Joint modelling of potentially avoidable hospitalisation for five diseases accounting for spatiotemporal effects: A case study in New South Wales, Australia.

PubMed

Baker, Jannah; White, Nicole; Mengersen, Kerrie; Rolfe, Margaret; Morgan, Geoffrey G

2017-01-01

Three variant formulations of a spatiotemporal shared component model are proposed that allow examination of changes in shared underlying factors over time. Models are evaluated within the context of a case study examining hospitalisation rates for five chronic diseases for residents of a regional area in New South Wales: type II diabetes mellitus (DMII), chronic obstructive pulmonary disease (COPD), coronary arterial disease (CAD), hypertension (HT) and congestive heart failure (CHF) between 2001-2006. These represent ambulatory care sensitive (ACS) conditions, often used as a proxy for avoidable hospitalisations. Using a selected model, the effects of socio-economic status (SES) as a shared component are estimated and temporal patterns in the influence of the residual shared spatial component are examined. Choice of model depends upon the application. In the featured application, a model allowing for changing influence of the shared spatial component over time was found to have the best fit and was selected for further analyses. Hospitalisation rates were found to be increasing for COPD and DMII, decreasing for CHF and stable for CAD and HT. SES was substantively associated with hospitalisation rates, with differing degrees of influence for each disease. In general, most of the spatial variation in hospitalisation rates was explained by disease-specific spatial components, followed by the residual shared spatial component. Appropriate selection of a joint disease model allows for the examination of temporal patterns of disease outcomes and shared underlying spatial factors, and distinction between different shared spatial factors.

Studying the Warm Layer and the Hardening Factor in Cygnus X-1

NASA Technical Reports Server (NTRS)

Yao, Yangsen; Zhang, Shuangnan; Zhang, Xiaoling; Feng, Yuxin

2002-01-01

As the first dynamically determined black hole X-ray binary system, Cygnus X-1 has been studied extensively. However, its broadband spectrum observed with BeppoSax is still not well understood. Besides the soft excess described by the multi-color disk model (MCD), the power-law hard component and a broad excess feature above 10 keV (a disk reflection component), there is also an additional soft component around 1 keV, whose origin is not known currently. Here we propose that the additional soft component is due to the thermal Comptonization between the soft disk photons and a warm plasma cloud just above the disk, i.e., a warm layer. We use the Monte-Carlo technique to simulate this Compton scattering process and build a table model based on our simulation results. With this table model, we study the disk structure and estimate the hardening factor to the MCD component in Cygnus X-1.

Adolescent emotionality and effortful control: Core latent constructs and links to psychopathology and functioning

PubMed Central

Snyder, Hannah R.; Gulley, Lauren D.; Bijttebier, Patricia; Hartman, Catharina A.; Oldehinkel, Albertine J.; Mezulis, Amy; Young, Jami F.; Hankin, Benjamin L.

2015-01-01

Temperament is associated with important outcomes in adolescence, including academic and interpersonal functioning and psychopathology. Rothbart’s temperament model is among the most well-studied and supported approaches to adolescent temperament, and contains three main components: positive emotionality (PE), negative emotionality (NE), and effortful control (EC). However, the latent factor structure of Rothbart’s temperament measure for adolescents, the Early Adolescent Temperament Questionnaire Revised (EATQ-R, Ellis & Rothbart, 2001) has not been definitively established. To address this problem and investigate links between adolescent temperament and functioning, we used confirmatory factor analysis to examine the latent constructs of the EATQ-R in a large combined sample. For EC and NE, bifactor models consisting of a common factor plus specific factors for some sub-facets of each component fit best, providing a more nuanced understanding of these temperament dimensions. The nature of the PE construct in the EATQ-R is less clear. Models replicated in a hold-out dataset. The common components of high NE and low EC where broadly associated with increased psychopathology symptoms, and poor interpersonal and school functioning, while specific components of NE were further associated with corresponding specific components of psychopathology. Further questioning the construct validity of PE as measured by the EATQ-R, PE factors did not correlate with construct validity measures in a way consistent with theories of PE. Bringing consistency to the way the EATQ-R is modeled and using purer latent variables has the potential to advance the field in understanding links between dimensions of temperament and important outcomes of adolescent development. PMID:26011660

Adolescent emotionality and effortful control: Core latent constructs and links to psychopathology and functioning.

PubMed

Snyder, Hannah R; Gulley, Lauren D; Bijttebier, Patricia; Hartman, Catharina A; Oldehinkel, Albertine J; Mezulis, Amy; Young, Jami F; Hankin, Benjamin L

2015-12-01

Temperament is associated with important outcomes in adolescence, including academic and interpersonal functioning and psychopathology. Rothbart's temperament model is among the most well-studied and supported approaches to adolescent temperament, and contains 3 main components: positive emotionality (PE), negative emotionality (NE), and effortful control (EC). However, the latent factor structure of Rothbart's temperament measure for adolescents, the Early Adolescent Temperament Questionnaire Revised (EATQ-R; Ellis & Rothbart, 2001) has not been definitively established. To address this problem and investigate links between adolescent temperament and functioning, we used confirmatory factor analysis to examine the latent constructs of the EATQ-R in a large combined sample. For EC and NE, bifactor models consisting of a common factor plus specific factors for some subfacets of each component fit best, providing a more nuanced understanding of these temperament dimensions. The nature of the PE construct in the EATQ-R is less clear. Models replicated in a hold-out dataset. The common components of high NE and low EC where broadly associated with increased psychopathology symptoms, and poor interpersonal and school functioning, while specific components of NE were further associated with corresponding specific components of psychopathology. Further questioning the construct validity of PE as measured by the EATQ-R, PE factors did not correlate with construct validity measures in a way consistent with theories of PE. Bringing consistency to the way the EATQ-R is modeled and using purer latent variables has the potential to advance the field in understanding links between dimensions of temperament and important outcomes of adolescent development. (c) 2015 APA, all rights reserved).

What distinguishes individual stocks from the index?

NASA Astrophysics Data System (ADS)

Wagner, F.; Milaković, M.; Alfarano, S.

2010-01-01

Stochastic volatility models decompose the time series of financial returns into the product of a volatility factor and an iid noise factor. Assuming a slow dynamic for the volatility factor, we show via nonparametric tests that both the index as well as its individual stocks share a common volatility factor. While the noise component is Gaussian for the index, individual stock returns turn out to require a leptokurtic noise. Thus we propose a two-component model for stocks, given by the sum of Gaussian noise, which reflects market-wide fluctuations, and Laplacian noise, which incorporates firm-specific factors such as firm profitability or growth performance, both of which are known to be Laplacian distributed. In the case of purely Gaussian noise, the chi-squared probability for the density of individual stock returns is typically on the order of 10-20, while it increases to values of O(1) by adding the Laplace component.

78 FR 12127 - Self-Regulatory Organizations; Chicago Mercantile Exchange Inc.; Notice of Designation of a...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-21

... risk factor component of its credit default swap (``CDS'') margin model. CME proposes to use an index... with the liquidity risk factor component. The proposed rule change was published for comment in the... on Proposed Rule Change Related to the Liquidity Factor of CME's CDS Margin Methodology February 14...

On the Extraction of Components and the Applicability of the Factor Model.

ERIC Educational Resources Information Center

Dziuban, Charles D.; Harris, Chester W.

A reanalysis of Shaycroft's matrix of intercorrelations of 10 test variables plus 4 random variables is discussed. Three different procedures were used in the reanalysis: (1) Image Component Analysis, (2) Uniqueness Rescaling Factor Analysis, and (3) Alpha Factor Analysis. The results of these analyses are presented in tables. It is concluded from…

A GRAPHICAL DIAGNOSTIC METHOD FOR ASSESSING THE ROTATION IN FACTOR ANALYTICAL MODELS OF ATMOSPHERIC POLLUTION. (R831078)

EPA Science Inventory

Factor analytic tools such as principal component analysis (PCA) and positive matrix factorization (PMF), suffer from rotational ambiguity in the results: different solutions (factors) provide equally good fits to the measured data. The PMF model imposes non-negativity of both...

Assessing Cognitive and Affective Empathy Through the Interpersonal Reactivity Index: An Argument Against a Two-Factor Model.

PubMed

Chrysikou, Evangelia G; Thompson, W Jake

2016-12-01

One aspect of higher order social cognition is empathy, a psychological construct comprising a cognitive (recognizing emotions) and an affective (responding to emotions) component. The complex nature of empathy complicates the accurate measurement of these components. The most widely used measure of empathy is the Interpersonal Reactivity Index (IRI). However, the factor structure of the IRI as it is predominantly used in the psychological literature differs from Davis's original four-factor model in that it arbitrarily combines the subscales to form two factors: cognitive and affective empathy. This two-factor model of the IRI, although popular, has yet to be examined for psychometric support. In the current study, we examine, for the first time, the validity of this alternative model. A confirmatory factor analysis showed poor model fit for this two-factor structure. Additional analyses offered support for the original four-factor model, as well as a hierarchical model for the scale. In line with previous findings, females scored higher on the IRI than males. Our findings indicate that the IRI, as it is currently used in the literature, does not accurately measure cognitive and affective empathy and highlight the advantages of using the original four-factor structure of the scale for empathy assessments. © The Author(s) 2015.

Impact of covariate models on the assessment of the air pollution-mortality association in a single- and multipollutant context.

PubMed

Sacks, Jason D; Ito, Kazuhiko; Wilson, William E; Neas, Lucas M

2012-10-01

With the advent of multicity studies, uniform statistical approaches have been developed to examine air pollution-mortality associations across cities. To assess the sensitivity of the air pollution-mortality association to different model specifications in a single and multipollutant context, the authors applied various regression models developed in previous multicity time-series studies of air pollution and mortality to data from Philadelphia, Pennsylvania (May 1992-September 1995). Single-pollutant analyses used daily cardiovascular mortality, fine particulate matter (particles with an aerodynamic diameter ≤2.5 µm; PM(2.5)), speciated PM(2.5), and gaseous pollutant data, while multipollutant analyses used source factors identified through principal component analysis. In single-pollutant analyses, risk estimates were relatively consistent across models for most PM(2.5) components and gaseous pollutants. However, risk estimates were inconsistent for ozone in all-year and warm-season analyses. Principal component analysis yielded factors with species associated with traffic, crustal material, residual oil, and coal. Risk estimates for these factors exhibited less sensitivity to alternative regression models compared with single-pollutant models. Factors associated with traffic and crustal material showed consistently positive associations in the warm season, while the coal combustion factor showed consistently positive associations in the cold season. Overall, mortality risk estimates examined using a source-oriented approach yielded more stable and precise risk estimates, compared with single-pollutant analyses.

Bayes Factor Covariance Testing in Item Response Models.

PubMed

Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

2017-12-01

Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.

Factor analysis of the Foreign Language Classroom Anxiety Scale in Korean learners of English as a foreign language.

PubMed

Park, Gi-Pyo

2014-08-01

This study examined the latent constructs of the Foreign Language Classroom Anxiety Scale (FLCAS) using two different groups of Korean English as a foreign language (EFL) university students. Maximum likelihood exploratory factor analysis with direct oblimin rotation was performed among the first group of 217 participants and produced two meaningful latent components in the FLCAS. The two components of the FLCAS were closely examined among the second group of 244 participants to find the extent to which the two components of the FLCAS fit the data. The model fit indexes showed that the two-factor model in general adequately fit the data. Findings of this study were discussed with the focus on the two components of the FLCAS, followed by future study areas to be undertaken to shed further light on the role of foreign language anxiety in L2 acquisition.

Thermal cut-off response modelling of universal motors

NASA Astrophysics Data System (ADS)

Thangaveloo, Kashveen; Chin, Yung Shin

2017-04-01

This paper presents a model to predict the thermal cut-off (TCO) response behaviour in universal motors. The mathematical model includes the calculations of heat loss in the universal motor and the flow characteristics around the TCO component which together are the main parameters for TCO response prediction. In order to accurately predict the TCO component temperature, factors like the TCO component resistance, the effect of ambient, and the flow conditions through the motor are taken into account to improve the prediction accuracy of the model.

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.

PubMed

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2011-01-01

The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.

Development of a scale to measure adherence to self-monitoring of blood glucose with latent variable measurement.

PubMed

Wagner, J A; Schnoll, R A; Gipson, M T

1998-07-01

Adherence to self-monitoring of blood glucose (SMBG) is problematic for many people with diabetes. Self-reports of adherence have been found to be unreliable, and existing paper-and-pencil measures have limitations. This study developed a brief measure of SMBG adherence with good psychometric properties and a useful factor structure that can be used in research and in practice. A total of 216 adults with diabetes responded to 30 items rated on a 9-point Likert scale that asked about blood monitoring habits. In part I of the study, items were evaluated and retained based on their psychometric properties. The sample was divided into exploratory and confirmatory halves. Using the exploratory half, items with acceptable psychometric properties were subjected to a principal components analysis. In part II of the study, structural equation modeling was used to confirm the component solution with the entire sample. Structural modeling was also used to test the relationship between these components. It was hypothesized that the scale would produce four correlated factors. Principal components analysis suggested a two-component solution, and confirmatory factor analysis confirmed this solution. The first factor measures the degree to which patients rely on others to help them test and thus was named "social influence." The second component measures the degree to which patients use physical symptoms of blood glucose levels to help them test and thus was named "physical influence." Results of the structural model show that the components are correlated and make up the higher-order latent variable adherence. The resulting 15-item scale provides a short, reliable way to assess patient adherence to SMBG. Despite the existence of several aspects of adherence, this study indicates that the construct consists of only two components. This scale is an improvement on previous measures of adherence because of its good psychometric properties, its interpretable factor structure, and its rigorous empirical development.

The Common Factors Discrimination Model: An Integrated Approach to Counselor Supervision

ERIC Educational Resources Information Center

Crunk, A. Elizabeth; Barden, Sejal M.

2017-01-01

Numerous models of clinical supervision have been developed; however, there is little empirical support indicating that any one model is superior. Therefore, common factors approaches to supervision integrate essential components that are shared among counseling and supervision models. The purpose of this paper is to present an innovative model of…

Multicollinearity in prognostic factor analyses using the EORTC QLQ-C30: identification and impact on model selection.

PubMed

Van Steen, Kristel; Curran, Desmond; Kramer, Jocelyn; Molenberghs, Geert; Van Vreckem, Ann; Bottomley, Andrew; Sylvester, Richard

2002-12-30

Clinical and quality of life (QL) variables from an EORTC clinical trial of first line chemotherapy in advanced breast cancer were used in a prognostic factor analysis of survival and response to chemotherapy. For response, different final multivariate models were obtained from forward and backward selection methods, suggesting a disconcerting instability. Quality of life was measured using the EORTC QLQ-C30 questionnaire completed by patients. Subscales on the questionnaire are known to be highly correlated, and therefore it was hypothesized that multicollinearity contributed to model instability. A correlation matrix indicated that global QL was highly correlated with 7 out of 11 variables. In a first attempt to explore multicollinearity, we used global QL as dependent variable in a regression model with other QL subscales as predictors. Afterwards, standard diagnostic tests for multicollinearity were performed. An exploratory principal components analysis and factor analysis of the QL subscales identified at most three important components and indicated that inclusion of global QL made minimal difference to the loadings on each component, suggesting that it is redundant in the model. In a second approach, we advocate a bootstrap technique to assess the stability of the models. Based on these analyses and since global QL exacerbates problems of multicollinearity, we therefore recommend that global QL be excluded from prognostic factor analyses using the QLQ-C30. The prognostic factor analysis was rerun without global QL in the model, and selected the same significant prognostic factors as before. Copyright 2002 John Wiley & Sons, Ltd.

Computational model for fuel component supply into a combustion chamber of LRE

NASA Astrophysics Data System (ADS)

Teterev, A. V.; Mandrik, P. A.; Rudak, L. V.; Misyuchenko, N. I.

2017-12-01

A 2D-3D computational model for calculating a flow inside jet injectors that feed fuel components to a combustion chamber of a liquid rocket engine is described. The model is based on the gasdynamic calculation of compressible medium. Model software provides calculation of both one- and two-component injectors. Flow simulation in two-component injectors is realized using the scheme of separate supply of “gas-gas” or “gas-liquid” fuel components. An algorithm for converting a continuous liquid medium into a “cloud” of drops is described. Application areas of the developed model and the results of 2D simulation of injectors to obtain correction factors in the calculation formulas for fuel supply are discussed.

Removing an intersubject variance component in a general linear model improves multiway factoring of event-related spectral perturbations in group EEG studies.

PubMed

Spence, Jeffrey S; Brier, Matthew R; Hart, John; Ferree, Thomas C

2013-03-01

Linear statistical models are used very effectively to assess task-related differences in EEG power spectral analyses. Mixed models, in particular, accommodate more than one variance component in a multisubject study, where many trials of each condition of interest are measured on each subject. Generally, intra- and intersubject variances are both important to determine correct standard errors for inference on functions of model parameters, but it is often assumed that intersubject variance is the most important consideration in a group study. In this article, we show that, under common assumptions, estimates of some functions of model parameters, including estimates of task-related differences, are properly tested relative to the intrasubject variance component only. A substantial gain in statistical power can arise from the proper separation of variance components when there is more than one source of variability. We first develop this result analytically, then show how it benefits a multiway factoring of spectral, spatial, and temporal components from EEG data acquired in a group of healthy subjects performing a well-studied response inhibition task. Copyright © 2011 Wiley Periodicals, Inc.

Coupling of snow and permafrost processes using the Basic Modeling Interface (BMI)

NASA Astrophysics Data System (ADS)

Wang, K.; Overeem, I.; Jafarov, E. E.; Piper, M.; Stewart, S.; Clow, G. D.; Schaefer, K. M.

2017-12-01

We developed a permafrost modeling tool based by implementing the Kudryavtsev empirical permafrost active layer depth model (the so-called "Ku" component). The model is specifically set up to have a basic model interface (BMI), which enhances the potential coupling to other earth surface processes model components. This model is accessible through the Web Modeling Tool in Community Surface Dynamics Modeling System (CSDMS). The Kudryavtsev model has been applied for entire Alaska to model permafrost distribution at high spatial resolution and model predictions have been verified by Circumpolar Active Layer Monitoring (CALM) in-situ observations. The Ku component uses monthly meteorological forcing, including air temperature, snow depth, and snow density, and predicts active layer thickness (ALT) and temperature on the top of permafrost (TTOP), which are important factors in snow-hydrological processes. BMI provides an easy approach to couple the models with each other. Here, we provide a case of coupling the Ku component to snow process components, including the Snow-Degree-Day (SDD) method and Snow-Energy-Balance (SEB) method, which are existing components in the hydrological model TOPOFLOW. The work flow is (1) get variables from meteorology component, set the values to snow process component, and advance the snow process component, (2) get variables from meteorology and snow component, provide these to the Ku component and advance, (3) get variables from snow process component, set the values to meteorology component, and advance the meteorology component. The next phase is to couple the permafrost component with fully BMI-compliant TOPOFLOW hydrological model, which could provide a useful tool to investigate the permafrost hydrological effect.

Hardware-Based Non-Optimum Factors for Launch Vehicle Structural Design

NASA Technical Reports Server (NTRS)

Wu, K. Chauncey; Cerro, Jeffrey A.

2010-01-01

During aerospace vehicle conceptual and preliminary design, empirical non-optimum factors are typically applied to predicted structural component weights to account for undefined manufacturing and design details. Non-optimum factors are developed here for 32 aluminum-lithium 2195 orthogrid panels comprising the liquid hydrogen tank barrel of the Space Shuttle External Tank using measured panel weights and manufacturing drawings. Minimum values for skin thickness, axial and circumferential blade stiffener thickness and spacing, and overall panel thickness are used to estimate individual panel weights. Panel non-optimum factors computed using a coarse weights model range from 1.21 to 1.77, and a refined weights model (including weld lands and skin and stiffener transition details) yields non-optimum factors of between 1.02 and 1.54. Acreage panels have an average 1.24 non-optimum factor using the coarse model, and 1.03 with the refined version. The observed consistency of these acreage non-optimum factors suggests that relatively simple models can be used to accurately predict large structural component weights for future launch vehicles.

Exploring the Factor Structure of the Job Demands-Resources Measure With Patient Violence on Direct Care Workers in the Home Setting.

PubMed

Byon, Ha Do; Harrington, Donna; Storr, Carla L; Lipscomb, Jane

2017-08-01

Workplace violence research in health care settings using the Job Demands-Resources (JD-R) framework is hindered by the lack of comprehensive examination of the factor structure of the JD-R measure when it includes patient violence. Is patient violence a component of job demands or its own factor as an occupational outcome? Exploratory factor analysis and confirmatory factor analysis were conducted using a sample of direct care workers in the home setting (n = 961). The overall 2-construct JD-R structure persisted. Patient violence was not identified as a separate factor from job demands; rather, two demand factors emerged: violence/emotional and workload/physical demands. Although the three-factor model fits the data, the two-factor model with patient violence being a component of job demands is a parsimonious and effective measurement framework.

The Analysis of Three-Way Contingency Tables by Three-Mode Association Models.

ERIC Educational Resources Information Center

Anderson, Carolyn J.

1996-01-01

Generalizations of L. A. Goodman's RC(M) association model (1991 and earlier) are presented for three-way tables. These three-mode association models use L. R. Tucker's three-mode components model (1964, 1966) to represent the three-factor interaction or the combined effects of two- and three-factor interactions. (SLD)

Sparse modeling of spatial environmental variables associated with asthma

PubMed Central

Chang, Timothy S.; Gangnon, Ronald E.; Page, C. David; Buckingham, William R.; Tandias, Aman; Cowan, Kelly J.; Tomasallo, Carrie D.; Arndt, Brian G.; Hanrahan, Lawrence P.; Guilbert, Theresa W.

2014-01-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin’s Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5–50 years over a three-year period. Each patient’s home address was geocoded to one of 3,456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin’s geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. PMID:25533437

Sparse modeling of spatial environmental variables associated with asthma.

PubMed

Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W

2015-02-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS

PubMed Central

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2012-01-01

The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied. PMID:22661790

Effect of noise in principal component analysis with an application to ozone pollution

NASA Astrophysics Data System (ADS)

Tsakiri, Katerina G.

This thesis analyzes the effect of independent noise in principal components of k normally distributed random variables defined by a covariance matrix. We prove that the principal components as well as the canonical variate pairs determined from joint distribution of original sample affected by noise can be essentially different in comparison with those determined from the original sample. However when the differences between the eigenvalues of the original covariance matrix are sufficiently large compared to the level of the noise, the effect of noise in principal components and canonical variate pairs proved to be negligible. The theoretical results are supported by simulation study and examples. Moreover, we compare our results about the eigenvalues and eigenvectors in the two dimensional case with other models examined before. This theory can be applied in any field for the decomposition of the components in multivariate analysis. One application is the detection and prediction of the main atmospheric factor of ozone concentrations on the example of Albany, New York. Using daily ozone, solar radiation, temperature, wind speed and precipitation data, we determine the main atmospheric factor for the explanation and prediction of ozone concentrations. A methodology is described for the decomposition of the time series of ozone and other atmospheric variables into the global term component which describes the long term trend and the seasonal variations, and the synoptic scale component which describes the short term variations. By using the Canonical Correlation Analysis, we show that solar radiation is the only main factor between the atmospheric variables considered here for the explanation and prediction of the global and synoptic scale component of ozone. The global term components are modeled by a linear regression model, while the synoptic scale components by a vector autoregressive model and the Kalman filter. The coefficient of determination, R2, for the prediction of the synoptic scale ozone component was found to be the highest when we consider the synoptic scale component of the time series for solar radiation and temperature. KEY WORDS: multivariate analysis; principal component; canonical variate pairs; eigenvalue; eigenvector; ozone; solar radiation; spectral decomposition; Kalman filter; time series prediction

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

Tom Elicson; Bentley Harwood; Jim Bouchard

Over a 12 month period, a fire PRA was developed for a DOE facility using the NUREG/CR-6850 EPRI/NRC fire PRA methodology. The fire PRA modeling included calculation of fire severity factors (SFs) and fire non-suppression probabilities (PNS) for each safe shutdown (SSD) component considered in the fire PRA model. The SFs were developed by performing detailed fire modeling through a combination of CFAST fire zone model calculations and Latin Hypercube Sampling (LHS). Component damage times and automatic fire suppression system actuation times calculated in the CFAST LHS analyses were then input to a time-dependent model of fire non-suppression probability. Themore » fire non-suppression probability model is based on the modeling approach outlined in NUREG/CR-6850 and is supplemented with plant specific data. This paper presents the methodology used in the DOE facility fire PRA for modeling fire-induced SSD component failures and includes discussions of modeling techniques for: • Development of time-dependent fire heat release rate profiles (required as input to CFAST), • Calculation of fire severity factors based on CFAST detailed fire modeling, and • Calculation of fire non-suppression probabilities.« less

Analysis and improvement measures of flight delay in China

NASA Astrophysics Data System (ADS)

Zang, Yuhang

2017-03-01

Firstly, this paper establishes the principal component regression model to analyze the data quantitatively, based on principal component analysis to get the three principal component factors of flight delays. Then the least square method is used to analyze the factors and obtained the regression equation expression by substitution, and then found that the main reason for flight delays is airlines, followed by weather and traffic. Aiming at the above problems, this paper improves the controllable aspects of traffic flow control. For reasons of traffic flow control, an adaptive genetic queuing model is established for the runway terminal area. This paper, establish optimization method that fifteen planes landed simultaneously on the three runway based on Beijing capital international airport, comparing the results with the existing FCFS algorithm, the superiority of the model is proved.

Identifying fluorescent pulp mill effluent in the Gulf of Maine and its watershed

USGS Publications Warehouse

Cawley, Kaelin M.; Butler, Kenna D.; Aiken, George R.; Larsen, Laurel G.; Huntington, Thomas G.; McKnight, Diane M.

2012-01-01

Using fluorescence spectroscopy and parallel factor analysis (PARAFAC) we characterized and modeled the fluorescence properties of dissolved organic matter (DOM) in samples from the Penobscot River, Androscoggin River, Penobscot Bay, and the Gulf of Maine (GoM). We analyzed excitation-emission matrices (EEMs) using an existing PARAFAC model (Cory and McKnight, 2005) and created a system-specific model with seven components (GoM PARAFAC). The GoM PARAFAC model contained six components similar to those in other PARAFAC models and one unique component with a spectrum similar to a residual found using the Cory and McKnight (2005) model. The unique component was abundant in samples from the Androscoggin River immediately downstream of a pulp mill effluent release site. The detection of a PARAFAC component associated with an anthropogenic source of DOM, such as pulp mill effluent, demonstrates the importance for rigorously analyzing PARAFAC residuals and developing system-specific models.

Procedures and models for estimating preconstruction costs of highway projects.

DOT National Transportation Integrated Search

2012-07-01

This study presents data driven and component based PE cost prediction models by utilizing critical factors retrieved from ten years of historical project data obtained from ODOT roadway division. The study used factor analysis of covariance and corr...

Clustering of leptin and physical activity with components of metabolic syndrome in Iranian population: an exploratory factor analysis.

PubMed

Esteghamati, Alireza; Zandieh, Ali; Khalilzadeh, Omid; Morteza, Afsaneh; Meysamie, Alipasha; Nakhjavani, Manouchehr; Gouya, Mohammad Mehdi

2010-10-01

Metabolic syndrome (MetS), manifested by insulin resistance, dyslipidemia, central obesity, and hypertension, is conceived to be associated with hyperleptinemia and physical activity. The aim of this study was to elucidate the factors underlying components of MetS and also to test the suitability of leptin and physical activity as additional components of this syndrome. Data of the individuals without history of diabetes mellitus, aged 25-64 years, from third national surveillance of risk factors of non-communicable diseases (SuRFNCD-2007), were analyzed. Performing factor analysis on waist circumference, homeostasis model assessment of insulin resistance, systolic blood pressure, triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C) led to extraction of two factors which explained around 59.0% of the total variance in both genders. When TG and HDL-C were replaced by TG to HDL-C ratio, a single factor was obtained. In contrast to physical activity, addition of leptin was consistent with one-factor structure of MetS and improved the ability of suggested models to identify obesity (BMI≥30 kg/m2, P<0.01), using receiver-operator characteristics curve analysis. In general, physical activity loaded on the first identified factor. Our study shows that one underlying factor structure of MetS is also plausible and the inclusion of leptin does not interfere with this structure. Further, this study suggests that physical activity influences MetS components via modulation of the main underlying pathophysiologic pathway of this syndrome.

Individual and Environmental Factors Influencing Adolescents’ Dietary Behavior in Low- and Middle-Income Settings

PubMed Central

Verstraeten, Roosmarijn; Leroy, Jef L.; Pieniak, Zuzanna; Ochoa-Avilès, Angélica; Holdsworth, Michelle; Verbeke, Wim; Maes, Lea; Kolsteren, Patrick

2016-01-01

Objective Given the public health importance of improving dietary behavior in chronic disease prevention in low- and middle-income countries it is crucial to understand the factors influencing dietary behavior in these settings. This study tested the validity of a conceptual framework linking individual and environmental factors to dietary behavior among Ecuadorian adolescents aged 10–16 years. Methods A cross-sectional survey was conducted in 784 school-going Ecuadorian adolescents in urban and rural Southern Ecuador. Participants provided data on socio-economic status, anthropometry, dietary behavior and its determining factors. The relationships between individual (perceived benefits and barriers, self-efficacy, habit strength, and a better understanding of healthy food) and environmental factors (physical environment: accessibility to healthy food; social environment: parental permissiveness and school support), and their association with key components of dietary behavior (fruit and vegetables, sugary drinks, breakfast, and unhealthy snack intake) were assessed using structural equation modeling. Results The conceptual model performed well for each component of eating behavior, indicating acceptable goodness-of-fit for both the measurement and structural models. Models for vegetable intake and unhealthy snacking showed significant and direct effects of individual factors (perceived benefits). For breakfast and sugary drink consumption, there was a direct and positive association with socio-environmental factors (school support and parental permissiveness). Access to healthy food was associated indirectly with all eating behaviors (except for sugary drink intake) and this effect operated through socio-environmental (parental permissiveness and school support) and individual factors (perceived benefits). Conclusion Our study demonstrated that key components of adolescents’ dietary behaviors are influenced by a complex interplay of individual and environmental factors. The findings indicate that the influence of these factors varied by type of dietary behavior. PMID:27447169

Individual and Environmental Factors Influencing Adolescents' Dietary Behavior in Low- and Middle-Income Settings.

PubMed

Verstraeten, Roosmarijn; Leroy, Jef L; Pieniak, Zuzanna; Ochoa-Avilès, Angélica; Holdsworth, Michelle; Verbeke, Wim; Maes, Lea; Kolsteren, Patrick

2016-01-01

Given the public health importance of improving dietary behavior in chronic disease prevention in low- and middle-income countries it is crucial to understand the factors influencing dietary behavior in these settings. This study tested the validity of a conceptual framework linking individual and environmental factors to dietary behavior among Ecuadorian adolescents aged 10-16 years. A cross-sectional survey was conducted in 784 school-going Ecuadorian adolescents in urban and rural Southern Ecuador. Participants provided data on socio-economic status, anthropometry, dietary behavior and its determining factors. The relationships between individual (perceived benefits and barriers, self-efficacy, habit strength, and a better understanding of healthy food) and environmental factors (physical environment: accessibility to healthy food; social environment: parental permissiveness and school support), and their association with key components of dietary behavior (fruit and vegetables, sugary drinks, breakfast, and unhealthy snack intake) were assessed using structural equation modeling. The conceptual model performed well for each component of eating behavior, indicating acceptable goodness-of-fit for both the measurement and structural models. Models for vegetable intake and unhealthy snacking showed significant and direct effects of individual factors (perceived benefits). For breakfast and sugary drink consumption, there was a direct and positive association with socio-environmental factors (school support and parental permissiveness). Access to healthy food was associated indirectly with all eating behaviors (except for sugary drink intake) and this effect operated through socio-environmental (parental permissiveness and school support) and individual factors (perceived benefits). Our study demonstrated that key components of adolescents' dietary behaviors are influenced by a complex interplay of individual and environmental factors. The findings indicate that the influence of these factors varied by type of dietary behavior.

Numerical modeling evapotranspiration flux components in shrub-encroached grassland in Inner Mongolia, China

NASA Astrophysics Data System (ADS)

Wang, Pei; Li, Xiao-Yan; Huang, Jie-Yu; Yang, Wen-Xin; Wang, Qi-Dan; Xu, Kun; Zheng, Xiao-Ran

2016-04-01

Shrub encroachment into arid grasslands occurs around the world. However, few works on shrub encroachment has been conducted in China. Moreover, its hydrological implications remain poorly investigated in arid and semiarid regions. This study combined a two-source energy balanced model and Newton-Raphson iteration scheme to simulate the evapotranspiration (ET) and their components of shrub-encroached(with 15.4% shrub coverage) grassland in Inner Mongolia. Good agreements of ET flux between modelled and measured by Bowen ratio method with relatively insensitive to uncertainties/errors in the assigned models parameters or in measured input variables for its components illustrated that our model was feasible for simulating evapotranspiration flux components in shrub-encroached grassland. The transpiration fraction(T /ET)account for 58±17%during the growing season. With the designed shrub encroachment extreme scenarios (maximum and minimum coverage),the contribution of shrub to local plant transpiration (Tshrub/T) was 20.06±7%during the growing season. Canopy conductance was the main controlling factor of T /ET. In diurnal scale short wave solar radiation was the direct influential factor while in seasonal scale leaf area index (LAI) and soil water content were the direct influential factors. We find that the seasonal variation of Tshrub/T has a good relationship with ratio of LAIshrub/LAI, and rainfall characteristics widened the difference of contribution of shrub and herbs to ecosystem evapotranspiration.

Short communication: Principal components and factor analytic models for test-day milk yield in Brazilian Holstein cattle.

PubMed

Bignardi, A B; El Faro, L; Rosa, G J M; Cardoso, V L; Machado, P F; Albuquerque, L G

2012-04-01

A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Multiple Component Event-Related Potential (mcERP) Estimation

NASA Technical Reports Server (NTRS)

Knuth, K. H.; Clanton, S. T.; Shah, A. S.; Truccolo, W. A.; Ding, M.; Bressler, S. L.; Trejo, L. J.; Schroeder, C. E.; Clancy, Daniel (Technical Monitor)

2002-01-01

We show how model-based estimation of the neural sources responsible for transient neuroelectric signals can be improved by the analysis of single trial data. Previously, we showed that a multiple component event-related potential (mcERP) algorithm can extract the responses of individual sources from recordings of a mixture of multiple, possibly interacting, neural ensembles. McERP also estimated single-trial amplitudes and onset latencies, thus allowing more accurate estimation of ongoing neural activity during an experimental trial. The mcERP algorithm is related to informax independent component analysis (ICA); however, the underlying signal model is more physiologically realistic in that a component is modeled as a stereotypic waveshape varying both in amplitude and onset latency from trial to trial. The result is a model that reflects quantities of interest to the neuroscientist. Here we demonstrate that the mcERP algorithm provides more accurate results than more traditional methods such as factor analysis and the more recent ICA. Whereas factor analysis assumes the sources are orthogonal and ICA assumes the sources are statistically independent, the mcERP algorithm makes no such assumptions thus allowing investigators to examine interactions among components by estimating the properties of single-trial responses.

Modeling longitudinal data, I: principles of multivariate analysis.

PubMed

Ravani, Pietro; Barrett, Brendan; Parfrey, Patrick

2009-01-01

Statistical models are used to study the relationship between exposure and disease while accounting for the potential role of other factors' impact on outcomes. This adjustment is useful to obtain unbiased estimates of true effects or to predict future outcomes. Statistical models include a systematic component and an error component. The systematic component explains the variability of the response variable as a function of the predictors and is summarized in the effect estimates (model coefficients). The error element of the model represents the variability in the data unexplained by the model and is used to build measures of precision around the point estimates (confidence intervals).

Generalized Structured Component Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Takane, Yoshio

2004-01-01

We propose an alternative method to partial least squares for path analysis with components, called generalized structured component analysis. The proposed method replaces factors by exact linear combinations of observed variables. It employs a well-defined least squares criterion to estimate model parameters. As a result, the proposed method…

Exploring the Factor Structure of Neurocognitive Measures in Older Individuals

PubMed Central

Santos, Nadine Correia; Costa, Patrício Soares; Amorim, Liliana; Moreira, Pedro Silva; Cunha, Pedro; Cotter, Jorge; Sousa, Nuno

2015-01-01

Here we focus on factor analysis from a best practices point of view, by investigating the factor structure of neuropsychological tests and using the results obtained to illustrate on choosing a reasonable solution. The sample (n=1051 individuals) was randomly divided into two groups: one for exploratory factor analysis (EFA) and principal component analysis (PCA), to investigate the number of factors underlying the neurocognitive variables; the second to test the “best fit” model via confirmatory factor analysis (CFA). For the exploratory step, three extraction (maximum likelihood, principal axis factoring and principal components) and two rotation (orthogonal and oblique) methods were used. The analysis methodology allowed exploring how different cognitive/psychological tests correlated/discriminated between dimensions, indicating that to capture latent structures in similar sample sizes and measures, with approximately normal data distribution, reflective models with oblimin rotation might prove the most adequate. PMID:25880732

Associations of Extrinsic and Intrinsic Components of Work Stress with Health: A Systematic Review of Evidence on the Effort-Reward Imbalance Model.

