple human and robots (and other software participants), and some preliminary results for distinguishing robot-directed speech from human-directed speech. The domain of these experiments is Mars-analogue planetary exploration. These Mars-analogue field studies involve two subjects in simulated planetary space suits doing geological exploration with the help of 1-2 robots, supporting software agents, a habitat communicator and links to a remote science team. The two subjects are performing a task (geological exploration) which requires them to speak with each other while also speaking with their assistants. The technique used here is to use a probabilistic context-free grammar language model in the speech recognizer that is trained on prior robot-directed speech. Intuitively, the recognizer will give higher confidence to an utterance if it is similar to utterances that have been directed to the robot in the past.

Petiveria alliacea extracts uses multiple mechanisms to inhibit growth of human and mouse tumoral cells.

PubMed

Urueña, Claudia; Cifuentes, Claudia; Castañeda, Diana; Arango, Amparo; Kaur, Punit; Asea, Alexzander; Fiorentino, Susana

2008-11-18

There is ethnopharmacological evidence that Petiveria alliacea can have antitumor activity; however, the mechanism of its cytotoxic activity is not well understood. We assessed multiple in vitro biological activities of an ethyl acetate soluble plant fraction over several tumor cell lines. Tumor cell lines were evaluated using the following tests: trypan blue exclusion test, MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide], flow cytometry, cytoskeleton organization analysis, cell cycle, mitochondria membrane depolarization, clonogenicity test, DNA fragmentation test and differential protein expression by HPLC-Chip/MS analysis. F4 fraction characterization was made by HPLC-MS. Petiveria alliacea fraction characterized by de-replication was found to alter actin cytoskeleton organization, induce G2 cell cycle arrest and cause apoptotic cell death in a mitochondria independent way. In addition, we found down regulation of cytoskeleton, chaperone, signal transduction proteins, and proteins involved in metabolic pathways. Finally up regulation of proteins involved in translation and intracellular degradation was also observed. The results of this study indicate that Petiveria alliacea exerts multiple biological activities in vitro consistent with cytotoxicity. Further studies in animal models are needed but Petiveria alliacea appears to be a good candidate to be used as an antitumor agent.

Petiveria alliacea extracts uses multiple mechanisms to inhibit growth of human and mouse tumoral cells

PubMed Central

Urueña, Claudia; Cifuentes, Claudia; Castañeda, Diana; Arango, Amparo; Kaur, Punit; Asea, Alexzander; Fiorentino, Susana

2008-01-01

Background There is ethnopharmacological evidence that Petiveria alliacea can have antitumor activity; however, the mechanism of its cytotoxic activity is not well understood. We assessed multiple in vitro biological activities of an ethyl acetate soluble plant fraction over several tumor cell lines. Methods Tumor cell lines were evaluated using the following tests: trypan blue exclusion test, MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide], flow cytometry, cytoskeleton organization analysis, cell cycle, mitochondria membrane depolarization, clonogenicity test, DNA fragmentation test and differential protein expression by HPLC-Chip/MS analysis. F4 fraction characterization was made by HPLC-MS. Results Petiveria alliacea fraction characterized by de-replication was found to alter actin cytoskeleton organization, induce G2 cell cycle arrest and cause apoptotic cell death in a mitochondria independent way. In addition, we found down regulation of cytoskeleton, chaperone, signal transduction proteins, and proteins involved in metabolic pathways. Finally up regulation of proteins involved in translation and intracellular degradation was also observed. Conclusion The results of this study indicate that Petiveria alliacea exerts multiple biological activities in vitro consistent with cytotoxicity. Further studies in animal models are needed but Petiveria alliacea appears to be a good candidate to be used as an antitumor agent. PMID:19017389

Influence of primary fragment excitation energy and spin distributions on fission observables

NASA Astrophysics Data System (ADS)

Litaize, Olivier; Thulliez, Loïc; Serot, Olivier; Chebboubi, Abdelaziz; Tamagno, Pierre

2018-03-01

Fission observables in the case of 252Cf(sf) are investigated by exploring several models involved in the excitation energy sharing and spin-parity assignment between primary fission fragments. In a first step the parameters used in the FIFRELIN Monte Carlo code "reference route" are presented: two parameters for the mass dependent temperature ratio law and two constant spin cut-off parameters for light and heavy fragment groups respectively. These parameters determine the initial fragment entry zone in excitation energy and spin-parity (E*, Jπ). They are chosen to reproduce the light and heavy average prompt neutron multiplicities. When these target observables are achieved all other fission observables can be predicted. We show here the influence of input parameters on the saw-tooth curve and we discuss the influence of a mass and energy-dependent spin cut-off model on gamma-rays related fission observables. The part of the model involving level densities, neutron transmission coefficients or photon strength functions remains unchanged.

Hybrid Model Predictive Control for Sequential Decision Policies in Adaptive Behavioral Interventions.

PubMed

Dong, Yuwen; Deshpande, Sunil; Rivera, Daniel E; Downs, Danielle S; Savage, Jennifer S

2014-06-01

Control engineering offers a systematic and efficient method to optimize the effectiveness of individually tailored treatment and prevention policies known as adaptive or "just-in-time" behavioral interventions. The nature of these interventions requires assigning dosages at categorical levels, which has been addressed in prior work using Mixed Logical Dynamical (MLD)-based hybrid model predictive control (HMPC) schemes. However, certain requirements of adaptive behavioral interventions that involve sequential decision making have not been comprehensively explored in the literature. This paper presents an extension of the traditional MLD framework for HMPC by representing the requirements of sequential decision policies as mixed-integer linear constraints. This is accomplished with user-specified dosage sequence tables, manipulation of one input at a time, and a switching time strategy for assigning dosages at time intervals less frequent than the measurement sampling interval. A model developed for a gestational weight gain (GWG) intervention is used to illustrate the generation of these sequential decision policies and their effectiveness for implementing adaptive behavioral interventions involving multiple components.

What is a new drug worth? An innovative model for performance-based pricing.

PubMed

Dranitsaris, G; Dorward, K; Owens, R C; Schipper, H

2015-05-01

This article focuses on a novel method to derive prices for new pharmaceuticals by making price a function of drug performance. We briefly review current models for determining price for a new product and discuss alternatives that have historically been favoured by various funding bodies. The progressive approach to drug pricing, proposed herein, may better address the views and concerns of multiple stakeholders in a developed healthcare system by acknowledging and incorporating input from disparate parties via comprehensive and successive negotiation stages. In proposing a valid construct for performance-based pricing, the following model seeks to achieve several crucial objectives: earlier and wider access to new treatments; improved transparency in drug pricing; multi-stakeholder involvement through phased pricing negotiations; recognition of innovative product performance and latent changes in value; an earlier and more predictable return for developers without sacrificing total return on investment (ROI); more involved and informed risk sharing by the end-user. © 2014 John Wiley & Sons Ltd.

Preparation of organotypic brain slice cultures for the study of Alzheimer’s disease

PubMed Central

Croft, Cara L.; Noble, Wendy

2018-01-01

Alzheimer's disease, the most common cause of dementia, is a progressive neurodegenerative disorder characterised by amyloid-beta deposits in extracellular plaques, intracellular neurofibrillary tangles of aggregated tau, synaptic dysfunction and neuronal death. There are no cures for AD and current medications only alleviate some disease symptoms. Transgenic rodent models to study Alzheimer’s mimic features of human disease such as age-dependent accumulation of abnormal beta-amyloid and tau, synaptic dysfunction, cognitive deficits and neurodegeneration. These models have proven vital for improving our understanding of the molecular mechanisms underlying AD and for identifying promising therapeutic approaches. However, modelling neurodegenerative disease in animals commonly involves aging animals until they develop harmful phenotypes, often coupled with invasive procedures. In vivo studies are also resource, labour, time and cost intensive. We have developed a novel organotypic brain slice culture model to study Alzheimer’ disease which brings the potential of substantially reducing the number of rodents used in dementia research from an estimated 20,000 per year. We obtain 36 brain slices from each mouse pup, considerably reducing the numbers of animals required to investigate multiple stages of disease. This tractable model also allows the opportunity to modulate multiple pathways in tissues from a single animal. We believe that this model will most benefit dementia researchers in the academic and drug discovery sectors. We validated the slice culture model against aged mice, showing that the molecular phenotype closely mimics that displayed in vivo, albeit in an accelerated timescale. We showed beneficial outcomes following treatment of slices with agents previously shown to have therapeutic effects in vivo, and we also identified new mechanisms of action of other compounds. Thus, organotypic brain slice cultures from transgenic mouse models expressing Alzheimer’s disease-related genes may provide a valid and sensitive replacement for in vivo studies that do not involve behavioural analysis. PMID:29904599

Using the Landlab toolkit to evaluate and compare alternative geomorphic and hydrologic model formulations

NASA Astrophysics Data System (ADS)

Tucker, G. E.; Adams, J. M.; Doty, S. G.; Gasparini, N. M.; Hill, M. C.; Hobley, D. E. J.; Hutton, E.; Istanbulluoglu, E.; Nudurupati, S. S.

2016-12-01

Developing a better understanding of catchment hydrology and geomorphology ideally involves quantitative hypothesis testing. Often one seeks to identify the simplest mathematical and/or computational model that accounts for the essential dynamics in the system of interest. Development of alternative hypotheses involves testing and comparing alternative formulations, but the process of comparison and evaluation is made challenging by the rigid nature of many computational models, which are often built around a single assumed set of equations. Here we review a software framework for two-dimensional computational modeling that facilitates the creation, testing, and comparison of surface-dynamics models. Landlab is essentially a Python-language software library. Its gridding module allows for easy generation of a structured (raster, hex) or unstructured (Voronoi-Delaunay) mesh, with the capability to attach data arrays to particular types of element. Landlab includes functions that implement common numerical operations, such as gradient calculation and summation of fluxes within grid cells. Landlab also includes a collection of process components, which are encapsulated pieces of software that implement a numerical calculation of a particular process. Examples include downslope flow routing over topography, shallow-water hydrodynamics, stream erosion, and sediment transport on hillslopes. Individual components share a common grid and data arrays, and they can be coupled through the use of a simple Python script. We illustrate Landlab's capabilities with a case study of Holocene landscape development in the northeastern US, in which we seek to identify a collection of model components that can account for the formation of a series of incised canyons that have that developed since the Laurentide ice sheet last retreated. We compare sets of model ingredients related to (1) catchment hydrologic response, (2) hillslope evolution, and (3) stream channel and gully incision. The case-study example demonstrates the value of exploring multiple working hypotheses, in the form of multiple alternative model components.

75 FR 847 - Certain Steel Grating From the People's Republic of China: Preliminary Determination of Sales at...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-06

... that has been slit and expanded, and does not involve welding or joining of multiple pieces of steel... pierced and cold formed, and does not involve welding or joining of multiple pieces of steel. Certain...

Nrf2 and Nrf2-Related Proteins in Development and Developmental Toxicity: Insights from studies in Zebrafish (Danio rerio)

PubMed Central

Hahn, Mark E.; Timme-Laragy, Alicia R.; Karchner, Sibel I.; Stegeman, John J.

2015-01-01

Oxidative stress is an important mechanism of chemical toxicity, contributing to developmental toxicity and teratogenesis as well as to cardiovascular and neurodegenerative diseases and diabetic embryopathy. Developing animals are especially sensitive to effects of chemicals that disrupt the balance of processes generating reactive species and oxidative stress, and those anti-oxidant defenses that protect against oxidative stress. The expression and inducibility of anti-oxidant defenses through activation of NFE2-related factor 2 (Nrf2) and related proteins is an essential process affecting the susceptibility to oxidants, but the complex interactions of Nrf2 in determining embryonic response to oxidants and oxidative stress are only beginning to be understood. The zebrafish (Danio rerio) is an established model in developmental biology and now also in developmental toxicology and redox signaling. Here we review the regulation of genes involved in protection against oxidative stress in developing vertebrates, with a focus on Nrf2 and related cap’n’collar (CNC)-basic-leucine zipper (bZIP) transcription factors. Vertebrate animals including zebrafish share Nfe2, Nrf1, Nrf2, and Nrf3 as well as a core set of genes that respond to oxidative stress, contributing to the value of zebrafish as a model system with which to investigate the mechanisms involved in regulation of redox signaling and the response to oxidative stress during embryolarval development. Moreover, studies in zebrafish have revealed nrf and keap1 gene duplications that provide an opportunity to dissect multiple functions of vertebrate NRF genes, including multiple sensing mechanisms involved in chemical-specific effects. PMID:26130508

Through the looking glass: making the design and output of economic models useful for setting medical policy.

PubMed

Ollendorf, Daniel A; Pearson, Steven D

2014-01-01

Economic modeling has rarely been considered to be an essential component of healthcare policy-making in the USA, due to a lack of transparency in model design and assumptions, as well as political interests that equate examination of cost with unfair rationing. The Institute for Clinical and Economic Review has been involved in several efforts to bring economic modeling into public discussion of the comparative value of healthcare interventions, efforts that have evolved over time to suit the needs of multiple public forums. In this article, we review these initiatives and present a template that attempts to 'unpack' model output and present the major drivers of outcomes and cost. We conclude with a series of recommendations for effective presentation of economic models to US policy-makers.

Can Drosophila melanogaster represent a model system for the detection of reproductive adverse drug reactions?

PubMed

Avanesian, Agnesa; Semnani, Sahar; Jafari, Mahtab

2009-08-01

Once a molecule is identified as a potential drug, the detection of adverse drug reactions is one of the key components of its development and the FDA approval process. We propose using Drosophila melanogaster to screen for reproductive adverse drug reactions in the early stages of drug development. Compared with other non-mammalian models, D. melanogaster has many similarities to the mammalian reproductive system, including putative sex hormones and conserved proteins involved in genitourinary development. Furthermore, the D. melanogaster model would present significant advantages in time efficiency and cost-effectiveness compared with mammalian models. We present data on methotrexate (MTX) reproductive adverse events in multiple animal models, including fruit flies, as proof-of-concept for the use of the D. melanogaster model.

Projecting future expansion of invasive species: comparing and improving methodologies for species distribution modeling.

PubMed

Mainali, Kumar P; Warren, Dan L; Dhileepan, Kunjithapatham; McConnachie, Andrew; Strathie, Lorraine; Hassan, Gul; Karki, Debendra; Shrestha, Bharat B; Parmesan, Camille

2015-12-01

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships for Parthenium hysterophorus L. (Asteraceae) with four modeling methods run with multiple scenarios of (i) sources of occurrences and geographically isolated background ranges for absences, (ii) approaches to drawing background (absence) points, and (iii) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved using a global dataset for model training, rather than restricting data input to the species' native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e., into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g., boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post hoc test conducted on a new Parthenium dataset from Nepal validated excellent predictive performance of our 'best' model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for parthenium. However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. © 2015 John Wiley & Sons Ltd.

Motion compensation via redundant-wavelet multihypothesis.

PubMed

Fowler, James E; Cui, Suxia; Wang, Yonghui

2006-10-01

Multihypothesis motion compensation has been widely used in video coding with previous attention focused on techniques employing predictions that are diverse spatially or temporally. In this paper, the multihypothesis concept is extended into the transform domain by using a redundant wavelet transform to produce multiple predictions that are diverse in transform phase. The corresponding multiple-phase inverse transform implicitly combines the phase-diverse predictions into a single spatial-domain prediction for motion compensation. The performance advantage of this redundant-wavelet-multihypothesis approach is investigated analytically, invoking the fact that the multiple-phase inverse involves a projection that significantly reduces the power of a dense-motion residual modeled as additive noise. The analysis shows that redundant-wavelet multihypothesis is capable of up to a 7-dB reduction in prediction-residual variance over an equivalent single-phase, single-hypothesis approach. Experimental results substantiate the performance advantage for a block-based implementation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daleu, C. L.; Plant, R. S.; Woolnough, S. J.

Here, as part of an international intercomparison project, a set of single-column models (SCMs) and cloud-resolving models (CRMs) are run under the weak-temperature gradient (WTG) method and the damped gravity wave (DGW) method. For each model, the implementation of the WTG or DGW method involves a simulated column which is coupled to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. The simulated column has the same surface conditions as the reference state and is initialized with profiles from the reference state. We performed systematic comparison of the behavior of different models under a consistentmore » implementation of the WTG method and the DGW method and systematic comparison of the WTG and DGW methods in models with different physics and numerics. CRMs and SCMs produce a variety of behaviors under both WTG and DGW methods. Some of the models reproduce the reference state while others sustain a large-scale circulation which results in either substantially lower or higher precipitation compared to the value of the reference state. CRMs show a fairly linear relationship between precipitation and circulation strength. SCMs display a wider range of behaviors than CRMs. Some SCMs under the WTG method produce zero precipitation. Within an individual SCM, a DGW simulation and a corresponding WTG simulation can produce different signed circulation. When initialized with a dry troposphere, DGW simulations always result in a precipitating equilibrium state. The greatest sensitivities to the initial moisture conditions occur for multiple stable equilibria in some WTG simulations, corresponding to either a dry equilibrium state when initialized as dry or a precipitating equilibrium state when initialized as moist. Multiple equilibria are seen in more WTG simulations for higher SST. In some models, the existence of multiple equilibria is sensitive to some parameters in the WTG calculations.« less

A sample theory-based logic model to improve program development, implementation, and sustainability of Farm to School programs.

PubMed

Ratcliffe, Michelle M

2012-08-01

Farm to School programs hold promise to address childhood obesity. These programs may increase students’ access to healthier foods, increase students’ knowledge of and desire to eat these foods, and increase their consumption of them. Implementing Farm to School programs requires the involvement of multiple people, including nutrition services, educators, and food producers. Because these groups have not traditionally worked together and each has different goals, it is important to demonstrate how Farm to School programs that are designed to decrease childhood obesity may also address others’ objectives, such as academic achievement and economic development. A logic model is an effective tool to help articulate a shared vision for how Farm to School programs may work to accomplish multiple goals. Furthermore, there is evidence that programs based on theory are more likely to be effective at changing individuals’ behaviors. Logic models based on theory may help to explain how a program works, aid in efficient and sustained implementation, and support the development of a coherent evaluation plan. This article presents a sample theory-based logic model for Farm to School programs. The presented logic model is informed by the polytheoretical model for food and garden-based education in school settings (PMFGBE). The logic model has been applied to multiple settings, including Farm to School program development and evaluation in urban and rural school districts. This article also includes a brief discussion on the development of the PMFGBE, a detailed explanation of how Farm to School programs may enhance the curricular, physical, and social learning environments of schools, and suggestions for the applicability of the logic model for practitioners, researchers, and policy makers.

Robust THP Transceiver Designs for Multiuser MIMO Downlink with Imperfect CSIT

NASA Astrophysics Data System (ADS)

Ubaidulla, P.; Chockalingam, A.

2009-12-01

We present robust joint nonlinear transceiver designs for multiuser multiple-input multiple-output (MIMO) downlink in the presence of imperfections in the channel state information at the transmitter (CSIT). The base station (BS) is equipped with multiple transmit antennas, and each user terminal is equipped with one or more receive antennas. The BS employs Tomlinson-Harashima precoding (THP) for interuser interference precancellation at the transmitter. We consider robust transceiver designs that jointly optimize the transmit THP filters and receive filter for two models of CSIT errors. The first model is a stochastic error (SE) model, where the CSIT error is Gaussian-distributed. This model is applicable when the CSIT error is dominated by channel estimation error. In this case, the proposed robust transceiver design seeks to minimize a stochastic function of the sum mean square error (SMSE) under a constraint on the total BS transmit power. We propose an iterative algorithm to solve this problem. The other model we consider is a norm-bounded error (NBE) model, where the CSIT error can be specified by an uncertainty set. This model is applicable when the CSIT error is dominated by quantization errors. In this case, we consider a worst-case design. For this model, we consider robust (i) minimum SMSE, (ii) MSE-constrained, and (iii) MSE-balancing transceiver designs. We propose iterative algorithms to solve these problems, wherein each iteration involves a pair of semidefinite programs (SDPs). Further, we consider an extension of the proposed algorithm to the case with per-antenna power constraints. We evaluate the robustness of the proposed algorithms to imperfections in CSIT through simulation, and show that the proposed robust designs outperform nonrobust designs as well as robust linear transceiver designs reported in the recent literature.

A consensus least squares support vector regression (LS-SVR) for analysis of near-infrared spectra of plant samples.

PubMed

Li, Yankun; Shao, Xueguang; Cai, Wensheng

2007-04-15

Consensus modeling of combining the results of multiple independent models to produce a single prediction avoids the instability of single model. Based on the principle of consensus modeling, a consensus least squares support vector regression (LS-SVR) method for calibrating the near-infrared (NIR) spectra was proposed. In the proposed approach, NIR spectra of plant samples were firstly preprocessed using discrete wavelet transform (DWT) for filtering the spectral background and noise, then, consensus LS-SVR technique was used for building the calibration model. With an optimization of the parameters involved in the modeling, a satisfied model was achieved for predicting the content of reducing sugar in plant samples. The predicted results show that consensus LS-SVR model is more robust and reliable than the conventional partial least squares (PLS) and LS-SVR methods.

Using a Large-scale Neural Model of Cortical Object Processing to Investigate the Neural Substrate for Managing Multiple Items in Short-term Memory.

PubMed

Liu, Qin; Ulloa, Antonio; Horwitz, Barry

2017-11-01

Many cognitive and computational models have been proposed to help understand working memory. In this article, we present a simulation study of cortical processing of visual objects during several working memory tasks using an extended version of a previously constructed large-scale neural model [Tagamets, M. A., & Horwitz, B. Integrating electrophysiological and anatomical experimental data to create a large-scale model that simulates a delayed match-to-sample human brain imaging study. Cerebral Cortex, 8, 310-320, 1998]. The original model consisted of arrays of Wilson-Cowan type of neuronal populations representing primary and secondary visual cortices, inferotemporal (IT) cortex, and pFC. We added a module representing entorhinal cortex, which functions as a gating module. We successfully implemented multiple working memory tasks using the same model and produced neuronal patterns in visual cortex, IT cortex, and pFC that match experimental findings. These working memory tasks can include distractor stimuli or can require that multiple items be retained in mind during a delay period (Sternberg's task). Besides electrophysiology data and behavioral data, we also generated fMRI BOLD time series from our simulation. Our results support the involvement of IT cortex in working memory maintenance and suggest the cortical architecture underlying the neural mechanisms mediating particular working memory tasks. Furthermore, we noticed that, during simulations of memorizing a list of objects, the first and last items in the sequence were recalled best, which may implicate the neural mechanism behind this important psychological effect (i.e., the primacy and recency effect).

Interaction of Multiple Particles with a Solidification Front: From Compacted Particle Layer to Particle Trapping.

PubMed

Saint-Michel, Brice; Georgelin, Marc; Deville, Sylvain; Pocheau, Alain

2017-06-13

The interaction of solidification fronts with objects such as particles, droplets, cells, or bubbles is a phenomenon with many natural and technological occurrences. For an object facing the front, it may yield various fates, from trapping to rejection, with large implications regarding the solidification pattern. However, whereas most situations involve multiple particles interacting with each other and the front, attention has focused almost exclusively on the interaction of a single, isolated object with the front. Here we address experimentally the interaction of multiple particles with a solidification front by performing solidification experiments of a monodisperse particle suspension in a Hele-Shaw cell with precise control of growth conditions and real-time visualization. We evidence the growth of a particle layer ahead of the front at a close-packing volume fraction, and we document its steady-state value at various solidification velocities. We then extend single-particle models to the situation of multiple particles by taking into account the additional force induced on an entering particle by viscous friction in the compacted particle layer. By a force balance model this provides an indirect measure of the repelling mean thermomolecular pressure over a particle entering the front. The presence of multiple particles is found to increase it following a reduction of the thickness of the thin liquid film that separates particles and front. We anticipate the findings reported here to provide a relevant basis to understand many complex solidification situations in geophysics, engineering, biology, or food engineering, where multiple objects interact with the front and control the resulting solidification patterns.

Dynamics of a intraguild predation model with generalist or specialist predator.

PubMed

Kang, Yun; Wedekin, Lauren

2013-11-01

Intraguild predation (IGP) is a combination of competition and predation which is the most basic system in food webs that contains three species where two species that are involved in a predator/prey relationship are also competing for a shared resource or prey. We formulate two intraguild predation (IGP: resource, IG prey and IG predator) models: one has generalist predator while the other one has specialist predator. Both models have Holling-Type I functional response between resource-IG prey and resource-IG predator; Holling-Type III functional response between IG prey and IG predator. We provide sufficient conditions of the persistence and extinction of all possible scenarios for these two models, which give us a complete picture on their global dynamics. In addition, we show that both IGP models can have multiple interior equilibria under certain parameters range. These analytical results indicate that IGP model with generalist predator has "top down" regulation by comparing to IGP model with specialist predator. Our analysis and numerical simulations suggest that: (1) Both IGP models can have multiple attractors with complicated dynamical patterns; (2) Only IGP model with specialist predator can have both boundary attractor and interior attractor, i.e., whether the system has the extinction of one species or the coexistence of three species depending on initial conditions; (3) IGP model with generalist predator is prone to have coexistence of three species.

Two-Electron Transfer Pathways.