PubMed

Siegrist, Johannes; Li, Jian

2016-04-19

Mainstream psychological stress theory claims that it is important to include information on people's ways of coping with work stress when assessing the impact of stressful psychosocial work environments on health. Yet, some widely used respective theoretical models focus exclusively on extrinsic factors. The model of effort-reward imbalance (ERI) differs from them as it explicitly combines information on extrinsic and intrinsic factors in studying workers' health. As a growing number of studies used the ERI model in recent past, we conducted a systematic review of available evidence, with a special focus on the distinct contribution of its intrinsic component, the coping pattern "over-commitment", towards explaining health. Moreover, we explore whether the interaction of intrinsic and extrinsic components exceeds the size of effects on health attributable to single components. Results based on 51 reports document an independent explanatory role of "over-commitment" in explaining workers' health in a majority of studies. However, support in favour of the interaction hypothesis is limited and requires further exploration. In conclusion, the findings of this review support the usefulness of a work stress model that combines extrinsic and intrinsic components in terms of scientific explanation and of designing more comprehensive worksite stress prevention programs.

Associations of Extrinsic and Intrinsic Components of Work Stress with Health: A Systematic Review of Evidence on the Effort-Reward Imbalance Model

PubMed Central

Siegrist, Johannes; Li, Jian

2016-01-01

Mainstream psychological stress theory claims that it is important to include information on people’s ways of coping with work stress when assessing the impact of stressful psychosocial work environments on health. Yet, some widely used respective theoretical models focus exclusively on extrinsic factors. The model of effort-reward imbalance (ERI) differs from them as it explicitly combines information on extrinsic and intrinsic factors in studying workers’ health. As a growing number of studies used the ERI model in recent past, we conducted a systematic review of available evidence, with a special focus on the distinct contribution of its intrinsic component, the coping pattern “over-commitment”, towards explaining health. Moreover, we explore whether the interaction of intrinsic and extrinsic components exceeds the size of effects on health attributable to single components. Results based on 51 reports document an independent explanatory role of “over-commitment” in explaining workers’ health in a majority of studies. However, support in favour of the interaction hypothesis is limited and requires further exploration. In conclusion, the findings of this review support the usefulness of a work stress model that combines extrinsic and intrinsic components in terms of scientific explanation and of designing more comprehensive worksite stress prevention programs. PMID:27104548

Comparison of factor-analytic and reduced rank models for test-day milk yield in Gyr dairy cattle (Bos indicus).

PubMed

Pereira, R J; Ayres, D R; El Faro, L; Verneque, R S; Vercesi Filho, A E; Albuquerque, L G

2013-09-27

We analyzed 46,161 monthly test-day records of milk production from 7453 first lactations of crossbred dairy Gyr (Bos indicus) x Holstein cows. The following seven models were compared: standard multivariate model (M10), three reduced rank models fitting the first 2, 3, or 4 genetic principal components, and three models considering a 2-, 3-, or 4-factor structure for the genetic covariance matrix. Full rank residual covariance matrices were considered for all models. The model fitting the first two principal components (PC2) was the best according to the model selection criteria. Similar phenotypic, genetic, and residual variances were obtained with models M10 and PC2. The heritability estimates ranged from 0.14 to 0.21 and from 0.13 to 0.21 for models M10 and PC2, respectively. The genetic correlations obtained with model PC2 were slightly higher than those estimated with model M10. PC2 markedly reduced the number of parameters estimated and the time spent to reach convergence. We concluded that two principal components are sufficient to model the structure of genetic covariances between test-day milk yields.

Source apportionment of exposures to volatile organic compounds. I. Evaluation of receptor models using simulated exposure data

NASA Astrophysics Data System (ADS)

Miller, Shelly L.; Anderson, Melissa J.; Daly, Eileen P.; Milford, Jana B.

Four receptor-oriented source apportionment models were evaluated by applying them to simulated personal exposure data for select volatile organic compounds (VOCs) that were generated by Monte Carlo sampling from known source contributions and profiles. The exposure sources modeled are environmental tobacco smoke, paint emissions, cleaning and/or pesticide products, gasoline vapors, automobile exhaust, and wastewater treatment plant emissions. The receptor models analyzed are chemical mass balance, principal component analysis/absolute principal component scores, positive matrix factorization (PMF), and graphical ratio analysis for composition estimates/source apportionment by factors with explicit restriction, incorporated in the UNMIX model. All models identified only the major contributors to total exposure concentrations. PMF extracted factor profiles that most closely represented the major sources used to generate the simulated data. None of the models were able to distinguish between sources with similar chemical profiles. Sources that contributed <5% to the average total VOC exposure were not identified.

The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models

ERIC Educational Resources Information Center

Schoeneberger, Jason A.

2016-01-01

The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…

How preschool executive functioning predicts several aspects of math achievement in Grades 1 and 3: A longitudinal study.

PubMed

Viterbori, Paola; Usai, M Carmen; Traverso, Laura; De Franchis, Valentina

2015-12-01

This longitudinal study analyzes whether selected components of executive function (EF) measured during the preschool period predict several indices of math achievement in primary school. Six EF measures were assessed in a sample of 5-year-old children (N = 175). The math achievement of the same children was then tested in Grades 1 and 3 using both a composite math score and three single indices of written calculation, arithmetical facts, and problem solving. Using previous results obtained from the same sample of children, a confirmatory factor analysis examining the latent EF structure in kindergarten indicated that a two-factor model provided the best fit for the data. In this model, inhibition and working memory (WM)-flexibility were separate dimensions. A full structural equation model was then used to test the hypothesis that math achievement (the composite math score and single math scores) in Grades 1 and 3 could be explained by the two EF components comprising the kindergarten model. The results indicate that the WM-flexibility component measured during the preschool period substantially predicts mathematical achievement, especially in Grade 3. The math composite scores were predicted by the WM-flexibility factor at both grade levels. In Grade 3, both problem solving and arithmetical facts were predicted by the WM-flexibility component. The results empirically support interventions that target EF as an important component of early childhood mathematics education. Copyright © 2015 Elsevier Inc. All rights reserved.

Ego-resiliency reloaded: a three-component model of general resiliency.

PubMed

Farkas, Dávid; Orosz, Gábor

2015-01-01

Ego-resiliency (ER) is a capacity that enables individuals to adapt to constantly changing environmental demands. The goal of our research was to identify components of Ego-resiliency, and to test the reliability and the structural and convergent validity of the refined version of the ER11 Ego-resiliency scale. In Study 1 we used a factor analytical approach to assess structural validity and to identify factors of Ego-resiliency. Comparing alternative factor-structures, a hierarchical model was chosen including three factors: Active Engagement with the World (AEW), Repertoire of Problem Solving Strategies (RPSS), and Integrated Performance under Stress (IPS). In Study 2, the convergent and divergent validity of the ER11 scale and its factors and their relationship with resilience were tested. The results suggested that resiliency is a double-faced construct, with one function to keep the personality system stable and intact, and the other function to adjust the personality system in an adaptive way to the dynamically changing environment. The stability function is represented by the RPSS and IPS components of ER. Their relationship pattern is similar to other constructs of resilience, e.g. the Revised Connor-Davidson Resilience Scale (R-CD-RISC). The flexibility function is represented by the unit of RPSS and AEW components. In Study 3 we tested ER11 on a Hungarian online representative sample and integrated the results in a model of general resiliency. This framework allows us to grasp both the stability-focused and the plasticity-focused nature of resiliency.

Ego-Resiliency Reloaded: A Three-Component Model of General Resiliency

PubMed Central

Farkas, Dávid; Orosz, Gábor

2015-01-01

Ego-resiliency (ER) is a capacity that enables individuals to adapt to constantly changing environmental demands. The goal of our research was to identify components of Ego-resiliency, and to test the reliability and the structural and convergent validity of the refined version of the ER11 Ego-resiliency scale. In Study 1 we used a factor analytical approach to assess structural validity and to identify factors of Ego-resiliency. Comparing alternative factor-structures, a hierarchical model was chosen including three factors: Active Engagement with the World (AEW), Repertoire of Problem Solving Strategies (RPSS), and Integrated Performance under Stress (IPS). In Study 2, the convergent and divergent validity of the ER11 scale and its factors and their relationship with resilience were tested. The results suggested that resiliency is a double-faced construct, with one function to keep the personality system stable and intact, and the other function to adjust the personality system in an adaptive way to the dynamically changing environment. The stability function is represented by the RPSS and IPS components of ER. Their relationship pattern is similar to other constructs of resilience, e.g. the Revised Connor-Davidson Resilience Scale (R-CD-RISC). The flexibility function is represented by the unit of RPSS and AEW components. In Study 3 we tested ER11 on a Hungarian online representative sample and integrated the results in a model of general resiliency. This framework allows us to grasp both the stability-focused and the plasticity-focused nature of resiliency. PMID:25815881

Effects of risk factors for and components of metabolic syndrome on the quality of life of patients with systemic lupus erythematosus: a structural equation modeling approach.

PubMed

Lee, Jeong-Won; Kang, Ji-Hyoun; Lee, Kyung-Eun; Park, Dong-Jin; Kang, Seong Wook; Kwok, Seung-Ki; Kim, Seong-Kyu; Choe, Jung-Yoon; Kim, Hyoun-Ah; Sung, Yoon-Kyoung; Shin, Kichul; Lee, Sang-Il; Lee, Chang Hoon; Choi, Sung Jae; Lee, Shin-Seok

2018-01-01

This study assessed the relationships among the risk factors for and components of metabolic syndrome (MetS) and health-related quality of life (HRQOL) in a hypothesized causal model using structural equation modeling (SEM) in patients with systemic lupus erythematosus (SLE). Of the 505 SLE patients enrolled in the Korean Lupus Network (KORNET registry), 244 had sufficient data to assess the components of MetS at enrollment. Education level, monthly income, corticosteroid dose, Systemic Lupus Erythematosus Disease Activity Index, Physicians' Global Assessment, Beck Depression Inventory, MetS components, and the Short Form-36 at the time of cohort entry were determined. SEM was used to test the causal relationship based on the Analysis of Moment Structure. The average age of the 244 patients was 40.7 ± 11.8 years. The SEM results supported the good fit of the model (χ 2  = 71.629, p = 0.078, RMSEA 0.034, CFI 0.972). The final model showed a direct negative effect of higher socioeconomic status and a positive indirect effect of higher disease activity on MetS, the latter through corticosteroid dose. MetS did not directly impact HRQOL but had an indirect negative impact on it, through depression. In our causal model, MetS risk factors were related to MetS components. The latter had a negative indirect impact on HRQOL, through depression. Clinicians should consider socioeconomic status and medication and seek to modify disease activity, MetS, and depression to improve the HRQOL of SLE patients.

Assessing School Work Culture: A Higher-Order Analysis and Strategy.

ERIC Educational Resources Information Center

Johnson, William L.; Johnson, Annabel M.; Zimmerman, Kurt J.

This paper reviews a work culture productivity model and reports the development of a work culture instrument based on the culture productivity model. Higher order principal components analysis was used to assess work culture, and a third-order factor analysis shows how the first-order factors group into higher-order factors. The school work…

Joint genome-wide prediction in several populations accounting for randomness of genotypes: A hierarchical Bayes approach. II: Multivariate spike and slab priors for marker effects and derivation of approximate Bayes and fractional Bayes factors for the complete family of models.

PubMed

Martínez, Carlos Alberto; Khare, Kshitij; Banerjee, Arunava; Elzo, Mauricio A

2017-03-21

This study corresponds to the second part of a companion paper devoted to the development of Bayesian multiple regression models accounting for randomness of genotypes in across population genome-wide prediction. This family of models considers heterogeneous and correlated marker effects and allelic frequencies across populations, and has the ability of considering records from non-genotyped individuals and individuals with missing genotypes in any subset of loci without the need for previous imputation, taking into account uncertainty about imputed genotypes. This paper extends this family of models by considering multivariate spike and slab conditional priors for marker allele substitution effects and contains derivations of approximate Bayes factors and fractional Bayes factors to compare models from part I and those developed here with their null versions. These null versions correspond to simpler models ignoring heterogeneity of populations, but still accounting for randomness of genotypes. For each marker loci, the spike component of priors corresponded to point mass at 0 in R S , where S is the number of populations, and the slab component was a S-variate Gaussian distribution, independent conditional priors were assumed. For the Gaussian components, covariance matrices were assumed to be either the same for all markers or different for each marker. For null models, the priors were simply univariate versions of these finite mixture distributions. Approximate algebraic expressions for Bayes factors and fractional Bayes factors were found using the Laplace approximation. Using the simulated datasets described in part I, these models were implemented and compared with models derived in part I using measures of predictive performance based on squared Pearson correlations, Deviance Information Criterion, Bayes factors, and fractional Bayes factors. The extensions presented here enlarge our family of genome-wide prediction models making it more flexible in the sense that it now offers more modeling options. Copyright © 2017 Elsevier Ltd. All rights reserved.

Job Performance as Multivariate Dynamic Criteria: Experience Sampling and Multiway Component Analysis.

PubMed

Spain, Seth M; Miner, Andrew G; Kroonenberg, Pieter M; Drasgow, Fritz

2010-08-06

Questions about the dynamic processes that drive behavior at work have been the focus of increasing attention in recent years. Models describing behavior at work and research on momentary behavior indicate that substantial variation exists within individuals. This article examines the rationale behind this body of work and explores a method of analyzing momentary work behavior using experience sampling methods. The article also examines a previously unused set of methods for analyzing data produced by experience sampling. These methods are known collectively as multiway component analysis. Two archetypal techniques of multimode factor analysis, the Parallel factor analysis and the Tucker3 models, are used to analyze data from Miner, Glomb, and Hulin's (2010) experience sampling study of work behavior. The efficacy of these techniques for analyzing experience sampling data is discussed as are the substantive multimode component models obtained.

State Variability and Psychopathological Attractors: the Behavioural Complexity as Discriminating Factor Between the Pathology and Normality Profiles

NASA Astrophysics Data System (ADS)

Marconi, Pier Luigi

369 patients, selected within a set of 1215 outpatients, were studied. The data were clustered into two set: the baseline set and the endpoint set. The clinical parameters had a higher variability at the baseline than at the endpoint. 4 to 5 factors were extracted in total group and 3 subgroups (190 "affective", 34 type-B personality, 166 without any of both disorders). In all subgroups there was a background pattern of 6 components: 3 components confirming the trifactorial temperamental model of Cloninger; 1 component related to the quality of social relationships; 2 components (that are the main components of factorial model about in all groups) relating to quality of life and adjustment self perceived by patients, and to pattern of dysfunctional behavior, inner feelings, and thought processes externally evaluated. These background components seem to aggregate differently in the subgroups in accordance to the clinical diagnosis. These patterns may be interpreted as expression of an increased "coherence" among parameters due to a lack of flexibility caused by the illness. The different class of illness can be further distinguished by intensity of maladjustment, that is related to the intensity of clinical signs just only at the baseline. These data suggest that the main interfering factors are clinical psychopathology at baseline and stable personality traits at endpoint. This persistent chronic maladjustment personality-driven is evidenced after the clinical disorder was cured by treatment. An interpretative model is presented by the author.

Conceptual design and analysis of a dynamic scale model of the Space Station Freedom

NASA Technical Reports Server (NTRS)

Davis, D. A.; Gronet, M. J.; Tan, M. K.; Thorne, J.

1994-01-01

This report documents the conceptual design study performed to evaluate design options for a subscale dynamic test model which could be used to investigate the expected on-orbit structural dynamic characteristics of the Space Station Freedom early build configurations. The baseline option was a 'near-replica' model of the SSF SC-7 pre-integrated truss configuration. The approach used to develop conceptual design options involved three sets of studies: evaluation of the full-scale design and analysis databases, conducting scale factor trade studies, and performing design sensitivity studies. The scale factor trade study was conducted to develop a fundamental understanding of the key scaling parameters that drive design, performance and cost of a SSF dynamic scale model. Four scale model options were estimated: 1/4, 1/5, 1/7, and 1/10 scale. Prototype hardware was fabricated to assess producibility issues. Based on the results of the study, a 1/4-scale size is recommended based on the increased model fidelity associated with a larger scale factor. A design sensitivity study was performed to identify critical hardware component properties that drive dynamic performance. A total of 118 component properties were identified which require high-fidelity replication. Lower fidelity dynamic similarity scaling can be used for non-critical components.

Writing fluency and quality in kindergarten and first grade: The role of attention, reading, transcription, and oral language

PubMed Central

Kent, Shawn; Wanzek, Jeanne; Petscher, Yaacov; Al Otaiba, Stephanie; Kim, Young-Suk

2013-01-01

In the present study, we examined the influence of kindergarten component skills on writing outcomes, both concurrently and longitudinally to first grade. Using data from 265 students, we investigated a model of writing development including attention regulation along with students’ reading, spelling, handwriting fluency, and oral language component skills. Results from structural equation modeling demonstrated that a model including attention was better fitting than a model with only language and literacy factors. Attention, a higher-order literacy factor related to reading and spelling proficiency, and automaticity in letter-writing were uniquely and positively related to compositional fluency in kindergarten. Attention and higher-order literacy factor were predictive of both composition quality and fluency in first grade, while oral language showed unique relations with first grade writing quality. Implications for writing development and instruction are discussed. PMID:25132722

Use of Cox's Cure Model to Establish Clinical Determinants of Long-Term Disease-Free Survival in Neoadjuvant-Chemotherapy-Treated Breast Cancer Patients without Pathologic Complete Response.

PubMed

Asano, Junichi; Hirakawa, Akihiro; Hamada, Chikuma; Yonemori, Kan; Hirata, Taizo; Shimizu, Chikako; Tamura, Kenji; Fujiwara, Yasuhiro

2013-01-01

In prognostic studies for breast cancer patients treated with neoadjuvant chemotherapy (NAC), the ordinary Cox proportional-hazards (PH) model has been often used to identify prognostic factors for disease-free survival (DFS). This model assumes that all patients eventually experience relapse or death. However, a subset of NAC-treated breast cancer patients never experience these events during long-term follow-up (>10 years) and may be considered clinically "cured." Clinical factors associated with cure have not been studied adequately. Because the ordinary Cox PH model cannot be used to identify such clinical factors, we used the Cox PH cure model, a recently developed statistical method. This model includes both a logistic regression component for the cure rate and a Cox regression component for the hazard for uncured patients. The purpose of this study was to identify the clinical factors associated with cure and the variables associated with the time to recurrence or death in NAC-treated breast cancer patients without a pathologic complete response, by using the Cox PH cure model. We found that hormone receptor status, clinical response, human epidermal growth factor receptor 2 status, histological grade, and the number of lymph node metastases were associated with cure.

Methodology to develop crash modification functions for road safety treatments with fully specified and hierarchical models.

PubMed

Chen, Yongsheng; Persaud, Bhagwant

2014-09-01

Crash modification factors (CMFs) for road safety treatments are developed as multiplicative factors that are used to reflect the expected changes in safety performance associated with changes in highway design and/or the traffic control features. However, current CMFs have methodological drawbacks. For example, variability with application circumstance is not well understood, and, as important, correlation is not addressed when several CMFs are applied multiplicatively. These issues can be addressed by developing safety performance functions (SPFs) with components of crash modification functions (CM-Functions), an approach that includes all CMF related variables, along with others, while capturing quantitative and other effects of factors and accounting for cross-factor correlations. CM-Functions can capture the safety impact of factors through a continuous and quantitative approach, avoiding the problematic categorical analysis that is often used to capture CMF variability. There are two formulations to develop such SPFs with CM-Function components - fully specified models and hierarchical models. Based on sample datasets from two Canadian cities, both approaches are investigated in this paper. While both model formulations yielded promising results and reasonable CM-Functions, the hierarchical model was found to be more suitable in retaining homogeneity of first-level SPFs, while addressing CM-Functions in sub-level modeling. In addition, hierarchical models better capture the correlations between different impact factors. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analysis of Korean Students' International Mobility by 2-D Model: Driving Force Factor and Directional Factor

ERIC Educational Resources Information Center

Park, Elisa L.

2009-01-01

The purpose of this study is to understand the dynamics of Korean students' international mobility to study abroad by using the 2-D Model. The first D, "the driving force factor," explains how and what components of the dissatisfaction with domestic higher education perceived by Korean students drives students' outward mobility to seek…

The Simple View of Reading as a Framework for National Literacy Initiatives: A Hierarchical Model of Pupil-Level and Classroom-Level Factors

ERIC Educational Resources Information Center

Savage, Robert; Burgos, Giovani; Wood, Eileen; Piquette, Noella

2015-01-01

The Simple View of Reading (SVR) describes Reading Comprehension as the product of distinct child-level variance in decoding (D) and linguistic comprehension (LC) component abilities. When used as a model for educational policy, distinct classroom-level influences of each of the components of the SVR model have been assumed, but have not yet been…

Modeling metabolic syndrome and its association with cognition: the Northern Manhattan study.

PubMed

Levin, Bonnie E; Llabre, Maria M; Dong, Chuanhui; Elkind, Mitchell S V; Stern, Yaakov; Rundek, Tatjana; Sacco, Ralph L; Wright, Clinton B

2014-11-01

Metabolic syndrome (MetS) is a clustering of vascular risk factors and is associated with increased risk of cardiovascular disease. Less is known about the relationship between MetS and cognition. We examined component vascular risk factors of MetS as correlates of different cognitive domains. The Northern Manhattan Study (NOMAS) includes 1290 stroke-free participants from a largely Hispanic multi-ethnic urban community. We used structural equation modeling (SEM) to model latent variables of MetS, assessed at baseline and an average of 10 years later, at which time participants also underwent a full cognitive battery. The two four-factor models, of the metabolic syndrome (blood pressure, lipid levels, obesity, and fasting glucose) and of cognition (language, executive function, psychomotor, and memory), were each well supported (CFI=0.97 and CFI=0.95, respectively). When the two models were combined, the correlation between metabolic syndrome and cognition was -.31. Among the metabolic syndrome components, only blood pressure uniquely predicted all four cognitive domains. After adjusting for age, gender, race/ethnicity, education, smoking, alcohol, and risk factor treatment variables, blood pressure remained a significant correlate of all domains except memory. In this stroke-free race/ethnically diverse community-based cohort, MetS was associated with cognitive function suggesting that MetS and its components may be important predictors of cognitive outcomes. After adjusting for sociodemographic and vascular risk factors, blood pressure was the strongest correlate of cognitive performance. Findings suggest MetS, and in particular blood pressure, may represent markers of vascular or neurodegenerative damage in aging populations.

Generalized Structured Component Analysis with Uniqueness Terms for Accommodating Measurement Error

PubMed Central

Hwang, Heungsun; Takane, Yoshio; Jung, Kwanghee

2017-01-01

Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling (SEM), where latent variables are approximated by weighted composites of indicators. It has no formal mechanism to incorporate errors in indicators, which in turn renders components prone to the errors as well. We propose to extend GSCA to account for errors in indicators explicitly. This extension, called GSCAM, considers both common and unique parts of indicators, as postulated in common factor analysis, and estimates a weighted composite of indicators with their unique parts removed. Adding such unique parts or uniqueness terms serves to account for measurement errors in indicators in a manner similar to common factor analysis. Simulation studies are conducted to compare parameter recovery of GSCAM and existing methods. These methods are also applied to fit a substantively well-established model to real data. PMID:29270146

Social goals, social behavior, and social status in middle childhood.

PubMed

Rodkin, Philip C; Ryan, Allison M; Jamison, Rhonda; Wilson, Travis

2013-06-01

This study examines motivational precursors of social status and the applicability of a dual-component model of social competence to middle childhood. Concurrent and longitudinal relationships between self-reported social goals (social development, demonstration-approach, demonstration-avoid goal orientations), teacher-rated prosocial and aggressive behavior, and peer nominations of social status (preference, popularity) were examined over the course of an academic year among 980 3rd- to 5th-grade children. Findings support dual-component expectations. Confirmatory factor analyses verified the expected 3-factor structure of social goals and 2-factor structure of social status. Structural equation modeling (SEM) found that (a) social development goals were associated with prosocial behavior and increased preference, and (b) demonstration-approach goals were associated with aggressive behavior and increased popularity. Demonstration-avoid goals were associated with a popularity decrease. SEMs were invariant across grade, gender, and ethnicity. Discussion concerns the potential risks of high social status, extensions to the dual-component model, and the generality of an achievement goal approach to child social development. PsycINFO Database Record (c) 2013 APA, all rights reserved

Clustering of metabolic and cardiovascular risk factors in the polycystic ovary syndrome: a principal component analysis.

PubMed

Stuckey, Bronwyn G A; Opie, Nicole; Cussons, Andrea J; Watts, Gerald F; Burke, Valerie

2014-08-01

Polycystic ovary syndrome (PCOS) is a prevalent condition with heterogeneity of clinical features and cardiovascular risk factors that implies multiple aetiological factors and possible outcomes. To reduce a set of correlated variables to a smaller number of uncorrelated and interpretable factors that may delineate subgroups within PCOS or suggest pathogenetic mechanisms. We used principal component analysis (PCA) to examine the endocrine and cardiometabolic variables associated with PCOS defined by the National Institutes of Health (NIH) criteria. Data were retrieved from the database of a single clinical endocrinologist. We included women with PCOS (N = 378) who were not taking the oral contraceptive pill or other sex hormones, lipid lowering medication, metformin or other medication that could influence the variables of interest. PCA was performed retaining those factors with eigenvalues of at least 1.0. Varimax rotation was used to produce interpretable factors. We identified three principal components. In component 1, the dominant variables were homeostatic model assessment (HOMA) index, body mass index (BMI), high density lipoprotein (HDL) cholesterol and sex hormone binding globulin (SHBG); in component 2, systolic blood pressure, low density lipoprotein (LDL) cholesterol and triglycerides; in component 3, total testosterone and LH/FSH ratio. These components explained 37%, 13% and 11% of the variance in the PCOS cohort respectively. Multiple correlated variables from patients with PCOS can be reduced to three uncorrelated components characterised by insulin resistance, dyslipidaemia/hypertension or hyperandrogenaemia. Clustering of risk factors is consistent with different pathogenetic pathways within PCOS and/or differing cardiometabolic outcomes. Copyright © 2014 Elsevier Inc. All rights reserved.

Model Checking of a Diabetes-Cancer Model

NASA Astrophysics Data System (ADS)

Gong, Haijun; Zuliani, Paolo; Clarke, Edmund M.

2011-06-01

Accumulating evidence suggests that cancer incidence might be associated with diabetes mellitus, especially Type II diabetes which is characterized by hyperinsulinaemia, hyperglycaemia, obesity, and overexpression of multiple WNT pathway components. These diabetes risk factors can activate a number of signaling pathways that are important in the development of different cancers. To systematically understand the signaling components that link diabetes and cancer risk, we have constructed a single-cell, Boolean network model by integrating the signaling pathways that are influenced by these risk factors to study insulin resistance, cancer cell proliferation and apoptosis. Then, we introduce and apply the Symbolic Model Verifier (SMV), a formal verification tool, to qualitatively study some temporal logic properties of our diabetes-cancer model. The verification results show that the diabetes risk factors might not increase cancer risk in normal cells, but they will promote cell proliferation if the cell is in a precancerous or cancerous stage characterized by losses of the tumor-suppressor proteins ARF and INK4a.

From prediction error to incentive salience: mesolimbic computation of reward motivation

PubMed Central

Berridge, Kent C.

2011-01-01

Reward contains separable psychological components of learning, incentive motivation and pleasure. Most computational models have focused only on the learning component of reward, but the motivational component is equally important in reward circuitry, and even more directly controls behavior. Modeling the motivational component requires recognition of additional control factors besides learning. Here I will discuss how mesocorticolimbic mechanisms generate the motivation component of incentive salience. Incentive salience takes Pavlovian learning and memory as one input and as an equally important input takes neurobiological state factors (e.g., drug states, appetite states, satiety states) that can vary independently of learning. Neurobiological state changes can produce unlearned fluctuations or even reversals in the ability of a previously-learned reward cue to trigger motivation. Such fluctuations in cue-triggered motivation can dramatically depart from all previously learned values about the associated reward outcome. Thus a consequence of the difference between incentive salience and learning can be to decouple cue-triggered motivation of the moment from previously learned values of how good the associated reward has been in the past. Another consequence can be to produce irrationally strong motivation urges that are not justified by any memories of previous reward values (and without distorting associative predictions of future reward value). Such irrationally strong motivation may be especially problematic in addiction. To comprehend these phenomena, future models of mesocorticolimbic reward function should address the neurobiological state factors that participate to control generation of incentive salience. PMID:22487042

Personality in sanctuary-housed chimpanzees: A comparative approach of psychobiological and penta-factorial human models.

PubMed

Úbeda, Yulán; Llorente, Miquel

2015-02-18

We evaluate a sanctuary chimpanzee sample (N = 11) using two adapted human assessment instruments: the Five-Factor Model (FFM) and Eysenck's Psychoticism-Extraversion-Neuroticism (PEN) model. The former has been widely used in studies of animal personality, whereas the latter has never been used to assess chimpanzees. We asked familiar keepers and scientists (N = 28) to rate 38 (FFM) and 12 (PEN) personality items. The personality surveys showed reliability in all of the items for both instruments. These were then analyzed in a principal component analysis and a regularized exploratory factor analysis, which revealed four and three components, respectively. The results indicate that both questionnaires show a clear factor structure, with characteristic factors not just for the species, but also for the sample type. However, due to its brevity, the PEN may be more suitable for assessing personality in a sanctuary, where employees do not have much time to devote to the evaluation process. In summary, both models are sensitive enough to evaluate the personality of a group of chimpanzees housed in a sanctuary.

Method for Automatic Selection of Parameters in Normal Tissue Complication Probability Modeling.

PubMed

Christophides, Damianos; Appelt, Ane L; Gusnanto, Arief; Lilley, John; Sebag-Montefiore, David

2018-07-01

To present a fully automatic method to generate multiparameter normal tissue complication probability (NTCP) models and compare its results with those of a published model, using the same patient cohort. Data were analyzed from 345 rectal cancer patients treated with external radiation therapy to predict the risk of patients developing grade 1 or ≥2 cystitis. In total, 23 clinical factors were included in the analysis as candidate predictors of cystitis. Principal component analysis was used to decompose the bladder dose-volume histogram into 8 principal components, explaining more than 95% of the variance. The data set of clinical factors and principal components was divided into training (70%) and test (30%) data sets, with the training data set used by the algorithm to compute an NTCP model. The first step of the algorithm was to obtain a bootstrap sample, followed by multicollinearity reduction using the variance inflation factor and genetic algorithm optimization to determine an ordinal logistic regression model that minimizes the Bayesian information criterion. The process was repeated 100 times, and the model with the minimum Bayesian information criterion was recorded on each iteration. The most frequent model was selected as the final "automatically generated model" (AGM). The published model and AGM were fitted on the training data sets, and the risk of cystitis was calculated. The 2 models had no significant differences in predictive performance, both for the training and test data sets (P value > .05) and found similar clinical and dosimetric factors as predictors. Both models exhibited good explanatory performance on the training data set (P values > .44), which was reduced on the test data sets (P values < .05). The predictive value of the AGM is equivalent to that of the expert-derived published model. It demonstrates potential in saving time, tackling problems with a large number of parameters, and standardizing variable selection in NTCP modeling. Crown Copyright © 2018. Published by Elsevier Inc. All rights reserved.

Use of Cusp Catastrophe for Risk Analysis of Navigational Environment: A Case Study of Three Gorges Reservoir Area

PubMed Central

Hao, Guozhu

2016-01-01

A water traffic system is a huge, nonlinear, complex system, and its stability is affected by various factors. Water traffic accidents can be considered to be a kind of mutation of a water traffic system caused by the coupling of multiple navigational environment factors. In this study, the catastrophe theory, principal component analysis (PCA), and multivariate statistics are integrated to establish a situation recognition model for a navigational environment with the aim of performing a quantitative analysis of the situation of this environment via the extraction and classification of its key influencing factors; in this model, the natural environment and traffic environment are considered to be two control variables. The Three Gorges Reservoir area of the Yangtze River is considered as an example, and six critical factors, i.e., the visibility, wind, current velocity, route intersection, channel dimension, and traffic flow, are classified into two principal components: the natural environment and traffic environment. These two components are assumed to have the greatest influence on the navigation risk. Then, the cusp catastrophe model is employed to identify the safety situation of the regional navigational environment in the Three Gorges Reservoir area. The simulation results indicate that the situation of the navigational environment of this area is gradually worsening from downstream to upstream. PMID:27391057

Use of Cusp Catastrophe for Risk Analysis of Navigational Environment: A Case Study of Three Gorges Reservoir Area.

PubMed

Jiang, Dan; Hao, Guozhu; Huang, Liwen; Zhang, Dan

2016-01-01

A water traffic system is a huge, nonlinear, complex system, and its stability is affected by various factors. Water traffic accidents can be considered to be a kind of mutation of a water traffic system caused by the coupling of multiple navigational environment factors. In this study, the catastrophe theory, principal component analysis (PCA), and multivariate statistics are integrated to establish a situation recognition model for a navigational environment with the aim of performing a quantitative analysis of the situation of this environment via the extraction and classification of its key influencing factors; in this model, the natural environment and traffic environment are considered to be two control variables. The Three Gorges Reservoir area of the Yangtze River is considered as an example, and six critical factors, i.e., the visibility, wind, current velocity, route intersection, channel dimension, and traffic flow, are classified into two principal components: the natural environment and traffic environment. These two components are assumed to have the greatest influence on the navigation risk. Then, the cusp catastrophe model is employed to identify the safety situation of the regional navigational environment in the Three Gorges Reservoir area. The simulation results indicate that the situation of the navigational environment of this area is gradually worsening from downstream to upstream.

Navier-Stokes Computations With One-Equation Turbulence Model for Flows Along Concave Wall Surfaces

NASA Technical Reports Server (NTRS)

Wang, Chi R.

2005-01-01

This report presents the use of a time-marching three-dimensional compressible Navier-Stokes equation numerical solver with a one-equation turbulence model to simulate the flow fields developed along concave wall surfaces without and with a downstream extension flat wall surface. The 3-D Navier- Stokes numerical solver came from the NASA Glenn-HT code. The one-equation turbulence model was derived from the Spalart and Allmaras model. The computational approach was first calibrated with the computations of the velocity and Reynolds shear stress profiles of a steady flat plate boundary layer flow. The computational approach was then used to simulate developing boundary layer flows along concave wall surfaces without and with a downstream extension wall. The author investigated the computational results of surface friction factors, near surface velocity components, near wall temperatures, and a turbulent shear stress component in terms of turbulence modeling, computational mesh configurations, inlet turbulence level, and time iteration step. The computational results were compared with existing measurements of skin friction factors, velocity components, and shear stresses of the developing boundary layer flows. With a fine computational mesh and a one-equation model, the computational approach could predict accurately the skin friction factors, near surface velocity and temperature, and shear stress within the flows. The computed velocity components and shear stresses also showed the vortices effect on the velocity variations over a concave wall. The computed eddy viscosities at the near wall locations were also compared with the results from a two equation turbulence modeling technique. The inlet turbulence length scale was found to have little effect on the eddy viscosities at locations near the concave wall surface. The eddy viscosities, from the one-equation and two-equation modeling, were comparable at most stream-wise stations. The present one-equation turbulence model is an effective approach for turbulence modeling in the near solid wall surface region of flow over a concave wall.

Deciphering structural and temporal interplays during the architectural development of mango trees.

PubMed

Dambreville, Anaëlle; Lauri, Pierre-Éric; Trottier, Catherine; Guédon, Yann; Normand, Frédéric

2013-05-01

Plant architecture is commonly defined by the adjacency of organs within the structure and their properties. Few studies consider the effect of endogenous temporal factors, namely phenological factors, on the establishment of plant architecture. This study hypothesized that, in addition to the effect of environmental factors, the observed plant architecture results from both endogenous structural and temporal components, and their interplays. Mango tree, which is characterized by strong phenological asynchronisms within and between trees and by repeated vegetative and reproductive flushes during a growing cycle, was chosen as a plant model. During two consecutive growing cycles, this study described vegetative and reproductive development of 20 trees submitted to the same environmental conditions. Four mango cultivars were considered to assess possible cultivar-specific patterns. Integrative vegetative and reproductive development models incorporating generalized linear models as components were built. These models described the occurrence, intensity, and timing of vegetative and reproductive development at the growth unit scale. This study showed significant interplays between structural and temporal components of plant architectural development at two temporal scales. Within a growing cycle, earliness of bud burst was highly and positively related to earliness of vegetative development and flowering. Between growing cycles, flowering growth units delayed vegetative development compared to growth units that did not flower. These interplays explained how vegetative and reproductive phenological asynchronisms within and between trees were generated and maintained. It is suggested that causation networks involving structural and temporal components may give rise to contrasted tree architectures.