PubMed

Lin, Jiaxing; Balamurugan, D; Zhang, Peng; Skourtis, Spiros S; Beratan, David N

2015-06-18

The frontiers of electron-transfer chemistry demand that we develop theoretical frameworks to describe the delivery of multiple electrons, atoms, and ions in molecular systems. When electrons move over long distances through high barriers, where the probability for thermal population of oxidized or reduced bridge-localized states is very small, the electrons will tunnel from the donor (D) to acceptor (A), facilitated by bridge-mediated superexchange interactions. If the stable donor and acceptor redox states on D and A differ by two electrons, it is possible that the electrons will propagate coherently from D to A. While structure-function relations for single-electron superexchange in molecules are well established, strategies to manipulate the coherent flow of multiple electrons are largely unknown. In contrast to one-electron superexchange, two-electron superexchange involves both one- and two-electron virtual intermediate states, the number of virtual intermediates increases very rapidly with system size, and multiple classes of pathways interfere with one another. In the study described here, we developed simple superexchange models for two-electron transfer. We explored how the bridge structure and energetics influence multielectron superexchange, and we compared two-electron superexchange interactions to single-electron superexchange. Multielectron superexchange introduces interference between singly and doubly oxidized (or reduced) bridge virtual states, so that even simple linear donor-bridge-acceptor systems have pathway topologies that resemble those seen for one-electron superexchange through bridges with multiple parallel pathways. The simple model systems studied here exhibit a richness that is amenable to experimental exploration by manipulating the multiple pathways, pathway crosstalk, and changes in the number of donor and acceptor species. The features that emerge from these studies may assist in developing new strategies to deliver multiple electrons in condensed-phase redox systems, including multiple-electron redox species, multimetallic/multielectron redox catalysts, and multiexciton excited states.

ELV Payload Safety Program Workshop Green Propulsion Update

NASA Technical Reports Server (NTRS)

Robinson, Joel

2014-01-01

MSFC is engaged on the system solution: thrusters and power units; GRC is working plume diagnostics/modeling and independent thruster testing on GPIM.; GSFC is working slosh characteristics on GPIM tank.; JPL and ARC continually interested to infuse green propellant as potential replacement to hydrazine.; Mike Gazarik, AA of STMD, has requested MSFC lead the development of an Agency-level green propellant roadmap involving multiple Centers., Tentatively planned for August 2015 in Huntsville.

Framework for Smart Electronic Health Record- Linked Predictive Models to Optimize Care for Complex Digestive Diseases

DTIC Science & Technology

2015-03-01

data against previous published outcomes in AP and Chronic Pancreatitis (CP). This served as useful validation of our data set before entering the...These patients can develop multiple complications from their disease. In addition, the treatments for CD (both medical and surgical ) can impose...years of diagnosis. The treatment for CD can sometimes involve very expensive medications with potentially serious side effects, as well as surgical

DNA-dependent protein kinase in nonhomologous end joining: a lock with multiple keys?

PubMed

Weterings, Eric; Chen, David J

2007-10-22

The DNA-dependent protein kinase (DNA-PK) is one of the central enzymes involved in DNA double-strand break (DSB) repair. It facilitates proper alignment of the two ends of the broken DNA molecule and coordinates access of other factors to the repair complex. We discuss the latest findings on DNA-PK phosphorylation and offer a working model for the regulation of DNA-PK during DSB repair.

Theory of multicolor lattice gas - A cellular automaton Poisson solver

NASA Technical Reports Server (NTRS)

Chen, H.; Matthaeus, W. H.; Klein, L. W.

1990-01-01

The present class of models for cellular automata involving a quiescent hydrodynamic lattice gas with multiple-valued passive labels termed 'colors', the lattice collisions change individual particle colors while preserving net color. The rigorous proofs of the multicolor lattice gases' essential features are rendered more tractable by an equivalent subparticle representation in which the color is represented by underlying two-state 'spins'. Schemes for the introduction of Dirichlet and Neumann boundary conditions are described, and two illustrative numerical test cases are used to verify the theory. The lattice gas model is equivalent to a Poisson equation solution.

A Game Theoretical Model for Location of Terror Response Facilities under Capacitated Resources

PubMed Central

Kang, Qi; Xu, Weisheng; Wu, Qidi

2013-01-01

This paper is concerned with the effect of capacity constraints on the locations of terror response facilities. We assume that the state has limited resources, and multiple facilities may be involved in the response until the demand is satisfied consequently. We formulate a leader-follower game model between the state and the terrorist and prove the existence and uniqueness of the Nash equilibrium. An integer linear programming is proposed to obtain the equilibrium results when the facility number is fixed. The problem is demonstrated by a case study of the 19 districts of Shanghai, China. PMID:24459446

Transcription Profiles Reveal Sugar and Hormone Signaling Pathways Mediating Flower Induction in Apple (Malus domestica Borkh.).

PubMed

Xing, Li-Bo; Zhang, Dong; Li, You-Mei; Shen, Ya-Wen; Zhao, Cai-Ping; Ma, Juan-Juan; An, Na; Han, Ming-Yu

2015-10-01

Flower induction in apple (Malus domestica Borkh.) is regulated by complex gene networks that involve multiple signal pathways to ensure flower bud formation in the next year, but the molecular determinants of apple flower induction are still unknown. In this research, transcriptomic profiles from differentiating buds allowed us to identify genes potentially involved in signaling pathways that mediate the regulatory mechanisms of flower induction. A hypothetical model for this regulatory mechanism was obtained by analysis of the available transcriptomic data, suggesting that sugar-, hormone- and flowering-related genes, as well as those involved in cell-cycle induction, participated in the apple flower induction process. Sugar levels and metabolism-related gene expression profiles revealed that sucrose is the initiation signal in flower induction. Complex hormone regulatory networks involved in cytokinin (CK), abscisic acid (ABA) and gibberellic acid pathways also induce apple flower formation. CK plays a key role in the regulation of cell formation and differentiation, and in affecting flowering-related gene expression levels during these processes. Meanwhile, ABA levels and ABA-related gene expression levels gradually increased, as did those of sugar metabolism-related genes, in developing buds, indicating that ABA signals regulate apple flower induction by participating in the sugar-mediated flowering pathway. Furthermore, changes in sugar and starch deposition levels in buds can be affected by ABA content and the expression of the genes involved in the ABA signaling pathway. Thus, multiple pathways, which are mainly mediated by crosstalk between sugar and hormone signals, regulate the molecular network involved in bud growth and flower induction in apple trees. © The Author 2015. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.

Theoretical analysis of the effects of light intensity on the photocorrosion of semiconductor electrodes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Benito, R.M.; Nozik, A.J.

1985-07-18

A kinetic model was developed to describe the effects of light intensity on the photocorrosion of n-type semiconductor electrodes. The model is an extension of previous work by Gomes and co-workers that includes the possibility of multiple steps for the oxidation reaction of the reducing agent in the electrolyte. Six cases are considered where the semiconductor decomposition reaction is multistep (each step involves a hole); the oxidation reaction of the reducing agent is multistep (each step after the first involves a hole or a chemical intermediate), and the first steps of the competing oxidation reactions are reversible or irreversible. Itmore » was found, contrary to previous results, that the photostability of semiconductor electrodes could increase with increased light intensity if the desired oxidation reaction of the reducing agent in the electrolyte was multistep with the first step being reversible. 14 references, 5 figures, 1 table.« less

Youth violence in South Africa: exposure, attitudes, and resilience in Zulu adolescents.

PubMed

Choe, Daniel Ewon; Zimmerman, Marc A; Devnarain, Bashi

2012-01-01

Exposure to violence is common in South Africa. Yet, few studies examine how violence exposure contributes to South African adolescents' participation in youth violence. The aims of this study were to examine effects of different violence exposures on violent attitudes and behavior, to test whether attitudes mediated effects of violence exposures on violent behavior, and to test whether adult involvement had protective or promotive effects. Questionnaires were administered to 424 Zulu adolescents in township high schools around Durban, South Africa. Structural equation modeling (SEM) was used to test associations among violence exposures and both violent attitudes and behavior. Victimization, witnessing violence, and friends' violent behavior contributed directly to violent behavior. Only family conflict and friends' violence influenced violent attitudes. Attitudes mediated effects of friends' violence on violent behavior. Multiple-group SEM indicated that adult involvement fit a protective model of resilience. These findings are discussed regarding their implications for prevention.

Intergenerational transmission of adaptive functioning: a test of the interactionist model of SES and human development.

PubMed

Schofield, Thomas J; Martin, Monica J; Conger, Katherine J; Neppl, Tricia M; Donnellan, M Brent; Conger, Rand D

2011-01-01

The interactionist model (IM) of human development (R. D. Conger & M. B. Donellan, 2007) proposes that the association between socioeconomic status (SES) and human development involves a dynamic interplay that includes both social causation (SES influences human development) and social selection (individual characteristics affect SES). Using a multigenerational data set involving 271 families, the current study finds empirical support for the IM. Adolescent personality characteristics indicative of social competence, goal-setting, hard work, and emotional stability predicted later SES, parenting, and family characteristics that were related to the positive development of a third-generation child. Processes of both social selection and social causation appear to account for the association between SES and dimensions of human development indicative of healthy functioning across multiple generations. © 2011 The Authors. Child Development © 2011 Society for Research in Child Development, Inc.

Prediction processes during multiple object tracking (MOT): involvement of dorsal and ventral premotor cortices

PubMed Central

Atmaca, Silke; Stadler, Waltraud; Keitel, Anne; Ott, Derek V M; Lepsien, Jöran; Prinz, Wolfgang

2013-01-01

Background The multiple object tracking (MOT) paradigm is a cognitive task that requires parallel tracking of several identical, moving objects following nongoal-directed, arbitrary motion trajectories. Aims The current study aimed to investigate the employment of prediction processes during MOT. As an indicator for the involvement of prediction processes, we targeted the human premotor cortex (PM). The PM has been repeatedly implicated to serve the internal modeling of future actions and action effects, as well as purely perceptual events, by means of predictive feedforward functions. Materials and methods Using functional magnetic resonance imaging (fMRI), BOLD activations recorded during MOT were contrasted with those recorded during the execution of a cognitive control task that used an identical stimulus display and demanded similar attentional load. A particular effort was made to identify and exclude previously found activation in the PM-adjacent frontal eye fields (FEF). Results We replicated prior results, revealing occipitotemporal, parietal, and frontal areas to be engaged in MOT. Discussion The activation in frontal areas is interpreted to originate from dorsal and ventral premotor cortices. The results are discussed in light of our assumption that MOT engages prediction processes. Conclusion We propose that our results provide first clues that MOT does not only involve visuospatial perception and attention processes, but prediction processes as well. PMID:24363971

Accounting for multiple births in randomised trials: a systematic review.

PubMed

Yelland, Lisa Nicole; Sullivan, Thomas Richard; Makrides, Maria

2015-03-01

Multiple births are an important subgroup to consider in trials aimed at reducing preterm birth or its consequences. Including multiples results in a unique mixture of independent and clustered data, which has implications for the design, analysis and reporting of the trial. We aimed to determine how multiple births were taken into account in the design and analysis of recent trials involving preterm infants, and whether key information relevant to multiple births was reported. We conducted a systematic review of multicentre randomised trials involving preterm infants published between 2008 and 2013. Information relevant to multiple births was extracted. Of the 56 trials included in the review, 6 (11%) excluded multiples and 24 (43%) failed to indicate whether multiples were included. Among the 26 trials that reported multiples were included, only one (4%) accounted for clustering in the sample size calculations and eight (31%) took the clustering into account in the analysis of the primary outcome. Of the 20 trials that randomised infants, 12 (60%) failed to report how infants from the same birth were randomised. Information on multiple births is often poorly reported in trials involving preterm infants, and clustering due to multiple births is rarely taken into account. Since ignoring clustering could result in inappropriate recommendations for clinical practice, clustering should be taken into account in the design and analysis of future neonatal and perinatal trials including infants from a multiple birth. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Adolescent Non-Involvement in Multiple Risk Behaviors: An Indicator of Successful Development?

ERIC Educational Resources Information Center

Willoughby, Teena; Chalmers, Heather; Busseri, Michael A.; Bosacki, Sandra; Dupont, Diane; Marini, Zopito; Rose-Krasnor, Linda; Sadava, Stan; Ward, Anthony; Woloshyn, Vera

2007-01-01

Based on the conceptualization of successful development as the joint maximization of desirable outcomes and minimization of undesirable outcomes (Baltes, 1997), the present study examined connections between adolescent non-involvement in multiple risk behaviors and positive developmental status. Results from a survey of 7290 high school students…

Learning Setting-Generalized Activity Models for Smart Spaces

PubMed Central

Cook, Diane J.

2011-01-01

The data mining and pervasive computing technologies found in smart homes offer unprecedented opportunities for providing context-aware services, including health monitoring and assistance to individuals experiencing difficulties living independently at home. In order to provide these services, smart environment algorithms need to recognize and track activities that people normally perform as part of their daily routines. However, activity recognition has typically involved gathering and labeling large amounts of data in each setting to learn a model for activities in that setting. We hypothesize that generalized models can be learned for common activities that span multiple environment settings and resident types. We describe our approach to learning these models and demonstrate the approach using eleven CASAS datasets collected in seven environments. PMID:21461133

Experiences Using Formal Methods for Requirements Modeling

NASA Technical Reports Server (NTRS)

Easterbrook, Steve; Lutz, Robyn; Covington, Rick; Kelly, John; Ampo, Yoko; Hamilton, David

1996-01-01

This paper describes three cases studies in the lightweight application of formal methods to requirements modeling for spacecraft fault protection systems. The case studies differ from previously reported applications of formal methods in that formal methods were applied very early in the requirements engineering process, to validate the evolving requirements. The results were fed back into the projects, to improve the informal specifications. For each case study, we describe what methods were applied, how they were applied, how much effort was involved, and what the findings were. In all three cases, the formal modeling provided a cost effective enhancement of the existing verification and validation processes. We conclude that the benefits gained from early modeling of unstable requirements more than outweigh the effort needed to maintain multiple representations.

Bayesian dynamical systems modelling in the social sciences.

PubMed

Ranganathan, Shyam; Spaiser, Viktoria; Mann, Richard P; Sumpter, David J T

2014-01-01

Data arising from social systems is often highly complex, involving non-linear relationships between the macro-level variables that characterize these systems. We present a method for analyzing this type of longitudinal or panel data using differential equations. We identify the best non-linear functions that capture interactions between variables, employing Bayes factor to decide how many interaction terms should be included in the model. This method punishes overly complicated models and identifies models with the most explanatory power. We illustrate our approach on the classic example of relating democracy and economic growth, identifying non-linear relationships between these two variables. We show how multiple variables and variable lags can be accounted for and provide a toolbox in R to implement our approach.

The relation between perceived parental involvement and academic achievement: the roles of Taiwanese students' academic beliefs and filial piety.

PubMed

Chen, Wei-Wen; Ho, Hsiu-Zu

2012-01-01

The excellent academic performance among East-Asian students has drawn international attention from educators and psychologists. However, the process that underlies student academic achievement for this particular group has rarely been documented. The present study examines how the relation between perceived parental involvement and Taiwanese students' academic achievement is mediated by student academic beliefs (i.e., beliefs about effort, academic self-concept, and perceived control). The study further explores whether this mediating effect varies with types of filial piety. Participants were 468 first-year students from colleges and universities in Taiwan. Multiple-group mediating models were analyzed using structural equation modeling (SEM). Results indicated that, for the Taiwanese sample, students' academic beliefs mediated the relation between perceived parental involvement and academic achievement. Furthermore, the mediational effect was significant for the reciprocal filial type, but not for the authoritarian filial type. The importance of the quality of the parent-child relationship and the internalization process related to children's assumptions of their parents' educational values indicate the need for a contextual view when examining predictors of student academic achievement.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koniges, A.E.; Craddock, G.G.; Schnack, D.D.

The purpose of the workshop was to assemble workers, both within and outside of the fusion-related computations areas, for discussion regarding the issues of dynamically adaptive gridding. There were three invited talks related to adaptive gridding application experiences in various related fields of computational fluid dynamics (CFD), and nine short talks reporting on the progress of adaptive techniques in the specific areas of scrape-off-layer (SOL) modeling and magnetohydrodynamic (MHD) stability. Adaptive mesh methods have been successful in a number of diverse fields of CFD for over a decade. The method involves dynamic refinement of computed field profiles in a waymore » that disperses uniformly the numerical errors associated with discrete approximations. Because the process optimizes computational effort, adaptive mesh methods can be used to study otherwise the intractable physical problems that involve complex boundary shapes or multiple spatial/temporal scales. Recent results indicate that these adaptive techniques will be required for tokamak fluid-based simulations involving the diverted tokamak SOL modeling and MHD simulations problems related to the highest priority ITER relevant issues.Individual papers are indexed separately on the energy data bases.« less

Exogenous administration of Substance P enhances wound healing in a novel skin-injury model.

PubMed

Delgado, Angel V; McManus, Albert T; Chambers, James P

2005-04-01

Soft tissue injury accounts for approximately 44% of all wounds in both the military and civilian populations. Following injury to soft tissue, Substance P (SP) and other neuropeptides are released by cutaneous neurons and modulate the function of immunocompetent and inflammatory cells, as well as epithelial and endothelial cells. The interaction between these components of the nervous system and multiple target cells affecting cutaneous repair is of increasing interest. In this report, we describe the effects of SP on wound repair in a novel, laser-induced, skin-wound model. Gross and histologic examination of laser-induced injury revealed that exogenously administered SP affects wound healing via neurite outgrowth, in addition to adhesion molecule and neurokinin-1 receptor involvement in vivo. All SP effects were decreased by pretreatment with Spantide II, an SP antagonist. The elucidation of SP-mediating mechanisms is crucial to firmly establishing the involvement and interaction of the peripheral nervous system and the immune system in cutaneous repair. Findings presented here suggest that SP participates in the complex network of mediators involved in cutaneous inflammation and wound healing.

Using Soft Sculpture Microfossils and Other Crafted Models to Teach Geoscience

NASA Astrophysics Data System (ADS)

Spinak, N. R.

2017-12-01

For the past 5 years, the International Ocean Discovery Program (IODP) has been using the author's sewn models of microfossils to help learners understand the shapes and design of these tiny fossils. These tactile objects make the study of ancient underwater life more tangible. Multiple studies have shown that interactive models can help many learners understand science. The Montessori and Waldorf education programs are based in large part on earlier insights into meeting these needs. The act of drawing has been an essential part of medical education. The STEAM (Science, Technology, Engineering, Arts and Math) movement has advocated for STEM supporters to recognize the inseparability of science and art. This presentation describes how the author's knitted or sewn models of microfossils incorporate art and design into geoscience education. The geoscience research and art processes used in developing and creating these educational soft sculptures will be described. In multiple entry points to science study, specific reciprocal benefits to boundary crossing among the arts and sciences for those who have primary talents in a particular area of study will be discussed. Geoscience education can benefit from using art and craft items such as models. Many websites now offer soft sculptures for biology study such as organs and germs (e.g. (https://www.giantmicrobes.com/us/main/nasty-germs). The Wortheim project involving community and crochet is another approach (http://crochetcoralreef.org/). These tactile artifacts give learners an entry-level experience with biology. Three dimensional models are multisensory. The enlarged manipulative microfossil models invite learners to make comparisons and gain insights when microscopes are not available or appropriate for the audience. Adding the physical involvement of creating a microfossil yourself increases the multi-sensory experience even further. Learning craft skills extends the cross-cutting concepts of the NGSS to a mutual relationship between science and art.

Schistosoma haematobium infection in the opossum (Didelphis marsupialis): involvement of the urogenital system.

PubMed

Kuntz, R E; Myers, B J; Cheever, A W

1971-01-01

Investigations of experimental schistosomiasis haematobia have suffered for want of satisfactory mammals in which schistosome infections would establish host-parasite situations more or less comparable with those seen in man. As a consequence, mammals representing different major groups have been exposed to infection by Schistosoma haematobium (Iran strain) to determine their potential use as models for more detailed investigations. In preliminary studies, 8 American opossums (Didelphis marsupialis) were exposed to 1000 or 2000 cercariae. Macroscopic involvement of the urogenital tract was noted in 3 animals, one of which had a 1-cm fibrous plaque in the bladder. In another animal, multiple transitional cell papillomas were present in the bladder and in one ureter.

Cost-effective solutions to maintaining smart grid reliability

NASA Astrophysics Data System (ADS)

Qin, Qiu

As the aging power systems are increasingly working closer to the capacity and thermal limits, maintaining an sufficient reliability has been of great concern to the government agency, utility companies and users. This dissertation focuses on improving the reliability of transmission and distribution systems. Based on the wide area measurements, multiple model algorithms are developed to diagnose transmission line three-phase short to ground faults in the presence of protection misoperations. The multiple model algorithms utilize the electric network dynamics to provide prompt and reliable diagnosis outcomes. Computational complexity of the diagnosis algorithm is reduced by using a two-step heuristic. The multiple model algorithm is incorporated into a hybrid simulation framework, which consist of both continuous state simulation and discrete event simulation, to study the operation of transmission systems. With hybrid simulation, line switching strategy for enhancing the tolerance to protection misoperations is studied based on the concept of security index, which involves the faulted mode probability and stability coverage. Local measurements are used to track the generator state and faulty mode probabilities are calculated in the multiple model algorithms. FACTS devices are considered as controllers for the transmission system. The placement of FACTS devices into power systems is investigated with a criterion of maintaining a prescribed level of control reconfigurability. Control reconfigurability measures the small signal combined controllability and observability of a power system with an additional requirement on fault tolerance. For the distribution systems, a hierarchical framework, including a high level recloser allocation scheme and a low level recloser placement scheme, is presented. The impacts of recloser placement on the reliability indices is analyzed. Evaluation of reliability indices in the placement process is carried out via discrete event simulation. The reliability requirements are described with probabilities and evaluated from the empirical distributions of reliability indices.

Patch models and their applications to multivehicle command and control.

PubMed

Rao, Venkatesh G; D'Andrea, Raffaello

2007-06-01

We introduce patch models, a computational modeling formalism for multivehicle combat domains, based on spatiotemporal abstraction methods developed in the computer science community. The framework yields models that are expressive enough to accommodate nontrivial controlled vehicle dynamics while being within the representational capabilities of common artificial intelligence techniques used in the construction of autonomous systems. The framework allows several key design requirements of next-generation network-centric command and control systems, such as maintenance of shared situation awareness, to be achieved. Major features include support for multiple situation models at each decision node and rapid mission plan adaptation. We describe the formal specification of patch models and our prototype implementation, i.e., Patchworks. The capabilities of patch models are validated through a combat mission simulation in Patchworks, which involves two defending teams protecting a camp from an enemy attacking team.

SUMMIT (Serially Unified Multicenter Multiple Sclerosis Investigation): creating a repository of deeply phenotyped contemporary multiple sclerosis cohorts.

PubMed

Bove, Riley; Chitnis, Tanuja; Cree, Bruce Ac; Tintoré, Mar; Naegelin, Yvonne; Uitdehaag, Bernard Mj; Kappos, Ludwig; Khoury, Samia J; Montalban, Xavier; Hauser, Stephen L; Weiner, Howard L

2017-08-01

There is a pressing need for robust longitudinal cohort studies in the modern treatment era of multiple sclerosis. Build a multiple sclerosis (MS) cohort repository to capture the variability of disability accumulation, as well as provide the depth of characterization (clinical, radiologic, genetic, biospecimens) required to adequately model and ultimately predict a patient's course. Serially Unified Multicenter Multiple Sclerosis Investigation (SUMMIT) is an international multi-center, prospectively enrolled cohort with over a decade of comprehensive follow-up on more than 1000 patients from two large North American academic MS Centers (Brigham and Women's Hospital (Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital (CLIMB; BWH)) and University of California, San Francisco (Expression/genomics, Proteomics, Imaging, and Clinical (EPIC))). It is bringing online more than 2500 patients from additional international MS Centers (Basel (Universitätsspital Basel (UHB)), VU University Medical Center MS Center Amsterdam (MSCA), Multiple Sclerosis Center of Catalonia-Vall d'Hebron Hospital (Barcelona clinically isolated syndrome (CIS) cohort), and American University of Beirut Medical Center (AUBMC-Multiple Sclerosis Interdisciplinary Research (AMIR)). We provide evidence for harmonization of two of the initial cohorts in terms of the characterization of demographics, disease, and treatment-related variables; demonstrate several proof-of-principle analyses examining genetic and radiologic predictors of disease progression; and discuss the steps involved in expanding SUMMIT into a repository accessible to the broader scientific community.

Improving Healthcare in Pediatric Oncology: Development and Testing of Multiple Indicators to Evaluate a Hub-And-Spoke Model.

PubMed

Zucchetti, Giulia; Bertorello, Nicoletta; Angelastro, Angela; Gianino, Paola; Bona, Gianni; Barbara, Affif; Besenzon, Luigi; Brach Del Prever, Adalberto; Pesce, Fernando; Nangeroni, Marco; Fagioli, Franca

2017-06-01

Purpose The hub-and-spoke is a new innovation model in healthcare that has been adopted in some countries to manage rare pathologies. We developed a set of indicators to assess current quality practices of the hub-and-spoke model adopted in the Interregional Pediatric Oncology Network in Northwest Italy and to promote patient, family, and professional healthcare empowerment. Methods Literature and evidence-based clinical guidelines were reviewed and multiprofessional team workshops were carried out to highlight some important issues on healthcare in pediatric oncology and to translate them into a set of multiple indicators. For each indicator, specific questions were formulated and tested through a series of questionnaires completed by 80 healthcare professionals and 50 pediatric patients and their parents. Results The results highlighted a positive perception of healthcare delivered by the hub-and-spoke model (M HP = 156, M Pat = 93, M Par = 104). Based on the participants' suggestions, some quality improvements have been implemented. Conclusions This study represents the first attempt to examine this new model of pediatric oncology care through the active involvement of patients, families, and healthcare professionals. Suggestions for adopting a hub-and-spoke model in pediatric oncology in other regions and countries are also highlighted.