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components, part 2

NASA Technical Reports Server (NTRS)

1991-01-01

The technical effort and computer code enhancements performed during the sixth year of the Probabilistic Structural Analysis Methods program are summarized. Various capabilities are described to probabilistically combine structural response and structural resistance to compute component reliability. A library of structural resistance models is implemented in the Numerical Evaluations of Stochastic Structures Under Stress (NESSUS) code that included fatigue, fracture, creep, multi-factor interaction, and other important effects. In addition, a user interface was developed for user-defined resistance models. An accurate and efficient reliability method was developed and was successfully implemented in the NESSUS code to compute component reliability based on user-selected response and resistance models. A risk module was developed to compute component risk with respect to cost, performance, or user-defined criteria. The new component risk assessment capabilities were validated and demonstrated using several examples. Various supporting methodologies were also developed in support of component risk assessment.

A Spatial Poisson Hurdle Model for Exploring Geographic Variation in Emergency Department Visits

PubMed Central

Neelon, Brian; Ghosh, Pulak; Loebs, Patrick F.

2012-01-01

Summary We develop a spatial Poisson hurdle model to explore geographic variation in emergency department (ED) visits while accounting for zero inflation. The model consists of two components: a Bernoulli component that models the probability of any ED use (i.e., at least one ED visit per year), and a truncated Poisson component that models the number of ED visits given use. Together, these components address both the abundance of zeros and the right-skewed nature of the nonzero counts. The model has a hierarchical structure that incorporates patient- and area-level covariates, as well as spatially correlated random effects for each areal unit. Because regions with high rates of ED use are likely to have high expected counts among users, we model the spatial random effects via a bivariate conditionally autoregressive (CAR) prior, which introduces dependence between the components and provides spatial smoothing and sharing of information across neighboring regions. Using a simulation study, we show that modeling the between-component correlation reduces bias in parameter estimates. We adopt a Bayesian estimation approach, and the model can be fit using standard Bayesian software. We apply the model to a study of patient and neighborhood factors influencing emergency department use in Durham County, North Carolina. PMID:23543242

Psychological Empowerment Among Urban Youth: Measurement Model and Associations with Youth Outcomes

PubMed Central

Eisman, Andria B.; Zimmerman, Marc A.; Kruger, Daniel; Reischl, Thomas M.; Miller, Alison L.; Franzen, Susan P.; Morrel-Samuels, Susan

2016-01-01

Empowerment-based strategies have become widely used method to address health inequities and promote social change. Few researchers, however, have tested theoretical models of empowerment, including multidimensional, higher-order models. We test empirically a multidimensional, higher-order model of psychological empowerment (PE), guided by Zimmerman’s (1995) conceptual framework including three components of PE: intrapersonal, interactional and behavioral. We also investigate if PE is associated with positive and negative outcomes among youth. The sample included 367 middle school youth aged 11–16 (M = 12.71; SD = 0.91); 60% female, 32% (n =117) white youth, 46% (n = 170) African-American youth, and 22% (n = 80) identifying as mixed race, Asian-American, Latino, Native American or other ethnic/racial group; schools reported 61–75% free/reduced lunch students. Our results indicated that each of the latent factors for the three PE components demonstrate a good fit with the data. Our results also indicated that these components loaded on to a higher-order PE factor (X2=32.68, df: 22, p=0.07; RMSEA: 0.04, 95% CI: 0.00, 0.06; CFI: 0.99). We found that the second order PE factor was negatively associated with aggressive behavior and positively associated with prosocial engagement. Our results suggest that empowerment-focused programs would benefit from incorporating components addressing how youth think about themselves in relation to their social contexts (intrapersonal), understanding social and material resources needed to achieve specific goals (interactional) and actions taken to influence outcomes (behavioral). Our results also suggest that integrating the three components and promoting PE may help increase likelihood of positive behaviors (e.g., prosocial involvement); we did not find an association between PE and aggressive behavior. Implications and future directions for empowerment research are discussed. PMID:27709632

Evaluation of the Use of Zero-Augmented Regression Techniques to Model Incidence of Campylobacter Infections in FoodNet.

PubMed

Tremblay, Marlène; Crim, Stacy M; Cole, Dana J; Hoekstra, Robert M; Henao, Olga L; Döpfer, Dörte

2017-10-01

The Foodborne Diseases Active Surveillance Network (FoodNet) is currently using a negative binomial (NB) regression model to estimate temporal changes in the incidence of Campylobacter infection. FoodNet active surveillance in 483 counties collected data on 40,212 Campylobacter cases between years 2004 and 2011. We explored models that disaggregated these data to allow us to account for demographic, geographic, and seasonal factors when examining changes in incidence of Campylobacter infection. We hypothesized that modeling structural zeros and including demographic variables would increase the fit of FoodNet's Campylobacter incidence regression models. Five different models were compared: NB without demographic covariates, NB with demographic covariates, hurdle NB with covariates in the count component only, hurdle NB with covariates in both zero and count components, and zero-inflated NB with covariates in the count component only. Of the models evaluated, the nonzero-augmented NB model with demographic variables provided the best fit. Results suggest that even though zero inflation was not present at this level, individualizing the level of aggregation and using different model structures and predictors per site might be required to correctly distinguish between structural and observational zeros and account for risk factors that vary geographically.

12 CFR Appendix B to Part 3 - Risk-Based Capital Guidelines; Market Risk Adjustment

Code of Federal Regulations, 2011 CFR

2011-01-01

... management systems at least annually. (c) Market risk factors. The bank's internal model must use risk factors sufficient to measure the market risk inherent in all covered positions. The risk factors must... risk weighting factor indicated in Table 2 of this appendix. The specific risk capital charge component...

An Interpretation of the Laminar-Turbulent Transition Startup against the Consideration of the Transverse Viscosity Factor

NASA Astrophysics Data System (ADS)

Kolodezhnov, V. N.

2018-03-01

This paper proposes a rheological model of a fluid having the Newtonian model applicability limit and a potential for further “addition” of the transverse viscosity factor. The dynamic equations for a fluid that has such rheological model are discussed, the analysis of which demonstrates the possibility of “generating” the cross stream velocity components. The transition to the dimensionless notation introduces four dimensionless complexes of local characterization for the transition conditions in the neighborhood of the flow region point in question. Based on such dimensionless complexes and using the known experimental data, the empiric conditions of “generating” the cross stream velocity components and starting the laminar-turbulent transition are proposed.

Body composition analysis: Cellular level modeling of body component ratios.

PubMed

Wang, Z; Heymsfield, S B; Pi-Sunyer, F X; Gallagher, D; Pierson, R N

2008-01-01

During the past two decades, a major outgrowth of efforts by our research group at St. Luke's-Roosevelt Hospital is the development of body composition models that include cellular level models, models based on body component ratios, total body potassium models, multi-component models, and resting energy expenditure-body composition models. This review summarizes these models with emphasis on component ratios that we believe are fundamental to understanding human body composition during growth and development and in response to disease and treatments. In-vivo measurements reveal that in healthy adults some component ratios show minimal variability and are relatively 'stable', for example total body water/fat-free mass and fat-free mass density. These ratios can be effectively applied for developing body composition methods. In contrast, other ratios, such as total body potassium/fat-free mass, are highly variable in vivo and therefore are less useful for developing body composition models. In order to understand the mechanisms governing the variability of these component ratios, we have developed eight cellular level ratio models and from them we derived simplified models that share as a major determining factor the ratio of extracellular to intracellular water ratio (E/I). The E/I value varies widely among adults. Model analysis reveals that the magnitude and variability of each body component ratio can be predicted by correlating the cellular level model with the E/I value. Our approach thus provides new insights into and improved understanding of body composition ratios in adults.

Pattern classification using an olfactory model with PCA feature selection in electronic noses: study and application.

PubMed

Fu, Jun; Huang, Canqin; Xing, Jianguo; Zheng, Junbao

2012-01-01

Biologically-inspired models and algorithms are considered as promising sensor array signal processing methods for electronic noses. Feature selection is one of the most important issues for developing robust pattern recognition models in machine learning. This paper describes an investigation into the classification performance of a bionic olfactory model with the increase of the dimensions of input feature vector (outer factor) as well as its parallel channels (inner factor). The principal component analysis technique was applied for feature selection and dimension reduction. Two data sets of three classes of wine derived from different cultivars and five classes of green tea derived from five different provinces of China were used for experiments. In the former case the results showed that the average correct classification rate increased as more principal components were put in to feature vector. In the latter case the results showed that sufficient parallel channels should be reserved in the model to avoid pattern space crowding. We concluded that 6~8 channels of the model with principal component feature vector values of at least 90% cumulative variance is adequate for a classification task of 3~5 pattern classes considering the trade-off between time consumption and classification rate.

On the dimensionality of the stress-related growth scale: one, three, or seven factors?

PubMed

Roesch, Scott C; Rowley, Anthony A; Vaughn, Allison A

2004-06-01

We examined the factorial validity and dimensionality of the Stress-Related Growth Scale (SRGS; Park, Cohen, & Murch, 1996) using a large multiethnic sample (n = 1,070). Exploratory and confirmatory factor analyses suggested that a multidimensional representation of the SRGS fit better than a unidimensional representation. Specifically, we cross-validated both a 3-factor model and a 7-factor model using confirmatory factor analysis and were shown to be invariant across gender and ethnic groups. The 3-factor model was represented by global dimensions of growth that included rational/mature thinking, affective/emotional growth, and religious/spiritual growth. We replicated the 7-factor model of Armeli, Gunthert, and Cohen (2001) and it represented more specific components of growth such as Self-Understanding and Treatment of Others. However, some factors of the 7-factor model had questionable internal consistency and were strongly intercorrelated, suggesting redundancy. The findings support the notion that the factor structure of both the original 1-factor and revised 7-factor models are unstable and that the 3-factor model developed in this research has more reliable psychometric properties and structure.

SU-F-J-138: An Extension of PCA-Based Respiratory Deformation Modeling Via Multi-Linear Decomposition

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

Iliopoulos, AS; Sun, X; Pitsianis, N

Purpose: To address and lift the limited degree of freedom (DoF) of globally bilinear motion components such as those based on principal components analysis (PCA), for encoding and modeling volumetric deformation motion. Methods: We provide a systematic approach to obtaining a multi-linear decomposition (MLD) and associated motion model from deformation vector field (DVF) data. We had previously introduced MLD for capturing multi-way relationships between DVF variables, without being restricted by the bilinear component format of PCA-based models. PCA-based modeling is commonly used for encoding patient-specific deformation as per planning 4D-CT images, and aiding on-board motion estimation during radiotherapy. However, themore » bilinear space-time decomposition inherently limits the DoF of such models by the small number of respiratory phases. While this limit is not reached in model studies using analytical or digital phantoms with low-rank motion, it compromises modeling power in the presence of relative motion, asymmetries and hysteresis, etc, which are often observed in patient data. Specifically, a low-DoF model will spuriously couple incoherent motion components, compromising its adaptability to on-board deformation changes. By the multi-linear format of extracted motion components, MLD-based models can encode higher-DoF deformation structure. Results: We conduct mathematical and experimental comparisons between PCA- and MLD-based models. A set of temporally-sampled analytical trajectories provides a synthetic, high-rank DVF; trajectories correspond to respiratory and cardiac motion factors, including different relative frequencies and spatial variations. Additionally, a digital XCAT phantom is used to simulate a lung lesion deforming incoherently with respect to the body, which adheres to a simple respiratory trend. In both cases, coupling of incoherent motion components due to a low model DoF is clearly demonstrated. Conclusion: Multi-linear decomposition can enable decoupling of distinct motion factors in high-rank DVF measurements. This may improve motion model expressiveness and adaptability to on-board deformation, aiding model-based image reconstruction for target verification. NIH Grant No. R01-184173.« less

77 FR 48192 - Self-Regulatory Organizations; Chicago Mercantile Exchange, Inc.; Notice of Filing of Proposed...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-13

... Liquidity Factor of Its Credit Default Swap Margin Methodology August 7, 2012. Pursuant to Section 19(b)(1... model. The liquidity margin component of the CME CDS margin model is designed to capture the risk... CDS Clearing Member. The current methodology for the liquidity factor is a function of a portfolio's...

Development of Writing: Key Components of Written Language

ERIC Educational Resources Information Center

Kantor, Patricia Thatcher

2012-01-01

This study utilized confirmatory factor analyses and latent change score analyses to model individual and developmental differences in a longitudinal study of children's writing. Participants were 158 children who completed a writing sample each year from 1st through 4th grade. At all four time points, a four-factor model of writing provided…

Sufficient Forecasting Using Factor Models

PubMed Central

Fan, Jianqing; Xue, Lingzhou; Yao, Jiawei

2017-01-01

We consider forecasting a single time series when there is a large number of predictors and a possible nonlinear effect. The dimensionality was first reduced via a high-dimensional (approximate) factor model implemented by the principal component analysis. Using the extracted factors, we develop a novel forecasting method called the sufficient forecasting, which provides a set of sufficient predictive indices, inferred from high-dimensional predictors, to deliver additional predictive power. The projected principal component analysis will be employed to enhance the accuracy of inferred factors when a semi-parametric (approximate) factor model is assumed. Our method is also applicable to cross-sectional sufficient regression using extracted factors. The connection between the sufficient forecasting and the deep learning architecture is explicitly stated. The sufficient forecasting correctly estimates projection indices of the underlying factors even in the presence of a nonparametric forecasting function. The proposed method extends the sufficient dimension reduction to high-dimensional regimes by condensing the cross-sectional information through factor models. We derive asymptotic properties for the estimate of the central subspace spanned by these projection directions as well as the estimates of the sufficient predictive indices. We further show that the natural method of running multiple regression of target on estimated factors yields a linear estimate that actually falls into this central subspace. Our method and theory allow the number of predictors to be larger than the number of observations. We finally demonstrate that the sufficient forecasting improves upon the linear forecasting in both simulation studies and an empirical study of forecasting macroeconomic variables. PMID:29731537

A Study on Components of Internal Control-Based Administrative System in Secondary Schools

ERIC Educational Resources Information Center

Montri, Paitoon; Sirisuth, Chaiyuth; Lammana, Preeda

2015-01-01

The aim of this study was to study the components of the internal control-based administrative system in secondary schools, and make a Confirmatory Factor Analysis (CFA) to confirm the goodness of fit of empirical data and component model that resulted from the CFA. The study consisted of three steps: 1) studying of principles, ideas, and theories…

Application of the QSPR approach to the boiling points of azeotropes.

PubMed

Katritzky, Alan R; Stoyanova-Slavova, Iva B; Tämm, Kaido; Tamm, Tarmo; Karelson, Mati

2011-04-21

CODESSA Pro derivative descriptors were calculated for a data set of 426 azeotropic mixtures by the centroid approximation and the weighted-contribution-factor approximation. The two approximations produced almost identical four-descriptor QSPR models relating the structural characteristic of the individual components of azeotropes to the azeotropic boiling points. These models were supported by internal and external validations. The descriptors contributing to the QSPR models are directly related to the three components of the enthalpy (heat) of vaporization.

From prediction error to incentive salience: mesolimbic computation of reward motivation.

PubMed

Berridge, Kent C

2012-04-01

Reward contains separable psychological components of learning, incentive motivation and pleasure. Most computational models have focused only on the learning component of reward, but the motivational component is equally important in reward circuitry, and even more directly controls behavior. Modeling the motivational component requires recognition of additional control factors besides learning. Here I discuss how mesocorticolimbic mechanisms generate the motivation component of incentive salience. Incentive salience takes Pavlovian learning and memory as one input and as an equally important input takes neurobiological state factors (e.g. drug states, appetite states, satiety states) that can vary independently of learning. Neurobiological state changes can produce unlearned fluctuations or even reversals in the ability of a previously learned reward cue to trigger motivation. Such fluctuations in cue-triggered motivation can dramatically depart from all previously learned values about the associated reward outcome. Thus, one consequence of the difference between incentive salience and learning can be to decouple cue-triggered motivation of the moment from previously learned values of how good the associated reward has been in the past. Another consequence can be to produce irrationally strong motivation urges that are not justified by any memories of previous reward values (and without distorting associative predictions of future reward value). Such irrationally strong motivation may be especially problematic in addiction. To understand these phenomena, future models of mesocorticolimbic reward function should address the neurobiological state factors that participate to control generation of incentive salience. © 2012 The Author. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

The Relationship between the Three Components of Commitment and Employee Performance in China.

ERIC Educational Resources Information Center

Chen, Zhen Xiong; Francesco, Anne Marie

2003-01-01

A three-component organizational commitment model was tested with 253 Chinese supervisor/supervisee dyads. Confirmatory factor analyses indicated that affective commitment (AC) related positively to in-role performance and organizational citizenship behavior (OCB); continuance commitment correlated negatively with OCB. Normative commitment…

Modeling soil respiration and variations of source components using a multi-factor global climate change experiment

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

Chen, Xiongwen; Post, Wilfred M; Norby, Richard J

2011-01-01

Soil respiration is an important component of the global carbon cycle and is highly responsive to changes in soil temperature and moisture. Accurate prediction of soil respiration and its changes under future climatic conditions requires a clear understanding of the processes involved. In spite of this, most current empirical soil respiration models incorporate just few of the underlying mechanisms that may influence its response. In this study, a new partial process-based component model built on source components of soil respiration was tested using data collected from a multi-factor climate change experiment that manipulates CO2 concentrations, temperature and precipitation. These resultsmore » were then compared to results generated using several other established models. The component model we tested performed well across different treatments of global climate change. In contrast, some other models, which worked well predicting ambient environmental conditions, were unable to predict the changes under different climate change treatments. Based on the component model, the relative proportions of heterotrophic respiration (Rh) in the total soil respiration at different treatments varied from 0.33 to 0.85. There is a significant increase in the proportion of Rh under the elevated atmospheric CO2 concentration in comparison ambient conditions. The dry treatment resulted in higher proportion of Rh at elevated CO2 and ambient T than under elevated CO2 and elevated T. Also, the ratios between root growth and root maintenance respiration varied across different treatments. Neither increased temperature nor elevated atmospheric CO2 changed Q10 values significantly, while the average Q10 value at wet sites was significantly higher than it at dry sites. There was a higher possibility of increased soil respiration under drying relative to wetting conditions across all treatments based on monthly data, indicating that soil respiration may also be related to soil moisture at previous time periods. Our results reveal that the extent, time delay and contribution of different source components need to be included into mechanistic/processes-based soil respiration models at corresponding scale.« less

Factors Affecting Study-Related Burnout among Finnish University Students: Teaching-Learning Environment, Achievement Motivation and the Meaning of Life

ERIC Educational Resources Information Center

Meriläinen, Matti

2014-01-01

This study of a large sample (n = 3035) examined relationships between study-related burnout and components of the teaching-learning environment, achievement motivation and the perceived meaning of life. The overall model, tested with structural equation modelling, revealed that the factor of the teaching-learning environment correlated with both…

Factors that Influence the Perceived Advantages and Relevance of Facebook as a Learning Tool: An Extension of the UTAUT

ERIC Educational Resources Information Center

Escobar-Rodríguez, Tomás; Carvajal-Trujillo, Elena; Monge-Lozano, Pedro

2014-01-01

Social media technologies are becoming a fundamental component of education. This study extends the Unified Theory of Acceptance and Use of Technology (UTAUT) to identify factors that influence the perceived advantages and relevance of Facebook as a learning tool. The proposed model is based on previous models of UTAUT. Constructs from previous…

Examining the Effects of Non-Cognitive Factors on Mathematics Achievement across National Groups: USA, Germany, Japan, and Korea

ERIC Educational Resources Information Center

Walker, Soung Hwa

2017-01-01

Since there is limited research on the applicability of the Theory of Planned Behavior (TPB) model in educational contexts, the current cross-national comparison study aimed to investigate how non-cognitive factors, specifically, the TPB model components, affect students' math outcomes in USA and their peers in three other countries, Germany,…

Designers' models of the human-computer interface

NASA Technical Reports Server (NTRS)

Gillan, Douglas J.; Breedin, Sarah D.

1993-01-01

Understanding design models of the human-computer interface (HCI) may produce two types of benefits. First, interface development often requires input from two different types of experts: human factors specialists and software developers. Given the differences in their backgrounds and roles, human factors specialists and software developers may have different cognitive models of the HCI. Yet, they have to communicate about the interface as part of the design process. If they have different models, their interactions are likely to involve a certain amount of miscommunication. Second, the design process in general is likely to be guided by designers' cognitive models of the HCI, as well as by their knowledge of the user, tasks, and system. Designers do not start with a blank slate; rather they begin with a general model of the object they are designing. The author's approach to a design model of the HCI was to have three groups make judgments of categorical similarity about the components of an interface: human factors specialists with HCI design experience, software developers with HCI design experience, and a baseline group of computer users with no experience in HCI design. The components of the user interface included both display components such as windows, text, and graphics, and user interaction concepts, such as command language, editing, and help. The judgments of the three groups were analyzed using hierarchical cluster analysis and Pathfinder. These methods indicated, respectively, how the groups categorized the concepts, and network representations of the concepts for each group. The Pathfinder analysis provides greater information about local, pairwise relations among concepts, whereas the cluster analysis shows global, categorical relations to a greater extent.

Analytic model for academic research productivity having factors, interactions and implications

PubMed Central

2011-01-01

Financial support is dear in academia and will tighten further. How can the research mission be accomplished within new restraints? A model is presented for evaluating source components of academic research productivity. It comprises six factors: funding; investigator quality; efficiency of the research institution; the research mix of novelty, incremental advancement, and confirmatory studies; analytic accuracy; and passion. Their interactions produce output and patterned influences between factors. Strategies for optimizing output are enabled. PMID:22130145

Hot Dust in Panchromatic SED Fitting: Identification of Active Galactic Nuclei and Improved Galaxy Properties

NASA Astrophysics Data System (ADS)

Leja, Joel; Johnson, Benjamin D.; Conroy, Charlie; van Dokkum, Pieter

2018-02-01

Forward modeling of the full galaxy SED is a powerful technique, providing self-consistent constraints on stellar ages, dust properties, and metallicities. However, the accuracy of these results is contingent on the accuracy of the model. One significant source of uncertainty is the contribution of obscured AGN, as they are relatively common and can produce substantial mid-IR (MIR) emission. Here we include emission from dusty AGN torii in the Prospector SED-fitting framework, and fit the UV–IR broadband photometry of 129 nearby galaxies. We find that 10% of the fitted galaxies host an AGN contributing >10% of the observed galaxy MIR luminosity. We demonstrate the necessity of this AGN component in the following ways. First, we compare observed spectral features to spectral features predicted from our model fit to the photometry. We find that the AGN component greatly improves predictions for observed Hα and Hβ luminosities, as well as mid-infrared Akari and Spitzer/IRS spectra. Second, we show that inclusion of the AGN component changes stellar ages and SFRs by up to a factor of 10, and dust attenuations by up to a factor of 2.5. Finally, we show that the strength of our model AGN component correlates with independent AGN indicators, suggesting that these galaxies truly host AGN. Notably, only 46% of the SED-detected AGN would be detected with a simple MIR color selection. Based on these results, we conclude that SED models which fit MIR data without AGN components are vulnerable to substantial bias in their derived parameters.

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors.

PubMed

Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

2007-01-01

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus.

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors

PubMed Central

Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

2007-01-01

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus. PMID:18466597

PARAFAC Modeling of Irradiation- and Oxidation-Induced Changes in Fluorescent Dissolved Organic Matter Extracted from Poultry Litter.

PubMed

Mangalgiri, Kiranmayi P; Timko, Stephen A; Gonsior, Michael; Blaney, Lee

2017-07-18

Parallel factor analysis (PARAFAC) applied to fluorescence excitation emission matrices (EEMs) allows quantitative assessment of the composition of fluorescent dissolved organic matter (DOM). In this study, we fit a four-component EEM-PARAFAC model to characterize DOM extracted from poultry litter. The data set included fluorescence EEMs from 291 untreated, irradiated (253.7 nm, 310-410 nm), and oxidized (UV-H 2 O 2 , ozone) poultry litter extracts. The four components were identified as microbial humic-, terrestrial humic-, tyrosine-, and tryptophan-like fluorescent signatures. The Tucker's congruence coefficients for components from the global (i.e., aggregated sample set) model and local (i.e., single poultry litter source) models were greater than 0.99, suggesting that the global EEM-PARAFAC model may be suitable to study poultry litter DOM from individual sources. In general, the transformation trends of the four fluorescence components were comparable for all poultry litter sources tested. For irradiation at 253.7 nm, ozonation, and UV-H 2 O 2 advanced oxidation, transformation of the humic-like components was slower than that of the tryptophan-like component. The opposite trend was observed for irradiation at 310-410 nm, due to differences in UV absorbance properties of components. Compared to the other EEM-PARAFAC components, the tyrosine-like component was fairly recalcitrant in irradiation and oxidation processes. This novel application of EEM-PARAFAC modeling provides insight into the composition and fate of agricultural DOM in natural and engineered systems.

Genetic and environmental influences on female sexual orientation, childhood gender typicality and adult gender identity.

PubMed

Burri, Andrea; Cherkas, Lynn; Spector, Timothy; Rahman, Qazi

2011-01-01

Human sexual orientation is influenced by genetic and non-shared environmental factors as are two important psychological correlates--childhood gender typicality (CGT) and adult gender identity (AGI). However, researchers have been unable to resolve the genetic and non-genetic components that contribute to the covariation between these traits, particularly in women. Here we performed a multivariate genetic analysis in a large sample of British female twins (N = 4,426) who completed a questionnaire assessing sexual attraction, CGT and AGI. Univariate genetic models indicated modest genetic influences on sexual attraction (25%), AGI (11%) and CGT (31%). For the multivariate analyses, a common pathway model best fitted the data. This indicated that a single latent variable influenced by a genetic component and common non-shared environmental component explained the association between the three traits but there was substantial measurement error. These findings highlight common developmental factors affecting differences in sexual orientation.

The Structure of Working Memory in Young Children and Its Relation to Intelligence

PubMed Central

Gray, Shelley; Green, Samuel; Alt, Mary; Hogan, Tiffany P.; Kuo, Trudy; Brinkley, Shara; Cowan, Nelson

2016-01-01

This study investigated the structure of working memory in young school-age children by testing the fit of three competing theoretical models using a wide variety of tasks. The best fitting models were then used to assess the relationship between working memory and nonverbal measures of fluid reasoning (Gf) and visual processing (Gv) intelligence. One hundred sixty-eight English-speaking 7–9 year olds with typical development, from three states, participated. Results showed that Cowan’s three-factor embedded processes model fit the data slightly better than Baddeley and Hitch’s (1974) three-factor model (specified according to Baddeley, 1986) and decisively better than Baddeley’s (2000) four-factor model that included an episodic buffer. The focus of attention factor in Cowan’s model was a significant predictor of Gf and Gv. The results suggest that the focus of attention, rather than storage, drives the relationship between working memory, Gf, and Gv in young school-age children. Our results do not rule out the Baddeley and Hitch model, but they place constraints on both it and Cowan’s model. A common attentional component is needed for feature binding, running digit span, and visual short-term memory tasks; phonological storage is separate, as is a component of central executive processing involved in task manipulation. The results contribute to a zeitgeist in which working memory models are coming together on common ground (cf. Cowan, Saults, & Blume, 2014; Hu, Allen, Baddeley, & Hitch, 2016). PMID:27990060

The Factor Structure of the Beck Depression Inventory-II: An Evaluation

ERIC Educational Resources Information Center

Vanheule, Stijn; Desmet, Mattias; Groenvynck, Hans; Rosseel, Yves; Fontaine, Johnny

2008-01-01

The Beck Depression Inventory-II (BDI-II) is a frequently used scale for measuring depressive severity. BDI-II data (404 clinical; 695 nonclinical adults) were analyzed by means of confirmatory factor analysis to test whether the factor structure model with a somatic-affective and cognitive component of depression, formulated by Beck and…

[Confirmative study of a French version of the Exercise Dependence Scale-revised with a French population].

PubMed

Allegre, B; Therme, P

2008-10-01

Since the first writings on excessive exercise, there has been an increased interest in exercise dependence. One of the major consequences of this increased interest has been the development of several definitions and measures of exercise dependence. The work of Veale [Does primary exercise dependence really exist? In: Annet J, Cripps B, Steinberg H, editors. Exercise addiction: Motivation for participation in sport and exercise.Leicester, UK: Br Psychol Soc; 1995. p. 1-5.] provides an advance for the definition and measure of exercise dependence. These studies have adapted the DSM-IV criteria for substance dependence to measure exercise dependence. The Exercise Dependence Scale-Revised is based on these diagnostic criteria, which are: tolerance; withdrawal effects; intention effect; lack of control; time; reductions in other activities; continuance. Confirmatory factor analyses of EDS-R provided support to present a measurement model (21 items loaded in seven factors) of EDS-R (Comparative Fit Index=0.97; Root mean Square Error of Approximation=0.05; Tucker-Lewis Index=0.96). The aim of this study was to examine the psychometric properties of a French version of the EDS-R [Factorial validity and psychometric examination of the exercise dependence scale-revised. Meas Phys Educ Exerc Sci 2004;8(4):183-201.] to test the stability of the seven-factor model of the original version with a French population. A total of 516 half-marathoners ranged in age from 17 to 74 years old (Mean age=39.02 years, ET=10.64), with 402 men (77.9%) and 114 women (22.1%) participated in the study. The principal component analysis results in a six-factor structure, which accounts for 68.60% of the total variance. Because principal component analysis presents a six-factor structure differing from the original seven-factor structure, two models were tested, using confirmatory factor analysis. The first model is the seven-factor model of the original version of the EDS-R and the second is the model produced by the principal component analysis. The results of confirmatory factor analysis presented the original model (with a seven-factor structure) as a good model and fit indices were good (X(2)/ddl=2.89, Root Mean Square Error of Approximation (RMSEA)=0.061, Expected Cross Validation Index (ECVI)=1.20, Goodness-of-Fit Index (GFI)=0.92, Comparative Fit Index (CFI)=0.94, Standardized Root Mean Square (SRMS)=0.048). These results showed that the French version of EDS-R has an identical factor structure to the original. Therefore, the French version of EDS-R was an acceptable scale to measure exercise dependence and can be used on a French population.

Towards end-to-end models for investigating the effects of climate and fishing in marine ecosystems

NASA Astrophysics Data System (ADS)

Travers, M.; Shin, Y.-J.; Jennings, S.; Cury, P.

2007-12-01

End-to-end models that represent ecosystem components from primary producers to top predators, linked through trophic interactions and affected by the abiotic environment, are expected to provide valuable tools for assessing the effects of climate change and fishing on ecosystem dynamics. Here, we review the main process-based approaches used for marine ecosystem modelling, focusing on the extent of the food web modelled, the forcing factors considered, the trophic processes represented, as well as the potential use and further development of the models. We consider models of a subset of the food web, models which represent the first attempts to couple low and high trophic levels, integrated models of the whole ecosystem, and size spectrum models. Comparisons within and among these groups of models highlight the preferential use of functional groups at low trophic levels and species at higher trophic levels and the different ways in which the models account for abiotic processes. The model comparisons also highlight the importance of choosing an appropriate spatial dimension for representing organism dynamics. Many of the reviewed models could be extended by adding components and by ensuring that the full life cycles of species components are represented, but end-to-end models should provide full coverage of ecosystem components, the integration of physical and biological processes at different scales and two-way interactions between ecosystem components. We suggest that this is best achieved by coupling models, but there are very few existing cases where the coupling supports true two-way interaction. The advantages of coupling models are that the extent of discretization and representation can be targeted to the part of the food web being considered, making their development time- and cost-effective. Processes such as predation can be coupled to allow the propagation of forcing factors effects up and down the food web. However, there needs to be a stronger focus on enabling two-way interaction, carefully selecting the key functional groups and species, reconciling different time and space scales and the methods of converting between energy, nutrients and mass.

Pattern Classification Using an Olfactory Model with PCA Feature Selection in Electronic Noses: Study and Application

PubMed Central

Fu, Jun; Huang, Canqin; Xing, Jianguo; Zheng, Junbao

2012-01-01

Biologically-inspired models and algorithms are considered as promising sensor array signal processing methods for electronic noses. Feature selection is one of the most important issues for developing robust pattern recognition models in machine learning. This paper describes an investigation into the classification performance of a bionic olfactory model with the increase of the dimensions of input feature vector (outer factor) as well as its parallel channels (inner factor). The principal component analysis technique was applied for feature selection and dimension reduction. Two data sets of three classes of wine derived from different cultivars and five classes of green tea derived from five different provinces of China were used for experiments. In the former case the results showed that the average correct classification rate increased as more principal components were put in to feature vector. In the latter case the results showed that sufficient parallel channels should be reserved in the model to avoid pattern space crowding. We concluded that 6∼8 channels of the model with principal component feature vector values of at least 90% cumulative variance is adequate for a classification task of 3∼5 pattern classes considering the trade-off between time consumption and classification rate. PMID:22736979

Identifying ontogenetic, environmental and individual components of forest tree growth

PubMed Central

Chaubert-Pereira, Florence; Caraglio, Yves; Lavergne, Christian; Guédon, Yann

2009-01-01

Background and Aims This study aimed to identify and characterize the ontogenetic, environmental and individual components of forest tree growth. In the proposed approach, the tree growth data typically correspond to the retrospective measurement of annual shoot characteristics (e.g. length) along the trunk. Methods Dedicated statistical models (semi-Markov switching linear mixed models) were applied to data sets of Corsican pine and sessile oak. In the semi-Markov switching linear mixed models estimated from these data sets, the underlying semi-Markov chain represents both the succession of growth phases and their lengths, while the linear mixed models represent both the influence of climatic factors and the inter-individual heterogeneity within each growth phase. Key Results On the basis of these integrative statistical models, it is shown that growth phases are not only defined by average growth level but also by growth fluctuation amplitudes in response to climatic factors and inter-individual heterogeneity and that the individual tree status within the population may change between phases. Species plasticity affected the response to climatic factors while tree origin, sampling strategy and silvicultural interventions impacted inter-individual heterogeneity. Conclusions The transposition of the proposed integrative statistical modelling approach to cambial growth in relation to climatic factors and the study of the relationship between apical growth and cambial growth constitute the next steps in this research. PMID:19684021

Effects of atmospheric variability on energy utilization and conservation. [Space heating energy demand modeling; Program HEATLOAD

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

Reiter, E.R.; Johnson, G.R.; Somervell, W.L. Jr.

Research conducted between 1 July 1975 and 31 October 1976 is reported. A ''physical-adaptive'' model of the space-conditioning demand for energy and its response to changes in weather regimes was developed. This model includes parameters pertaining to engineering factors of building construction, to weather-related factors, and to socio-economic factors. Preliminary testing of several components of the model on the city of Greeley, Colorado, yielded most encouraging results. Other components, especially those pertaining to socio-economic factors, are still under development. Expansion of model applications to different types of structures and larger regions is presently underway. A CRT-display model for energy demandmore » within the conterminous United States also has passed preliminary tests. A major effort was expended to obtain disaggregated data on energy use from utility companies throughout the United States. The study of atmospheric variability revealed that the 22- to 26-day vacillation in the potential and kinetic energy modes of the Northern Hemisphere is related to the behavior of the planetary long-waves, and that the midwinter dip in zonal available potential energy is reflected in the development of blocking highs. Attempts to classify weather patterns over the eastern and central United States have proceeded satisfactorily to the point where testing of our method for longer time periods appears desirable.« less

Mouse Models for Unraveling the Importance of Diet in Colon Cancer Prevention

PubMed Central

Tammariello, Alexandra E.; Milner, John A.

2010-01-01

Diet and genetics are both considered important risk determinants for colorectal cancer, a leading cause of death worldwide. Several genetically engineered mouse models have been created, including the ApcMin mouse, to aid in the identification of key cancer related processes and to assist with the characterization of environmental factors, including the diet, which influence risk. Current research using these models provides evidence that several bioactive food components can inhibit genetically predisposed colorectal cancer, while others increase risk. Specifically, calorie restriction or increased exposure to n-3 fatty acids, sulforaphane, chafuroside, curcumin, and dibenzoylmethane were reported protective. Total fat, calories and all-trans retinoic acid are associated with an increased risk. Unraveling the importance of specific dietary components in these models is complicated by the basal diet used, the quantity of test components provided, and interactions among food components. Newer models are increasingly available to evaluate fundamental cellular processes, including DNA mismatch repair, immune function and inflammation as markers for colon cancer risk. Unfortunately, these models have been used infrequently to examine the influence of specific dietary components. The enhanced use of these models can shed mechanistic insights about the involvement of specific bioactive food and components and energy as determinants of colon cancer risk. However, the use of available mouse models to exactly represent processes important to human gastrointestinal cancers will remain a continued scientific challenge. PMID:20122631

An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci

PubMed Central

Ju, Jin Hyun; Crystal, Ronald G.