A blended continuous–discontinuous finite element method for solving the multi-fluid plasma model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sousa, E.M., E-mail: sousae@uw.edu; Shumlak, U., E-mail: shumlak@uw.edu

The multi-fluid plasma model represents electrons, multiple ion species, and multiple neutral species as separate fluids that interact through short-range collisions and long-range electromagnetic fields. The model spans a large range of temporal and spatial scales, which renders the model stiff and presents numerical challenges. To address the large range of timescales, a blended continuous and discontinuous Galerkin method is proposed, where the massive ion and neutral species are modeled using an explicit discontinuous Galerkin method while the electrons and electromagnetic fields are modeled using an implicit continuous Galerkin method. This approach is able to capture large-gradient ion and neutralmore » physics like shock formation, while resolving high-frequency electron dynamics in a computationally efficient manner. The details of the Blended Finite Element Method (BFEM) are presented. The numerical method is benchmarked for accuracy and tested using two-fluid one-dimensional soliton problem and electromagnetic shock problem. The results are compared to conventional finite volume and finite element methods, and demonstrate that the BFEM is particularly effective in resolving physics in stiff problems involving realistic physical parameters, including realistic electron mass and speed of light. The benefit is illustrated by computing a three-fluid plasma application that demonstrates species separation in multi-component plasmas.« less

Multiple Scenarios of Transition to Chaos in the Alternative Splicing Model

NASA Astrophysics Data System (ADS)

Kogai, Vladislav V.; Likhoshvai, Vitaly A.; Fadeev, Stanislav I.; Khlebodarova, Tamara M.

We have investigated the scenarios of transition to chaos in the mathematical model of a genetic system constituted by a single transcription factor-encoding gene, the expression of which is self-regulated by a feedback loop that involves protein isoforms. Alternative splicing results in the synthesis of protein isoforms providing opposite regulatory outcomes — activation or repression. The model is represented by a differential equation with two delayed arguments. The possibility of transition to chaos dynamics via all classical scenarios: a cascade of period-doubling bifurcations, quasiperiodicity and type-I, type-II and type-III intermittencies, has been numerically demonstrated. The parametric features of each type of transition to chaos have been described.

Process-Improvement Cost Model for the Emergency Department.

PubMed

Dyas, Sheila R; Greenfield, Eric; Messimer, Sherri; Thotakura, Swati; Gholston, Sampson; Doughty, Tracy; Hays, Mary; Ivey, Richard; Spalding, Joseph; Phillips, Robin

2015-01-01

The objective of this report is to present a simplified, activity-based costing approach for hospital emergency departments (EDs) to use with Lean Six Sigma cost-benefit analyses. The cost model complexity is reduced by removing diagnostic and condition-specific costs, thereby revealing the underlying process activities' cost inefficiencies. Examples are provided for evaluating the cost savings from reducing discharge delays and the cost impact of keeping patients in the ED (boarding) after the decision to admit has been made. The process-improvement cost model provides a needed tool in selecting, prioritizing, and validating Lean process-improvement projects in the ED and other areas of patient care that involve multiple dissimilar diagnoses.

Integrated multiscale biomaterials experiment and modelling: a perspective

PubMed Central

Buehler, Markus J.; Genin, Guy M.

2016-01-01

Advances in multiscale models and computational power have enabled a broad toolset to predict how molecules, cells, tissues and organs behave and develop. A key theme in biological systems is the emergence of macroscale behaviour from collective behaviours across a range of length and timescales, and a key element of these models is therefore hierarchical simulation. However, this predictive capacity has far outstripped our ability to validate predictions experimentally, particularly when multiple hierarchical levels are involved. The state of the art represents careful integration of multiscale experiment and modelling, and yields not only validation, but also insights into deformation and relaxation mechanisms across scales. We present here a sampling of key results that highlight both challenges and opportunities for integrated multiscale experiment and modelling in biological systems. PMID:28981126

A principal component regression model to forecast airborne concentration of Cupressaceae pollen in the city of Granada (SE Spain), during 1995-2006.

PubMed

Ocaña-Peinado, Francisco M; Valderrama, Mariano J; Bouzas, Paula R

2013-05-01

The problem of developing a 2-week-on ahead forecast of atmospheric cypress pollen levels is tackled in this paper by developing a principal component multiple regression model involving several climatic variables. The efficacy of the proposed model is validated by means of an application to real data of Cupressaceae pollen concentration in the city of Granada (southeast of Spain). The model was applied to data from 11 consecutive years (1995-2005), with 2006 being used to validate the forecasts. Based on the work of different authors, factors as temperature, humidity, hours of sun and wind speed were incorporated in the model. This methodology explains approximately 75-80% of the variability in the airborne Cupressaceae pollen concentration.

Biofabricated constructs as tissue models: a short review.

PubMed

Costa, Pedro F

2015-04-01

Biofabrication is currently able to provide reliable models for studying the development of cells and tissues into multiple environments. As the complexity of biofabricated constructs is becoming increasingly higher their ability to closely mimic native tissues and organs is also increasing. Various biofabrication technologies currently allow to precisely build cell/tissue constructs at multiple dimension ranges with great accuracy. Such technologies are also able to assemble together multiple types of cells and/or materials and generate constructs closely mimicking various types of tissues. Furthermore, the high degree of automation involved in these technologies enables the study of large arrays of testing conditions within increasingly smaller and automated devices both in vitro and in vivo. Despite not yet being able to generate constructs similar to complex tissues and organs, biofabrication is rapidly evolving in that direction. One major hurdle to be overcome in order for such level of complex detail to be achieved is the ability to generate complex vascular structures within biofabricated constructs. This review describes several of the most relevant technologies and methodologies currently utilized within biofabrication and provides as well a brief overview of their current and future potential applications.

Rupture history of the 2008 Mw 7.9 Wenchuan, China, earthquake: Evaluation of separate and joint inversions of geodetic, teleseismic, and strong-motion data

USGS Publications Warehouse

Hartzell, Stephen; Mendoza, Carlos; Ramírez-Guzmán, Leonardo; Zeng, Yuesha; Mooney, Walter

2013-01-01

An extensive data set of teleseismic and strong-motion waveforms and geodetic offsets is used to study the rupture history of the 2008 Wenchuan, China, earthquake. A linear multiple-time-window approach is used to parameterize the rupture. Because of the complexity of the Wenchuan faulting, three separate planes are used to represent the rupturing surfaces. This earthquake clearly demonstrates the strengths and limitations of geodetic, teleseismic, and strong-motion data sets. Geodetic data (static offsets) are valuable for determining the distribution of shallower slip but are insensitive to deeper faulting and reveal nothing about the timing of slip. Teleseismic data in the distance range 30°–90° generally involve no modeling difficulties because of simple ray paths and can distinguish shallow from deep slip. Teleseismic data, however, cannot distinguish between different slip scenarios when multiple fault planes are involved because steep takeoff angles lead to ambiguity in timing. Local strong-motion data, on the other hand, are ideal for determining the direction of rupture from directivity but can easily be over modeled with inaccurate Green’s functions, leading to misinterpretation of the slip distribution. We show that all three data sets are required to give an accurate description of the Wenchuan rupture. The moment is estimated to be approximately 1.0 × 1021 N · m with the slip characterized by multiple large patches with slips up to 10 m. Rupture initiates on the southern end of the Pengguan fault and proceeds unilaterally to the northeast. Upon reaching the cross-cutting Xiaoyudong fault, rupture of the adjacent Beichuan fault starts at this juncture and proceeds bilaterally to the northeast and southwest.

The Multiple Correspondence Analysis Method and Brain Functional Connectivity: Its Application to the Study of the Non-linear Relationships of Motor Cortex and Basal Ganglia.

PubMed

Rodriguez-Sabate, Clara; Morales, Ingrid; Sanchez, Alberto; Rodriguez, Manuel

2017-01-01

The complexity of basal ganglia (BG) interactions is often condensed into simple models mainly based on animal data and that present BG in closed-loop cortico-subcortical circuits of excitatory/inhibitory pathways which analyze the incoming cortical data and return the processed information to the cortex. This study was aimed at identifying functional relationships in the BG motor-loop of 24 healthy-subjects who provided written, informed consent and whose BOLD-activity was recorded by MRI methods. The analysis of the functional interaction between these centers by correlation techniques and multiple linear regression showed non-linear relationships which cannot be suitably addressed with these methods. The multiple correspondence analysis (MCA), an unsupervised multivariable procedure which can identify non-linear interactions, was used to study the functional connectivity of BG when subjects were at rest. Linear methods showed different functional interactions expected according to current BG models. MCA showed additional functional interactions which were not evident when using lineal methods. Seven functional configurations of BG were identified with MCA, two involving the primary motor and somatosensory cortex, one involving the deepest BG (external-internal globus pallidum, subthalamic nucleus and substantia nigral), one with the input-output BG centers (putamen and motor thalamus), two linking the input-output centers with other BG (external pallidum and subthalamic nucleus), and one linking the external pallidum and the substantia nigral. The results provide evidence that the non-linear MCA and linear methods are complementary and should be best used in conjunction to more fully understand the nature of functional connectivity of brain centers.

Multilayer modeling and analysis of human brain networks

PubMed Central

2017-01-01

Abstract Understanding how the human brain is structured, and how its architecture is related to function, is of paramount importance for a variety of applications, including but not limited to new ways to prevent, deal with, and cure brain diseases, such as Alzheimer’s or Parkinson’s, and psychiatric disorders, such as schizophrenia. The recent advances in structural and functional neuroimaging, together with the increasing attitude toward interdisciplinary approaches involving computer science, mathematics, and physics, are fostering interesting results from computational neuroscience that are quite often based on the analysis of complex network representation of the human brain. In recent years, this representation experienced a theoretical and computational revolution that is breaching neuroscience, allowing us to cope with the increasing complexity of the human brain across multiple scales and in multiple dimensions and to model structural and functional connectivity from new perspectives, often combined with each other. In this work, we will review the main achievements obtained from interdisciplinary research based on magnetic resonance imaging and establish de facto, the birth of multilayer network analysis and modeling of the human brain. PMID:28327916

Using Modern C++ Idiom for the Discretisation of Sets of Coupled Transport Equations in Numerical Plasma Physics

NASA Astrophysics Data System (ADS)

van Dijk, Jan; Hartgers, Bart; van der Mullen, Joost

2006-10-01

Self-consistent modelling of plasma sources requires a simultaneous treatment of multiple physical phenomena. As a result plasma codes have a high degree of complexity. And with the growing interest in time-dependent modelling of non-equilibrium plasma in three dimensions, codes tend to become increasingly hard to explain-and-maintain. As a result of these trends there has been an increased interest in the software-engineering and implementation aspects of plasma modelling in our group at Eindhoven University of Technology. In this contribution we will present modern object-oriented techniques in C++ to solve an old problem: that of the discretisation of coupled linear(ized) equations involving multiple field variables on ortho-curvilinear meshes. The `LinSys' code has been tailored to the transport equations that occur in transport physics. The implementation has been made both efficient and user-friendly by using modern idiom like expression templates and template meta-programming. Live demonstrations will be given. The code is available to interested parties; please visit www.dischargemodelling.org.

Experimental Autoimmune Encephalomyelitis (EAE) as Animal Models of Multiple Sclerosis (MS).

PubMed

Glatigny, Simon; Bettelli, Estelle

2018-01-08

Multiple sclerosis (MS) is a multifocal demyelinating disease of the central nervous system (CNS) leading to the progressive destruction of the myelin sheath surrounding axons. It can present with variable clinical and pathological manifestations, which might reflect the involvement of distinct pathogenic processes. Although the mechanisms leading to the development of the disease are not fully understood, numerous evidences indicate that MS is an autoimmune disease, the initiation and progression of which are dependent on an autoimmune response against myelin antigens. In addition, genetic susceptibility and environmental triggers likely contribute to the initiation of the disease. At this time, there is no cure for MS, but several disease-modifying therapies (DMTs) are available to control and slow down disease progression. A good number of these DMTs were identified and tested using animal models of MS referred to as experimental autoimmune encephalomyelitis (EAE). In this review, we will recapitulate the characteristics of EAE models and discuss how they help shed light on MS pathogenesis and help test new treatments for MS patients. Copyright © 2018 Cold Spring Harbor Laboratory Press; all rights reserved.

A multichannel model for the self-consistent analysis of coherent transport in graphene nanoribbons.

PubMed

Mencarelli, Davide; Pierantoni, Luca; Farina, Marco; Di Donato, Andrea; Rozzi, Tullio

2011-08-23

In this contribution, we analyze the multichannel coherent transport in graphene nanoribbons (GNRs) by a scattering matrix approach. We consider the transport properties of GNR devices of a very general form, involving multiple bands and multiple leads. The 2D quantum transport over the whole GNR surface, described by the Schrödinger equation, is strongly nonlinear as it implies calculation of self-generated and externally applied electrostatic potentials, solutions of the 3D Poisson equation. The surface charge density is computed as a balance of carriers traveling through the channel at all of the allowed energies. Moreover, formation of bound charges corresponding to a discrete modal spectrum is observed and included in the model. We provide simulation examples by considering GNR configurations typical for transistor devices and GNR protrusions that find an interesting application as cold cathodes for X-ray generation. With reference to the latter case, a unified model is required in order to couple charge transport and charge emission. However, to a first approximation, these could be considered as independent problems, as in the example. © 2011 American Chemical Society

Impacts of climate change on the food-energy-water nexus in the upper Yellow River Basin: An integrated hydro-economic modeling approach

NASA Astrophysics Data System (ADS)

Si, Y.; Cai, X.

2017-12-01

The large-scale reservoir system built on the upper Yellow River serves multiple purposes. The generated hydropower supplies over 60% of the entire electricity for the regional power grid while the irrigated crop production feeds almost one-third of the total population throughout the whole river basin. Moreover, the reservoir system also bears the responsibility for controlling ice flood, which occurs during the non-flood season due to winter ice freezing followed by spring thawing process, and could be even more disastrous than the summer flood. The contradiction of water allocation to satisfy multi-sector demands while mitigating ice flood risk has been longstanding. However, few researchers endeavor to employ the nexus thinking to addressing the complexities involved in all the interlinked purposes. In this study, we develop an integrated hydro-economic model that can be used to explore both the tradeoffs and synergies between the multiple purposes, based on which the water infrastructures (e.g., reservoir, diversion canal, pumping well) can be coordinated for maximizing the co-benefits of multiple sectors. The model is based on a node-link schematic of multiple operations including hydropower generation, irrigation scheduling, and the conjunctive use of surface and ground water resources. In particular, the model depicts some details regarding reservoir operation rules during the ice season using two indicators, i.e., flow control period and flow control level. The rules are obtained from historical records using data mining techniques under different climate conditions, and they are added to the model as part of the system constraints. Future reservoir inflow series are generated by a hydrological model with future climate scenarios projected by General Circulation Model (GCM). By analyzing the model results under the various climate scenarios, the future possible shifting trajectory of the food-energy-water system characteristics will be derived compared to the baseline scenario (i.e., the status-quo condition). Thus the model and the results are expected to be useful for enlightening economically efficient water allocation policy coping with climate change.

Using input command pre-shaping to suppress multiple mode vibration

NASA Technical Reports Server (NTRS)

Hyde, James M.; Seering, Warren P.

1990-01-01

Spacecraft, space-borne robotic systems, and manufacturing equipment often utilize lightweight materials and configurations that give rise to vibration problems. Prior research has led to the development of input command pre-shapers that can significantly reduce residual vibration. These shapers exhibit marked insensitivity to errors in natural frequency estimates and can be combined to minimize vibration at more than one frequency. This paper presents a method for the development of multiple mode input shapers which are simpler to implement than previous designs and produce smaller system response delays. The new technique involves the solution of a group of simultaneous non-linear impulse constraint equations. The resulting shapers were tested on a model of MACE, an MIT/NASA experimental flexible structure.

Spatiotemporal multivariate mixture models for Bayesian model selection in disease mapping.

PubMed

Lawson, A B; Carroll, R; Faes, C; Kirby, R S; Aregay, M; Watjou, K

2017-12-01

It is often the case that researchers wish to simultaneously explore the behavior of and estimate overall risk for multiple, related diseases with varying rarity while accounting for potential spatial and/or temporal correlation. In this paper, we propose a flexible class of multivariate spatio-temporal mixture models to fill this role. Further, these models offer flexibility with the potential for model selection as well as the ability to accommodate lifestyle, socio-economic, and physical environmental variables with spatial, temporal, or both structures. Here, we explore the capability of this approach via a large scale simulation study and examine a motivating data example involving three cancers in South Carolina. The results which are focused on four model variants suggest that all models possess the ability to recover simulation ground truth and display improved model fit over two baseline Knorr-Held spatio-temporal interaction model variants in a real data application.

Modeling of multiple equilibria in the self-aggregation of di-n-decyldimethylammonium chloride/octaethylene glycol monododecyl ether/cyclodextrin ternary systems.

PubMed

Leclercq, Loïc; Lubart, Quentin; Aubry, Jean-Marie; Nardello-Rataj, Véronique

2013-05-28

The surface tension equations of binary surfactant mixtures (di-n-decyldimethylammonium chloride and octaethylene glycol monododecyl ether) are established by combining the Szyszkowski equation of surfactant solutions, the ideal or nonideal mixing theory, and the phase separation model. For surfactant mixtures, the surface tension at the air-water interface is calculated using nonideal theory due to synergism between the two adsorbed surfactant types. The incorporation of cyclodextrin complexation model to the surface tension equations gives a robust model for the description of the surface tension isotherms of binary, ternary, and more complex systems involving numerous inclusion complexes. The surface tension data obtained experimentally shows excellent agreement with the theoretical model below and above the formation of micelles. The strong synergistic effect observed between the two surfactants is disrupted by the presence of CDs, leading to ideal behavior of ternary systems. Indeed, depending on the nature of the cyclodextrin (i.e., α, β, or γ), which allows a tuning of the cavity size, the binding constants with the surfactants are modified as well as the surface properties due to strong modification of equilibria involved in the ternary mixture.

Connections of the Lateral Hypothalamic Area Juxtadorsomedial Region in the Male Rat

PubMed Central

Hahn, Joel D.; Swanson, Larry W.

2014-01-01

The connections of the lateral hypothalamic area juxtadorsomedial region (LHAjd) were investigated in a series of pathway-tracing experiments involving iontophoretic co-injection of the tracers Phaseolus vulgaris-leucoagglutinin (PHA-L; for outputs) and cholera toxin B subunit (CTB; for inputs). Results revealed that the LHAjd has connections with some 318 distinct gray matter regions encompassing all four subsystems—motor, sensory, cognitive, and behavioral state—included in a basic structure–function network model of the nervous system. Integration of these subsystems is necessary for the coordination and control of emotion and behavior, and in that regard the connections of the LHAjd indicate that it may have a prominent role. Furthermore, the LHAjd connections, together with the connections of other LHA differentiations studied similarly to date, indicate a distinct topographic organization that suggests each LHA differentiation has specifically differing degrees of involvement in the control of multiple behaviors. For the LHAjd, its involvement to a high degree in the control of defensive behavior, and to a lesser degree in the control of other behaviors, including ingestive and reproductive, is suggested. Moreover, the connections of the LHAjd suggest that its possible role in the control of these behaviors may be very broad in scope because they involve the somatic, neuroendocrine, and autonomic divisions of the nervous system. In addition, we suggest that connections between LHA differentiations may provide, at the level of the hypothalamus, a neuronal substrate for the coordinated control of multiple themes in the behavioral repertoire. PMID:22488503

Too much of a good thing? How breadth of extracurricular participation relates to school-related affect and academic outcomes during adolescence.

PubMed

Knifsend, Casey A; Graham, Sandra

2012-03-01

Although adolescents often participate in multiple extracurricular activities, little research has examined how the breadth of activities in which an adolescent is involved relates to school-related affect and academic performance. Relying on a large, multi-ethnic sample (N = 864; 55.9% female), the current study investigated linear and non-linear relationships of 11th grade activity participation in four activity domains (academic/leadership groups, arts activities, clubs, and sports) to adolescents' sense of belonging at school, academic engagement, and grade point average, contemporarily and in 12th grade. Results of multiple regression models revealed curvilinear relationships for sense of belonging at school in 11th and 12th grade, grade point average in 11th grade, and academic engagement in 12th grade. Adolescents who were moderately involved (i.e., in two domains) reported a greater sense of belonging at school in 11th and 12th grade, a higher grade point average in 11th grade, and greater academic engagement in 12th grade, relative to those who were more or less involved. Furthermore, adolescents' sense of belonging at school in 11th grade mediated the relationship of domain participation in 11th grade to academic engagement in 12th grade. This study suggests that involvement in a moderate number of activity domains promotes positive school-related affect and greater academic performance. School policy implications and recommendations are discussed.

Cellular Decision Making by Non-Integrative Processing of TLR Inputs.

PubMed

Kellogg, Ryan A; Tian, Chengzhe; Etzrodt, Martin; Tay, Savaş

2017-04-04

Cells receive a multitude of signals from the environment, but how they process simultaneous signaling inputs is not well understood. Response to infection, for example, involves parallel activation of multiple Toll-like receptors (TLRs) that converge on the nuclear factor κB (NF-κB) pathway. Although we increasingly understand inflammatory responses for isolated signals, it is not clear how cells process multiple signals that co-occur in physiological settings. We therefore examined a bacterial infection scenario involving co-stimulation of TLR4 and TLR2. Independent stimulation of these receptors induced distinct NF-κB dynamic profiles, although surprisingly, under co-stimulation, single cells continued to show ligand-specific dynamic responses characteristic of TLR2 or TLR4 signaling rather than a mixed response, comprising a cellular decision that we term "non-integrative" processing. Iterating modeling and microfluidic experiments revealed that non-integrative processing occurred through interaction of switch-like NF-κB activation, receptor-specific processing timescales, cell-to-cell variability, and TLR cross-tolerance mediated by multilayer negative feedback. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Drebrin and Spermatogenesis

PubMed Central

Chen, Haiqi; Li, Michelle W.M.

2018-01-01

Drebrin is a family of actin-binding proteins with two known members called drebrin A and E. Apart from the ability to stabilize F-actin microfilaments via their actin-binding domains near the N-terminus, drebrin also regulates multiple cellular functions due to its unique ability to recruit multiple binding partners to a specific cellular domain, such as the seminiferous epithelium during the epithelial cycle of spermatogenesis. Recent studies have illustrated the role of drebrin E in the testis during spermatogenesis in particular via its ability to recruit branched actin polymerization protein known as actin-related protein 3 (Arp3), illustrating its involvement in modifying the organization of actin microfilaments at the ectoplasmic specialization (ES) which includes the testis-specific anchoring junction at the Sertoli-spermatid (apical ES) interface and at the Sertoli cell-cell (basal ES) interface. These data are carefully evaluated in light of other recent findings herein regarding the role of drebrin in actin filament organization at the ES. We also provide the hypothetical model regarding its involvement in germ cell transport during the epithelial cycle in the seminiferous epithelium to support spermatogenesis. PMID:28865027

Significant Linkage for Tourette Syndrome in a Large French Canadian Family

PubMed Central

Mérette, Chantal; Brassard, Andrée; Potvin, Anne; Bouvier, Hélène; Rousseau, François; Émond, Claudia; Bissonnette, Luc; Roy, Marc-André; Maziade, Michel; Ott, Jurg; Caron, Chantal

2000-01-01

Family and twin studies provide strong evidence that genetic factors are involved in the transmission of Gilles de la Tourette syndrome (TS) and related psychiatric disorders. To detect the underlying susceptibility gene(s) for TS, we performed linkage analysis in one large French Canadian family (127 members) from the Charlevoix region, in which 20 family members were definitely affected by TS and 20 others showed related tic disorders. Using model-based linkage analysis, we observed a LOD score of 3.24 on chromosome 11 (11q23). This result was obtained in a multipoint approach involving marker D11S1377, the marker for which significant linkage disequilibrium with TS recently has been detected in an Afrikaner population. Altogether, 25 markers were studied, and, for level of significance, we derived a criterion that took into account the multiple testing arising from the use of three phenotype definitions and three modes of inheritance, a procedure that yielded a LOD score of 3.18. Hence, even after adjustment for multiple testing, the present study shows statistically significant evidence for genetic linkage with TS. PMID:10986045

Multiobjective optimisation design for enterprise system operation in the case of scheduling problem with deteriorating jobs

NASA Astrophysics Data System (ADS)

Wang, Hongfeng; Fu, Yaping; Huang, Min; Wang, Junwei

2016-03-01

The operation process design is one of the key issues in the manufacturing and service sectors. As a typical operation process, the scheduling with consideration of the deteriorating effect has been widely studied; however, the current literature only studied single function requirement and rarely considered the multiple function requirements which are critical for a real-world scheduling process. In this article, two function requirements are involved in the design of a scheduling process with consideration of the deteriorating effect and then formulated into two objectives of a mathematical programming model. A novel multiobjective evolutionary algorithm is proposed to solve this model with combination of three strategies, i.e. a multiple population scheme, a rule-based local search method and an elitist preserve strategy. To validate the proposed model and algorithm, a series of randomly-generated instances are tested and the experimental results indicate that the model is effective and the proposed algorithm can achieve the satisfactory performance which outperforms the other state-of-the-art multiobjective evolutionary algorithms, such as nondominated sorting genetic algorithm II and multiobjective evolutionary algorithm based on decomposition, on all the test instances.

Automatic image database generation from CAD for 3D object recognition

NASA Astrophysics Data System (ADS)

Sardana, Harish K.; Daemi, Mohammad F.; Ibrahim, Mohammad K.