2017-01-01

Genome-wide expression Quantitative Trait Loci (eQTL) studies in humans have provided numerous insights into the genetics of both gene expression and complex diseases. While the majority of eQTL identified in genome-wide analyses impact a single gene, eQTL that impact many genes are particularly valuable for network modeling and disease analysis. To enable the identification of such broad impact eQTL, we introduce CONFETI: Confounding Factor Estimation Through Independent component analysis. CONFETI is designed to address two conflicting issues when searching for broad impact eQTL: the need to account for non-genetic confounding factors that can lower the power of the analysis or produce broad impact eQTL false positives, and the tendency of methods that account for confounding factors to model broad impact eQTL as non-genetic variation. The key advance of the CONFETI framework is the use of Independent Component Analysis (ICA) to identify variation likely caused by broad impact eQTL when constructing the sample covariance matrix used for the random effect in a mixed model. We show that CONFETI has better performance than other mixed model confounding factor methods when considering broad impact eQTL recovery from synthetic data. We also used the CONFETI framework and these same confounding factor methods to identify eQTL that replicate between matched twin pair datasets in the Multiple Tissue Human Expression Resource (MuTHER), the Depression Genes Networks study (DGN), the Netherlands Study of Depression and Anxiety (NESDA), and multiple tissue types in the Genotype-Tissue Expression (GTEx) consortium. These analyses identified both cis-eQTL and trans-eQTL impacting individual genes, and CONFETI had better or comparable performance to other mixed model confounding factor analysis methods when identifying such eQTL. In these analyses, we were able to identify and replicate a few broad impact eQTL although the overall number was small even when applying CONFETI. In light of these results, we discuss the broad impact eQTL that have been previously reported from the analysis of human data and suggest that considerable caution should be exercised when making biological inferences based on these reported eQTL. PMID:28505156

An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci.

PubMed

Ju, Jin Hyun; Shenoy, Sushila A; Crystal, Ronald G; Mezey, Jason G

2017-05-01

Genome-wide expression Quantitative Trait Loci (eQTL) studies in humans have provided numerous insights into the genetics of both gene expression and complex diseases. While the majority of eQTL identified in genome-wide analyses impact a single gene, eQTL that impact many genes are particularly valuable for network modeling and disease analysis. To enable the identification of such broad impact eQTL, we introduce CONFETI: Confounding Factor Estimation Through Independent component analysis. CONFETI is designed to address two conflicting issues when searching for broad impact eQTL: the need to account for non-genetic confounding factors that can lower the power of the analysis or produce broad impact eQTL false positives, and the tendency of methods that account for confounding factors to model broad impact eQTL as non-genetic variation. The key advance of the CONFETI framework is the use of Independent Component Analysis (ICA) to identify variation likely caused by broad impact eQTL when constructing the sample covariance matrix used for the random effect in a mixed model. We show that CONFETI has better performance than other mixed model confounding factor methods when considering broad impact eQTL recovery from synthetic data. We also used the CONFETI framework and these same confounding factor methods to identify eQTL that replicate between matched twin pair datasets in the Multiple Tissue Human Expression Resource (MuTHER), the Depression Genes Networks study (DGN), the Netherlands Study of Depression and Anxiety (NESDA), and multiple tissue types in the Genotype-Tissue Expression (GTEx) consortium. These analyses identified both cis-eQTL and trans-eQTL impacting individual genes, and CONFETI had better or comparable performance to other mixed model confounding factor analysis methods when identifying such eQTL. In these analyses, we were able to identify and replicate a few broad impact eQTL although the overall number was small even when applying CONFETI. In light of these results, we discuss the broad impact eQTL that have been previously reported from the analysis of human data and suggest that considerable caution should be exercised when making biological inferences based on these reported eQTL.

Rapid fingerprinting of spilled petroleum products using fluorescence spectroscopy coupled with parallel factor and principal component analysis.

PubMed

Mirnaghi, Fatemeh S; Soucy, Nicholas; Hollebone, Bruce P; Brown, Carl E

2018-05-19

The characterization of spilled petroleum products in an oil spill is necessary for identifying the spill source, selection of clean-up strategies, and evaluating potential environmental and ecological impacts. Existing standard methods for the chemical characterization of spilled oils are time-consuming due to the lengthy sample preparation for analysis. The main objective of this study is the development of a rapid screening method for the fingerprinting of spilled petroleum products using excitation/emission matrix (EEM) fluorescence spectroscopy, thereby delivering a preliminary evaluation of the petroleum products within hours after a spill. In addition, the developed model can be used for monitoring the changes of aromatic compositions of known spilled oils over time. This study involves establishing a fingerprinting model based on the composition of polycyclic and heterocyclic aromatic hydrocarbons (PAH and HAHs, respectively) of 130 petroleum products at different states of evaporative weathering. The screening model was developed using parallel factor analysis (PARAFAC) of a large EEM dataset. The significant fluorescing components for each sample class were determined. After which, through principal component analysis (PCA), the variation of scores of their modeled factors was discriminated based on the different classes of petroleum products. This model was then validated using gas chromatography-mass spectrometry (GC-MS) analysis. The rapid fingerprinting and the identification of unknown and new spilled oils occurs through matching the spilled product with the products of the developed model. Finally, it was shown that HAH compounds in asphaltene and resins contribute to ≥4-ring PAHs compounds in petroleum products. Copyright © 2018. Published by Elsevier Ltd.

Toward a Multicultural Model of the Stress Process.

ERIC Educational Resources Information Center

Slavin, Lesley A.; And Others

1991-01-01

Attempts to expand Lazarus and Folkman's stress model to include culture-relevant dimensions. Discusses cultural factors that influence each component of the stress model, including types and frequency of events experienced, appraisals of stressfulness of events, appraisals of available coping resources, selection of coping strategies, and…

A multifactor approach to forecasting Romanian gross domestic product (GDP) in the short run.

PubMed

Armeanu, Daniel; Andrei, Jean Vasile; Lache, Leonard; Panait, Mirela

2017-01-01

The purpose of this paper is to investigate the application of a generalized dynamic factor model (GDFM) based on dynamic principal components analysis to forecasting short-term economic growth in Romania. We have used a generalized principal components approach to estimate a dynamic model based on a dataset comprising 86 economic and non-economic variables that are linked to economic output. The model exploits the dynamic correlations between these variables and uses three common components that account for roughly 72% of the information contained in the original space. We show that it is possible to generate reliable forecasts of quarterly real gross domestic product (GDP) using just the common components while also assessing the contribution of the individual variables to the dynamics of real GDP. In order to assess the relative performance of the GDFM to standard models based on principal components analysis, we have also estimated two Stock-Watson (SW) models that were used to perform the same out-of-sample forecasts as the GDFM. The results indicate significantly better performance of the GDFM compared with the competing SW models, which empirically confirms our expectations that the GDFM produces more accurate forecasts when dealing with large datasets.

A multifactor approach to forecasting Romanian gross domestic product (GDP) in the short run

PubMed Central

Armeanu, Daniel; Lache, Leonard; Panait, Mirela

2017-01-01

The purpose of this paper is to investigate the application of a generalized dynamic factor model (GDFM) based on dynamic principal components analysis to forecasting short-term economic growth in Romania. We have used a generalized principal components approach to estimate a dynamic model based on a dataset comprising 86 economic and non-economic variables that are linked to economic output. The model exploits the dynamic correlations between these variables and uses three common components that account for roughly 72% of the information contained in the original space. We show that it is possible to generate reliable forecasts of quarterly real gross domestic product (GDP) using just the common components while also assessing the contribution of the individual variables to the dynamics of real GDP. In order to assess the relative performance of the GDFM to standard models based on principal components analysis, we have also estimated two Stock-Watson (SW) models that were used to perform the same out-of-sample forecasts as the GDFM. The results indicate significantly better performance of the GDFM compared with the competing SW models, which empirically confirms our expectations that the GDFM produces more accurate forecasts when dealing with large datasets. PMID:28742100

Toying with Enzyme Catalysis.

ERIC Educational Resources Information Center

Richards, Debbie

1998-01-01

Describes a set of manipulatives that are used to establish a secure understanding of the concepts related to the environmental factors that affect the activities of enzymes. Includes a description of the model components and procedures for construction of the model. (DDR)

United States Air Force Research Initiation Program for 1987. Volume 1

DTIC Science & Technology

1989-04-01

complexity for analyzing such models depends upon the repair or replace- ment times distributions, the repair policy for damaged components and a...distributions, repair policy for various comDonents and a number of other factors. Problems o interest for such models include the determinations of (a...Thus. some more assumption is needed as to the order in which repair is to be made when more than one component is damaged. We will adopt a policy

Thomson scattering from a three-component plasma.

PubMed

Johnson, W R; Nilsen, J

2014-02-01

A model for a three-component plasma consisting of two distinct ionic species and electrons is developed and applied to study x-ray Thomson scattering. Ions of a specific type are assumed to be identical and are treated in the average-atom approximation. Given the plasma temperature and density, the model predicts mass densities, effective ionic charges, and cell volumes for each ionic type, together with the plasma chemical potential and free-electron density. Additionally, the average-atom treatment of individual ions provides a quantum-mechanical description of bound and continuum electrons. The model is used to obtain parameters needed to determine the dynamic structure factors for x-ray Thomson scattering from a three-component plasma. The contribution from inelastic scattering by free electrons is evaluated in the random-phase approximation. The contribution from inelastic scattering by bound electrons is evaluated using the bound-state and scattering wave functions obtained from the average-atom calculations. Finally, the partial static structure factors for elastic scattering by ions are evaluated using a two-component version of the Ornstein-Zernike equations with hypernetted chain closure, in which electron-ion interactions are accounted for using screened ion-ion interaction potentials. The model is used to predict the x-ray Thomson scattering spectrum from a CH plasma and the resulting spectrum is compared with experimental results obtained by Feltcher et al. [Phys. Plasmas 20, 056316 (2013)].

Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers

PubMed Central

Zoccolotti, Pierluigi; De Luca, Maria; Marinelli, Chiara V.; Spinelli, Donatella

2014-01-01

This study was aimed at predicting individual differences in text reading fluency. The basic proposal included two factors, i.e., the ability to decode letter strings (measured by discrete pseudo-word reading) and integration of the various sub-components involved in reading (measured by Rapid Automatized Naming, RAN). Subsequently, a third factor was added to the model, i.e., naming of discrete digits. In order to use homogeneous measures, all contributing variables considered the entire processing of the item, including pronunciation time. The model, which was based on commonality analysis, was applied to data from a group of 43 typically developing readers (11- to 13-year-olds) and a group of 25 chronologically matched dyslexic children. In typically developing readers, both orthographic decoding and integration of reading sub-components contributed significantly to the overall prediction of text reading fluency. The model prediction was higher (from ca. 37 to 52% of the explained variance) when we included the naming of discrete digits variable, which had a suppressive effect on pseudo-word reading. In the dyslexic readers, the variance explained by the two-factor model was high (69%) and did not change when the third factor was added. The lack of a suppression effect was likely due to the prominent individual differences in poor orthographic decoding of the dyslexic children. Analyses on data from both groups of children were replicated by using patches of colors as stimuli (both in the RAN task and in the discrete naming task) obtaining similar results. We conclude that it is possible to predict much of the variance in text-reading fluency using basic processes, such as orthographic decoding and integration of reading sub-components, even without taking into consideration higher-order linguistic factors such as lexical, semantic and contextual abilities. The approach validity of using proximal vs. distal causes to predict reading fluency is discussed. PMID:25477856

Five-Factor Model of Personality and Organizational Commitment: The Mediating Role of Positive and Negative Affective States

ERIC Educational Resources Information Center

Panaccio, Alexandra; Vandenberghe, Christian

2012-01-01

Using a one-year longitudinal study of four components of organizational commitment (affective, normative, continuance-sacrifices, and continuance-alternatives) on a sample of employees from multiple organizations (N=220), we examined the relationships of employee Big-Five personality traits to employee commitment components, and the mediating…

Optimizing shoot culture media for Rubus germplasm: the effects of NH4+, NO3-, and total nitrogen

USDA-ARS?s Scientific Manuscript database

The nitrogen components of Murashige and Skoog (MS) medium were significant factors for improved growth in our earlier study that modeled the effects of mineral nutrition on growth and development of micropropagated red raspberry(Rubus idaeus L.). In this study, a mixture component design was applie...

Theory-of-mind development influences suggestibility and source monitoring.

PubMed

Bright-Paul, Alexandra; Jarrold, Christopher; Wright, Daniel B

2008-07-01

According to the mental-state reasoning model of suggestibility, 2 components of theory of mind mediate reductions in suggestibility across the preschool years. The authors examined whether theory-of-mind performance may be legitimately separated into 2 components and explored the memory processes underlying the associations between theory of mind and suggestibility, independent of verbal ability. Children 3 to 6 years old completed 6 theory-of-mind tasks and a postevent misinformation procedure. Contrary to the model's prediction, a single latent theory-of-mind factor emerged, suggesting a single-component rather than a dual-component conceptualization of theory-of-mind performance. This factor provided statistical justification for computing a single composite theory-of-mind score. Improvements in theory of mind predicted reductions in suggestibility, independent of verbal ability (Study 1, n = 72). Furthermore, once attribution biases were controlled (Study 2, n = 45), there was also a positive relationship between theory of mind and source memory, but not recognition performance. The findings suggest a substantial, and possibly causal, association between theory-of-mind development and resistance to suggestion, driven specifically by improvements in source monitoring.

Establishment of A431 cell membrane chromatography-RPLC method for screening target components from Radix Caulophylli.

PubMed

Hou, Xiaofang; Wang, Sicen; Hou, Jingjing; He, Langchong

2011-03-01

We describe here an analytical method of A431 cell membrane chromatography (A431/CMC) (CMC, cell membrane chromatography) combined with RPLC for recognition, separation, and identification of target components from traditional Chinese medicines (TCMs) Radix Caulophylli. The A431 cells with high expressed epidermal growth factor receptor (EGFR) were used to prepare the stationary phase in the CMC model. Retention fractions on the A431-CMC model were collected using an automated fraction collection and injection module (FC/I). Each fraction was analyzed by RPLC under the optimized conditions. Gefitinib and erlotinib were used as standard compounds to investigate the suitability and reliability of the A431 cell membrane chromatography-RPLC method prior to screening target component from Radix Caulophylli total alkaloids. The results indicated that caulophine and taspine were the target component acting on the epidermal growth factor receptor. This method could be an efficient way in drug discovery using natural medicinal herbs as a source of novel compounds. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Psychological Empowerment Among Urban Youth: Measurement Model and Associations with Youth Outcomes.

PubMed

Eisman, Andria B; Zimmerman, Marc A; Kruger, Daniel; Reischl, Thomas M; Miller, Alison L; Franzen, Susan P; Morrel-Samuels, Susan

2016-12-01

Empowerment-based strategies have become widely used method to address health inequities and promote social change. Few researchers, however, have tested theoretical models of empowerment, including multidimensional, higher-order models. We test empirically a multidimensional, higher-order model of psychological empowerment (PE), guided by Zimmerman's conceptual framework including three components of PE: intrapersonal, interactional, and behavioral. We also investigate if PE is associated with positive and negative outcomes among youth. The sample included 367 middle school youth aged 11-16 (M = 12.71; SD = 0.91); 60% female, 32% (n = 117) white youth, 46% (n = 170) African-American youth, and 22% (n = 80) identifying as mixed race, Asian-American, Latino, Native American, or other ethnic/racial group; schools reported 61-75% free/reduced lunch students. Our results indicated that each of the latent factors for the three PE components demonstrate a good fit with the data. Our results also indicated that these components loaded on to a higher-order PE factor (X 2  = 32.68; df: 22; p = .07; RMSEA: 0.04; 95% CI: .00, .06; CFI: 0.99). We found that the second-order PE factor was negatively associated with aggressive behavior and positively associated with prosocial engagement. Our results suggest that empowerment-focused programs would benefit from incorporating components addressing how youth think about themselves in relation to their social contexts (intrapersonal), understanding social and material resources needed to achieve specific goals (interactional), and actions taken to influence outcomes (behavioral). Our results also suggest that integrating the three components and promoting PE may help increase likelihood of positive behaviors (e.g., prosocial involvement); we did not find an association between PE and aggressive behavior. Implications and future directions for empowerment research are discussed. © Society for Community Research and Action 2016.

Retinopathy of prematurity: molecular pathology and therapeutic strategies.

PubMed

Mechoulam, Hadas; Pierce, Eric A

2003-01-01

Retinopathy of prematurity (ROP) is an ischemia-induced proliferative retinopathy, which affects premature infants with low birth weight. It is a leading cause of visual impairment and blindness in children, and shares pathophysiological characteristics with other common ocular diseases such as diabetic retinopathy, central vein occlusion, and age-related macular degeneration. Pathologically similar inherited diseases such as Norrie disease suggest a possible genetic component in the susceptibility to ROP. The process of retinal neovascularization in ROP and in animal models of oxygen-induced retinopathy is complex, and involves angiogenic factors, such as vascular endothelial growth factor, and basement membrane components. Potential medical therapies for ROP, including modulators of angiogenic factors, inhibitors of basement membrane changes, endogenous inhibitors such as pigment epithelium derived factor, and anti-inflammatory drugs, have shown efficacy against neovascularization in several animal models. Some of these therapies are in clinical trials now for diabetic retinopathy and age-related macular degeneration, and in the future may prove efficacious for the treatment of ROP.

A model of the pre-assessment learning effects of assessment is operational in an undergraduate clinical context

PubMed Central

2012-01-01

Background No validated model exists to explain the learning effects of assessment, a problem when designing and researching assessment for learning. We recently developed a model explaining the pre-assessment learning effects of summative assessment in a theory teaching context. The challenge now is to validate this model. The purpose of this study was to explore whether the model was operational in a clinical context as a first step in this process. Methods Given the complexity of the model, we adopted a qualitative approach. Data from in-depth interviews with eighteen medical students were subject to content analysis. We utilised a code book developed previously using grounded theory. During analysis, we remained alert to data that might not conform to the coding framework and open to the possibility of deploying inductive coding. Ethical clearance and informed consent were obtained. Results The three components of the model i.e., assessment factors, mechanism factors and learning effects were all evident in the clinical context. Associations between these components could all be explained by the model. Interaction with preceptors was identified as a new subcomponent of assessment factors. The model could explain the interrelationships of the three facets of this subcomponent i.e., regular accountability, personal consequences and emotional valence of the learning environment, with previously described components of the model. Conclusions The model could be utilized to analyse and explain observations in an assessment context different to that from which it was derived. In the clinical setting, the (negative) influence of preceptors on student learning was particularly prominent. In this setting, learning effects resulted not only from the high-stakes nature of summative assessment but also from personal stakes, e.g. for esteem and agency. The results suggest that to influence student learning, consequences should accrue from assessment that are immediate, concrete and substantial. The model could have utility as a planning or diagnostic tool in practice and research settings. PMID:22420839

Integration of Component Knowledge in Penalized-Likelihood Reconstruction with Morphological and Spectral Uncertainties.

PubMed

Stayman, J Webster; Tilley, Steven; Siewerdsen, Jeffrey H

2014-01-01

Previous investigations [1-3] have demonstrated that integrating specific knowledge of the structure and composition of components like surgical implants, devices, and tools into a model-based reconstruction framework can improve image quality and allow for potential exposure reductions in CT. Using device knowledge in practice is complicated by uncertainties in the exact shape of components and their particular material composition. Such unknowns in the morphology and attenuation properties lead to errors in the forward model that limit the utility of component integration. In this work, a methodology is presented to accommodate both uncertainties in shape as well as unknown energy-dependent attenuation properties of the surgical devices. This work leverages the so-called known-component reconstruction (KCR) framework [1] with a generalized deformable registration operator and modifications to accommodate a spectral transfer function in the component model. Moreover, since this framework decomposes the object into separate background anatomy and "known" component factors, a mixed fidelity forward model can be adopted so that measurements associated with projections through the surgical devices can be modeled with much greater accuracy. A deformable KCR (dKCR) approach using the mixed fidelity model is introduced and applied to a flexible wire component with unknown structure and composition. Image quality advantages of dKCR over traditional reconstruction methods are illustrated in cone-beam CT (CBCT) data acquired on a testbench emulating a 3D-guided needle biopsy procedure - i.e., a deformable component (needle) with strong energy-dependent attenuation characteristics (steel) within a complex soft-tissue background.

Developing a suitable model for supplier selection based on supply chain risks: an empirical study from Iranian pharmaceutical companies.

PubMed

Mehralian, Gholamhossein; Rajabzadeh Gatari, Ali; Morakabati, Mohadese; Vatanpour, Hossein

2012-01-01

The supply chain represents the critical link between the development of new product and the market in pharmaceutical industry. Over the years, improvements made in supply chain operations have focused largely on ways to reduce cost and gain efficiencies in scale. In addition, powerful regulatory and market forces have provided new incentives for pharmaceutical firms to basically rethink the way they produce and distribute products, and also to re-imagine the role of the supply chain in driving strategic growth, brand differentiation and economic value in the health continuum. The purpose of this paper is to formulate basic factors involved in risk analysis of pharmaceutical industry, and also determine the effective factors involved in suppliers selection and their priorities. This paper is based on the results of literature review, experts' opinion acquisition, statistical analysis and also using MADM models on data gathered from distributed questionnaires. The model consists of the following steps and components: first factors involved in to supply chain risks are determined. Based on them a framework is considered. According the result of statistical analysis and MADM models the risk factors are formulated. The paper determines the main components and influenceial factors involving in the supply chain risks. Results showed that delivery risk can make an important contribution to mitigate the risk of pharmaceutical industry.

Developing a Suitable Model for Supplier Selection Based on Supply Chain Risks: An Empirical Study from Iranian Pharmaceutical Companies

PubMed Central

Mehralian, Gholamhossein; Rajabzadeh Gatari, Ali; Morakabati, Mohadese; Vatanpour, Hossein

2012-01-01

The supply chain represents the critical link between the development of new product and the market in pharmaceutical industry. Over the years, improvements made in supply chain operations have focused largely on ways to reduce cost and gain efficiencies in scale. In addition, powerful regulatory and market forces have provided new incentives for pharmaceutical firms to basically rethink the way they produce and distribute products, and also to re-imagine the role of the supply chain in driving strategic growth, brand differentiation and economic value in the health continuum. The purpose of this paper is to formulate basic factors involved in risk analysis of pharmaceutical industry, and also determine the effective factors involved in suppliers selection and their priorities. This paper is based on the results of literature review, experts’ opinion acquisition, statistical analysis and also using MADM models on data gathered from distributed questionnaires. The model consists of the following steps and components: first factors involved in to supply chain risks are determined. Based on them a framework is considered. According the result of statistical analysis and MADM models the risk factors are formulated. The paper determines the main components and influenceial factors involving in the supply chain risks. Results showed that delivery risk can make an important contribution to mitigate the risk of pharmaceutical industry. PMID:24250442

bioWidgets: data interaction components for genomics.

PubMed

Fischer, S; Crabtree, J; Brunk, B; Gibson, M; Overton, G C

1999-10-01

The presentation of genomics data in a perspicuous visual format is critical for its rapid interpretation and validation. Relatively few public database developers have the resources to implement sophisticated front-end user interfaces themselves. Accordingly, these developers would benefit from a reusable toolkit of user interface and data visualization components. We have designed the bioWidget toolkit as a set of JavaBean components. It includes a wide array of user interface components and defines an architecture for assembling applications. The toolkit is founded on established software engineering design patterns and principles, including componentry, Model-View-Controller, factored models and schema neutrality. As a proof of concept, we have used the bioWidget toolkit to create three extendible applications: AnnotView, BlastView and AlignView.

Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition

EPA Science Inventory

Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base-flow conditions. Factors that affect instream biological components, based on ...

Heritability of the somatotype components in Biscay families.

PubMed

Rebato, E; Jelenkovic, A; Salces, I

2007-01-01

The anthropometric somatotype is a quantitative description of body shape and composition. Familial studies indicate the existence of a familial resemblance for this phenotype and they suggest a substantial action by genetic factors on this aggregation. The aim of this study is to examine the degree of familial resemblance of the somatotype components and of a factor of shape, in a sample of Biscay nuclear families (Basque Country, Spain). One thousand three hundred and thirty nuclear families were analysed. The anthropometric somatotype components [Carter, J.E.L., Heath, B.H., 1990. Somatotyping. Development and applications. Cambridge University Press, Cambridge, p. 503] were computed. Each component was fitted for the other two through a stepwise multiple regression, and also fitted through the LMS method [Cole, T., 1988. Fitting smoothed centile curves to reference data. J. Roy. Stat. Soc. 151, 385-418] in order to eliminate the age, sex and generation effects. The three raw components were introduced in a PCA from which a shape factor (PC1) was extracted for each generation. The correlations analysis was performed with the SEGPATH package [Province, M.A., Rao, D.C., 1995. General purpose model and computer programme for combined segregation and path analysis (SEGPATH): automatically creating computer from symbolic language model specifications. Genet. Epidemiol. 12, 203-219]. A general model of transmission and nine reduced models were tested. Maximal heritability was estimated with the formula of [Rice, T., Warwick, D.E., Gagnon, J., Bouchard, C., Leon, A.S., Skinner, J.S., Wilmore, J.H., Rao, D.C., 1997. Familial resemblance for body composition measures: the HERITAGE family study. Obes. Res. 5, 557-562]. The correlations were higher between offspring than in parents and offspring and a significant resemblance between mating partners existed. Maximum heritabilities were 55%, 52% and 46% for endomorphy, mesomorphy and ectomorphy, respectively, and 52% for PC1. In conclusion, the somatotype presents a moderate degree of familial aggregation. For the somatotype components, as well as for PC1, the degree of familial resemblance depends on age. The sex only has a significant effect on ectomorphy.

Unsupervised Bayesian linear unmixing of gene expression microarrays.

PubMed

Bazot, Cécile; Dobigeon, Nicolas; Tourneret, Jean-Yves; Zaas, Aimee K; Ginsburg, Geoffrey S; Hero, Alfred O

2013-03-19

This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters. Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here. The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores collected during the study. Using a constrained model allows recovery of all the inflammatory genes in a single factor.

The psychology of doing nothing: forms of decision avoidance result from reason and emotion.

PubMed

Anderson, Christopher J

2003-01-01

Several independent lines of research bear on the question of why individuals avoid decisions by postponing them, failing to act, or accepting the status quo. This review relates findings across several different disciplines and uncovers 4 decision avoidance effects that offer insight into this common but troubling behavior: choice deferral, status quo bias, omission bias, and inaction inertia. These findings are related by common antecedents and consequences in a rational-emotional model of the factors that predispose humans to do nothing. Prominent components of the model include cost-benefit calculations, anticipated regret, and selection difficulty. Other factors affecting decision avoidance through these key components, such as anticipatory negative emotions, decision strategies, counterfactual thinking, and preference uncertainty, are also discussed.

An evaluation of the nursing practice environment and successful change management using the new generation Magnet Model.

PubMed

Grant, Bettyanne; Colello, Sandra; Riehle, Martha; Dende, Denise

2010-04-01

To discuss the new Magnet Model as it relates to the successful implementation of a practice change. There is growing international interest in the Magnet Recognition Programme. The latest generation of the Magnet Model has been designed not only as a road map for organizations seeking to achieve Magnet recognition but also as a framework for nursing practice and research in the future. The Magnet Model was used to identify success factors related to a practice change and to evaluate the nursing practice environment. Even when proposed changes to practice are evidence based and thoughtfully considered, the nurses' work environment must be supportive and empowering in order to yield successful and sustainable implementation of new practice. Success factors for implementation of a practice change can be illuminated by aligning environmental characteristics to the components of the new Magnet Model. The Magnet Model provides an exceptional framework for building an agile and dynamic work force. Thoughtful consideration of the components and inter-relationships represented in the new model can help to both predict and ensure organizational vitality.

Quantum theory for the dynamic structure factor in correlated two-component systems in nonequilibrium: Application to x-ray scattering.

PubMed

Vorberger, J; Chapman, D A

2018-01-01

We present a quantum theory for the dynamic structure factors in nonequilibrium, correlated, two-component systems such as plasmas or warm dense matter. The polarization function, which is needed as the input for the calculation of the structure factors, is calculated in nonequilibrium based on a perturbation expansion in the interaction strength. To make our theory applicable for x-ray scattering, a generalized Chihara decomposition for the total electron structure factor in nonequilibrium is derived. Examples are given and the influence of correlations and exchange on the structure and the x-ray-scattering spectrum are discussed for a model nonequilibrium distribution, as often encountered during laser heating of materials, as well as for two-temperature systems.

Quantum theory for the dynamic structure factor in correlated two-component systems in nonequilibrium: Application to x-ray scattering

NASA Astrophysics Data System (ADS)

Vorberger, J.; Chapman, D. A.

2018-01-01

We present a quantum theory for the dynamic structure factors in nonequilibrium, correlated, two-component systems such as plasmas or warm dense matter. The polarization function, which is needed as the input for the calculation of the structure factors, is calculated in nonequilibrium based on a perturbation expansion in the interaction strength. To make our theory applicable for x-ray scattering, a generalized Chihara decomposition for the total electron structure factor in nonequilibrium is derived. Examples are given and the influence of correlations and exchange on the structure and the x-ray-scattering spectrum are discussed for a model nonequilibrium distribution, as often encountered during laser heating of materials, as well as for two-temperature systems.

The Structure of Intellect, Its Interpretations and Uses.

ERIC Educational Resources Information Center

Meeker, Mary Nacol

Using Guilford's model, the text reviews the structure of the intellect (SOI) and its operations, contents, and products. Those operations and components are further described, including the factors of cognition, memory, evaluation, convergent-production, and divergent-production. For each factor, the figural, symbolic, and semantic dimensions are…

Construction of a Cyber Attack Model for Nuclear Power Plants

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

Varuttamaseni, Athi; Bari, Robert A.; Youngblood, Robert

The consideration of how one compromised digital equipment can impact neighboring equipment is critical to understanding the progression of cyber attacks. The degree of influence that one component may have on another depends on a variety of factors, including the sharing of resources such as network bandwidth or processing power, the level of trust between components, and the inclusion of segmentation devices such as firewalls. The interactions among components via mechanisms that are unique to the digital world are not usually considered in traditional PRA. This means potential sequences of events that may occur during an attack may be missedmore » if one were to only look at conventional accident sequences. This paper presents a method where, starting from the initial attack vector, the progression of a cyber attack can be modeled. The propagation of the attack is modeled by considering certain attributes of the digital components in the system. These attributes determine the potential vulnerability of a component to a class of attack and the capability gained by the attackers once they are in control of the equipment. The use of attributes allows similar components (components with the same set of attributes) to be modeled in the same way, thereby reducing the computing resources required for analysis of large systems.« less

Engineering Breast Cancer Microenvironments and 3D Bioprinting

PubMed Central

Belgodere, Jorge A.; King, Connor T.; Bursavich, Jacob B.; Burow, Matthew E.; Martin, Elizabeth C.; Jung, Jangwook P.

2018-01-01

The extracellular matrix (ECM) is a critical cue to direct tumorigenesis and metastasis. Although two-dimensional (2D) culture models have been widely employed to understand breast cancer microenvironments over the past several decades, the 2D models still exhibit limited success. Overwhelming evidence supports that three dimensional (3D), physiologically relevant culture models are required to better understand cancer progression and develop more effective treatment. Such platforms should include cancer-specific architectures, relevant physicochemical signals, stromal–cancer cell interactions, immune components, vascular components, and cell-ECM interactions found in patient tumors. This review briefly summarizes how cancer microenvironments (stromal component, cell-ECM interactions, and molecular modulators) are defined and what emerging technologies (perfusable scaffold, tumor stiffness, supporting cells within tumors and complex patterning) can be utilized to better mimic native-like breast cancer microenvironments. Furthermore, this review emphasizes biophysical properties that differ between primary tumor ECM and tissue sites of metastatic lesions with a focus on matrix modulation of cancer stem cells, providing a rationale for investigation of underexplored ECM proteins that could alter patient prognosis. To engineer breast cancer microenvironments, we categorized technologies into two groups: (1) biochemical factors modulating breast cancer cell-ECM interactions and (2) 3D bioprinting methods and its applications to model breast cancer microenvironments. Biochemical factors include matrix-associated proteins, soluble factors, ECMs, and synthetic biomaterials. For the application of 3D bioprinting, we discuss the transition of 2D patterning to 3D scaffolding with various bioprinting technologies to implement biophysical cues to model breast cancer microenvironments. PMID:29881724

Group-level self-definition and self-investment: a hierarchical (multicomponent) model of in-group identification.

PubMed

Leach, Colin Wayne; van Zomeren, Martijn; Zebel, Sven; Vliek, Michael L W; Pennekamp, Sjoerd F; Doosje, Bertjan; Ouwerkerk, Jaap W; Spears, Russell

2008-07-01

Recent research shows individuals' identification with in-groups to be psychologically important and socially consequential. However, there is little agreement about how identification should be conceptualized or measured. On the basis of previous work, the authors identified 5 specific components of in-group identification and offered a hierarchical 2-dimensional model within which these components are organized. Studies 1 and 2 used confirmatory factor analysis to validate the proposed model of self-definition (individual self-stereotyping, in-group homogeneity) and self-investment (solidarity, satisfaction, and centrality) dimensions, across 3 different group identities. Studies 3 and 4 demonstrated the construct validity of the 5 components by examining their (concurrent) correlations with established measures of in-group identification. Studies 5-7 demonstrated the predictive and discriminant validity of the 5 components by examining their (prospective) prediction of individuals' orientation to, and emotions about, real intergroup relations. Together, these studies illustrate the conceptual and empirical value of a hierarchical multicomponent model of in-group identification.

Modeling genetic and environmental factors to increase heritability and ease the identification of candidate genes for birth weight: a twin study.

PubMed

Gielen, M; Lindsey, P J; Derom, C; Smeets, H J M; Souren, N Y; Paulussen, A D C; Derom, R; Nijhuis, J G

2008-01-01

Heritability estimates of birth weight have been inconsistent. Possible explanations are heritability changes during gestational age or the influence of covariates (e.g. chorionicity). The aim of this study was to model birth weights of twins across gestational age and to quantify the genetic and environmental components. We intended to reduce the common environmental variance to increase heritability and thereby the chance of identifying candidate genes influencing the genetic variance of birth weight. Perinatal data were obtained from 4232 live-born twin pairs from the East Flanders Prospective Twin Survey, Belgium. Heritability of birth weights across gestational ages was estimated using a non-linear multivariate Gaussian regression with covariates in the means model and in covariance structure. Maternal, twin-specific, and placental factors were considered as covariates. Heritability of birth weight decreased during gestation from 25 to 42 weeks. However, adjusting for covariates increased the heritability over this time period, with the highest heritability for first-born twins of multipara with separate placentas, who were staying alive (from 52% at 25 weeks to 30% at 42 weeks). Twin-specific factors revealed latent genetic components, whereas placental factors explained common and unique environmental factors. The number of placentas and site of the insertion of the umbilical cord masked the effect of chorionicity. Modeling genetic and environmental factors leads to a better estimate of their role in growth during gestation. For birth weight, mainly environmental factors were explained, resulting in an increase of the heritability and thereby the chance of finding genes influencing birth weight in linkage and association studies.

The Coherence Formation Model of Illustrated Text Comprehension: A Path Model of Attention to Multimedia Text

ERIC Educational Resources Information Center

Fitzhugh, Shannon Leigh

2012-01-01

The study reported here tests a model that includes several factors thought to contribute to the comprehension of static multimedia learning materials (i.e. background knowledge, working memory, attention to components as measured with eye movement measures). The model examines the effects of working memory capacity, domain specific (biology) and…

Feeding modes in stream salmonid population models: Is drift feeding the whole story?

Treesearch

Bret Harvey; Steve Railsback

2014-01-01

Drift-feeding models are essential components of broader models that link stream habitat to salmonid populations and community dynamics. But is an additional feeding mode needed for understanding and predicting salmonid population responses to streamflow and other environmental factors? We addressed this question by applying two versions of the individual-based model...

The Development and Validation of the Empathy Components Questionnaire (ECQ).