1993-06-01

The development and evaluation of Multiple-View 3-D object recognition systems is based on a large set of model images. Due to the various advantages of using CAD, it is becoming more and more practical to use existing CAD data in computer vision systems. Current PC- level CAD systems are capable of providing physical image modelling and rendering involving positional variations in cameras, light sources etc. We have formulated a modular scheme for automatic generation of various aspects (views) of the objects in a model based 3-D object recognition system. These views are generated at desired orientations on the unit Gaussian sphere. With a suitable network file sharing system (NFS), the images can directly be stored on a database located on a file server. This paper presents the image modelling solutions using CAD in relation to multiple-view approach. Our modular scheme for data conversion and automatic image database storage for such a system is discussed. We have used this approach in 3-D polyhedron recognition. An overview of the results, advantages and limitations of using CAD data and conclusions using such as scheme are also presented.

Carbon farming economics: What have we learned?

PubMed

Tang, Kai; Kragt, Marit E; Hailu, Atakelty; Ma, Chunbo

2016-05-01

This study reviewed 62 economic analyses published between 1995 and 2014 on the economic impacts of policies that incentivise agricultural greenhouse (GHG) mitigation. Typically, biophysical models are used to evaluate the changes in GHG mitigation that result from landholders changing their farm and land management practices. The estimated results of biophysical models are then integrated with economic models to simulate the costs of different policy scenarios to production systems. The cost estimates vary between $3 and $130/t CO2 equivalent in 2012 US dollars, depending on the mitigation strategies, spatial locations, and policy scenarios considered. Most studies assessed the consequences of a single, rather than multiple, mitigation strategies, and few considered the co-benefits of carbon farming. These omissions could challenge the reality and robustness of the studies' results. One of the biggest challenges facing agricultural economists is to assess the full extent of the trade-offs involved in carbon farming. We need to improve our biophysical knowledge about carbon farming co-benefits, predict the economic impacts of employing multiple strategies and policy incentives, and develop the associated integrated models, to estimate the full costs and benefits of agricultural GHG mitigation to farmers and the rest of society. Copyright © 2016 Elsevier Ltd. All rights reserved.

Enhancing the Ability of Experimental Autoimmune Encephalomyelitis to Serve as a More Rigorous Model of Multiple Sclerosis through Refinement of the Experimental Design

PubMed Central

Emerson, Mitchell R; Gallagher, Ryan J; Marquis, Janet G; LeVine, Steven M

2009-01-01

Advancing the understanding of the mechanisms involved in the pathogenesis of multiple sclerosis (MS) likely will lead to new and better therapeutics. Although important information about the disease process has been obtained from research on pathologic specimens, peripheral blood lymphocytes and MRI studies, the elucidation of detailed mechanisms has progressed largely through investigations using animal models of MS. In addition, animal models serve as an important tool for the testing of putative interventions. The most commonly studied model of MS is experimental autoimmune encephalomyelitis (EAE). This model can be induced in a variety of species and by various means, but there has been concern that the model may not accurately reflect the disease process, and more importantly, it may give rise to erroneous findings when it is used to test possible therapeutics. Several reasons have been given to explain the shortcomings of this model as a useful testing platform, but one idea provides a framework for improving the value of this model, and thus, it deserves careful consideration. In particular, the idea asserts that EAE studies are inadequately designed to enable appropriate evaluation of putative therapeutics. Here we discuss problem areas within EAE study designs and provide suggestions for their improvement. This paper is principally directed at investigators new to the field of EAE, although experienced investigators may find useful suggestions herein. PMID:19389303

BioEarth: Envisioning and developing a new regional earth system model to inform natural and agricultural resource management

DOE PAGES

Adam, Jennifer C.; Stephens, Jennie C.; Chung, Serena H.; ...

2014-04-24

Uncertainties in global change impacts, the complexities associated with the interconnected cycling of nitrogen, carbon, and water present daunting management challenges. Existing models provide detailed information on specific sub-systems (e.g., land, air, water, and economics). An increasing awareness of the unintended consequences of management decisions resulting from interconnectedness of these sub-systems, however, necessitates coupled regional earth system models (EaSMs). Decision makers’ needs and priorities can be integrated into the model design and development processes to enhance decision-making relevance and “usability” of EaSMs. BioEarth is a research initiative currently under development with a focus on the U.S. Pacific Northwest region thatmore » explores the coupling of multiple stand-alone EaSMs to generate usable information for resource decision-making. Direct engagement between model developers and non-academic stakeholders involved in resource and environmental management decisions throughout the model development process is a critical component of this effort. BioEarth utilizes a bottom-up approach for its land surface model that preserves fine spatial-scale sensitivities and lateral hydrologic connectivity, which makes it unique among many regional EaSMs. Here, we describe the BioEarth initiative and highlights opportunities and challenges associated with coupling multiple stand-alone models to generate usable information for agricultural and natural resource decision-making.« less

Involvement in the Juvenile Justice System for African American Adolescents: Examining Associations with Behavioral Health Problems

PubMed Central

Voisin, Dexter R.; Kim, Dongha; Takahashi, Lois; Morotta, Phillip; Bocanegra, Kathryn

2017-01-01

While researchers have found that African American youth experience higher levels of juvenile justice involvement at every system level (arrest, sentencing, and incarceration) relative to their other ethnic counterparts, few studies have explored how juvenile justice involvement and number of contacts might be correlated with this broad range of problems. A convenience sample of 638 African American adolescents living in predominantly low-income, urban communities participated in a survey related to juvenile justice involvement. Major findings using logistic regression models indicated that adolescents who reported juvenile justice system involvement versus no involvement were 2.3 times as likely to report mental health problems, substance abuse, and delinquent or youth offending behaviors. Additional findings documented that the higher the number of juvenile justice system contacts, the higher the rates of delinquent behaviors, alcohol and marijuana use, sex while high on drugs, and commercial sex. These findings suggest that identifying and targeting youth who have multiple juvenile justice system contacts, especially those in low-resourced communities for early intervention services, may be beneficial. Future research should examine whether peer network norms might mediate the relationships between juvenile justice involvement and youth problem behaviors. PMID:28966415

Involvement in the Juvenile Justice System for African American Adolescents: Examining Associations with Behavioral Health Problems.

PubMed

Voisin, Dexter R; Kim, Dongha; Takahashi, Lois; Morotta, Phillip; Bocanegra, Kathryn

2017-01-01

While researchers have found that African American youth experience higher levels of juvenile justice involvement at every system level (arrest, sentencing, and incarceration) relative to their other ethnic counterparts, few studies have explored how juvenile justice involvement and number of contacts might be correlated with this broad range of problems. A convenience sample of 638 African American adolescents living in predominantly low-income, urban communities participated in a survey related to juvenile justice involvement. Major findings using logistic regression models indicated that adolescents who reported juvenile justice system involvement versus no involvement were 2.3 times as likely to report mental health problems, substance abuse, and delinquent or youth offending behaviors. Additional findings documented that the higher the number of juvenile justice system contacts, the higher the rates of delinquent behaviors, alcohol and marijuana use, sex while high on drugs, and commercial sex. These findings suggest that identifying and targeting youth who have multiple juvenile justice system contacts, especially those in low-resourced communities for early intervention services, may be beneficial. Future research should examine whether peer network norms might mediate the relationships between juvenile justice involvement and youth problem behaviors.

Working Memory Load and Automaticity in Relation to Mental Multiplication

ERIC Educational Resources Information Center

Ding, Yi; Liu, Ru-De; Xu, Le; Wang, Jia; Zhang, Dake

2017-01-01

The authors' aim was to examine the relations among mental multiplication, working memory load (WML), and automaticity by alternating the difficulty level of task characteristics. In Experiment 1, involving 30 fifth-grade students with mixed abilities, a 2 (WML) × 2 (automaticity) design was utilized. In Experiment 2, involving 21 high-achieving…

Religious Involvement and the Social Competence and Adjustment of Indonesian Muslim Adolescents

ERIC Educational Resources Information Center

French, Doran C.; Eisenberg, Nancy; Vaughan, Julie; Purwono, Urip; Suryanti, Telie A.

2008-01-01

This study assessed the relation between religious involvement and multiple indices of competence in 183 eighth- and ninth-grade Indonesian Muslim adolescents (M = 13.3 years). The authors assessed spirituality and religiosity using both parent and adolescent reports, and social competence and adjustment using multiple measures and data sources.…

Colors Of Liquid Crystals Used To Measure Surface Shear Stresses

NASA Technical Reports Server (NTRS)

Reda, D. C.; Muratore, J. J., Jr.

1996-01-01

Developmental method of mapping shear stresses on aerodynamic surfaces involves observation, at multiple viewing angles, of colors of liquid-crystal surface coats illuminated by white light. Report describing method referenced in "Liquid Crystals Indicate Directions Of Surface Shear Stresses" (ARC-13379). Resulting maps of surface shear stresses contain valuable data on magnitudes and directions of skin friction forces associated with surface flows; data used to refine mathematical models of aerodynamics for research and design purposes.

Inference of vessel intent and behaviour for maritime security operations

NASA Astrophysics Data System (ADS)

van den Broek, Bert; Smith, Arthur; den Breejen, Eric; van de Voorde, Imelda

2014-10-01

Coastguard and Navy assets are increasingly involved in Maritime Security Operations (MSO) for countering piracy, weapons and drugs smuggling, terrorism and illegal trafficking. Persistent tracking of vessels in interrupted time series over long distances and the modelling of intent and behaviour from multiple data sources are key enablers for Situation Assessment in MSO. Results of situation assessment are presented for AIS/VTS observations in the Dutch North Sea and for simulated scenarios in the Gulf of Oman.

Developmental dissociation in the neural responses to simple multiplication and subtraction problems

PubMed Central

Prado, Jérôme; Mutreja, Rachna; Booth, James R.

2014-01-01

Mastering single-digit arithmetic during school years is commonly thought to depend upon an increasing reliance on verbally memorized facts. An alternative model, however, posits that fluency in single-digit arithmetic might also be achieved via the increasing use of efficient calculation procedures. To test between these hypotheses, we used a cross-sectional design to measure the neural activity associated with single-digit subtraction and multiplication in 34 children from 2nd to 7th grade. The neural correlates of language and numerical processing were also identified in each child via localizer scans. Although multiplication and subtraction were undistinguishable in terms of behavior, we found a striking developmental dissociation in their neural correlates. First, we observed grade-related increases of activity for multiplication, but not for subtraction, in a language-related region of the left temporal cortex. Second, we found grade-related increases of activity for subtraction, but not for multiplication, in a region of the right parietal cortex involved in the procedural manipulation of numerical quantities. The present results suggest that fluency in simple arithmetic in children may be achieved by both increasing reliance on verbal retrieval and by greater use of efficient quantity-based procedures, depending on the operation. PMID:25089323

Application of optimization technique for flood damage modeling in river system

NASA Astrophysics Data System (ADS)

Barman, Sangita Deb; Choudhury, Parthasarathi

2018-04-01

A river system is defined as a network of channels that drains different parts of a basin uniting downstream to form a common outflow. An application of various models found in literatures, to a river system having multiple upstream flows is not always straight forward, involves a lengthy procedure; and with non-availability of data sets model calibration and applications may become difficult. In the case of a river system the flow modeling can be simplified to a large extent if the channel network is replaced by an equivalent single channel. In the present work optimization model formulations based on equivalent flow and applications of the mixed integer programming based pre-emptive goal programming model in evaluating flood control alternatives for a real life river system in India are proposed to be covered in the study.

Measuring and partitioning the high-order linkage disequilibrium by multiple order Markov chains.

PubMed

Kim, Yunjung; Feng, Sheng; Zeng, Zhao-Bang

2008-05-01

A map of the background levels of disequilibrium between nearby markers can be useful for association mapping studies. In order to assess the background levels of linkage disequilibrium (LD), multilocus LD measures are more advantageous than pairwise LD measures because the combined analysis of pairwise LD measures is not adequate to detect simultaneous allele associations among multiple markers. Various multilocus LD measures based on haplotypes have been proposed. However, most of these measures provide a single index of association among multiple markers and does not reveal the complex patterns and different levels of LD structure. In this paper, we employ non-homogeneous, multiple order Markov Chain models as a statistical framework to measure and partition the LD among multiple markers into components due to different orders of marker associations. Using a sliding window of multiple markers on phased haplotype data, we compute corresponding likelihoods for different Markov Chain (MC) orders in each window. The log-likelihood difference between the lowest MC order model (MC0) and the highest MC order model in each window is used as a measure of the total LD or the overall deviation from the gametic equilibrium for the window. Then, we partition the total LD into lower order disequilibria and estimate the effects from two-, three-, and higher order disequilibria. The relationship between different orders of LD and the log-likelihood difference involving two different orders of MC models are explored. By applying our method to the phased haplotype data in the ENCODE regions of the HapMap project, we are able to identify high/low multilocus LD regions. Our results reveal that the most LD in the HapMap data is attributed to the LD between adjacent pairs of markers across the whole region. LD between adjacent pairs of markers appears to be more significant in high multilocus LD regions than in low multilocus LD regions. We also find that as the multilocus total LD increases, the effects of high-order LD tends to get weaker due to the lack of observed multilocus haplotypes. The overall estimates of first, second, third, and fourth order LD across the ENCODE regions are 64, 23, 9, and 3%.