PubMed

Batchelder, Laurie; Brosnan, Mark; Ashwin, Chris

2017-01-01

Key research suggests that empathy is a multidimensional construct comprising of both cognitive and affective components. More recent theories and research suggest even further factors within these components of empathy, including the ability to empathize with others versus the drive towards empathizing with others. While numerous self-report measures have been developed to examine empathy, none of them currently index all of these wider components together. The aim of the present research was to develop and validate the Empathy Components Questionnaire (ECQ) to measure cognitive and affective components, as well as ability and drive components within each. Study one utilized items measuring cognitive and affective empathy taken from various established questionnaires to create an initial version of the ECQ. Principal component analysis (PCA) was used to examine the underlying components of empathy within the ECQ in a sample of 101 typical adults. Results revealed a five-component model consisting of cognitive ability, cognitive drive, affective ability, affective drive, and a fifth factor assessing affective reactivity. This five-component structure was then validated and confirmed using confirmatory factor analysis (CFA) in an independent sample of 211 typical adults. Results also showed that females scored higher than males overall on the ECQ, and on specific components, which is consistent with previous findings of a female advantage on self-reported empathy. Findings also showed certain components predicted scores on an independent measure of social behavior, which provided good convergent validity of the ECQ. Together, these findings validate the newly developed ECQ as a multidimensional measure of empathy more in-line with current theories of empathy. The ECQ provides a useful new tool for quick and easy measurement of empathy and its components for research with both healthy and clinical populations.

The Development and Validation of the Empathy Components Questionnaire (ECQ)

PubMed Central

Batchelder, Laurie; Brosnan, Mark; Ashwin, Chris

2017-01-01

Key research suggests that empathy is a multidimensional construct comprising of both cognitive and affective components. More recent theories and research suggest even further factors within these components of empathy, including the ability to empathize with others versus the drive towards empathizing with others. While numerous self-report measures have been developed to examine empathy, none of them currently index all of these wider components together. The aim of the present research was to develop and validate the Empathy Components Questionnaire (ECQ) to measure cognitive and affective components, as well as ability and drive components within each. Study one utilized items measuring cognitive and affective empathy taken from various established questionnaires to create an initial version of the ECQ. Principal component analysis (PCA) was used to examine the underlying components of empathy within the ECQ in a sample of 101 typical adults. Results revealed a five-component model consisting of cognitive ability, cognitive drive, affective ability, affective drive, and a fifth factor assessing affective reactivity. This five-component structure was then validated and confirmed using confirmatory factor analysis (CFA) in an independent sample of 211 typical adults. Results also showed that females scored higher than males overall on the ECQ, and on specific components, which is consistent with previous findings of a female advantage on self-reported empathy. Findings also showed certain components predicted scores on an independent measure of social behavior, which provided good convergent validity of the ECQ. Together, these findings validate the newly developed ECQ as a multidimensional measure of empathy more in-line with current theories of empathy. The ECQ provides a useful new tool for quick and easy measurement of empathy and its components for research with both healthy and clinical populations. PMID:28076406

The structural invariance of the Temporal Experience of Pleasure Scale across time and culture.

PubMed

Li, Zhi; Shi, Hai-Song; Elis, Ori; Yang, Zhuo-Ya; Wang, Ya; Lui, Simon S Y; Cheung, Eric F C; Kring, Ann M; Chan, Raymond C K

2018-06-01

The Temporal Experience of Pleasure Scale (TEPS) is a self-report instrument that assesses pleasure experience. Initial scale development and validation in the United States yielded a two-factor solution comprising anticipatory and consummatory pleasure. However, a four-factor model that further parsed anticipatory and consummatory pleasure experience into abstract and contextual components was a better model fit in China. In this study, we tested both models using confirmatory factor analysis in an American and a Chinese sample and examined the configural measurement invariance of both models across culture. We also examined the temporal stability of the four-factor model in the Chinese sample. The results indicated that the four-factor model of the TEPS was a better fit than the two-factor model in the Chinese sample. In contrast, both models fit the American sample, which also included many Asian American participants. The four-factor model fit both the Asian American and Chinese samples equally well. Finally, the four-factor model demonstrated good measurement and structural invariance across culture and time, suggesting that this model may be applicable in both cross-cultural and longitudinal studies. © 2018 The Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Hierarchical, parallel computing strategies using component object model for process modelling responses of forest plantations to interacting multiple stresses

Treesearch

J. G. Isebrands; G. E. Host; K. Lenz; G. Wu; H. W. Stech

2000-01-01

Process models are powerful research tools for assessing the effects of multiple environmental stresses on forest plantations. These models are driven by interacting environmental variables and often include genetic factors necessary for assessing forest plantation growth over a range of different site, climate, and silvicultural conditions. However, process models are...

A detailed analysis of the high-resolution X-ray spectra of NGC 3516: variability of the ionized absorbers

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

Huerta, E. M.; Krongold, Y.; Jimenez-Bailon, E.

2014-09-20

The 1.5 Seyfert galaxy NGC 3516 presents a strong time variability in X-rays. We re-analyzed the nine observations performed in 2006 October by XMM-Newton and Chandra in the 0.3 to 10 keV energy band. An acceptable model was found for the XMM-Newton data fitting the EPIC-PN and RGS spectra simultaneously; later, this model was successfully applied to the contemporary Chandra high-resolution data. The model consists of a continuum emission component (power law + blackbody) absorbed by four ionized components (warm absorbers), and 10 narrow emission lines. Three absorbing components are warm, producing features only in the soft X-ray band. Themore » fourth ionization component produces Fe XXV and Fe XXVI in the hard-energy band. We study the time response of the absorbing components to the well-detected changes in the X-ray luminosity of this source and find that the two components with the lower ionization state show clear opacity changes consistent with gas close to photoionization equilibrium. These changes are supported by the models and by differences in the spectral features among the nine observations. On the other hand, the two components with higher ionization state do not seem to respond to continuum variations. The response time of the ionized absorbers allows us to constrain their electron density and location. We find that one component (with intermediate ionization) must be located within the obscuring torus at a distance 2.7 × 10{sup 17} cm from the central engine. This outflowing component likely originated in the accretion disk. The three remaining components are at distances larger than 10{sup 16}-10{sup 17} cm. Two of the absorbing components in the soft X-rays have similar outflow velocities and locations. These components may be in pressure equilibrium, forming a multi-phase medium, if the gas has metallicity larger than the solar one (≳ 5 Z {sub ☉}). We also search for variations in the covering factor of the ionized absorbers (although partial covering is not required in our models). We find no correlation between the change in covering factor and the flux of the source. This, in connection with the observed variability of the ionized absorbers, suggests that the changes in flux are not produced by this material. If the variations are indeed produced by obscuring clumps of gas, these must be located much closer in to the central source.« less

Differential associations of job control components with both waist circumference and body mass index.

PubMed

Bean, Christopher G; Winefield, Helen R; Sargent, Charli; Hutchinson, Amanda D

2015-10-01

The Job Demand-Control-Support (JDCS) model is commonly used to investigate associations between psychosocial work factors and employee health, yet research considering obesity using the JDCS model remains inconclusive. This study investigates which parts of the JDCS model are associated with measures of obesity and provides a comparison between waist circumference (higher values imply central obesity) and body mass index (BMI, higher values imply overall obesity). Contrary to common practice, in this study the JDCS components are not reduced into composite or global scores. In light of emerging evidence that the two components of job control (skill discretion and decision authority) could have differential associations with related health outcomes, components of the JDCS model were analysed at the subscale level. A cross-sectional design with a South Australian cohort (N = 450) combined computer-assisted telephone interview data and clinic-measured height, weight and waist circumference. After controlling for sex, age, household income, work hours and job nature (blue vs. white-collar), the two components of job control were the only parts of the JDCS model to hold significant associations with measures of obesity. Notably, the associations between skill discretion and waist circumference (b = -.502, p = .001), and skill discretion and BMI (b = -.163, p = .005) were negative. Conversely, the association between decision authority and waist circumference (b = .282, p = .022) was positive. These findings are significant since skill discretion and decision authority are typically combined into a composite measure of job control or decision latitude. Our findings suggest skill discretion and decision authority should be treated separately since combining these theoretically distinct components may conceal their differential associations with measures of obesity, masking their individual importance. Psychosocial work factors displayed stronger associations and explained greater variance in waist circumference compared with BMI, and possible reasons for this are discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Product competitiveness analysis for e-commerce platform of special agricultural products

NASA Astrophysics Data System (ADS)

Wan, Fucheng; Ma, Ning; Yang, Dongwei; Xiong, Zhangyuan

2017-09-01

On the basis of analyzing the influence factors of the product competitiveness of the e-commerce platform of the special agricultural products and the characteristics of the analytical methods for the competitiveness of the special agricultural products, the price, the sales volume, the postage included service, the store reputation, the popularity, etc. were selected in this paper as the dimensionality for analyzing the competitiveness of the agricultural products, and the principal component factor analysis was taken as the competitiveness analysis method. Specifically, the web crawler was adopted to capture the information of various special agricultural products in the e-commerce platform ---- chi.taobao.com. Then, the original data captured thereby were preprocessed and MYSQL database was adopted to establish the information library for the special agricultural products. Then, the principal component factor analysis method was adopted to establish the analysis model for the competitiveness of the special agricultural products, and SPSS was adopted in the principal component factor analysis process to obtain the competitiveness evaluation factor system (support degree factor, price factor, service factor and evaluation factor) of the special agricultural products. Then, the linear regression method was adopted to establish the competitiveness index equation of the special agricultural products for estimating the competitiveness of the special agricultural products.

Clinical Complexity in Medicine: A Measurement Model of Task and Patient Complexity.

PubMed

Islam, R; Weir, C; Del Fiol, G

2016-01-01

Complexity in medicine needs to be reduced to simple components in a way that is comprehensible to researchers and clinicians. Few studies in the current literature propose a measurement model that addresses both task and patient complexity in medicine. The objective of this paper is to develop an integrated approach to understand and measure clinical complexity by incorporating both task and patient complexity components focusing on the infectious disease domain. The measurement model was adapted and modified for the healthcare domain. Three clinical infectious disease teams were observed, audio-recorded and transcribed. Each team included an infectious diseases expert, one infectious diseases fellow, one physician assistant and one pharmacy resident fellow. The transcripts were parsed and the authors independently coded complexity attributes. This baseline measurement model of clinical complexity was modified in an initial set of coding processes and further validated in a consensus-based iterative process that included several meetings and email discussions by three clinical experts from diverse backgrounds from the Department of Biomedical Informatics at the University of Utah. Inter-rater reliability was calculated using Cohen's kappa. The proposed clinical complexity model consists of two separate components. The first is a clinical task complexity model with 13 clinical complexity-contributing factors and 7 dimensions. The second is the patient complexity model with 11 complexity-contributing factors and 5 dimensions. The measurement model for complexity encompassing both task and patient complexity will be a valuable resource for future researchers and industry to measure and understand complexity in healthcare.

GEOSS AIP-2 Climate Change and Biodiversity Use Scenarios: Interoperability Infrastructures (Invited)

NASA Astrophysics Data System (ADS)

Nativi, S.; Santoro, M.

2009-12-01

Currently, one of the major challenges for scientific community is the study of climate change effects on life on Earth. To achieve this, it is crucial to understand how climate change will impact on biodiversity and, in this context, several application scenarios require modeling the impact of climate change on distribution of individual species. In the context of GEOSS AIP-2 (Global Earth Observation System of Systems, Architecture Implementation Pilot- Phase 2), the Climate Change & Biodiversity thematic Working Group developed three significant user scenarios. A couple of them make use of a GEOSS-based framework to study the impact of climate change factors on regional species distribution. The presentation introduces and discusses this framework which provides an interoperability infrastructures to loosely couple standard services and components to discover and access climate and biodiversity data, and run forecast and processing models. The framework is comprised of the following main components and services: a)GEO Portal: through this component end user is able to search, find and access the needed services for the scenario execution; b)Graphical User Interface (GUI): this component provides user interaction functionalities. It controls the workflow manager to perform the required operations for the scenario implementation; c)Use Scenario controller: this component acts as a workflow controller implementing the scenario business process -i.e. a typical climate change & biodiversity projection scenario; d)Service Broker implementing Mediation Services: this component realizes a distributed catalogue which federates several discovery and access components (exposing them through a unique CSW standard interface). Federated components publish climate, environmental and biodiversity datasets; e)Ecological Niche Model Server: this component is able to run one or more Ecological Niche Models (ENM) on selected biodiversity and climate datasets; f)Data Access Transaction server: this component publishes the model outputs. The framework was successfully tested in two use scenarios of the GEOSS AIP-2 Climate Change and Biodiversity WG aiming to predict species distribution changes due to Climate Change factors, with the scientific patronage of the University of Colorado and the University of Alaska. The first scenario dealt with the Pikas specie regional distribution in the Great Basin area (North America). While, the second one concerned the modeling of the Arctic Food Chain species in the North Pole area -the relationships between different environmental parameters and Polar Bears distribution was analyzed. Results are published in the GEOSS AIP-2 web site: http://www.ogcnetwork.net/AIP2develop .

Substance and Artifact in the Higher-Order Factors of the Big Five

PubMed Central

McCrae, Robert R.; Jang, Kerry L.; Ando, Juko; Ono, Yutaka; Yamagata, Shinji; Riemann, Rainer; Angleitner, Alois; Spinath, Frank M.

2018-01-01

J. M. Digman (1997) proposed that the Big Five personality traits showed a higher-order structure with 2 factors he labeled α and β. These factors have been alternatively interpreted as heritable components of personality or as artifacts of evaluative bias. Using structural equation modeling, the authors reanalyzed data from a cross-national twin study and from American cross-observer studies and analyzed new multimethod data from a German twin study. In all analyses, artifact models outperformed substance models by root-mean-square error of approximation criteria, but models combining both artifact and substance were slightly better. These findings suggest that the search for the biological basis of personality traits may be more profitably focused on the 5 factors themselves and their specific facets, especially in monomethod studies. PMID:18665712

Assessing Underreporting Response Bias on the MMPI-2

ERIC Educational Resources Information Center

Bagby, R. Michael; Marshall, Margarita B.

2004-01-01

The authors assess the replicability of the two-factor model of underreporting response style. They then examine the relative performance of scales measuring these styles in analog (ARD) and differential prevalence group (DPG) designs. Principal components analysis produced a two-factor structure corresponding to self-deceptive (SD) and impression…

Applying the Extended Parallel Process Model to workplace safety messages.

PubMed

Basil, Michael; Basil, Debra; Deshpande, Sameer; Lavack, Anne M

2013-01-01

The extended parallel process model (EPPM) proposes fear appeals are most effective when they combine threat and efficacy. Three studies conducted in the workplace safety context examine the use of various EPPM factors and their effects, especially multiplicative effects. Study 1 was a content analysis examining the use of EPPM factors in actual workplace safety messages. Study 2 experimentally tested these messages with 212 construction trainees. Study 3 replicated this experiment with 1,802 men across four English-speaking countries-Australia, Canada, the United Kingdom, and the United States. The results of these three studies (1) demonstrate the inconsistent use of EPPM components in real-world work safety communications, (2) support the necessity of self-efficacy for the effective use of threat, (3) show a multiplicative effect where communication effectiveness is maximized when all model components are present (severity, susceptibility, and efficacy), and (4) validate these findings with gory appeals across four English-speaking countries.

Dark traits and suicide: Associations between psychopathy, narcissism, and components of the interpersonal-psychological theory of suicide.

PubMed

Harrop, Tiffany M; Preston, Olivia C; Khazem, Lauren R; Anestis, Michael D; Junearick, Regis; Green, Bradley A; Anestis, Joye C

2017-10-01

Studies have identified independent relationships between psychopathy, narcissism, and suicidality. The current study expands upon the extant literature by exploring psychopathic and narcissistic personality traits and components of the interpersonal-psychological theory of suicide, utilizing a 3-factor model of psychopathy and 2-factor model of pathological narcissism in community, undergraduate, and military individuals. We hypothesized that the impulsive-antisocial facets of psychopathy would be related to suicidal desire, whereas all facets of psychopathy would relate to the capability for suicide. We anticipated an association between pathological narcissism, thwarted belongingness, and capability for suicide, but not perceived burdensomeness. We further hypothesized a relationship between physical pain tolerance and persistence and the affective (i.e., callousness) facet of psychopathy. Results partially supported these hypotheses and underscore the need for further examination of these associations utilizing contemporary models of psychopathy and narcissism. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Attractiveness in African American and Caucasian women: is beauty in the eyes of the observer?

PubMed

Davis, Dawnavan S; Sbrocco, Tracy; Odoms-Young, Angela; Smith, Dionne M

2010-01-01

Traditional body image studies have been constrained by focusing on body thinness as the sole component of attractiveness. Evidence suggests that African American women may hold a multifactorial view of attractiveness that extends beyond size to include factors such as dress attire and race. The current study employed a culturally sensitive silhouette Model Rating Task (MRT) to examine the effects of attire, body size, and race on attractiveness. Unexpectedly, minimal differences on attractiveness ratings emerged by attire, body size, or model race between African American and Caucasian women. Overall, participants preferred the dressed, underweight, and African American models. Factors such as exposure to diverse groups and changes in African American culture may explain the present findings. Future studies to delineate the components of attractiveness for African American and Caucasian women using the MRT are needed to broaden our understanding and conceptualization of attractiveness across racial groups.

Attractiveness in African American and Caucasian Women: Is Beauty in the Eyes of the Observer?

PubMed Central

Davis, Dawnavan S.; Sbrocco, Tracy; Odoms-Young, Angela; Smith, Dionne M.

2010-01-01

Traditional body image studies have been constrained by focusing on body thinness as the sole component of attractiveness. Evidence suggests that African American women may hold a multifactorial view of attractiveness that extends beyond size to include factors such as dress attire and race. The current study employed a culturally sensitive silhouette Model Rating Task (MRT) to examine the effects of attire, body size, and race on attractiveness. Unexpectedly, minimal differences on attractiveness ratings emerged by attire, body size, or model race between African American and Caucasian women. Overall, participants preferred the dressed, underweight, and African American models. Factors such as exposure to diverse groups and changes in African American culture may explain the present findings. Future studies to delineate the components of attractiveness for African American and Caucasian women using the MRT are needed to broaden our understanding and conceptualization of attractiveness across racial groups. PMID:19962117

Components of Mathematics Anxiety: Factor Modeling of the MARS30-Brief

PubMed Central

Pletzer, Belinda; Wood, Guilherme; Scherndl, Thomas; Kerschbaum, Hubert H.; Nuerk, Hans-Christoph

2016-01-01

Mathematics anxiety involves feelings of tension, discomfort, high arousal, and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study. The Mathematics Anxiety Rating Scale (MARS) is a reliable measure of mathematics anxiety (Richardson and Suinn, 1972), for which several reduced forms have been developed. Most recently, a shortened version of the MARS (MARS30-brief) with comparable reliability was published. Different studies suggest that mathematics anxiety involves up to seven different factors. Here we examined the factor structure of the MARS30-brief by means of confirmatory factor analysis. The best model fit was obtained by a six-factor model, dismembering the known two general factors “Mathematical Test Anxiety” (MTA) and “Numerical Anxiety” (NA) in three factors each. However, a more parsimonious 5-factor model with two sub-factors for MTA and three for NA fitted the data comparably well. Factors were differentially susceptible to sex differences and differences between majors. Measurement invariance for sex was established. PMID:26924996

Components of Mathematics Anxiety: Factor Modeling of the MARS30-Brief.

PubMed

Pletzer, Belinda; Wood, Guilherme; Scherndl, Thomas; Kerschbaum, Hubert H; Nuerk, Hans-Christoph

2016-01-01

Mathematics anxiety involves feelings of tension, discomfort, high arousal, and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study. The Mathematics Anxiety Rating Scale (MARS) is a reliable measure of mathematics anxiety (Richardson and Suinn, 1972), for which several reduced forms have been developed. Most recently, a shortened version of the MARS (MARS30-brief) with comparable reliability was published. Different studies suggest that mathematics anxiety involves up to seven different factors. Here we examined the factor structure of the MARS30-brief by means of confirmatory factor analysis. The best model fit was obtained by a six-factor model, dismembering the known two general factors "Mathematical Test Anxiety" (MTA) and "Numerical Anxiety" (NA) in three factors each. However, a more parsimonious 5-factor model with two sub-factors for MTA and three for NA fitted the data comparably well. Factors were differentially susceptible to sex differences and differences between majors. Measurement invariance for sex was established.

A Model for Evaluating Programs for the Gifted under Non-Experimental Conditions.

ERIC Educational Resources Information Center

Carter, Kyle R.

1992-01-01

The article presents and illustrates use of an evaluation model for assessing programs for the gifted where tight experimental control is not possible. The model consists of four components: ex post factor designs including intact groups; comparative evaluation; strength of treatment; and multiple outcome assessment from flexible data sources. (DB)

The utility of the bifactor model in understanding unique components of anxiety sensitivity in a South Korean sample.

PubMed

Ebesutani, Chad; Kim, Mirihae; Park, Hee-Hoon

2016-08-01

The present study was the first to examine the applicability of the bifactor structure underlying the Anxiety Sensitivity Index-3 (ASI-3) in an East Asian (South Korean) sample and to determine which factors in the bifactor model were significantly associated with anxiety, depression, and negative affect. Using a sample of 289 South Korean university students, we compared (a) the original 3-factor AS model, (b) a 3-group bifactor AS model, and (c) a 2-group bifactor AS model (with only the physical and social concern group factors present). Results revealed that the 2-group bifactor AS model fit the ASI-3 data the best. Relatedly, although all ASI-3 items loaded on the general AS factor, the Cognitive Concern group factor was not defined in the bifactor model and may therefore need to be omitted in order to accurately model AS when conducting factor analysis and structural equation modeling (SEM) in cross cultural contexts. SEM results also revealed that the general AS factor was the only factor from the 2-group bifactor model that significantly predicted anxiety, depression, and negative affect. Implications and importance of this new bifactor structure of Anxiety Sensitivity in East Asian samples are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Fast Decomposition of Three-Component Spectra of Fluorescence Quenching by White and Grey Methods of Data Modeling.

PubMed

Kałka, Andrzej J; Turek, Andrzej M

2018-04-03

'White' and 'grey' methods of data modeling have been employed to resolve the heterogeneous fluorescence from a fluorophore mixture of 9-cyanoanthracene (CNA), 10-chloro-9-cyanoanthracene (ClCNA) and 9,10-dicyanoanthracene (DCNA) into component individual fluorescence spectra. The three-component spectra of fluorescence quenching in methanol were recorded for increasing amounts of lithium bromide used as a quencher. The associated intensity decay profiles of differentially quenched fluorescence of single components were modeled on the basis of a linear Stern-Volmer plot. These profiles are necessary to initiate the fitting procedure in both 'white' and 'grey' modeling of the original data matrices. 'White' methods of data modeling, called also 'hard' methods, are based on chemical/physical laws expressed in terms of some well-known or generally accepted mathematical equations. The parameters of these models are not known and they are estimated by least squares curve fitting. 'Grey' approaches to data modeling, also known as hard-soft modeling techniques, make use of both hard-model and soft-model parts. In practice, the difference between 'white' and 'grey' methods lies in the way in which the 'crude' fluorescence intensity decays of the mixture components are estimated. In the former case they are given in a functional form while in the latter as digitized curves which, in general, can only be obtained by using dedicated techniques of factor analysis. In the paper, the initial values of the Stern-Volmer constants of pure components were evaluated by both 'point-by-point' and 'matrix' versions of the method making use of the concept of wavelength dependent intensity fractions as well as by the rank annihilation factor analysis applied to the data matrices of the difference fluorescence spectra constructed in two ways: from the spectra recorded for a few excitation lines at the same concentration of a fluorescence quencher or classically from a series of the spectra measured for one selected excitation line but for increasing concentration of the quencher. The results of multiple curve resolution obtained by all types of the applied methods have been scrutinized and compared. In addition, the effect of inadequacy of sample preparation and increasing instrumental noise on the shape of the resolved spectral profiles has been studied on several datasets mimicking the measured data matrices. Graphical Abstract ᅟ.

Towards an Enhancement of Organizational Information Security through Threat Factor Profiling (TFP) Model

NASA Astrophysics Data System (ADS)

Sidi, Fatimah; Daud, Maslina; Ahmad, Sabariah; Zainuddin, Naqliyah; Anneisa Abdullah, Syafiqa; Jabar, Marzanah A.; Suriani Affendey, Lilly; Ishak, Iskandar; Sharef, Nurfadhlina Mohd; Zolkepli, Maslina; Nur Majdina Nordin, Fatin; Amat Sejani, Hashimah; Ramadzan Hairani, Saiful

2017-09-01

Information security has been identified by organizations as part of internal operations that need to be well implemented and protected. This is because each day the organizations face a high probability of increase of threats to their networks and services that will lead to information security issues. Thus, effective information security management is required in order to protect their information assets. Threat profiling is a method that can be used by an organization to address the security challenges. Threat profiling allows analysts to understand and organize intelligent information related to threat groups. This paper presents a comparative analysis that was conducted to study the existing threat profiling models. It was found that existing threat models were constructed based on specific objectives, thus each model is limited to only certain components or factors such as assets, threat sources, countermeasures, threat agents, threat outcomes and threat actors. It is suggested that threat profiling can be improved by the combination of components found in each existing threat profiling model/framework. The proposed model can be used by an organization in executing a proactive approach to incident management.

Genetic and Environmental Influences on Female Sexual Orientation, Childhood Gender Typicality and Adult Gender Identity

PubMed Central

Burri, Andrea; Cherkas, Lynn; Spector, Timothy; Rahman, Qazi

2011-01-01

Background Human sexual orientation is influenced by genetic and non-shared environmental factors as are two important psychological correlates – childhood gender typicality (CGT) and adult gender identity (AGI). However, researchers have been unable to resolve the genetic and non-genetic components that contribute to the covariation between these traits, particularly in women. Methodology/Principal Findings Here we performed a multivariate genetic analysis in a large sample of British female twins (N = 4,426) who completed a questionnaire assessing sexual attraction, CGT and AGI. Univariate genetic models indicated modest genetic influences on sexual attraction (25%), AGI (11%) and CGT (31%). For the multivariate analyses, a common pathway model best fitted the data. Conclusions/Significance This indicated that a single latent variable influenced by a genetic component and common non-shared environmental component explained the association between the three traits but there was substantial measurement error. These findings highlight common developmental factors affecting differences in sexual orientation. PMID:21760939

A stochastic atmospheric model for remote sensing applications

NASA Technical Reports Server (NTRS)

Turner, R. E.

1983-01-01

There are many factors which reduce the accuracy of classification of objects in the satellite remote sensing of Earth's surface. One important factor is the variability in the scattering and absorptive properties of the atmospheric components such as particulates and the variable gases. For multispectral remote sensing of the Earth's surface in the visible and infrared parts of the spectrum the atmospheric particulates are a major source of variability in the received signal. It is difficult to design a sensor which will determine the unknown atmospheric components by remote sensing methods, at least to the accuracy needed for multispectral classification. The problem of spatial and temporal variations in the atmospheric quantities which can affect the measured radiances are examined. A method based upon the stochastic nature of the atmospheric components was developed, and, using actual data the statistical parameters needed for inclusion into a radiometric model was generated. Methods are then described for an improved correction of radiances. These algorithms will then result in a more accurate and consistent classification procedure.

[The healthy life-style as one of components of human safety].

PubMed

Vasendin, V N; Tchebotarkova, S A; Kobalyeva, D A

2012-01-01

The technique of single-step anonymous questionnaire was applied to sampling of students of technical university to study propagation of health risk factors. The very high propagation of behavioral factors of life-style among students is noted. The model of healthy life-style is considered with emphasis on internal and external aspects of its functioning. It is established that particular steps in implementation of this model are ultimately individual.

Volatility of organic aerosol and its components in the Megacity of Paris

NASA Astrophysics Data System (ADS)

Paciga, A.; Karnezi, E.; Kostenidou, E.; Hildebrandt, L.; Psichoudaki, M.; Engelhart, G. J.; Lee, B.-H.; Crippa, M.; Prévôt, A. S. H.; Baltensperger, U.; Pandis, S. N.

2015-08-01

Using a mass transfer model and the volatility basis set, we estimate the volatility distribution for the organic aerosol (OA) components during summer and winter in Paris, France as part of the collaborative project MEGAPOLI. The concentrations of the OA components as a function of temperature were measured combining data from a thermodenuder and an aerosol mass spectrometer (AMS) with Positive Matrix Factorization (PMF) analysis. The hydrocarbon-like organic aerosol (HOA) had similar volatility distributions for the summer and winter campaigns with half of the material in the saturation concentration bin of 10 μg m-3 and another 35-40 % consisting of low and extremely low volatility organic compounds (LVOCs and ELVOCs, respectively). The winter cooking OA (COA) was more than an order of magnitude less volatile than the summer COA. The low volatility oxygenated OA (LV-OOA) factor detected in the summer had the lowest volatility of all the derived factors and consisted almost exclusively of ELVOCs. The volatility for the semi-volatile oxygenated OA (SV-OOA) was significantly higher than that of the LV-OOA, containing both semi-volatile organic components (SVOCs) and LVOCs. The oxygenated OA (OOA) factor in winter consisted of SVOCs (45 %), LVOCs (25 %) and ELVOCs (30 %). The volatility of marine OA (MOA) was higher than that of the other factors containing around 60 % SVOCs. The biomass burning OA (BBOA) factor contained components with a wide range of volatilities with significant contributions from both SVOCs (50 %) and LVOCs (30 %). Finally, combining the O : C ratio and volatility distributions of the various factors, we incorporated our results into the two-dimensional volatility basis set (2D-VBS). Our results show that the factors cover a broad spectrum of volatilities with no direct link between the average volatility and average O : C of the OA components. Agreement between our findings and previous publications is encouraging for our understanding of the evolution of atmospheric OA.

Modelling temporal variance of component temperatures and directional anisotropy over vegetated canopy

NASA Astrophysics Data System (ADS)

Bian, Zunjian; du, yongming; li, hua

2016-04-01

Land surface temperature (LST) as a key variable plays an important role on hydrological, meteorology and climatological study. Thermal infrared directional anisotropy is one of essential factors to LST retrieval and application on longwave radiance estimation. Many approaches have been proposed to estimate directional brightness temperatures (DBT) over natural and urban surfaces. While less efforts focus on 3-D scene and the surface component temperatures used in DBT models are quiet difficult to acquire. Therefor a combined 3-D model of TRGM (Thermal-region Radiosity-Graphics combined Model) and energy balance method is proposed in the paper for the attempt of synchronously simulation of component temperatures and DBT in the row planted canopy. The surface thermodynamic equilibrium can be final determined by the iteration strategy of TRGM and energy balance method. The combined model was validated by the top-of-canopy DBTs using airborne observations. The results indicated that the proposed model performs well on the simulation of directional anisotropy, especially the hotspot effect. Though we find that the model overestimate the DBT with Bias of 1.2K, it can be an option as a data reference to study temporal variance of component temperatures and DBTs when field measurement is inaccessible

The Socioeconomic Factors and the Indigenous Component of Tuberculosis in Amazonas

PubMed Central

2016-01-01

Despite the availability of tuberculosis prevention and control services throughout Amazonas, high rates of morbidity and mortality from tuberculosis remain in the region. Knowledge of the social determinants of tuberculosis in Amazonas is important for the establishment of public policies and the planning of effective preventive and control measures for the disease. To analyze the relationship of the spatial distribution of the incidence of tuberculosis in municipalities and regions of Amazonas to the socioeconomic factors and indigenous tuberculosis component, from 2007 to 2013. An ecological study was conducted based on secondary data from the epidemiological surveillance of tuberculosis. A linear regression model was used to analyze the relationship of the annual incidence of tuberculosis to the socioeconomic factors, performance indicators of health services, and indigenous tuberculosis component. The distribution of the incidence of tuberculosis in the municipalities of Amazonas was positively associated with the Gini index and the population attributable fraction of tuberculosis in the indigenous peoples, but negatively associated with the proportion of the poor and the unemployment rate. The spatial distribution of tuberculosis in the different regions of Amazonas was heterogeneous and closely related with the socioeconomic factors and indigenous component of tuberculosis. PMID:27362428

Effect of multiple perfusion components on pseudo-diffusion coefficient in intravoxel incoherent motion imaging

NASA Astrophysics Data System (ADS)

Kuai, Zi-Xiang; Liu, Wan-Yu; Zhu, Yue-Min

2017-11-01

The aim of this work was to investigate the effect of multiple perfusion components on the pseudo-diffusion coefficient D * in the bi-exponential intravoxel incoherent motion (IVIM) model. Simulations were first performed to examine how the presence of multiple perfusion components influences D *. The real data of livers (n  =  31), spleens (n  =  31) and kidneys (n  =  31) of 31 volunteers was then acquired using DWI for in vivo study and the number of perfusion components in these tissues was determined together with their perfusion fraction and D *, using an adaptive multi-exponential IVIM model. Finally, the bi-exponential model was applied to the real data and the mean, standard variance and coefficient of variation of D * as well as the fitting residual were calculated over the 31 volunteers for each of the three tissues and compared between them. The results of both the simulations and the in vivo study showed that, for the bi-exponential IVIM model, both the variance of D * and the fitting residual tended to increase when the number of perfusion components was increased or when the difference between perfusion components became large. In addition, it was found that the kidney presented the fewest perfusion components among the three tissues. The present study demonstrated that multi-component perfusion is a main factor that causes high variance of D * and the bi-exponential model should be used only when the tissues under investigation have few perfusion components, for example the kidney.

A review and update of the Virginia Department of Transportation cash flow forecasting model.

DOT National Transportation Integrated Search

1996-01-01

This report details the research done to review and update components of the VDOT cash flow forecasting model. Specifically, the study updated the monthly factors submodel used to predict payments on construction contracts. For the other submodel rev...

Correaltion of full-scale drag predictions with flight measurements on the C-141A aircraft. Phase 2: Wind tunnel test, analysis, and prediction techniques. Volume 1: Drag predictions, wind tunnel data analysis and correlation

NASA Technical Reports Server (NTRS)

Macwilkinson, D. G.; Blackerby, W. T.; Paterson, J. H.

1974-01-01

The degree of cruise drag correlation on the C-141A aircraft is determined between predictions based on wind tunnel test data, and flight test results. An analysis of wind tunnel tests on a 0.0275 scale model at Reynolds number up to 3.05 x 1 million/MAC is reported. Model support interference corrections are evaluated through a series of tests, and fully corrected model data are analyzed to provide details on model component interference factors. It is shown that predicted minimum profile drag for the complete configuration agrees within 0.75% of flight test data, using a wind tunnel extrapolation method based on flat plate skin friction and component shape factors. An alternative method of extrapolation, based on computed profile drag from a subsonic viscous theory, results in a prediction four percent lower than flight test data.

A Comparative Study of the Proposed Models for the Components of the National Health Information System

PubMed Central

Ahmadi, Maryam; Damanabi, Shahla; Sadoughi, Farahnaz

2014-01-01

Introduction: National Health Information System plays an important role in ensuring timely and reliable access to Health information, which is essential for strategic and operational decisions that improve health, quality and effectiveness of health care. In other words, using the National Health information system you can improve the quality of health data, information and knowledge used to support decision making at all levels and areas of the health sector. Since full identification of the components of this system – for better planning and management influential factors of performanceseems necessary, therefore, in this study different attitudes towards components of this system are explored comparatively. Methods: This is a descriptive and comparative kind of study. The society includes printed and electronic documents containing components of the national health information system in three parts: input, process and output. In this context, search for information using library resources and internet search were conducted, and data analysis was expressed using comparative tables and qualitative data. Results: The findings showed that there are three different perspectives presenting the components of national health information system Lippeveld and Sauerborn and Bodart model in 2000, Health Metrics Network (HMN) model from World Health Organization in 2008, and Gattini’s 2009 model. All three models outlined above in the input (resources and structure) require components of management and leadership, planning and design programs, supply of staff, software and hardware facilities and equipment. Plus, in the “process” section from three models, we pointed up the actions ensuring the quality of health information system, and in output section, except for Lippeveld Model, two other models consider information products and use and distribution of information as components of the national health information system. Conclusion: the results showed that all the three models have had a brief discussion about the components of health information in input section. But Lippeveld model has overlooked the components of national health information in process and output sections. Therefore, it seems that the health measurement model of network has a comprehensive presentation for the components of health system in all three sections-input, process and output. PMID:24825937

A comparative study of the proposed models for the components of the national health information system.

PubMed

Ahmadi, Maryam; Damanabi, Shahla; Sadoughi, Farahnaz

2014-04-01

National Health Information System plays an important role in ensuring timely and reliable access to Health information, which is essential for strategic and operational decisions that improve health, quality and effectiveness of health care. In other words, using the National Health information system you can improve the quality of health data, information and knowledge used to support decision making at all levels and areas of the health sector. Since full identification of the components of this system - for better planning and management influential factors of performanceseems necessary, therefore, in this study different attitudes towards components of this system are explored comparatively. This is a descriptive and comparative kind of study. The society includes printed and electronic documents containing components of the national health information system in three parts: input, process and output. In this context, search for information using library resources and internet search were conducted, and data analysis was expressed using comparative tables and qualitative data. The findings showed that there are three different perspectives presenting the components of national health information system Lippeveld and Sauerborn and Bodart model in 2000, Health Metrics Network (HMN) model from World Health Organization in 2008, and Gattini's 2009 model. All three models outlined above in the input (resources and structure) require components of management and leadership, planning and design programs, supply of staff, software and hardware facilities and equipment. Plus, in the "process" section from three models, we pointed up the actions ensuring the quality of health information system, and in output section, except for Lippeveld Model, two other models consider information products and use and distribution of information as components of the national health information system. the results showed that all the three models have had a brief discussion about the components of health information in input section. But Lippeveld model has overlooked the components of national health information in process and output sections. Therefore, it seems that the health measurement model of network has a comprehensive presentation for the components of health system in all three sections-input, process and output.

Research on Fault Rate Prediction Method of T/R Component

NASA Astrophysics Data System (ADS)

Hou, Xiaodong; Yang, Jiangping; Bi, Zengjun; Zhang, Yu

2017-07-01

T/R component is an important part of the large phased array radar antenna array, because of its large numbers, high fault rate, it has important significance for fault prediction. Aiming at the problems of traditional grey model GM(1,1) in practical operation, the discrete grey model is established based on the original model in this paper, and the optimization factor is introduced to optimize the background value, and the linear form of the prediction model is added, the improved discrete grey model of linear regression is proposed, finally, an example is simulated and compared with other models. The results show that the method proposed in this paper has higher accuracy and the solution is simple and the application scope is more extensive.

Return-to-Work Within a Complex and Dynamic Organizational Work Disability System.

PubMed

Jetha, Arif; Pransky, Glenn; Fish, Jon; Hettinger, Lawrence J

2016-09-01

Background Return-to-work (RTW) within a complex organizational system can be associated with suboptimal outcomes. Purpose To apply a sociotechnical systems perspective to investigate complexity in RTW; to utilize system dynamics modeling (SDM) to examine how feedback relationships between individual, psychosocial, and organizational factors make up the work disability system and influence RTW. Methods SDMs were developed within two companies. Thirty stakeholders including senior managers, and frontline supervisors and workers participated in model building sessions. Participants were asked questions that elicited information about the structure of the work disability system and were translated into feedback loops. To parameterize the model, participants were asked to estimate the shape and magnitude of the relationship between key model components. Data from published literature were also accessed to supplement participant estimates. Data were entered into a model created in the software program Vensim. Simulations were conducted to examine how financial incentives and light duty work disability-related policies, utilized by the participating companies, influenced RTW likelihood and preparedness. Results The SDMs were multidimensional, including individual attitudinal characteristics, health factors, and organizational components. Among the causal pathways uncovered, psychosocial components including workplace social support, supervisor and co-worker pressure, and supervisor-frontline worker communication impacted RTW likelihood and preparedness. Interestingly, SDM simulations showed that work disability-related policies in both companies resulted in a diminishing or opposing impact on RTW preparedness and likelihood. Conclusion SDM provides a novel systems view of RTW. Policy and psychosocial component relationships within the system have important implications for RTW, and may contribute to unanticipated outcomes.

[Future status of ischaemic heart disease in the state of San Luis Potosí: A predictive dynamic model].

PubMed

Gaytán-Hernández, Darío; Díaz-Oviedo, Aracely; Gallegos-García, Verónica; Terán-Figueroa, Yolanda

To develop a predictive dynamic model to generate and analyse the future status of the incidence rate of ischaemic heart disease in a population of 25 years and over in Mexico, according to the variation in time of some risk factors. Retrospective ecological study performed during the period 2013-2015, in San Luis Potosí City, Mexico. Secondary databases that corresponded to the years 2000, 2005, and 2010, were used along with official indicators of the 58 municipalities of the state of San Luis Potosí. Eight indicators were analysed at municipality level, using principal components analysis, structural equation modelling, dynamic modelling, and simulation software methods. Three components were extracted, which together explained 80.43% of the total variance of the official indicators used. The second component had a weight of 16.36 units that favoured an increase of the disease analysed. This component was integrated only by the indicator AGE 60-64 and the expected stage of it increasing. The structural model confirmed that the indicators explain 42% of the variation of this disease. The possible stages for the years 2015, 2020, and 2025 are 195.7, 240.7, and 298.0, respectively for every 100,000 inhabitants aged 25 and over. An exponential increase in the incidence rate of ischaemic heart disease is expected, with the age of 60-64 years being identified as the highest risk factor. Copyright © 2017 Instituto Nacional de Cardiología Ignacio Chávez. Publicado por Masson Doyma México S.A. All rights reserved.

Insight into the heterogeneous adsorption of humic acid fluorescent components on multi-walled carbon nanotubes by excitation-emission matrix and parallel factor analysis.

PubMed

Yang, Chenghu; Liu, Yangzhi; Cen, Qiulin; Zhu, Yaxian; Zhang, Yong

2018-02-01

The heterogeneous adsorption behavior of commercial humic acid (HA) on pristine and functionalized multi-walled carbon nanotubes (MWCNTs) was investigated by fluorescence excitation-emission matrix and parallel factor (EEM- PARAFAC) analysis. The kinetics, isotherms, thermodynamics and mechanisms of adsorption of HA fluorescent components onto MWCNTs were the focus of the present study. Three humic-like fluorescent components were distinguished, including one carboxylic-like fluorophore C1 (λ ex /λ em = (250, 310) nm/428nm), and two phenolic-like fluorophores, C2 (λ ex /λ em = (300, 460) nm/552nm) and C3 (λ ex /λ em = (270, 375) nm/520nm). The Lagergren pseudo-second-order model can be used to describe the adsorption kinetics of the HA fluorescent components. In addition, both the Freundlich and Langmuir models can be suitably employed to describe the adsorption of the HA fluorescent components onto MWCNTs with significantly high correlation coefficients (R 2 > 0.94, P< 0.05). The dissimilarity in the adsorption affinity (K d ) and nonlinear adsorption degree from the HA fluorescent components to MWCNTs was clearly observed. The adsorption mechanism suggested that the π-π electron donor-acceptor (EDA) interaction played an important role in the interaction between HA fluorescent components and the three MWCNTs. Furthermore, the values of the thermodynamic parameters, including the Gibbs free energy change (ΔG°), enthalpy change (ΔH°) and entropy change (ΔS°), showed that the adsorption of the HA fluorescent components on MWCNTs was spontaneous and exothermic. Copyright © 2017 Elsevier Inc. All rights reserved.

Ecological, psychological, and cognitive components of reading difficulties: testing the component model of reading in fourth graders across 38 countries.

PubMed

Chiu, Ming Ming; McBride-Chang, Catherine; Lin, Dan

2012-01-01

The authors tested the component model of reading (CMR) among 186,725 fourth grade students from 38 countries (45 regions) on five continents by analyzing the 2006 Progress in International Reading Literacy Study data using measures of ecological (country, family, school, teacher), psychological, and cognitive components. More than 91% of the differences in student difficulty occurred at the country (61%) and classroom (30%) levels (ecological), with less than 9% at the student level (cognitive and psychological). All three components were negatively associated with reading difficulties: cognitive (student's early literacy skills), ecological (family characteristics [socioeconomic status, number of books at home, and attitudes about reading], school characteristics [school climate and resources]), and psychological (students' attitudes about reading, reading self-concept, and being a girl). These results extend the CMR by demonstrating the importance of multiple levels of factors for reading deficits across diverse cultures.

Dimensionality and consequences of employee commitment to supervisors: a two-study examination.

PubMed

Landry, Guylaine; Panaccio, Alexandra; Vandenberghe, Christian

2010-01-01

Research on the 3-component model of organizational commitment--affective, normative, and continuance--has suggested that continuance commitment comprises 2 subcomponents, perceived lack of alternatives and sacrifice (e.g., S. J. Jaros, 1997; G. W. McGee & R. C. Ford, 1987). The authors aimed to extend that research in the context of employees' commitment to their immediate supervisors. Through two studies, they examined the validity and consequences of a 4-factor model of commitment to supervisors including affective, normative, continuance-alternatives, and continuance-sacrifice components. Study 1 (N = 317) revealed that the 4 components of commitment to supervisors were distinguishable from the corresponding components of organizational commitment. Study 2 (N = 240) further showed that the 4 components of commitment to supervisors differentially related to intention to leave the supervisor, supervisor-directed negative affect and emotional exhaustion. The authors discuss the implications of these findings for the management of employee commitment in organizations.

Estimation of Soil Moisture with L-band Multi-polarization Radar

NASA Technical Reports Server (NTRS)

Shi, J.; Chen, K. S.; Kim, Chung-Li Y.; Van Zyl, J. J.; Njoku, E.; Sun, G.; O'Neill, P.; Jackson, T.; Entekhabi, D.

2004-01-01

Through analyses of the model simulated data-base, we developed a technique to estimate surface soil moisture under HYDROS radar sensor (L-band multi-polarizations and 40deg incidence) configuration. This technique includes two steps. First, it decomposes the total backscattering signals into two components - the surface scattering components (the bare surface backscattering signals attenuated by the overlaying vegetation layer) and the sum of the direct volume scattering components and surface-volume interaction components at different polarizations. From the model simulated data-base, our decomposition technique works quit well in estimation of the surface scattering components with RMSEs of 0.12,0.25, and 0.55 dB for VV, HH, and VH polarizations, respectively. Then, we use the decomposed surface backscattering signals to estimate the soil moisture and the combined surface roughness and vegetation attenuation correction factors with all three polarizations.

Spectral damping scaling factors for shallow crustal earthquakes in active tectonic regions

USGS Publications Warehouse

Rezaeian, Sanaz; Bozorgnia, Yousef; Idriss, I.M.; Campbell, Kenneth; Abrahamson, Norman; Silva, Walter

2012-01-01

Ground motion prediction equations (GMPEs) for elastic response spectra, including the Next Generation Attenuation (NGA) models, are typically developed at a 5% viscous damping ratio. In reality, however, structural and non-structural systems can have damping ratios other than 5%, depending on various factors such as structural types, construction materials, level of ground motion excitations, among others. This report provides the findings of a comprehensive study to develop a new model for a Damping Scaling Factor (DSF) that can be used to adjust the 5% damped spectral ordinates predicted by a GMPE to spectral ordinates with damping ratios between 0.5 to 30%. Using the updated, 2011 version of the NGA database of ground motions recorded in worldwide shallow crustal earthquakes in active tectonic regions (i.e., the NGA-West2 database), dependencies of the DSF on variables including damping ratio, spectral period, moment magnitude, source-to-site distance, duration, and local site conditions are examined. The strong influence of duration is captured by inclusion of both magnitude and distance in the DSF model. Site conditions are found to have less significant influence on DSF and are not included in the model. The proposed model for DSF provides functional forms for the median value and the logarithmic standard deviation of DSF. This model is heteroscedastic, where the variance is a function of the damping ratio. Damping Scaling Factor models are developed for the “average” horizontal ground motion components, i.e., RotD50 and GMRotI50, as well as the vertical component of ground motion.

Conditional Random Fields for Fast, Large-Scale Genome-Wide Association Studies

PubMed Central

Huang, Jim C.; Meek, Christopher; Kadie, Carl; Heckerman, David

2011-01-01

Understanding the role of genetic variation in human diseases remains an important problem to be solved in genomics. An important component of such variation consist of variations at single sites in DNA, or single nucleotide polymorphisms (SNPs). Typically, the problem of associating particular SNPs to phenotypes has been confounded by hidden factors such as the presence of population structure, family structure or cryptic relatedness in the sample of individuals being analyzed. Such confounding factors lead to a large number of spurious associations and missed associations. Various statistical methods have been proposed to account for such confounding factors such as linear mixed-effect models (LMMs) or methods that adjust data based on a principal components analysis (PCA), but these methods either suffer from low power or cease to be tractable for larger numbers of individuals in the sample. Here we present a statistical model for conducting genome-wide association studies (GWAS) that accounts for such confounding factors. Our method scales in runtime quadratic in the number of individuals being studied with only a modest loss in statistical power as compared to LMM-based and PCA-based methods when testing on synthetic data that was generated from a generalized LMM. Applying our method to both real and synthetic human genotype/phenotype data, we demonstrate the ability of our model to correct for confounding factors while requiring significantly less runtime relative to LMMs. We have implemented methods for fitting these models, which are available at http://www.microsoft.com/science. PMID:21765897

Dependency-based Siamese long short-term memory network for learning sentence representations

PubMed Central

Zhu, Wenhao; Ni, Jianyue; Wei, Baogang; Lu, Zhiguo

2018-01-01

Textual representations play an important role in the field of natural language processing (NLP). The efficiency of NLP tasks, such as text comprehension and information extraction, can be significantly improved with proper textual representations. As neural networks are gradually applied to learn the representation of words and phrases, fairly efficient models of learning short text representations have been developed, such as the continuous bag of words (CBOW) and skip-gram models, and they have been extensively employed in a variety of NLP tasks. Because of the complex structure generated by the longer text lengths, such as sentences, algorithms appropriate for learning short textual representations are not applicable for learning long textual representations. One method of learning long textual representations is the Long Short-Term Memory (LSTM) network, which is suitable for processing sequences. However, the standard LSTM does not adequately address the primary sentence structure (subject, predicate and object), which is an important factor for producing appropriate sentence representations. To resolve this issue, this paper proposes the dependency-based LSTM model (D-LSTM). The D-LSTM divides a sentence representation into two parts: a basic component and a supporting component. The D-LSTM uses a pre-trained dependency parser to obtain the primary sentence information and generate supporting components, and it also uses a standard LSTM model to generate the basic sentence components. A weight factor that can adjust the ratio of the basic and supporting components in a sentence is introduced to generate the sentence representation. Compared with the representation learned by the standard LSTM, the sentence representation learned by the D-LSTM contains a greater amount of useful information. The experimental results show that the D-LSTM is superior to the standard LSTM for sentences involving compositional knowledge (SICK) data. PMID:29513748

Accurate and efficient modeling of the detector response in small animal multi-head PET systems.

PubMed

Cecchetti, Matteo; Moehrs, Sascha; Belcari, Nicola; Del Guerra, Alberto

2013-10-07

In fully three-dimensional PET imaging, iterative image reconstruction techniques usually outperform analytical algorithms in terms of image quality provided that an appropriate system model is used. In this study we concentrate on the calculation of an accurate system model for the YAP-(S)PET II small animal scanner, with the aim to obtain fully resolution- and contrast-recovered images at low levels of image roughness. For this purpose we calculate the system model by decomposing it into a product of five matrices: (1) a detector response component obtained via Monte Carlo simulations, (2) a geometric component which describes the scanner geometry and which is calculated via a multi-ray method, (3) a detector normalization component derived from the acquisition of a planar source, (4) a photon attenuation component calculated from x-ray computed tomography data, and finally, (5) a positron range component is formally included. This system model factorization allows the optimization of each component in terms of computation time, storage requirements and accuracy. The main contribution of this work is a new, efficient way to calculate the detector response component for rotating, planar detectors, that consists of a GEANT4 based simulation of a subset of lines of flight (LOFs) for a single detector head whereas the missing LOFs are obtained by using intrinsic detector symmetries. Additionally, we introduce and analyze a probability threshold for matrix elements of the detector component to optimize the trade-off between the matrix size in terms of non-zero elements and the resulting quality of the reconstructed images. In order to evaluate our proposed system model we reconstructed various images of objects, acquired according to the NEMA NU 4-2008 standard, and we compared them to the images reconstructed with two other system models: a model that does not include any detector response component and a model that approximates analytically the depth of interaction as detector response component. The comparisons confirm previous research results, showing that the usage of an accurate system model with a realistic detector response leads to reconstructed images with better resolution and contrast recovery at low levels of image roughness.

Accurate and efficient modeling of the detector response in small animal multi-head PET systems

NASA Astrophysics Data System (ADS)

Cecchetti, Matteo; Moehrs, Sascha; Belcari, Nicola; Del Guerra, Alberto

2013-10-01

In fully three-dimensional PET imaging, iterative image reconstruction techniques usually outperform analytical algorithms in terms of image quality provided that an appropriate system model is used. In this study we concentrate on the calculation of an accurate system model for the YAP-(S)PET II small animal scanner, with the aim to obtain fully resolution- and contrast-recovered images at low levels of image roughness. For this purpose we calculate the system model by decomposing it into a product of five matrices: (1) a detector response component obtained via Monte Carlo simulations, (2) a geometric component which describes the scanner geometry and which is calculated via a multi-ray method, (3) a detector normalization component derived from the acquisition of a planar source, (4) a photon attenuation component calculated from x-ray computed tomography data, and finally, (5) a positron range component is formally included. This system model factorization allows the optimization of each component in terms of computation time, storage requirements and accuracy. The main contribution of this work is a new, efficient way to calculate the detector response component for rotating, planar detectors, that consists of a GEANT4 based simulation of a subset of lines of flight (LOFs) for a single detector head whereas the missing LOFs are obtained by using intrinsic detector symmetries. Additionally, we introduce and analyze a probability threshold for matrix elements of the detector component to optimize the trade-off between the matrix size in terms of non-zero elements and the resulting quality of the reconstructed images. In order to evaluate our proposed system model we reconstructed various images of objects, acquired according to the NEMA NU 4-2008 standard, and we compared them to the images reconstructed with two other system models: a model that does not include any detector response component and a model that approximates analytically the depth of interaction as detector response component. The comparisons confirm previous research results, showing that the usage of an accurate system model with a realistic detector response leads to reconstructed images with better resolution and contrast recovery at low levels of image roughness.

Factor Analysis of Drawings: Application to college student models of the greenhouse effect

NASA Astrophysics Data System (ADS)

Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

2015-09-01

Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance, suggesting that 4 archetype models of the greenhouse effect dominate thinking within this population. Factor scores, indicating the extent to which each student's drawing aligned with representative models, were compared to performance on conceptual understanding and attitudes measures, demographics, and non-cognitive features of drawings. Student drawings were also compared to drawings made by scientists to ascertain the extent to which models reflect more sophisticated and accurate models. Results indicate that student and scientist drawings share some similarities, most notably the presence of some features of the most sophisticated non-scientific model held among the study population. Prior knowledge, prior attitudes, gender, and non-cognitive components are also predictive of an individual student's model. This work presents a new technique for analyzing drawings, with general implications for the use of drawings in investigating student conceptions.

A risk-based approach to management of leachables utilizing statistical analysis of extractables.

PubMed

Stults, Cheryl L M; Mikl, Jaromir; Whelehan, Oliver; Morrical, Bradley; Duffield, William; Nagao, Lee M

2015-04-01

To incorporate quality by design concepts into the management of leachables, an emphasis is often put on understanding the extractable profile for the materials of construction for manufacturing disposables, container-closure, or delivery systems. Component manufacturing processes may also impact the extractable profile. An approach was developed to (1) identify critical components that may be sources of leachables, (2) enable an understanding of manufacturing process factors that affect extractable profiles, (3) determine if quantitative models can be developed that predict the effect of those key factors, and (4) evaluate the practical impact of the key factors on the product. A risk evaluation for an inhalation product identified injection molding as a key process. Designed experiments were performed to evaluate the impact of molding process parameters on the extractable profile from an ABS inhaler component. Statistical analysis of the resulting GC chromatographic profiles identified processing factors that were correlated with peak levels in the extractable profiles. The combination of statistically significant molding process parameters was different for different types of extractable compounds. ANOVA models were used to obtain optimal process settings and predict extractable levels for a selected number of compounds. The proposed paradigm may be applied to evaluate the impact of material composition and processing parameters on extractable profiles and utilized to manage product leachables early in the development process and throughout the product lifecycle.

Models of Workplace Incivility: The Relationships to Instigated Incivility and Negative Outcomes

PubMed Central

2015-01-01

The aim of the study was to investigate workplace incivility as a social process, examining its components and relationships to both instigated incivility and negative outcomes in the form of well-being, job satisfaction, turnover intentions, and sleeping problems. The different components of incivility that were examined were experienced and witnessed incivility from coworkers as well as supervisors. In addition, the organizational factors, social support, control, and job demands, were included in the models. A total of 2871 (2058 women and 813 men) employees who were connected to the Swedish Hotel and Restaurant Workers Union completed an online questionnaire. Overall, the results from structural equation modelling indicate that whereas instigated incivility to a large extent was explained by witnessing coworker incivility, negative outcomes were to a high degree explained by experienced supervisor incivility via mediation through perceived low social support, low control, and high job demands. Unexpectedly, the relationships between incivility (experienced coworker and supervisor incivility, as well as witnessed supervisor incivility) and instigated incivility were moderated by perceived high control and high social support. The results highlight the importance of including different components of workplace incivility and organizational factors in future studies of the area. PMID:26557714

Models of Workplace Incivility: The Relationships to Instigated Incivility and Negative Outcomes.

PubMed

Holm, Kristoffer; Torkelson, Eva; Bäckström, Martin

2015-01-01

The aim of the study was to investigate workplace incivility as a social process, examining its components and relationships to both instigated incivility and negative outcomes in the form of well-being, job satisfaction, turnover intentions, and sleeping problems. The different components of incivility that were examined were experienced and witnessed incivility from coworkers as well as supervisors. In addition, the organizational factors, social support, control, and job demands, were included in the models. A total of 2871 (2058 women and 813 men) employees who were connected to the Swedish Hotel and Restaurant Workers Union completed an online questionnaire. Overall, the results from structural equation modelling indicate that whereas instigated incivility to a large extent was explained by witnessing coworker incivility, negative outcomes were to a high degree explained by experienced supervisor incivility via mediation through perceived low social support, low control, and high job demands. Unexpectedly, the relationships between incivility (experienced coworker and supervisor incivility, as well as witnessed supervisor incivility) and instigated incivility were moderated by perceived high control and high social support. The results highlight the importance of including different components of workplace incivility and organizational factors in future studies of the area.

A new empirical model to estimate hourly diffuse photosynthetic photon flux density

NASA Astrophysics Data System (ADS)

Foyo-Moreno, I.; Alados, I.; Alados-Arboledas, L.

2018-05-01

Knowledge of the photosynthetic photon flux density (Qp) is critical in different applications dealing with climate change, plant physiology, biomass production, and natural illumination in greenhouses. This is particularly true regarding its diffuse component (Qpd), which can enhance canopy light-use efficiency and thereby boost carbon uptake. Therefore, diffuse photosynthetic photon flux density is a key driving factor of ecosystem-productivity models. In this work, we propose a model to estimate this component, using a previous model to calculate Qp and furthermore divide it into its components. We have used measurements in urban Granada (southern Spain), of global solar radiation (Rs) to study relationships between the ratio Qpd/Rs with different parameters accounting for solar position, water-vapour absorption and sky conditions. The model performance has been validated with experimental measurements from sites having varied climatic conditions. The model provides acceptable results, with the mean bias error and root mean square error varying between - 0.3 and - 8.8% and between 9.6 and 20.4%, respectively. Direct measurements of this flux are very scarce so that modelling simulations are needed, this is particularly true regarding its diffuse component. We propose a new parameterization to estimate this component using only measured data of solar global irradiance, which facilitates its use for the construction of long-term data series of PAR in regions where continuous measurements of PAR are not yet performed.

Telepresence: A "Real" Component in a Model to Make Human-Computer Interface Factors Meaningful in the Virtual Learning Environment

ERIC Educational Resources Information Center

Selverian, Melissa E. Markaridian; Lombard, Matthew

2009-01-01

A thorough review of the research relating to Human-Computer Interface (HCI) form and content factors in the education, communication and computer science disciplines reveals strong associations of meaningful perceptual "illusions" with enhanced learning and satisfaction in the evolving classroom. Specifically, associations emerge…

[Core factors of schizophrenia structure based on PANSS and SAPS/SANS results. Discerning and head-to-head comparisson of PANSS and SASPS/SANS validity].

PubMed

Masiak, Marek; Loza, Bartosz

2004-01-01

A lot of inconsistencies across dimensional studies of schizophrenia(s) are being unveiled. These problems are strongly related to the methodological aspects of collecting data and specific statistical analyses. Psychiatrists have developed lots of psychopathological models derived from analytic studies based on SAPS/SANS (the Scale for the Assessment of Positive Symptoms/the Scale for the Assessment of Negative Symptoms) and PANSS (The Positive and Negative Syndrome Scale). The unique validation of parallel two independent factor models was performed--ascribed to the same illness and based on different diagnostic scales--to investigate indirect methodological causes of clinical discrepancies. 100 newly admitted patients (mean age--33.5, 18-45, males--64, females--36, hospitalised on average 5.15 times) with paranoid schizophrenia (according to ICD-10) were scored and analysed using PANSS and SAPS/SANS during psychotic exacerbation. All patients were treated with neuroleptics of various kinds with 410mg equivalents of chlorpromazine (atypicals:typicals --> 41:59). Factor analyses were applied to basic results (with principal component analysis, normalised varimax rotation). Investing the cross-model validity, canonical analysis was applied. Models of schizophrenia varied from 3 to 5 factors. PANSS model included: positive, negative, disorganisation, cognitive and depressive components and SAPS/SANS model was dominated by positive, negative and disorganisation factors. The SAPS/SANS accounted for merely 48% of the PANSS common variances. The SAPS/SANS combined measurement preferentially (67% of canonical variance) targeted positive-negative dichotomy. Respectively, PANSS shared positive-negative phenomenology in 35% of its own variance. The general concept of five-dimensionality in paranoid schizophrenia looks clinically more heuristic and statistically more stabilised.

Factors of collaborative working: a framework for a collaboration model.

PubMed

Patel, Harshada; Pettitt, Michael; Wilson, John R

2012-01-01

The ability of organisations to support collaborative working environments is of increasing importance as they move towards more distributed ways of working. Despite the attention collaboration has received from a number of disparate fields, there is a lack of a unified understanding of the component factors of collaboration. As part of our work on a European Integrated Project, CoSpaces, collaboration and collaborative working and the factors which define it were examined through the literature and new empirical work with a number of partner user companies in the aerospace, automotive and construction sectors. This was to support development of a descriptive human factors model of collaboration - the CoSpaces Collaborative Working Model (CCWM). We identified seven main categories of factors involved in collaboration: Context, Support, Tasks, Interaction Processes, Teams, Individuals, and Overarching Factors, and summarised these in a framework which forms a basis for the model. We discuss supporting evidence for the factors which emerged from our fieldwork with user partners, and use of the model in activities such as collaboration readiness profiling. Copyright © 2011 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Optimal experimental design in an epidermal growth factor receptor signalling and down-regulation model.

PubMed

Casey, F P; Baird, D; Feng, Q; Gutenkunst, R N; Waterfall, J J; Myers, C R; Brown, K S; Cerione, R A; Sethna, J P

2007-05-01

We apply the methods of optimal experimental design to a differential equation model for epidermal growth factor receptor signalling, trafficking and down-regulation. The model incorporates the role of a recently discovered protein complex made up of the E3 ubiquitin ligase, Cbl, the guanine exchange factor (GEF), Cool-1 (beta -Pix) and the Rho family G protein Cdc42. The complex has been suggested to be important in disrupting receptor down-regulation. We demonstrate that the model interactions can accurately reproduce the experimental observations, that they can be used to make predictions with accompanying uncertainties, and that we can apply ideas of optimal experimental design to suggest new experiments that reduce the uncertainty on unmeasurable components of the system.

Construct Validation of the Louisiana School Analysis Model (SAM) Instructional Staff Questionnaire

ERIC Educational Resources Information Center

Bray-Clark, Nikki; Bates, Reid

2005-01-01

The purpose of this study was to validate the Louisiana SAM Instructional Staff Questionnaire, a key component of the Louisiana School Analysis Model. The model was designed as a comprehensive evaluation tool for schools. Principle axis factoring with oblique rotation was used to uncover the underlying structure of the SISQ. (Contains 1 table.)

The Robust Learning Model (RLM): A Comprehensive Approach to a New Online University

ERIC Educational Resources Information Center

Neumann, Yoram; Neumann, Edith F.

2010-01-01

This paper outlines the components of the Robust Learning Model (RLM) as a conceptual framework for creating a new online university offering numerous degree programs at all degree levels. The RLM is a multi-factorial model based on the basic belief that successful learning outcomes depend on multiple factors employed together in a holistic…

Damping scaling factors for elastic response spectra for shallow crustal earthquakes in active tectonic regions: "average" horizontal component

USGS Publications Warehouse

Rezaeian, Sanaz; Bozorgnia, Yousef; Idriss, I.M.; Abrahamson, Norman; Campbell, Kenneth; Silva, Walter

2014-01-01

Ground motion prediction equations (GMPEs) for elastic response spectra are typically developed at a 5% viscous damping ratio. In reality, however, structural and nonstructural systems can have other damping ratios. This paper develops a new model for a damping scaling factor (DSF) that can be used to adjust the 5% damped spectral ordinates predicted by a GMPE for damping ratios between 0.5% to 30%. The model is developed based on empirical data from worldwide shallow crustal earthquakes in active tectonic regions. Dependencies of the DSF on potential predictor variables, such as the damping ratio, spectral period, ground motion duration, moment magnitude, source-to-site distance, and site conditions, are examined. The strong influence of duration is captured by the inclusion of both magnitude and distance in the DSF model. Site conditions show weak influence on the DSF. The proposed damping scaling model provides functional forms for the median and logarithmic standard deviation of DSF, and is developed for both RotD50 and GMRotI50 horizontal components. A follow-up paper develops a DSF model for vertical ground motion.

Assessing variance components in multilevel linear models using approximate Bayes factors: A case study of ethnic disparities in birthweight

PubMed Central

Saville, Benjamin R.; Herring, Amy H.; Kaufman, Jay S.

2013-01-01

Racial/ethnic disparities in birthweight are a large source of differential morbidity and mortality worldwide and have remained largely unexplained in epidemiologic models. We assess the impact of maternal ancestry and census tract residence on infant birth weights in New York City and the modifying effects of race and nativity by incorporating random effects in a multilevel linear model. Evaluating the significance of these predictors involves the test of whether the variances of the random effects are equal to zero. This is problematic because the null hypothesis lies on the boundary of the parameter space. We generalize an approach for assessing random effects in the two-level linear model to a broader class of multilevel linear models by scaling the random effects to the residual variance and introducing parameters that control the relative contribution of the random effects. After integrating over the random effects and variance components, the resulting integrals needed to calculate the Bayes factor can be efficiently approximated with Laplace’s method. PMID:24082430

Inverse Problems in Complex Models and Applications to Earth Sciences

NASA Astrophysics Data System (ADS)

Bosch, M. E.

2015-12-01

The inference of the subsurface earth structure and properties requires the integration of different types of data, information and knowledge, by combined processes of analysis and synthesis. To support the process of integrating information, the regular concept of data inversion is evolving to expand its application to models with multiple inner components (properties, scales, structural parameters) that explain multiple data (geophysical survey data, well-logs, core data). The probabilistic inference methods provide the natural framework for the formulation of these problems, considering a posterior probability density function (PDF) that combines the information from a prior information PDF and the new sets of observations. To formulate the posterior PDF in the context of multiple datasets, the data likelihood functions are factorized assuming independence of uncertainties for data originating across different surveys. A realistic description of the earth medium requires modeling several properties and structural parameters, which relate to each other according to dependency and independency notions. Thus, conditional probabilities across model components also factorize. A common setting proceeds by structuring the model parameter space in hierarchical layers. A primary layer (e.g. lithology) conditions a secondary layer (e.g. physical medium properties), which conditions a third layer (e.g. geophysical data). In general, less structured relations within model components and data emerge from the analysis of other inverse problems. They can be described with flexibility via direct acyclic graphs, which are graphs that map dependency relations between the model components. Examples of inverse problems in complex models can be shown at various scales. At local scale, for example, the distribution of gas saturation is inferred from pre-stack seismic data and a calibrated rock-physics model. At regional scale, joint inversion of gravity and magnetic data is applied for the estimation of lithological structure of the crust, with the lithotype body regions conditioning the mass density and magnetic susceptibility fields. At planetary scale, the Earth mantle temperature and element composition is inferred from seismic travel-time and geodetic data.

Modeling the macrodynamics of international migration: determinants of emigration from Cyprus, 1946-85.

PubMed

Diamantides, N D; Constantinou, S T

1989-07-01

"A model is presented of international migration that is based on the concept of a pool of potential emigrants at the origin created by push-pull forces and by the establishment of information feedback between origin and destination. The forces can be economic, political, or both, and are analytically expressed by the 'mediating factor'. The model is macrodynamic in nature and provides both for the main secular component of the migratory flow and for transient components caused by extraordinary events. The model is expressed in a Bernoulli-type differential equation through which quantitative weights can be derived for each of the operating causes. Out-migration from the Republic of Cyprus is used to test the tenets of the model." excerpt

Hospital survey on patient safety culture: psychometric analysis on a Scottish sample.

PubMed

Sarac, Cakil; Flin, Rhona; Mearns, Kathryn; Jackson, Jeanette

2011-10-01

To investigate the psychometric properties of the Hospital Survey on Patient Safety Culture on a Scottish NHS data set. The data were collected from 1969 clinical staff (estimated 22% response rate) from one acute hospital from each of seven Scottish Health boards. Using a split-half validation technique, the data were randomly split; an exploratory factor analysis was conducted on the calibration data set, and confirmatory factor analyses were conducted on the validation data set to investigate and check the original US model fit in a Scottish sample. Following the split-half validation technique, exploratory factor analysis results showed a 10-factor optimal measurement model. The confirmatory factor analyses were then performed to compare the model fit of two competing models (10-factor alternative model vs 12-factor original model). An S-B scaled χ(2) square difference test demonstrated that the original 12-factor model performed significantly better in a Scottish sample. Furthermore, reliability analyses of each component yielded satisfactory results. The mean scores on the climate dimensions in the Scottish sample were comparable with those found in other European countries. This study provided evidence that the original 12-factor structure of the Hospital Survey on Patient Safety Culture scale has been replicated in this Scottish sample. Therefore, no modifications are required to the original 12-factor model, which is suggested for use, since it would allow researchers the possibility of cross-national comparisons.

Modeling Systems-Level Regulation of Host Immune Responses

PubMed Central

Thakar, Juilee; Pilione, Mylisa; Kirimanjeswara, Girish; Harvill, Eric T; Albert, Réka

2007-01-01

Many pathogens are able to manipulate the signaling pathways responsible for the generation of host immune responses. Here we examine and model a respiratory infection system in which disruption of host immune functions or of bacterial factors changes the dynamics of the infection. We synthesize the network of interactions between host immune components and two closely related bacteria in the genus Bordetellae. We incorporate existing experimental information on the timing of immune regulatory events into a discrete dynamic model, and verify the model by comparing the effects of simulated disruptions to the experimental outcome of knockout mutations. Our model indicates that the infection time course of both Bordetellae can be separated into three distinct phases based on the most active immune processes. We compare and discuss the effect of the species-specific virulence factors on disrupting the immune response during their infection of naive, antibody-treated, diseased, or convalescent hosts. Our model offers predictions regarding cytokine regulation, key immune components, and clearance of secondary infections; we experimentally validate two of these predictions. This type of modeling provides new insights into the virulence, pathogenesis, and host adaptation of disease-causing microorganisms and allows systems-level analysis that is not always possible using traditional methods. PMID:17559300

Models of borderline personality disorder: recent advances and new perspectives.

PubMed

D'Agostino, Alessandra; Rossi Monti, Mario; Starcevic, Vladan

2018-01-01

The purpose of this article is to review the most relevant conceptual models of borderline personality disorder (BPD), with a focus on recent developments in this area. Several conceptual models have been proposed with the aim of better understanding BPD: the borderline personality organization, emotion dysregulation, reflective (mentalization) dysfunction, interpersonal hypersensitivity and hyperbolic temperament models. These models have all been supported to some extent and their common components include disorganized attachment and traumatic early experiences, emotion dysregulation, interpersonal sensitivity and difficulties with social cognition. An attempt to integrate some components of the conceptual models of BPD has resulted in an emerging new perspective, the interpersonal dysphoria model, which emphasizes dysphoria as an overarching phenomenon that connects the dispositional and situational aspects of BPD. Various conceptual models have expanded our understanding of BPD, but it appears that further development entails theoretical integration. More research is needed to better understand interactions between various components of BPD, including the situational factors that activate symptoms of BPD. This will help develop therapeutic approaches that are more tailored to the heterogeneous psychopathology of BPD.

Research environments that promote integrity.

PubMed

Jeffers, Brenda Recchia; Whittemore, Robin

2005-01-01

The body of empirical knowledge about research integrity and the factors that promote research integrity in nursing research environments remains small. To propose an internal control model as an innovative framework for the design and structure of nursing research environments that promote integrity. An internal control model is adapted to illustrate its use for conceptualizing and designing research environments that promote integrity. The internal control model integrates both the organizational elements necessary to promote research integrity and the processes needed to assess research environments. The model provides five interrelated process components within which any number of research integrity variables and processes may be used and studied: internal control environment, risk assessment, internal control activities, monitoring, and information and communication. The components of the proposed research integrity internal control model proposed comprise an integrated conceptualization of the processes that provide reasonable assurance that research integrity will be promoted within the nursing research environment. Schools of nursing can use the model to design, implement, and evaluate systems that promote research integrity. The model process components need further exploration to substantiate the use of the model in nursing research environments.