Usability and potential of geostatistics for spatial discrimination of multiple sclerosis lesion patterns.

PubMed

Marschallinger, Robert; Golaszewski, Stefan M; Kunz, Alexander B; Kronbichler, Martin; Ladurner, Gunther; Hofmann, Peter; Trinka, Eugen; McCoy, Mark; Kraus, Jörg

2014-01-01

In multiple sclerosis (MS) the individual disease courses are very heterogeneous among patients and biomarkers for setting the diagnosis and the estimation of the prognosis for individual patients would be very helpful. For this purpose, we are developing a multidisciplinary method and workflow for the quantitative, spatial, and spatiotemporal analysis and characterization of MS lesion patterns from MRI with geostatistics. We worked on a small data set involving three synthetic and three real-world MS lesion patterns, covering a wide range of possible MS lesion configurations. After brain normalization, MS lesions were extracted and the resulting binary 3-dimensional models of MS lesion patterns were subject to geostatistical indicator variography in three orthogonal directions. By applying geostatistical indicator variography, we were able to describe the 3-dimensional spatial structure of MS lesion patterns in a standardized manner. Fitting a model function to the empirical variograms, spatial characteristics of the MS lesion patterns could be expressed and quantified by two parameters. An orthogonal plot of these parameters enabled a well-arranged comparison of the involved MS lesion patterns. This method in development is a promising candidate to complement standard image-based statistics by incorporating spatial quantification. The work flow is generic and not limited to analyzing MS lesion patterns. It can be completely automated for the screening of radiological archives. Copyright © 2013 by the American Society of Neuroimaging.

G protein-coupled receptor 30 contributes to improved remyelination after cuprizone-induced demyelination.

PubMed

Hirahara, Yukie; Matsuda, Ken Ichi; Yamada, Hisao; Saitou, Akira; Morisaki, Shinsuke; Takanami, Keiko; Boggs, Joan M; Kawata, Mitsuhiro

2013-03-01

Estrogen exerts neuroprotective and promyelinating actions. The therapeutic effect has been shown in animal models of multiple sclerosis, in which the myelin sheath is specifically destroyed in the central nervous system. However, it remains unproven whether estrogen is directly involved in remyelination via the myelin producing cells, oligodendrocytes, or which estrogen receptors are involved. In this study, we found that the membrane-associated estrogen receptor, the G protein-coupled receptor 30 (GPR30), also known as GPER, was expressed in oligodendrocytes in rat spinal cord and corpus callosum. Moreover, GPR30 was expressed throughout oligodendrocyte differentiation and promyelinating stages in primary oligodendrocyte cultures derived from rat spinal cords and brains. To evaluate the role of signaling via GPR30 in promyelination, a specific agonist for GPR30, G1, was administered to a rat model of demyelination induced by cuprizone treatment. Histological examination of the corpus callosum with oligodendrocyte differentiation stage-specific markers showed that G1 enhanced oligodendrocyte maturation in corpus callosum of cuprizone-treated animals. It also enhanced oligodendrocyte ensheathment of dorsal root ganglion (DRG) neurons in co-culture and myelination in cuprizone-treated animals. This study is the first evidence that GPR30 signaling promotes remyelination by oligodendrocytes after demyelination. GPR30 ligands may provide a novel therapy for the treatment of multiple sclerosis. Copyright © 2012 Wiley Periodicals, Inc.

Using stereophotogrammetric technology for obtaining intraoral digital impressions of implants.

PubMed

Pradíes, Guillermo; Ferreiroa, Alberto; Özcan, Mutlu; Giménez, Beatriz; Martínez-Rus, Francisco

2014-04-01

The procedure for making impressions of multiple implants continues to be a challenge, despite the various techniques proposed to date. The authors' objective in this case report is to describe a novel digital impression method for multiple implants involving the use of stereophotogrammetric technology. The authors present three cases of patients who had multiple implants in which the impressions were obtained with this technology. Initially, a stereo camera with an infrared flash detects the position of special flag abutments screwed into the implants. This process is based on registering the x, y and z coordinates of each implant and the distances between them. This information is converted into a stereolithographic (STL) file. To add the soft-tissue information, the user must obtain another STL file by using an intraoral or extraoral scanner. In the first case presented, this information was acquired from the plaster model with an extraoral scanner; in the second case, from a Digital Imaging and Communication in Medicine (DICOM) file of the plaster model obtained with cone-beam computed tomography; and in the third case, through an intraoral digital impression with a confocal scanner. In the three cases, the frameworks manufactured from this technique showed a correct clinical passive fit. At follow-up appointments held six, 12 and 24 months after insertion of the prosthesis, no complications were reported. Stereophotogrammetric technology is a viable, accurate and easy technique for making multiple implant impressions. Clinicians can use stereophotogrammetric technology to acquire reliable digital master models as a first step in producing frameworks with a correct passive fit.

Multimodal, high-dimensional, model-based, Bayesian inverse problems with applications in biomechanics

NASA Astrophysics Data System (ADS)

Franck, I. M.; Koutsourelakis, P. S.

2017-01-01

This paper is concerned with the numerical solution of model-based, Bayesian inverse problems. We are particularly interested in cases where the cost of each likelihood evaluation (forward-model call) is expensive and the number of unknown (latent) variables is high. This is the setting in many problems in computational physics where forward models with nonlinear PDEs are used and the parameters to be calibrated involve spatio-temporarily varying coefficients, which upon discretization give rise to a high-dimensional vector of unknowns. One of the consequences of the well-documented ill-posedness of inverse problems is the possibility of multiple solutions. While such information is contained in the posterior density in Bayesian formulations, the discovery of a single mode, let alone multiple, poses a formidable computational task. The goal of the present paper is two-fold. On one hand, we propose approximate, adaptive inference strategies using mixture densities to capture multi-modal posteriors. On the other, we extend our work in [1] with regard to effective dimensionality reduction techniques that reveal low-dimensional subspaces where the posterior variance is mostly concentrated. We validate the proposed model by employing Importance Sampling which confirms that the bias introduced is small and can be efficiently corrected if the analyst wishes to do so. We demonstrate the performance of the proposed strategy in nonlinear elastography where the identification of the mechanical properties of biological materials can inform non-invasive, medical diagnosis. The discovery of multiple modes (solutions) in such problems is critical in achieving the diagnostic objectives.

Long-term impact on alcohol-involved crashes of lowering the minimum purchase age in New Zealand.

PubMed

Huckle, Taisia; Parker, Karl

2014-06-01

We assessed the long-term effect of lowering the minimum purchase age for alcohol from age 20 to age 18 years on alcohol-involved crashes in New Zealand. We modeled ratios of drivers in alcohol-involved crashes to drivers in non-alcohol-involved crashes by age group in 3 time periods using logistic regression, controlling for gender and adjusting for multiple comparisons. Before the law change, drivers aged 18 to 19 and 20 to 24 years had similar odds of an alcohol-involved crash (P = .1). Directly following the law change, drivers aged 18 to 19 years had a 15% higher odds of being in an alcohol-involved crash than did drivers aged 20 to 24 years (P = .038). In the long term, drivers aged 18 to 19 years had 21% higher odds of an alcohol-involved crash than did the age control group (P ≤ .001). We found no effects for fatal alcohol-involved crashes alone and no trickle-down effects for the youngest group. Lowering the purchase age for alcohol was associated with a long-term impact on alcohol-involved crashes among drivers aged 18 to 19 years. Raising the minimum purchase age for alcohol would be appropriate.

Long-Term Impact on Alcohol-Involved Crashes of Lowering the Minimum Purchase Age in New Zealand

PubMed Central

Parker, Karl

2014-01-01

Objectives. We assessed the long-term effect of lowering the minimum purchase age for alcohol from age 20 to age 18 years on alcohol-involved crashes in New Zealand. Methods. We modeled ratios of drivers in alcohol-involved crashes to drivers in non–alcohol-involved crashes by age group in 3 time periods using logistic regression, controlling for gender and adjusting for multiple comparisons. Results. Before the law change, drivers aged 18 to 19 and 20 to 24 years had similar odds of an alcohol-involved crash (P = .1). Directly following the law change, drivers aged 18 to 19 years had a 15% higher odds of being in an alcohol-involved crash than did drivers aged 20 to 24 years (P = .038). In the long term, drivers aged 18 to 19 years had 21% higher odds of an alcohol-involved crash than did the age control group (P ≤ .001). We found no effects for fatal alcohol-involved crashes alone and no trickle-down effects for the youngest group. Conclusions. Lowering the purchase age for alcohol was associated with a long-term impact on alcohol-involved crashes among drivers aged 18 to 19 years. Raising the minimum purchase age for alcohol would be appropriate. PMID:24825211

Space Shuttle Propulsion Systems Plume Modeling and Simulation for the Lift-Off Computational Fluid Dynamics Model

NASA Technical Reports Server (NTRS)

Strutzenberg, L. L.; Dougherty, N. S.; Liever, P. A.; West, J. S.; Smith, S. D.

2007-01-01

This paper details advances being made in the development of Reynolds-Averaged Navier-Stokes numerical simulation tools, models, and methods for the integrated Space Shuttle Vehicle at launch. The conceptual model and modeling approach described includes the development of multiple computational models to appropriately analyze the potential debris transport for critical debris sources at Lift-Off. The conceptual model described herein involves the integration of propulsion analysis for the nozzle/plume flow with the overall 3D vehicle flowfield at Lift-Off. Debris Transport Analyses are being performed using the Shuttle Lift-Off models to assess the risk to the vehicle from Lift-Off debris and appropriately prioritized mitigation of potential debris sources to continue to reduce vehicle risk. These integrated simulations are being used to evaluate plume-induced debris environments where the multi-plume interactions with the launch facility can potentially accelerate debris particles toward the vehicle.

A structured analysis of uncertainty surrounding modeled impacts of groundwater-extraction rules

NASA Astrophysics Data System (ADS)

Guillaume, Joseph H. A.; Qureshi, M. Ejaz; Jakeman, Anthony J.

2012-08-01

Integrating economic and groundwater models for groundwater-management can help improve understanding of trade-offs involved between conflicting socioeconomic and biophysical objectives. However, there is significant uncertainty in most strategic decision-making situations, including in the models constructed to represent them. If not addressed, this uncertainty may be used to challenge the legitimacy of the models and decisions made using them. In this context, a preliminary uncertainty analysis was conducted of a dynamic coupled economic-groundwater model aimed at assessing groundwater extraction rules. The analysis demonstrates how a variety of uncertainties in such a model can be addressed. A number of methods are used including propagation of scenarios and bounds on parameters, multiple models, block bootstrap time-series sampling and robust linear regression for model calibration. These methods are described within the context of a theoretical uncertainty management framework, using a set of fundamental uncertainty management tasks and an uncertainty typology.

Accounting for measurement error in log regression models with applications to accelerated testing.

PubMed

Richardson, Robert; Tolley, H Dennis; Evenson, William E; Lunt, Barry M

2018-01-01

In regression settings, parameter estimates will be biased when the explanatory variables are measured with error. This bias can significantly affect modeling goals. In particular, accelerated lifetime testing involves an extrapolation of the fitted model, and a small amount of bias in parameter estimates may result in a significant increase in the bias of the extrapolated predictions. Additionally, bias may arise when the stochastic component of a log regression model is assumed to be multiplicative when the actual underlying stochastic component is additive. To account for these possible sources of bias, a log regression model with measurement error and additive error is approximated by a weighted regression model which can be estimated using Iteratively Re-weighted Least Squares. Using the reduced Eyring equation in an accelerated testing setting, the model is compared to previously accepted approaches to modeling accelerated testing data with both simulations and real data.

Statistical methods and neural network approaches for classification of data from multiple sources

NASA Technical Reports Server (NTRS)

Benediktsson, Jon Atli; Swain, Philip H.

1990-01-01

Statistical methods for classification of data from multiple data sources are investigated and compared to neural network models. A problem with using conventional multivariate statistical approaches for classification of data of multiple types is in general that a multivariate distribution cannot be assumed for the classes in the data sources. Another common problem with statistical classification methods is that the data sources are not equally reliable. This means that the data sources need to be weighted according to their reliability but most statistical classification methods do not have a mechanism for this. This research focuses on statistical methods which can overcome these problems: a method of statistical multisource analysis and consensus theory. Reliability measures for weighting the data sources in these methods are suggested and investigated. Secondly, this research focuses on neural network models. The neural networks are distribution free since no prior knowledge of the statistical distribution of the data is needed. This is an obvious advantage over most statistical classification methods. The neural networks also automatically take care of the problem involving how much weight each data source should have. On the other hand, their training process is iterative and can take a very long time. Methods to speed up the training procedure are introduced and investigated. Experimental results of classification using both neural network models and statistical methods are given, and the approaches are compared based on these results.