Functional Data Analysis in NTCP Modeling: A New Method to Explore the Radiation Dose-Volume Effects

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

Benadjaoud, Mohamed Amine, E-mail: mohamedamine.benadjaoud@gustaveroussy.fr; Université Paris sud, Le Kremlin-Bicêtre; Institut Gustave Roussy, Villejuif

2014-11-01

Purpose/Objective(s): To describe a novel method to explore radiation dose-volume effects. Functional data analysis is used to investigate the information contained in differential dose-volume histograms. The method is applied to the normal tissue complication probability modeling of rectal bleeding (RB) for patients irradiated in the prostatic bed by 3-dimensional conformal radiation therapy. Methods and Materials: Kernel density estimation was used to estimate the individual probability density functions from each of the 141 rectum differential dose-volume histograms. Functional principal component analysis was performed on the estimated probability density functions to explore the variation modes in the dose distribution. The functional principalmore » components were then tested for association with RB using logistic regression adapted to functional covariates (FLR). For comparison, 3 other normal tissue complication probability models were considered: the Lyman-Kutcher-Burman model, logistic model based on standard dosimetric parameters (LM), and logistic model based on multivariate principal component analysis (PCA). Results: The incidence rate of grade ≥2 RB was 14%. V{sub 65Gy} was the most predictive factor for the LM (P=.058). The best fit for the Lyman-Kutcher-Burman model was obtained with n=0.12, m = 0.17, and TD50 = 72.6 Gy. In PCA and FLR, the components that describe the interdependence between the relative volumes exposed at intermediate and high doses were the most correlated to the complication. The FLR parameter function leads to a better understanding of the volume effect by including the treatment specificity in the delivered mechanistic information. For RB grade ≥2, patients with advanced age are significantly at risk (odds ratio, 1.123; 95% confidence interval, 1.03-1.22), and the fits of the LM, PCA, and functional principal component analysis models are significantly improved by including this clinical factor. Conclusion: Functional data analysis provides an attractive method for flexibly estimating the dose-volume effect for normal tissues in external radiation therapy.« less

DEVELOPMENT OF A MICROSCALE EMISSION FACTOR MODEL FOR PARTICULATE MATTER (MICROFACPM) FOR PREDICTING REAL TIME MOTOR VEHICLE EMISSIONS

EPA Science Inventory

Health risk evaluation needs precise measurement and modeling of human exposures in microenvironments to support review of current air quality standards. The particulate matter emissions from motor vehicles are a major component of human exposures in urban microenvironments. Cu...

THE ABCS OF SNOWMELT: A TOPOGRAPHICALLY FACTORIZED ENERGY COMPONENT SNOWMELT MODEL. (R824784)

EPA Science Inventory

Because of the crucial role snowmelt plays in many watersheds around the world, it is important to understand and accurately quantify the melt process. As such, numerous mathematical models attempting to describe and predict snowmelt have arisen. There are two main categories of ...

Simulation for Prediction of Entry Article Demise (SPEAD): an Analysis Tool for Spacecraft Safety Analysis and Ascent/Reentry Risk Assessment

NASA Technical Reports Server (NTRS)

Ling, Lisa

2014-01-01

For the purpose of performing safety analysis and risk assessment for a probable offnominal suborbital/orbital atmospheric reentry resulting in vehicle breakup, a synthesis of trajectory propagation coupled with thermal analysis and the evaluation of node failure is required to predict the sequence of events, the timeline, and the progressive demise of spacecraft components. To provide this capability, the Simulation for Prediction of Entry Article Demise (SPEAD) analysis tool was developed. This report discusses the capabilities, modeling, and validation of the SPEAD analysis tool. SPEAD is applicable for Earth or Mars, with the option for 3 or 6 degrees-of-freedom (DOF) trajectory propagation. The atmosphere and aerodynamics data are supplied in tables, for linear interpolation of up to 4 independent variables. The gravitation model can include up to 20 zonal harmonic coefficients. The modeling of a single motor is available and can be adapted to multiple motors. For thermal analysis, the aerodynamic radiative and free-molecular/continuum convective heating, black-body radiative cooling, conductive heat transfer between adjacent nodes, and node ablation are modeled. In a 6- DOF simulation, the local convective heating on a node is a function of Mach, angle-ofattack, and sideslip angle, and is dependent on 1) the location of the node in the spacecraft and its orientation to the flow modeled by an exposure factor, and 2) the geometries of the spacecraft and the node modeled by a heating factor and convective area. Node failure is evaluated using criteria based on melting temperature, reference heat load, g-load, or a combination of the above. The failure of a liquid propellant tank is evaluated based on burnout flux from nucleate boiling or excess internal pressure. Following a component failure, updates are made as needed to the spacecraft mass and aerodynamic properties, nodal exposure and heating factors, and nodal convective and conductive areas. This allows the trajectory to be propagated seamlessly in a single run, inclusive of the trajectories of components that have separated from the spacecraft. The node ablation simulates the decreasing mass and convective/reference areas, and variable heating factor. A built-in database provides the thermo-mechanical properties of For the purpose of performing safety analysis and risk assessment for a probable offnominal suborbital/orbital atmospheric reentry resulting in vehicle breakup, a synthesis of trajectory propagation coupled with thermal analysis and the evaluation of node failure is required to predict the sequence of events, the timeline, and the progressive demise of spacecraft components. To provide this capability, the Simulation for Prediction of Entry Article Demise (SPEAD) analysis tool was developed. This report discusses the capabilities, modeling, and validation of the SPEAD analysis tool. SPEAD is applicable for Earth or Mars, with the option for 3 or 6 degrees-of-freedom (DOF) trajectory propagation. The atmosphere and aerodynamics data are supplied in tables, for linear interpolation of up to 4 independent variables. The gravitation model can include up to 20 zonal harmonic coefficients. The modeling of a single motor is available and can be adapted to multiple motors. For thermal analysis, the aerodynamic radiative and free-molecular/continuum convective heating, black-body radiative cooling, conductive heat transfer between adjacent nodes, and node ablation are modeled. In a 6- DOF simulation, the local convective heating on a node is a function of Mach, angle-ofattack, and sideslip angle, and is dependent on 1) the location of the node in the spacecraft and its orientation to the flow modeled by an exposure factor, and 2) the geometries of the spacecraft and the node modeled by a heating factor and convective area. Node failure is evaluated using criteria based on melting temperature, reference heat load, g-load, or a combination of the above. The failure of a liquid propellant tank is evaluated based on burnout flux from nucleate boiling or excess internal pressure. Following a component failure, updates are made as needed to the spacecraft mass and aerodynamic properties, nodal exposure and heating factors, and nodal convective and conductive areas. This allows the trajectory to be propagated seamlessly in a single run, inclusive of the trajectories of components that have separated from the spacecraft. The node ablation simulates the decreasing mass and convective/reference areas, and variable heating factor. A built-in database provides the thermo-mechanical properties of

Item-Level Psychometrics of the Glasgow Outcome Scale: Extended Structured Interviews.

PubMed

Hong, Ickpyo; Li, Chih-Ying; Velozo, Craig A

2016-04-01

The Glasgow Outcome Scale-Extended (GOSE) structured interview captures critical components of activities and participation, including home, shopping, work, leisure, and family/friend relationships. Eighty-nine community dwelling adults with mild-moderate traumatic brain injury (TBI) were recruited (average = 2.7 year post injury). Nine items of the 19 items were used for the psychometrics analysis purpose. Factor analysis and item-level psychometrics were investigated using the Rasch partial-credit model. Although the principal components analysis of residuals suggests that a single measurement factor dominates the measure, the instrument did not meet the factor analysis criteria. Five items met the rating scale criteria. Eight items fit the Rasch model. The instrument demonstrated low person reliability (0.63), low person strata (2.07), and a slight ceiling effect. The GOSE demonstrated limitations in precisely measuring activities/participation for individuals after TBI. Future studies should examine the impact of the low precision of the GOSE on effect size. © The Author(s) 2016.

Application of Semiparametric Spline Regression Model in Analyzing Factors that In uence Population Density in Central Java

NASA Astrophysics Data System (ADS)

Sumantari, Y. D.; Slamet, I.; Sugiyanto

2017-06-01

Semiparametric regression is a statistical analysis method that consists of parametric and nonparametric regression. There are various approach techniques in nonparametric regression. One of the approach techniques is spline. Central Java is one of the most densely populated province in Indonesia. Population density in this province can be modeled by semiparametric regression because it consists of parametric and nonparametric component. Therefore, the purpose of this paper is to determine the factors that in uence population density in Central Java using the semiparametric spline regression model. The result shows that the factors which in uence population density in Central Java is Family Planning (FP) active participants and district minimum wage.

Interactive effects of global change factors on soil respiration and its components: a meta-analysis.

PubMed

Zhou, Lingyan; Zhou, Xuhui; Shao, Junjiong; Nie, Yuanyuan; He, Yanghui; Jiang, Liling; Wu, Zhuoting; Hosseini Bai, Shahla

2016-09-01

As the second largest carbon (C) flux between the atmosphere and terrestrial ecosystems, soil respiration (Rs) plays vital roles in regulating atmospheric CO2 concentration ([CO2 ]) and climatic dynamics in the earth system. Although numerous manipulative studies and a few meta-analyses have been conducted to determine the responses of Rs and its two components [i.e., autotrophic (Ra) and heterotrophic (Rh) respiration] to single global change factors, the interactive effects of the multiple factors are still unclear. In this study, we performed a meta-analysis of 150 multiple-factor (≥2) studies to examine the main and interactive effects of global change factors on Rs and its two components. Our results showed that elevated [CO2 ] (E), nitrogen addition (N), irrigation (I), and warming (W) induced significant increases in Rs by 28.6%, 8.8%, 9.7%, and 7.1%, respectively. The combined effects of the multiple factors, EN, EW, DE, IE, IN, IW, IEW, and DEW, were also significantly positive on Rs to a greater extent than those of the single-factor ones. For all the individual studies, the additive interactions were predominant on Rs (90.6%) and its components (≈70.0%) relative to synergistic and antagonistic ones. However, the different combinations of global change factors (e.g., EN, NW, EW, IW) indicated that the three types of interactions were all important, with two combinations for synergistic effects, two for antagonistic, and five for additive when at least eight independent experiments were considered. In addition, the interactions of elevated [CO2 ] and warming had opposite effects on Ra and Rh, suggesting that different processes may influence their responses to the multifactor interactions. Our study highlights the crucial importance of the interactive effects among the multiple factors on Rs and its components, which could inform regional and global models to assess the climate-biosphere feedbacks and improve predictions of the future states of the ecological and climate systems. © 2016 John Wiley & Sons Ltd.

Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

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

Matsuo, Yukinori, E-mail: ymatsuo@kuhp.kyoto-u.ac.

Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiplemore » causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.« less

Probabilistic modeling of discourse-aware sentence processing.

PubMed

Dubey, Amit; Keller, Frank; Sturt, Patrick

2013-07-01

Probabilistic models of sentence comprehension are increasingly relevant to questions concerning human language processing. However, such models are often limited to syntactic factors. This restriction is unrealistic in light of experimental results suggesting interactions between syntax and other forms of linguistic information in human sentence processing. To address this limitation, this article introduces two sentence processing models that augment a syntactic component with information about discourse co-reference. The novel combination of probabilistic syntactic components with co-reference classifiers permits them to more closely mimic human behavior than existing models. The first model uses a deep model of linguistics, based in part on probabilistic logic, allowing it to make qualitative predictions on experimental data; the second model uses shallow processing to make quantitative predictions on a broad-coverage reading-time corpus. Copyright © 2013 Cognitive Science Society, Inc.

Effects of changes along the risk chain on flood risk

NASA Astrophysics Data System (ADS)

Duha Metin, Ayse; Apel, Heiko; Viet Dung, Nguyen; Guse, Björn; Kreibich, Heidi; Schröter, Kai; Vorogushyn, Sergiy; Merz, Bruno

2017-04-01

Interactions of hydrological and socio-economic factors shape flood disaster risk. For this reason, assessment of flood risk ideally takes into account the whole flood risk chain from atmospheric processes, through the catchment and river system processes to the damage mechanisms in the affected areas. Since very different processes at various scales are interacting along the flood risk, the impact of the single components is rather unclear. However for flood risk management, it is required to know the controlling factor of flood damages. The present study, using the flood-prone Mulde catchment in Germany, discusses the sensitivity of flood risk to disturbances along the risk chain: How do disturbances propagate through the risk chain? How do different disturbances combine or conflict and affect flood risk? In this sensitivity analysis, the five components of the flood risk change are included. These are climate, catchment, river system, exposure and vulnerability. A model framework representing the complete risk chain is combined with observational data to understand how the sensitivities evolve along the risk chain by considering three plausible change scenarios for each of five components. The flood risk is calculated by using the Regional Flood Model (RFM) which is based on a continuous simulation approach, including rainfall-runoff, 1D river network, 2D hinterland inundation and damage estimation models. The sensitivity analysis covers more than 240 scenarios with different combinations of the five components. It is investigated how changes in different components affect risk indicators, such as the risk curve and expected annual damage (EAD). In conclusion, it seems that changes in exposure and vulnerability seem to outweigh changes in hazard.

[New method of mixed gas infrared spectrum analysis based on SVM].

PubMed

Bai, Peng; Xie, Wen-Jun; Liu, Jun-Hua

2007-07-01

A new method of infrared spectrum analysis based on support vector machine (SVM) for mixture gas was proposed. The kernel function in SVM was used to map the seriously overlapping absorption spectrum into high-dimensional space, and after transformation, the high-dimensional data could be processed in the original space, so the regression calibration model was established, then the regression calibration model with was applied to analyze the concentration of component gas. Meanwhile it was proved that the regression calibration model with SVM also could be used for component recognition of mixture gas. The method was applied to the analysis of different data samples. Some factors such as scan interval, range of the wavelength, kernel function and penalty coefficient C that affect the model were discussed. Experimental results show that the component concentration maximal Mean AE is 0.132%, and the component recognition accuracy is higher than 94%. The problems of overlapping absorption spectrum, using the same method for qualitative and quantitative analysis, and limit number of training sample, were solved. The method could be used in other mixture gas infrared spectrum analyses, promising theoretic and application values.

Staying in the zone: offshore drillers' situation awareness.

PubMed

Roberts, Ruby; Flin, Rhona; Cleland, Jennifer

2015-06-01

The aim of this study was to identify the cognitive components required for offshore drillers to develop and maintain situation awareness (SA) while controlling subsea hydrocarbon wells. SA issues are often identified as contributing factors to drilling incidents, most recently in the Deepwater Horizon blowout. Yet, there is a limited body of research investigating SA in the offshore drilling environment. In the first study, critical incident interviews were conducted with 18 experienced drilling personnel. Transcripts were subjected to theory-driven thematic analysis, producing a preliminary cognitive framework of how drillers develop and maintain SA during well control. In the second study, 24 hr of observations (in vivo and video) of drillers managing a high fidelity well-control simulator were analyzed to further develop the framework. The cognitive components that enable drillers to build up an understanding of what is happening in the wellbore and surrounding environment, to predict how this understanding may develop, were identified. These components included cue recognition, interpretation of information in conjunction with the current mental model, and projection through mental simulation. Factors such as distracters, expectations, and information sharing between crew members can both positively and negatively influence the drillers' SA. The findings give a preliminary understanding into the components of drillers' SA, highlighting the importance of SA for safe and effective performance and indicating that Endsley's model of SA can be applied to drilling. The results have consequences for training, task management, and work design recommendations. © 2014, Human Factors and Ergonomics Society.

Evaluating the Bulk Lorentz Factors of Outflow Material: Lessons Learned from the Extremely Energetic Outburst GRB 160625B

NASA Astrophysics Data System (ADS)

Wang, Yuan-Zhu; Wang, Hao; Zhang, Shuai; Liang, Yun-Feng; Jin, Zhi-Ping; He, Hao-Ning; Liao, Neng-Hui; Fan, Yi-Zhong; Wei, Da-Ming

2017-02-01

GRB 160625B is an extremely bright outburst with well-monitored afterglow emission. The geometry-corrected energy is high, up to ˜5.2 × 1052 erg or even ˜8 × 1052 erg, rendering it the most energetic GRB prompt emission recorded so far. We analyzed the time-resolved spectra of the prompt emission and found that in some intervals there were likely thermal-radiation components and the high energy emission was characterized by significant cutoff. The bulk Lorentz factors of the outflow material are estimated accordingly. We found out that the Lorentz factors derived in the thermal-radiation model are consistent with the luminosity-Lorentz factor correlation found in other bursts, as well as in GRB 090902B for the time-resolved thermal-radiation components, while the spectral cutoff model yields much lower Lorentz factors that are in tension with the constraints set by the electron pair Compton scattering process. We then suggest that these spectral cutoffs are more likely related to the particle acceleration process and that one should be careful in estimating the Lorentz factors if the spectrum cuts at a rather low energy (e.g., ˜tens of MeV). The nature of the central engine has also been discussed, and a stellar-mass black hole is favored.

Evaluation of Four Methods for Predicting Carbon Stocks of Korean Pine Plantations in Heilongjiang Province, China

PubMed Central

Gao, Huilin; Dong, Lihu; Li, Fengri; Zhang, Lianjun

2015-01-01

A total of 89 trees of Korean pine (Pinus koraiensis) were destructively sampled from the plantations in Heilongjiang Province, P.R. China. The sample trees were measured and calculated for the biomass and carbon stocks of tree components (i.e., stem, branch, foliage and root). Both compatible biomass and carbon stock models were developed with the total biomass and total carbon stocks as the constraints, respectively. Four methods were used to evaluate the carbon stocks of tree components. The first method predicted carbon stocks directly by the compatible carbon stocks models (Method 1). The other three methods indirectly predicted the carbon stocks in two steps: (1) estimating the biomass by the compatible biomass models, and (2) multiplying the estimated biomass by three different carbon conversion factors (i.e., carbon conversion factor 0.5 (Method 2), average carbon concentration of the sample trees (Method 3), and average carbon concentration of each tree component (Method 4)). The prediction errors of estimating the carbon stocks were compared and tested for the differences between the four methods. The results showed that the compatible biomass and carbon models with tree diameter (D) as the sole independent variable performed well so that Method 1 was the best method for predicting the carbon stocks of tree components and total. There were significant differences among the four methods for the carbon stock of stem. Method 2 produced the largest error, especially for stem and total. Methods 3 and Method 4 were slightly worse than Method 1, but the differences were not statistically significant. In practice, the indirect method using the mean carbon concentration of individual trees was sufficient to obtain accurate carbon stocks estimation if carbon stocks models are not available. PMID:26659257

Simultaneous UV and X-ray Spectroscopy of the Seyfert 1 Galaxy NGC 5548. I: Physical Conditions in the UV Absorbers

NASA Technical Reports Server (NTRS)

Crenshaw, D. M.; Kraemer, S. B.; Gabel, J. R.; Kaastra, J. S.; Steenbrugge, K. C.; Brinkman, A. C.; Dunn, J. P.; George, I. M.; Liedahl, D. A.; Paerels, F. B. S.

2003-01-01

We present new UV spectra of the nucleus of the Seyfert 1 galaxy NGC 5548, which we obtained with the Space Telescope Imaging Spectrograph at high spectral resolution, in conjunction with simultaneous Chandra X-ray Observatory spectra. Taking advantage of the low UV continuum and broad emission-line fluxes, we have determined that the deepest UV absorption component covers at least a portion of the inner, high-ionization narrow-line region (NLR). We find nonunity covering factors in the cores of several kinematic components, which increase the column density measurements of N V and C IV by factors of 1.2 to 1.9 over the full-covering case; however, the revised columns have only a minor effect on the parameters derived from our photoionization models. For the first time, we have simultaneous N V and C IV columns for component 1 (at -1040 km/s), and find that this component cannot be an X-ray warm absorber, contrary to our previous claim based on nonsimultaneous observations. We find that models of the absorbers based on solar abundances severely overpredict the O VI columns previously obtained with the Far Ultraviolet Spectrograph, and present arguments that this is not likely due to variability. However, models that include either enhanced nitrogen (twice solar) or dust, with strong depletion of carbon in either case, are successful in matching all of the observed ionic columns. These models result in substantially lower ionization parameters and total column densities compared to dust-free solar-abundance models, and produce little O VII or O VIII, indicating that none of the UV absorbers are X-ray warm absorbers.

The Effect of Multidimensional Motivation Interventions on Cognitive and Behavioral Components of Motivation: Testing Martin's Model

PubMed Central

Pooragha Roodbarde, Fatemeh; Talepasand, Siavash; Rahimian Boogar, Issac

2017-01-01

Objective: The present study aimed at examining the effect of multidimensional motivation interventions based on Martin's model on cognitive and behavioral components of motivation. Method: The research design was prospective with pretest, posttest, and follow-up, and 2 experimental groups. In this study, 90 students (45 participants in the experimental group and 45 in the control group) constituted the sample of the study, and they were selected by available sampling method. Motivation interventions were implemented for fifteen 60-minute sessions 3 times a week, which lasted for about 2 months. Data were analyzed using repeated measures multivariate variance analysis test. Results: The findings revealed that multidimensional motivation interventions resulted in a significant increase in the scores of cognitive components such as self-efficacy, mastery goal, test anxiety, and feeling of lack of control, and behavioral components such as task management. The results of one-month follow-up indicated the stability of the created changes in test anxiety and cognitive strategies; however, no significant difference was found between the 2 groups at the follow-up in self-efficacy, mastery goals, source of control, and motivation. Conclusion: The research evidence indicated that academic motivation is a multidimensional component and is affected by cognitive and behavioral factors; therefore, researchers, teachers, and other authorities should attend to these factors to increase academic motivation. PMID:28659984

The Effect of Multidimensional Motivation Interventions on Cognitive and Behavioral Components of Motivation: Testing Martin's Model.

PubMed

Pooragha Roodbarde, Fatemeh; Talepasand, Siavash; Rahimian Boogar, Issac

2017-04-01

Objective: The present study aimed at examining the effect of multidimensional motivation interventions based on Martin's model on cognitive and behavioral components of motivation. Method: The research design was prospective with pretest, posttest, and follow-up, and 2 experimental groups. In this study, 90 students (45 participants in the experimental group and 45 in the control group) constituted the sample of the study, and they were selected by available sampling method. Motivation interventions were implemented for fifteen 60-minute sessions 3 times a week, which lasted for about 2 months. Data were analyzed using repeated measures multivariate variance analysis test. Results: The findings revealed that multidimensional motivation interventions resulted in a significant increase in the scores of cognitive components such as self-efficacy, mastery goal, test anxiety, and feeling of lack of control, and behavioral components such as task management. The results of one-month follow-up indicated the stability of the created changes in test anxiety and cognitive strategies; however, no significant difference was found between the 2 groups at the follow-up in self-efficacy, mastery goals, source of control, and motivation. Conclusion: The research evidence indicated that academic motivation is a multidimensional component and is affected by cognitive and behavioral factors; therefore, researchers, teachers, and other authorities should attend to these factors to increase academic motivation.

The Latent Structure of Memory: A Confirmatory Factor-Analytic Study of Memory Distinctions.

ERIC Educational Resources Information Center

Herrman, Douglas J.; Schooler, Carmi; Caplan, Leslie J.; Lipman, Paula Darby; Grafman, Jordan; Schoenbach, Carrie; Schwab, Karen; Johnson, Marnie L.

2001-01-01

Used confirmatory factor analysis to study the nature of memory distinctions underlying the performance of two samples of Vietnam veterans. One sample (n=96) had received head injuries resulting in relatively small lesions; the other (n=85) had not. A four-component model with verbal-episodic, visual-episodic, semantic, and short-term memory…

78 FR 20160 - Self-Regulatory Organizations; Chicago Mercantile Exchange Inc.; Notice of Withdrawal of Proposed...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-03

... change to make adjustments to the liquidity risk factor component of its credit default swap (``CDS'') margin model. The proposed rule change would permit CME to use an index portfolio's market risk rather... Liquidity Factor of CME's CDS Margin Methodology March 28, 2013. On December 10, 2012, Chicago Mercantile...

Factors Affecting Faculty Use of Learning Technologies: Implications for Models of Technology Adoption

ERIC Educational Resources Information Center

Buchanan, Tom; Sainter, Phillip; Saunders, Gunter

2013-01-01

This study examines factors associated with the use of learning technologies by higher education faculty. In an online survey in a UK university, 114 faculty respondents completed a measure of Internet self-efficacy, and reported on their use of learning technologies along with barriers to their adoption. Principal components analysis suggested…

An integrated model of soil, hydrology, and vegetation for carbon dynamics in wetland ecosystems

Treesearch

Yu Zhang; Changsheng Li; Carl C. Trettin; Harbin Li; Ge Sun

2002-01-01

Wetland ecosystems are an important component in global carbon (C) cycles and may exert a large influence on global clinlate change. Predictions of C dynamics require us to consider interactions among many critical factors of soil, hydrology, and vegetation. However, few such integrated C models exist for wetland ecosystems. In this paper, we report a simulation model...

A constrained multinomial Probit route choice model in the metro network: Formulation, estimation and application

PubMed Central

Zhang, Yongsheng; Wei, Heng; Zheng, Kangning

2017-01-01

Considering that metro network expansion brings us with more alternative routes, it is attractive to integrate the impacts of routes set and the interdependency among alternative routes on route choice probability into route choice modeling. Therefore, the formulation, estimation and application of a constrained multinomial probit (CMNP) route choice model in the metro network are carried out in this paper. The utility function is formulated as three components: the compensatory component is a function of influencing factors; the non-compensatory component measures the impacts of routes set on utility; following a multivariate normal distribution, the covariance of error component is structured into three parts, representing the correlation among routes, the transfer variance of route, and the unobserved variance respectively. Considering multidimensional integrals of the multivariate normal probability density function, the CMNP model is rewritten as Hierarchical Bayes formula and M-H sampling algorithm based Monte Carlo Markov Chain approach is constructed to estimate all parameters. Based on Guangzhou Metro data, reliable estimation results are gained. Furthermore, the proposed CMNP model also shows a good forecasting performance for the route choice probabilities calculation and a good application performance for transfer flow volume prediction. PMID:28591188

Can the cosmic x ray and gamma ray background be due to reflection of a steep power law spectrum and Compton scattering by relativistic electrons?

NASA Technical Reports Server (NTRS)

Zycki, Piotr T.; Zdziarski, Andrzej A.; Svensson, Roland

1991-01-01

We reconsider the recent model for the origin in the cosmic X-ray and gamma-ray background by Rogers and Field. The background in the model is due to an unresolved population of AGNs. An individual AGN spectrum contains three components: a power law with the energy index of alpha = 1.1, an enhanced reflection component, and a component from Compton scattering by relativistic electrons with a low energy cutoff at some minimum Lorentz factor, gamma(sub min) much greater than 1. The MeV bump seen in the gamma-ray background is then explained by inverse Compton emission by the electrons. We show that the model does not reproduce the shape of the observed X-ray and gamma-ray background below 10 MeV and that it overproduces the background at larger energies. Furthermore, we find the assumptions made for the Compton component to be physically inconsistent. Relaxing the inconsistent assumptions leads to model spectra even more different from that of the observed cosmic background. Thus, we can reject the hypothesis that the high-energy cosmic background is due to the described model.

The principal components model: a model for advancing spirituality and spiritual care within nursing and health care practice.

PubMed

McSherry, Wilfred

2006-07-01

The aim of this study was to generate a deeper understanding of the factors and forces that may inhibit or advance the concepts of spirituality and spiritual care within both nursing and health care. This manuscript presents a model that emerged from a qualitative study using grounded theory. Implementation and use of this model may assist all health care practitioners and organizations to advance the concepts of spirituality and spiritual care within their own sphere of practice. The model has been termed the principal components model because participants identified six components as being crucial to the advancement of spiritual health care. Grounded theory was used meaning that there was concurrent data collection and analysis. Theoretical sampling was used to develop the emerging theory. These processes, along with data analysis, open, axial and theoretical coding led to the identification of a core category and the construction of the principal components model. Fifty-three participants (24 men and 29 women) were recruited and all consented to be interviewed. The sample included nurses (n=24), chaplains (n=7), a social worker (n=1), an occupational therapist (n=1), physiotherapists (n=2), patients (n=14) and the public (n=4). The investigation was conducted in three phases to substantiate the emerging theory and the development of the model. The principal components model contained six components: individuality, inclusivity, integrated, inter/intra-disciplinary, innate and institution. A great deal has been written on the concepts of spirituality and spiritual care. However, rhetoric alone will not remove some of the intrinsic and extrinsic barriers that are inhibiting the advancement of the spiritual dimension in terms of theory and practice. An awareness of and adherence to the principal components model may assist nurses and health care professionals to engage with and overcome some of the structural, organizational, political and social variables that are impacting upon spiritual care.

Warm and cold molecular gas conditions modeled in 87 galaxies observed by the Herschel SPIRE FTS

NASA Astrophysics Data System (ADS)

Kamenetzky, Julia; Rangwala, Naseem; Glenn, Jason

2018-01-01

Molecular gas is the raw material for star formation, and like the interstellar medium (ISM) in general, it can exist in regions of higher and lower excitation. Rotational transitions of the CO molecule are bright and sensitive to cold molecular gas. While the majority of the molecular gas exists in the very cold component traced by CO J=1-0, the higher-J lines trace the highly excited gas that may be more indicative of star formation processes. The atmosphere is opaque to these lines, but the launch of the Herschel Space Observatory made them accessible for study of Galactic and extragalactic sources. We have conducted two-component, non-local thermodynamic equilibrium (non-LTE) modeling of the CO lines from J=1‑0 through J=13‑12 in 87 galaxies observed by the Herschel SPIRE Fourier Transform Spectrometer (FTS). We used the nested sampling algorithm Multinest to compare the measured CO spectral line energy distributions (SLEDs) to the ones produced by a custom version of the non-LTE code RADEX. This allowed us to fully examine the degeneracies in parameter space for kinetic temperature, molecular gas density, CO column density, and area filling factor.Here we discuss the major findings of our study, as well as the important implications of two-component molecular gas modeling. The average pressure of the warm gas is slightly correlated with galaxy LFIR, but that of the cold gas is not. A high-J (such as J=11-10) to J=1-0 line ratio is diagnostic of warm component pressure. We find a very large spread in our derived values of "alpha-CO," with no discernable trend with LFIR, and average molecular gas depletion times that decrease with LFIR. If only a few molecular lines are available in a galaxy's SLED, the limited ability to model only one component will change the results. A one-component fit often underestimates the flux of carbon monoxide (CO) J=1‑0 and the mass. If low-J lines are not included, mass is underestimated by an order of magnitude. Even when modeling the low-J lines alone or using a CO-to-mass conversion factor, the mass should be considered to be uncertain to a factor of at least 0.4 dex, and the vast majority of the CO luminosity will be missed (median, 65 per cent).

Conceptualizing the dynamics of workplace stress: a systems-based study of nursing aides.

PubMed

Jetha, Arif; Kernan, Laura; Kurowski, Alicia

2017-01-05

Workplace stress is a complex phenomenon that may often be dynamic and evolving over time. Traditional linear modeling does not allow representation of recursive feedback loops among the implicated factors. The objective of this study was to develop a multidimensional system dynamics model (SDM) of workplace stress among nursing aides and conduct simulations to illustrate how changes in psychosocial perceptions and workplace factors might influence workplace stress over time. Eight key informants with prior experience in a large study of US nursing home workers participated in model building. Participants brainstormed the range of components related to workplace stress. Components were grouped together based on common themes and translated into feedback loops. The SDM was parameterized through key informant insight on the shape and magnitude of the relationship between model components. Model construction was also supported utilizing survey data collected as part of the larger study. All data was entered into the software program, Vensim. Simulations were conducted to examine how adaptations to model components would influence workplace stress. The SDM included perceptions of organizational conditions (e.g., job demands and job control), workplace social support (i.e., managerial and coworker social support), workplace safety, and demands outside of work (i.e. work-family conflict). Each component was part of a reinforcing feedback loop. Simulations exhibited that scenarios with increasing job control and decreasing job demands led to a decline in workplace stress. Within the context of the system, the effects of workplace social support, workplace safety, and work-family conflict were relatively minor. SDM methodology offers a unique perspective for researchers and practitioners to view workplace stress as a dynamic process. The portrayal of multiple recursive feedback loops can guide the development of policies and programs within complex organizational contexts with attention both to interactions among causes and avoidance of adverse unintended consequences. While additional research is needed to further test the modeling approach, findings might underscore the need to direct workplace interventions towards changing organizational conditions for nursing aides.

Minimum-complexity helicopter simulation math model

NASA Technical Reports Server (NTRS)

Heffley, Robert K.; Mnich, Marc A.

1988-01-01

An example of a minimal complexity simulation helicopter math model is presented. Motivating factors are the computational delays, cost, and inflexibility of the very sophisticated math models now in common use. A helicopter model form is given which addresses each of these factors and provides better engineering understanding of the specific handling qualities features which are apparent to the simulator pilot. The technical approach begins with specification of features which are to be modeled, followed by a build up of individual vehicle components and definition of equations. Model matching and estimation procedures are given which enable the modeling of specific helicopters from basic data sources such as flight manuals. Checkout procedures are given which provide for total model validation. A number of possible model extensions and refinement are discussed. Math model computer programs are defined and listed.

Dimensions Underlying Measures of Disability, Personal Factors, and Health Status in Cervical Radiculopathy

PubMed Central

Halvorsen, Marie; Kierkegaard, Marie; Harms-Ringdahl, Karin; Peolsson, Anneli; Dedering, Åsa

2015-01-01

Abstract This cross-sectional study sought to identify dimensions underlying measures of impairment, disability, personal factors, and health status in patients with cervical radiculopathy. One hundred twenty-four patients with magnetic resonance imaging-verified cervical radiculopathy, attending a neurosurgery clinic in Sweden, participated. Data from clinical tests and questionnaires on disability, personal factors, and health status were used in a principal-component analysis (PCA) with oblique rotation. The PCA supported a 3-component model including 14 variables from clinical tests and questionnaires, accounting for 73% of the cumulative percentage. The first component, pain and disability, explained 56%. The second component, health, fear-avoidance beliefs, kinesiophobia, and self-efficacy, explained 9.2%. The third component including anxiety, depression, and catastrophizing explained 7.6%. The strongest-loading variables of each dimension were “present neck pain intensity,” “fear avoidance,” and “anxiety.” The three underlying dimensions identified and labeled Pain and functioning, Health, beliefs, and kinesiophobia, and Mood state and catastrophizing captured aspects of importance for cervical radiculopathy. Since the variables “present neck pain intensity,” “fear avoidance,” and “anxiety” had the strongest loading in each of the three dimensions; it may be important to include them in a reduced multidimensional measurement set in cervical radiculopathy. PMID:26091482

Dimensions Underlying Measures of Disability, Personal Factors, and Health Status in Cervical Radiculopathy: A Cross-Sectional Study.

PubMed

Halvorsen, Marie; Kierkegaard, Marie; Harms-Ringdahl, Karin; Peolsson, Anneli; Dedering, Åsa

2015-06-01

This cross-sectional study sought to identify dimensions underlying measures of impairment, disability, personal factors, and health status in patients with cervical radiculopathy. One hundred twenty-four patients with magnetic resonance imaging-verified cervical radiculopathy, attending a neurosurgery clinic in Sweden, participated. Data from clinical tests and questionnaires on disability, personal factors, and health status were used in a principal-component analysis (PCA) with oblique rotation. The PCA supported a 3-component model including 14 variables from clinical tests and questionnaires, accounting for 73% of the cumulative percentage. The first component, pain and disability, explained 56%. The second component, health, fear-avoidance beliefs, kinesiophobia, and self-efficacy, explained 9.2%. The third component including anxiety, depression, and catastrophizing explained 7.6%. The strongest-loading variables of each dimension were "present neck pain intensity," "fear avoidance," and "anxiety." The three underlying dimensions identified and labeled Pain and functioning, Health, beliefs, and kinesiophobia, and Mood state and catastrophizing captured aspects of importance for cervical radiculopathy. Since the variables "present neck pain intensity," "fear avoidance," and "anxiety" had the strongest loading in each of the three dimensions; it may be important to include them in a reduced multidimensional measurement set in cervical radiculopathy.

Estimating times of surgeries with two component procedures: comparison of the lognormal and normal models.

PubMed

Strum, David P; May, Jerrold H; Sampson, Allan R; Vargas, Luis G; Spangler, William E

2003-01-01

Variability inherent in the duration of surgical procedures complicates surgical scheduling. Modeling the duration and variability of surgeries might improve time estimates. Accurate time estimates are important operationally to improve utilization, reduce costs, and identify surgeries that might be considered outliers. Surgeries with multiple procedures are difficult to model because they are difficult to segment into homogenous groups and because they are performed less frequently than single-procedure surgeries. The authors studied, retrospectively, 10,740 surgeries each with exactly two CPTs and 46,322 surgical cases with only one CPT from a large teaching hospital to determine if the distribution of dual-procedure surgery times fit more closely a lognormal or a normal model. The authors tested model goodness of fit to their data using Shapiro-Wilk tests, studied factors affecting the variability of time estimates, and examined the impact of coding permutations (ordered combinations) on modeling. The Shapiro-Wilk tests indicated that the lognormal model is statistically superior to the normal model for modeling dual-procedure surgeries. Permutations of component codes did not appear to differ significantly with respect to total procedure time and surgical time. To improve individual models for infrequent dual-procedure surgeries, permutations may be reduced and estimates may be based on the longest component procedure and type of anesthesia. The authors recommend use of the lognormal model for estimating surgical times for surgeries with two component procedures. Their results help legitimize the use of log transforms to normalize surgical procedure times prior to hypothesis testing using linear statistical models. Multiple-procedure surgeries may be modeled using the longest (statistically most important) component procedure and type of anesthesia.

Improved methods for the measurement and modeling of PV module and system performance for all operating conditions

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

King, D.L.

1995-11-01

The objective of this work was to develop improved performance model for modules and systems for for all operating conditions for use in module specifications, system and BOS component design, and system rating or monitoring. The approach taken was to identify and quantify the influence of dominant factors of solar irradiance, cell temperature, angle-of-incidence; and solar spectrum; use outdoor test procedures to separate the effects of electrical, thermal, and optical performance; use fundamental cell characteristics to improve analysis; and combine factors in simple model using the common variables.

Integrated healthy workplace model: An experience from North Indian industry

PubMed Central

Thakur, Jarnail Singh; Bains, Puneet; Kar, Sitanshu Sekhar; Wadhwa, Sanjay; Moirangthem, Prabha; Kumar, Rajesh; Wadwalker, Sanjay; Sharma, Yashpal

2012-01-01

Background: Keeping in view of rapid industrialization and growing Indian economy, there has been a substantial increase in the workforce in India. Currently there is no organized workplace model for promoting health of industrial workers in India. Objective: To develop and implement a healthy workplace model in three industrial settings of North India. Materials and Methods: An operations research was conducted for 12 months in purposively selected three industries of Chandigarh. In phase I, a multi-stakeholder workshop was conducted to finalize the components and tools for the healthy workplace model. NCD risk factors were assessed in 947 employees in these three industries. In phase II, the healthy workplace model was implemented on pilot basis for a period of 12 months in these three industries to finalize the model. Findings: Healthy workplace committee with involvement of representatives of management, labor union and research organization was formed in three industries. Various tools like comprehensive and rapid healthy workplace assessment forms, NCD work-lite format for risk factors surveillance and monitoring and evaluation format were developed. The prevalence of tobacco use, ever alcoholics was found to be 17.8% and 47%, respectively. Around one-third (28%) of employees complained of back pain in the past 12 months. Healthy workplace model with focus on three key components (physical environment, psychosocial work environment, and promoting healthy habits) was developed, implemented on pilot basis, and finalized based on experience in participating industries. A stepwise approach for model with a core, expanded, and optional components were also suggested. An accreditation system is also required for promoting healthy workplace program. Conclusion: Integrated healthy workplace model is feasible, could be implemented in industrial setting in northern India and needs to be pilot tested in other parts of the country. PMID:23776318

The effect of Chinese herbs and its effective components on coronary heart disease through PPARs-PGC1α pathway.

PubMed

Wang, Qiyan; Li, Chun; Zhang, Qian; Wang, Yuanyuan; Shi, Tianjiao; Lu, Linghui; Zhang, Yi; Wang, Yong; Wang, Wei

2016-12-12

DanQi pill (DQP) is prescribed widely in China and has definite cardioprotective effect on coronary heart disease. Our previous studies proved that DQP could effectively regulate plasma levels of high density lipoprotein (HDL) and low density lipoprotein (LDL). However, the regulatory mechanisms of DQP and its major components Salvianolic acids and Panax notoginseng saponins (DS) on lipid metabolism disorders haven't been comprehensively studied so far. Rat model of coronary heart disease was induced by left anterior descending (LAD) artery ligation operations. Rats were divided into sham, model, DQP treated, DS treated and positive drug (clofibrate) treated groups. At 28 days after surgery, cardiac functions were assessed by echocardiography. Expressions of transcription factors and key molecules in energy metabolism pathway were measured by reverse transcriptase polymerase chain reaction or western blotting. In ischemic heart model, cardiac functions were severely injured but improved by treatments of DQP and DS. Expression of LPL was down-regulated in model group. Both DQP and DS could up-regulate the mRNA expression of LPL. Membrane proteins involved in lipid transport and uptake, such as FABP4 and CPT-1A, were down-regulated in ischemic heart tissues. Treatment with DQP and DS regulated lipid metabolisms by up-regulating expressions of FABP4 and CPT-1A. DQP and DS also suppressed expression of cytochrome P450. Furthermore, transcriptional factors, such as PPARα, PPARγ, RXRA and PGC-1α, were down-regulated in ischemic model group. DQP and DS could up-regulate expressions of these factors. However, DS showed a better efficacy than DQP on PGC-1α, a coactivator of PPARs. Key molecules in signaling pathways such as AKT1/2, ERK and PI3K were also regulated by DQP and DS simultaneously. Salvianolic acids and Panax notoginseng are the major effective components of DanQi pill in improving lipid metabolism in ischemic heart model. The effects may be mediated by regulating transcriptional factors such as PPARs, RXRA and PGC-1α.

Equivalent parameter model of 1-3 piezocomposite with a sandwich polymer

NASA Astrophysics Data System (ADS)

Zhang, Yanjun; Wang, Likun; Qin, Lei

2018-06-01

A theoretical model was developed to investigate the performance of 1-3 piezoelectric composites with a sandwich polymer. Effective parameters, such as the electromechanical coupling factor, longitudinal velocity, and characteristic acoustic impedance of the piezocomposite, were predicted using the developed model. The influences of volume fractions and components of the polymer phase on the effective parameters of the piezoelectric composite were studied. The theoretical model was verified experimentally. The proposed model can reproduce the effective parameters of 1-3 piezoelectric composites with a sandwich polymer in the thickness mode. The measured electromechanical coupling factor was improved by more than 9.8% over the PZT/resin 1-3 piezoelectric composite.

A 3-factor model for the FACIT-Sp.

PubMed

Canada, Andrea L; Murphy, Patricia E; Fitchett, George; Peterman, Amy H; Schover, Leslie R

2008-09-01

The 12-item Functional Assessment of Chronic Illness Therapy-Spiritual Well-being Scale (FACIT-Sp) is a popular measure of the religious/spiritual (R/S) components of quality of life (QoL) in patients with cancer. The original factor analyses of the FACIT-Sp supported two factors: Meaning/Peace and Faith. Because Meaning suggests a cognitive aspect of R/S and Peace an affective component, we hypothesized a 3-factor solution: Meaning, Peace, and Faith. Participants were 240 long-term female survivors of cancer who completed the FACIT-Sp, the SF-12, and the BSI 18. We used confirmatory factor analysis to compare the 2- and 3-factor models of the FACIT-Sp and subsequently assessed associations between the resulting solutions and QoL domains. Survivors averaged 44 years of age and 10 years post-diagnosis. A 3-factor solution of the FACIT-Sp significantly improved the fit of the model to the data over the original 2-factor structure (Delta chi(2)=72.36, df=2, p<0.001). Further adjustments to the 3-factor model resulted in a final solution with even better goodness-of-fit indices (chi(2)=59.11, df=1, p=0.13, CFI=1.00, SMRM=0.05).The original Meaning/Peace factor controlling for Faith was associated with mental (r=0.63, p<0.000) and physical (r=0.22, p<0.01) health on the SF-12, and the original Faith factor controlling for Meaning/Peace was negatively associated with mental health (r=-0.15, p<0.05). The 3-factor model was more informative. Specifically, using partial correlations, the Peace factor was only related to mental health (r=0.53, p<0.001); Meaning was related to both physical (r=0.18, p<0.01) and mental (r=0.17, p<0.01) health; and Faith was negatively associated with mental health (r=-0.17, p<0.05). The results of this study support a 3-factor solution of the FACIT-Sp. The new solution not only represents a psychometric improvement over the original, but also enables a more detailed examination of the contribution of different dimensions of R/S to QoL. (c) 2007 John Wiley & Sons, Ltd.

Factors affecting medication adherence in community-managed patients with hypertension based on the principal component analysis: evidence from Xinjiang, China.

PubMed

Zhang, Yuji; Li, Xiaoju; Mao, Lu; Zhang, Mei; Li, Ke; Zheng, Yinxia; Cui, Wangfei; Yin, Hongpo; He, Yanli; Jing, Mingxia

2018-01-01

The analysis of factors affecting the nonadherence to antihypertensive medications is important in the control of blood pressure among patients with hypertension. The purpose of this study was to assess the relationship between factors and medication adherence in Xinjiang community-managed patients with hypertension based on the principal component analysis. A total of 1,916 community-managed patients with hypertension, selected randomly through a multi-stage sampling, participated in the survey. Self-designed questionnaires were used to classify the participants as either adherent or nonadherent to their medication regimen. A principal component analysis was used in order to eliminate the correlation between factors. Factors related to nonadherence were analyzed by using a χ 2 -test and a binary logistic regression model. This study extracted nine common factors, with a cumulative variance contribution rate of 63.6%. Further analysis revealed that the following variables were significantly related to nonadherence: severity of disease, community management, diabetes, and taking traditional medications. Community management plays an important role in improving the patients' medication-taking behavior. Regular medication regimen instruction and better community management services through community-level have the potential to reduce nonadherence. Mild hypertensive patients should be monitored by community health care providers.

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.

Volatility of organic aerosol and its components in the megacity of Paris

NASA Astrophysics Data System (ADS)

Paciga, Andrea; Karnezi, Eleni; Kostenidou, Evangelia; Hildebrandt, Lea; Psichoudaki, Magda; Engelhart, Gabriella J.; Lee, Byong-Hyoek; Crippa, Monica; Prévôt, André S. H.; Baltensperger, Urs; Pandis, Spyros N.

2016-02-01

Using a mass transfer model and the volatility basis set, we estimate the volatility distribution for the organic aerosol (OA) components during summer and winter in Paris, France as part of the collaborative project MEGAPOLI. The concentrations of the OA components as a function of temperature were measured combining data from a thermodenuder and an aerosol mass spectrometer (AMS) with Positive Matrix Factorization (PMF) analysis. The hydrocarbon-like organic aerosol (HOA) had similar volatility distributions for the summer and winter campaigns with half of the material in the saturation concentration bin of 10 µg m-3 and another 35-40 % consisting of low and extremely low volatility organic compounds (LVOCs with effective saturation concentrations C* of 10-3-0.1 µg m-3 and ELVOCs C* less or equal than 10-4 µg m-3, respectively). The winter cooking OA (COA) was more than an order of magnitude less volatile than the summer COA. The low-volatility oxygenated OA (LV-OOA) factor detected in the summer had the lowest volatility of all the derived factors and consisted almost exclusively of ELVOCs. The volatility for the semi-volatile oxygenated OA (SV-OOA) was significantly higher than that of the LV-OOA, containing both semi-volatile organic components (SVOCs with C* in the 1-100 µg m-3 range) and LVOCs. The oxygenated OA (OOA) factor in winter consisted of SVOCs (45 %), LVOCs (25 %) and ELVOCs (30 %). The volatility of marine OA (MOA) was higher than that of the other factors containing around 60 % SVOCs. The biomass burning OA (BBOA) factor contained components with a wide range of volatilities with significant contributions from both SVOCs (50 %) and LVOCs (30 %). Finally, combining the bulk average O : C ratios and volatility distributions of the various factors, our results are placed into the two-dimensional volatility basis set (2D-VBS) framework. The OA factors cover a broad spectrum of volatilities with no direct link between the average volatility and average O : C of the OA components.

Youth Engagement and Suicide Risk: Testing a Mediated Model in a Canadian Community Sample

ERIC Educational Resources Information Center

Ramey, Heather L.; Busseri, Michael A.; Khanna, Nishad; Rose-Krasnor, Linda

2010-01-01

Suicide is a leading cause of death among adolescents in many industrialized countries. We report evidence from a mediation model linking greater youth activity engagement, spanning behavioral and psychological components, with lower suicide risk through five hypothesized intrapersonal and interpersonal mediating factors. Self-report survey data…

The Role of Social Support in Students' Perceived Abilities and Attitudes toward Math and Science

ERIC Educational Resources Information Center

Rice, Lindsay; Barth, Joan M.; Guadagno, Rosanna E.; Smith, Gabrielle P. A.; McCallum, Debra M.

2013-01-01

Social cognitive models examining academic and career outcomes emphasize constructs such as attitude, interest, and self-efficacy as key factors affecting students' pursuit of STEM (science, technology, engineering and math) courses and careers. The current research examines another under-researched component of social cognitive models: social…

Individual Differences in Components of Reaction Time Distributions and Their Relations to Working Memory and Intelligence

ERIC Educational Resources Information Center

Schmiedek, Florian; Oberauer, Klaus; Wilhelm, Oliver; Suss, Heinz-Martin; Wittmann, Werner W.

2007-01-01

The authors bring together approaches from cognitive and individual differences psychology to model characteristics of reaction time distributions beyond measures of central tendency. Ex-Gaussian distributions and a diffusion model approach are used to describe individuals' reaction time data. The authors identified common latent factors for each…

The Performance of the Linear Logistic Test Model When the Q-Matrix Is Misspecified: A Simulation Study

ERIC Educational Resources Information Center

MacDonald, George T.

2014-01-01

A simulation study was conducted to explore the performance of the linear logistic test model (LLTM) when the relationships between items and cognitive components were misspecified. Factors manipulated included percent of misspecification (0%, 1%, 5%, 10%, and 15%), form of misspecification (under-specification, balanced misspecification, and…

[Study of building quantitative analysis model for chlorophyll in winter wheat with reflective spectrum using MSC-ANN algorithm].

PubMed

Liang, Xue; Ji, Hai-yan; Wang, Peng-xin; Rao, Zhen-hong; Shen, Bing-hui

2010-01-01

Preprocess method of multiplicative scatter correction (MSC) was used to reject noises in the original spectra produced by the environmental physical factor effectively, then the principal components of near-infrared spectroscopy were calculated by nonlinear iterative partial least squares (NIPALS) before building the back propagation artificial neural networks method (BP-ANN), and the numbers of principal components were calculated by the method of cross validation. The calculated principal components were used as the inputs of the artificial neural networks model, and the artificial neural networks model was used to find the relation between chlorophyll in winter wheat and reflective spectrum, which can predict the content of chlorophyll in winter wheat. The correlation coefficient (r) of calibration set was 0.9604, while the standard deviation (SD) and relative standard deviation (RSD) was 0.187 and 5.18% respectively. The correlation coefficient (r) of predicted set was 0.9600, and the standard deviation (SD) and relative standard deviation (RSD) was 0.145 and 4.21% respectively. It means that the MSC-ANN algorithm can reject noises in the original spectra produced by the environmental physical factor effectively and set up an exact model to predict the contents of chlorophyll in living leaves veraciously to replace the classical method and meet the needs of fast analysis of agricultural products.

Cosmic ray antiprotons in closed galaxy model

NASA Technical Reports Server (NTRS)

Protheroe, R.

1981-01-01

The flux of secondary antiprotons expected for the leaky-box model was calculated as well as that for the closed galaxy model of Peters and Westergard (1977). The antiproton/proton ratio observed at several GeV is a factor of 4 higher than the prediction for the leaky-box model but is consistent with that predicted for the closed galaxy model. New low energy data is not consistent with either model. The possibility of a primary antiproton component is discussed.

Prediction of Sliding Friction Coefficient Based on a Novel Hybrid Molecular-Mechanical Model.

PubMed

Zhang, Xiaogang; Zhang, Yali; Wang, Jianmei; Sheng, Chenxing; Li, Zhixiong

2018-08-01

Sliding friction is a complex phenomenon which arises from the mechanical and molecular interactions of asperities when examined in a microscale. To reveal and further understand the effects of micro scaled mechanical and molecular components of friction coefficient on overall frictional behavior, a hybrid molecular-mechanical model is developed to investigate the effects of main factors, including different loads and surface roughness values, on the sliding friction coefficient in a boundary lubrication condition. Numerical modelling was conducted using a deterministic contact model and based on the molecular-mechanical theory of friction. In the contact model, with given external loads and surface topographies, the pressure distribution, real contact area, and elastic/plastic deformation of each single asperity contact were calculated. Then asperity friction coefficient was predicted by the sum of mechanical and molecular components of friction coefficient. The mechanical component was mainly determined by the contact width and elastic/plastic deformation, and the molecular component was estimated as a function of the contact area and interfacial shear stress. Numerical results were compared with experimental results and a good agreement was obtained. The model was then used to predict friction coefficients in different operating and surface conditions. Numerical results explain why applied load has a minimum effect on the friction coefficients. They also provide insight into the effect of surface roughness on the mechanical and molecular components of friction coefficients. It is revealed that the mechanical component dominates the friction coefficient when the surface roughness is large (Rq > 0.2 μm), while the friction coefficient is mainly determined by the molecular component when the surface is relatively smooth (Rq < 0.2 μm). Furthermore, optimal roughness values for minimizing the friction coefficient are recommended.

Are elements of the chronic care model associated with cardiovascular risk factor control in type 2 diabetes?

PubMed

Parchman, Michael; Kaissi, Amer A

2009-03-01

Control of modifiable risk factors for cardiovascular (CV) disease, the most common cause of morbidity and mortality among people with Type 2 diabetes is dependent on both patient self-care behaviors and the characteristics of the clinic in which care is delivered. The relationship between control of CV risk factors, patient self-care behaviors, and the presence of CCM (Chronic Care Model) components across multiple primary care clinic settings was examined. Thirty consecutive patients presenting with Type 2 diabetes were enrolled from each of 20 primary care clinics from across South Texas. Patients were asked about their stage of change for four self-care behaviors: diet, exercise, glucose monitoring, and medication adherence. CV risk factors included the most recent values of glycosolated hemoglobin (A1C), blood pressure, and (low-density lipoprotein) cholesterol. Clinicians in each clinic completed the Assessment of Chronic Illness Care (ACIC) survey, a validated measure of the CCM components. Hierarchical logistic regression models were used. Only 25 (13%) of the 618 patients had good control of all three CV risk factors. Good control of these risk factors was positively associated with community linkages and delivery system design but was inversely associated with clinical information systems. Patients who were in the maintenance stage of change for all four self-care behaviors were more likely to have all three risk factors well controlled. Risk factors for CV disease among patients with diabetes are associated with the structure and design of the clinical microsystem where care is delivered. In addition to focusing on clinician knowledge, future interventions should address the clinical microsystem's structure and design to reduce the burden of CV disease among patients with Type 2 diabetes.

Measuring the effects of socioeconomic factors on mental health among migrants in urban China: a multiple indicators multiple causes model.

PubMed

Guan, Ming

2017-01-01

Since 1978, rural-urban migrants mainly contribute Chinese urbanization. The purpose of this paper is to examine the effects of socioeconomic factors on mental health of them. Their mental health was measured by 12-item general health questionnaire (GHQ-12). The study sample comprised 5925 migrants obtained from the 2009 rural-to-urban migrants survey (RUMiC). The relationships among the instruments were assessed by the correlation analysis. The one-factor (overall items), two-factor (positive vs. negative items), and model conducted by principal component analysis were tested in the confirmatory factor analysis (CFA). On the basis of three CFA models, the three multiple indicators multiple causes (MIMIC) models with age, gender, marriage, ethnicity, and employment were constructed to investigate the concurrent associations between socioeconomic factors and GHQ-12. Of the sample, only 1.94% were of ethnic origin and mean age was 31.63 (SD = ±10.43) years. The one-factor, two-factor, and three-factor structure (i.e. semi-positive/negative/independent usefulness) had good model fits in the CFA analysis and gave order (i.e. 2 factor>3 factor>1 factor), which suggests that the three models can be used to assess psychological symptoms of migrants in urban China. All MIMIC models had acceptable fit and gave order (i.e. one-dimensional model>two-dimensional model>three-dimensional model). There were weak associations of socioeconomic factors with mental health among migrants in urban China. Policy discussion suggested that improvement of socioeconomic status of rural-urban migrants and mental health systems in urban China should be highlighted and strengthened.

Adherence to an (n-3) Fatty Acid/Fish Intake Pattern Is Inversely Associated with Metabolic Syndrome among Puerto Rican Adults in the Greater Boston Area123

PubMed Central

Noel, Sabrina E.; Newby, P. K.; Ordovas, Jose M.; Tucker, Katherine L.

2010-01-01

Combinations of fatty acids may affect risk of metabolic syndrome. Puerto Ricans have a disproportionate number of chronic conditions compared with other Hispanic groups. We aimed to characterize fatty acid intake patterns of Puerto Rican adults aged 45–75 y and living in the Greater Boston area (n = 1207) and to examine associations between these patterns and metabolic syndrome. Dietary fatty acids, as a percentage of total fat, were entered into principle components analysis. Spearman correlation coefficients were used to examine associations between fatty acid intake patterns, nutrients, and food groups. Associations with metabolic syndrome were analyzed by using logistic regression and general linear models with quintiles of principal component scores. Four principal components (factors) emerged: factor 1, short- and medium-chain SFA/dairy; factor 2, (n-3) fatty acid/fish; factor 3, very long-chain (VLC) SFA and PUFA/oils; and factor 4, monounsaturated fatty acid/trans fat. The SFA/dairy factor was inversely associated with fasting serum glucose concentrations (P = 0.02) and the VLC SFA/oils factor was negatively related to waist circumference (P = 0.008). However, these associations were no longer significant after additional adjustment for BMI. The (n-3) fatty acid/fish factor was associated with a lower likelihood of metabolic syndrome (Q5 vs. Q1: odds ratio: 0.54, 95% CI: 0.34, 0.86). In summary, principal components analysis of fatty acid intakes revealed 4 dietary fatty acid patterns in this population. Identifying optimal combinations of fatty acids may be beneficial for understanding relationships with health outcomes given their diverse effects on metabolism. PMID:20702744

Battle Damage Modeling

DTIC Science & Technology

2010-05-01

has been an increasing move towards armor systems which are both structural and protection components at the same time. Analysis of material response...the materials can move. As the FE analysis progresses the component will move while the mesh remains motionless (Figure 4). Individual nodes and cells...this parameter. This subroutine needs many inputs, such as the speed of sound in the material , the FE size mesh and the safety factor, which prevents

Virulence control in group A Streptococcus by a two-component gene regulatory system: global expression profiling and in vivo infection modeling.

PubMed

Graham, Morag R; Smoot, Laura M; Migliaccio, Cristi A Lux; Virtaneva, Kimmo; Sturdevant, Daniel E; Porcella, Stephen F; Federle, Michael J; Adams, Gerald J; Scott, June R; Musser, James M

2002-10-15

Two-component gene regulatory systems composed of a membrane-bound sensor and cytoplasmic response regulator are important mechanisms used by bacteria to sense and respond to environmental stimuli. Group A Streptococcus, the causative agent of mild infections and life-threatening invasive diseases, produces many virulence factors that promote survival in humans. A two-component regulatory system, designated covRS (cov, control of virulence; csrRS), negatively controls expression of five proven or putative virulence factors (capsule, cysteine protease, streptokinase, streptolysin S, and streptodornase). Inactivation of covRS results in enhanced virulence in mouse models of invasive disease. Using DNA microarrays and quantitative RT-PCR, we found that CovR influences transcription of 15% (n = 271) of all chromosomal genes, including many that encode surface and secreted proteins mediating host-pathogen interactions. CovR also plays a central role in gene regulatory networks by influencing expression of genes encoding transcriptional regulators, including other two-component systems. Differential transcription of genes influenced by covR also was identified in mouse soft-tissue infection. This analysis provides a genome-scale overview of a virulence gene network in an important human pathogen and adds insight into the molecular mechanisms used by group A Streptococcus to interact with the host, promote survival, and cause disease.

Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

PubMed

Orbán, Levente L; Chartier, Sylvain

2015-01-01

Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

An empirical exploration of the relations between the health components of the International Classification of Functioning, Disability and Health (ICF).

PubMed

Perenboom, Rom J M; Wijlhuizen, Gert Jan; Garre, Francisca Galindo; Heerkens, Yvonne F; van Meeteren, Nico L U

2012-01-01

The aim of this study was to investigate the relations between the ICF components from a subjective perspective. Data on health condition and perceived functioning were collected among 2941 individuals with at least one chronic disease or disorder. Path analysis was used with perceived level of participation as the final denominator. Three models were tested: one with the number of chronic diseases and disorders as an indicator of health condition, one with perceived health as indicator of health condition, and one with perceived health as part of the personal factors. Although all models showed a good fit, the model with the best fit was that with perceived health as an indicator of health condition. From a patient's perspective, components of the ICF scheme appear to be associated with each other, with perceived health being the best indicator of the health condition.

Dissecting the role of milk components on gut microbiota composition

PubMed Central

Maga, Elizabeth A.; Weimer, Bart C.; Murray, James D.

2013-01-01

The composition of human milk is tailored to contribute to the development of the gastrointestinal (GI) tract of newborns and infants. Importantly, human milk contains the antimicrobial compounds lysozyme and lactoferrin that are thought to contribute to the formation of a health-promoting microbiota. As these protective factors are lacking in the milk of dairy animals, we genetically engineered goats expressing human lysozyme in their milk and have recently reported a new animal model to dissect out the role of milk components on gut microbiota formation. Using the pig as a more human-relevant animal model, we demonstrated that consumption of lysozyme-rich milk enriched the abundance of bacteria associated with GI health and decreased those associated with disease, much like human milk. This work demonstrated that the pig is a valid animal model for gut microbiome studies on the effects of dietary components on microbiota composition, host-microbe interactions and state of the intestine. PMID:23235404

Modeling silicon diode energy response factors for use in therapeutic photon beams.

PubMed

Eklund, Karin; Ahnesjö, Anders

2009-10-21

Silicon diodes have good spatial resolution, which makes them advantageous over ionization chambers for dosimetry in fields with high dose gradients. However, silicon diodes overrespond to low-energy photons, that are more abundant in scatter which increase with large fields and larger depths. We present a cavity-theory-based model for a general response function for silicon detectors at arbitrary positions within photon fields. The model uses photon and electron spectra calculated from fluence pencil kernels. The incident photons are treated according to their energy through a bipartition of the primary beam photon spectrum into low- and high-energy components. Primary electrons from the high-energy component are treated according to Spencer-Attix cavity theory. Low-energy primary photons together with all scattered photons are treated according to large cavity theory supplemented with an energy-dependent factor K(E) to compensate for energy variations in the electron equilibrium. The depth variation of the response for an unshielded silicon detector has been calculated for 5 x 5 cm(2), 10 x 10 cm(2) and 20 x 20 cm(2) fields in 6 and 15 MV beams and compared with measurements showing that our model calculates response factors with deviations less than 0.6%. An alternative method is also proposed, where we show that one can use a correlation with the scatter factor to determine the detector response of silicon diodes with an error of less than 3% in 6 MV and 15 MV photon beams.

Thermal design verification testing for the ATS-F and -G spacecraft.

NASA Technical Reports Server (NTRS)

Coyle, M.; Greenwell, J.

1972-01-01

There is a wide fluctuation in the internal power dissipation from the components within the earth viewing module (EVM). The electronic component functional reliability required for a two-to-five year mission is the most significant factor for the thermal design criteria. A mathematical thermal model of the EVM and the orbital environment is used to predict the performance of the thermal control system. Comparisons of the results obtained in chamber thermal balance tests with the data computed on the basis of the theoretical model provide the means for validating the thermal design.

Collisional-radiative model including recombination processes for W27+ ion★

NASA Astrophysics Data System (ADS)

Murakami, Izumi; Sasaki, Akira; Kato, Daiji; Koike, Fumihiro

2017-10-01

We have constructed a collisional-radiative (CR) model for W27+ ions including 226 configurations with n ≤ 9 and ł ≤ 5 for spectroscopic diagnostics. We newly include recombination processes in the model and this is the first result of extreme ultraviolet spectrum calculated for recombining plasma component. Calculated spectra in 40-70 Å range in ionizing and recombining plasma components show similar 3 strong lines and 1 line weak in recombining plasma component at 45-50 Å and many weak lines at 50-65 Å for both components. Recombination processes do not contribute much to the spectrum at around 60 Å for W27+ ion. Dielectronic satellite lines are also minor contribution to the spectrum of recombining plasma component. Dielectronic recombination (DR) rate coefficient from W28+ to W27+ ions is also calculated with the same atomic data in the CR model. We found that larger set of energy levels including many autoionizing states gave larger DR rate coefficients but our rate agree within factor 6 with other works at electron temperature around 1 keV in which W27+ and W28+ ions are usually observed in plasmas. Contribution to the Topical Issue "Atomic and Molecular Data and their Applications", edited by Gordon W.F. Drake, Jung-Sik Yoon, Daiji Kato, and Grzegorz Karwasz.

Soft X-ray spectral fits of Geminga with model neutron star atmospheres

NASA Technical Reports Server (NTRS)

Meyer, R. D.; Pavlov, G. G.; Meszaros, P.

1994-01-01

The spectrum of the soft X-ray pulsar Geminga consists of two components, a softer one which can be interpreted as thermal-like radiation from the surface of the neutron star, and a harder one interpreted as radiation from a polar cap heated by relativistic particles. We have fitted the soft spectrum using a detailed magnetized hydrogen atmosphere model. The fitting parameters are the hydrogen column density, the effective temperature T(sub eff), the gravitational redshift z, and the distance to radius ratio, for different values of the magnetic field B. The best fits for this model are obtained when B less than or approximately 1 x 10(exp 12) G and z lies on the upper boundary of the explored range (z = 0.45). The values of T(sub eff) approximately = (2-3) x 10(exp 5) K are a factor of 2-3 times lower than the value of T(sub eff) obtained for blackbody fits with the same z. The lower T(sub eff) increases the compatibility with some proposed schemes for fast neutrino cooling of neutron stars (NSs) by the direct Urca process or by exotic matter, but conventional cooling cannot be excluded. The hydrogen atmosphere fits also imply a smaller distance to Geminga than that inferred from a blackbody fit. An accurate evaluation of the distance would require a better knowledge of the ROSAT Position Sensitive Proportional Counter (PSPC) response to the low-energy region of the incident spectrum. Our modeling of the soft component with a cooler magnetized atmosphere also implies that the hard-component fit requires a characteristic temperature which is higher (by a factor of approximately 2-3) and a surface area which is smaller (by a factor of 10(exp 3), compared to previous blackbody fits.

Determinants of quality of life in patients with fibromyalgia: A structural equation modeling approach.

PubMed

Lee, Jeong-Won; Lee, Kyung-Eun; Park, Dong-Jin; Kim, Seong-Ho; Nah, Seong-Su; Lee, Ji Hyun; Kim, Seong-Kyu; Lee, Yeon-Ah; Hong, Seung-Jae; Kim, Hyun-Sook; Lee, Hye-Soon; Kim, Hyoun Ah; Joung, Chung-Il; Kim, Sang-Hyon; Lee, Shin-Seok

2017-01-01

Health-related quality of life (HRQOL) in patients with fibromyalgia (FM) is lower than in patients with other chronic diseases and the general population. Although various factors affect HRQOL, no study has examined a structural equation model of HRQOL as an outcome variable in FM patients. The present study assessed relationships among physical function, social factors, psychological factors, and HRQOL, and the effects of these variables on HRQOL in a hypothesized model using structural equation modeling (SEM). HRQOL was measured using SF-36, and the Fibromyalgia Impact Questionnaire (FIQ) was used to assess physical dysfunction. Social and psychological statuses were assessed using the Beck Depression Inventory (BDI), the State-Trait Anxiety Inventory (STAI), the Arthritis Self-Efficacy Scale (ASES), and the Social Support Scale. SEM analysis was used to test the structural relationships of the model using the AMOS software. Of the 336 patients, 301 (89.6%) were women with an average age of 47.9±10.9 years. The SEM results supported the hypothesized structural model (χ2 = 2.336, df = 3, p = 0.506). The final model showed that Physical Component Summary (PCS) was directly related to self-efficacy and inversely related to FIQ, and that Mental Component Summary (MCS) was inversely related to FIQ, BDI, and STAI. In our model of FM patients, HRQOL was affected by physical, social, and psychological variables. In these patients, higher levels of physical function and self-efficacy can improve the PCS of HRQOL, while physical function, depression, and anxiety negatively affect the MCS of HRQOL.

Determinants of quality of life in patients with fibromyalgia: A structural equation modeling approach

PubMed Central

Lee, Jeong-Won; Lee, Kyung-Eun; Park, Dong-Jin; Kim, Seong-Ho; Nah, Seong-Su; Lee, Ji Hyun; Kim, Seong-Kyu; Lee, Yeon-Ah; Hong, Seung-Jae; Kim, Hyun-Sook; Lee, Hye-Soon; Kim, Hyoun Ah; Joung, Chung-Il; Kim, Sang-Hyon

2017-01-01

Objective Health-related quality of life (HRQOL) in patients with fibromyalgia (FM) is lower than in patients with other chronic diseases and the general population. Although various factors affect HRQOL, no study has examined a structural equation model of HRQOL as an outcome variable in FM patients. The present study assessed relationships among physical function, social factors, psychological factors, and HRQOL, and the effects of these variables on HRQOL in a hypothesized model using structural equation modeling (SEM). Methods HRQOL was measured using SF-36, and the Fibromyalgia Impact Questionnaire (FIQ) was used to assess physical dysfunction. Social and psychological statuses were assessed using the Beck Depression Inventory (BDI), the State-Trait Anxiety Inventory (STAI), the Arthritis Self-Efficacy Scale (ASES), and the Social Support Scale. SEM analysis was used to test the structural relationships of the model using the AMOS software. Results Of the 336 patients, 301 (89.6%) were women with an average age of 47.9±10.9 years. The SEM results supported the hypothesized structural model (χ2 = 2.336, df = 3, p = 0.506). The final model showed that Physical Component Summary (PCS) was directly related to self-efficacy and inversely related to FIQ, and that Mental Component Summary (MCS) was inversely related to FIQ, BDI, and STAI. Conclusions In our model of FM patients, HRQOL was affected by physical, social, and psychological variables. In these patients, higher levels of physical function and self-efficacy can improve the PCS of HRQOL, while physical function, depression, and anxiety negatively affect the MCS of HRQOL. PMID:28158289

Comparison of emission factors for road traffic from a tunnel study (Gubrist tunnel, Switzerland) and from emission modeling

NASA Astrophysics Data System (ADS)

John, Christian; Friedrich, Rainer; Staehelin, Johannes; Schläpfer, Kurt; Stahel, Werner A.

The emission factors of NO x, VOC and CO of a road tunnel study performed in September 1993 in the Gubrist tunnel, close to Zürich (Switzerland) are compared with results of emission calculations based on recent results of dynamometric test measurements. The emission calculations are carried out with a traffic emission model taking into account the detailed composition of the vehicle fleet in the tunnel, the average speed and the gradient of the road and the special aerodynamics in a tunnel. With the exception of NO x emission factors for heavy duty vehicles no evidence for a discrepancy between the results of the tunnel study and the emission modeling was found. The measured emission factors of individual hydrocarbons of light duty vehicles were in good agreement with the expectations for most components.

The epidemiology of pelvic floor disorders and childbirth: an update

PubMed Central

Hallock, Jennifer L.; Handa, Victoria L.

2015-01-01

SYNOPSIS Using a life span model, this article presents new scientific findings regarding risk factors for pelvic floor disorders (PFDs), with a focus on the role of childbirth in the development of single or multiple co-existing PFDs. Phase I of the life span model includes predisposing factors such as genetic predisposition and race. Phase II of the model includes inciting factors such as obstetric events. Prolapse, urinary incontinence (UI) and fecal incontinence (FI) are more common among vaginally parous women, although the impact of vaginal delivery on risk of FI is less dramatic than for prolapse and UI. Finally, Phase III includes intervening factors such as age and obesity. Both age and obesity are associated with prevalence of PFDs. The prevention and treatment of obesity is an important component to PFD prevention. PMID:26880504

Two-component quantum Hall effects in topological flat bands

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

Zeng, Tian-Sheng; Zhu, Wei; Sheng, D. N.

2017-03-27

Here in this paper, we study quantum Hall states for two-component particles (hardcore bosons and fermions) loading in topological lattice models. By tuning the interplay of interspecies and intraspecies interactions, we demonstrate that two-component fractional quantum Hall states emerge at certain fractional filling factors ν = 1/2 for fermions (ν = 2/3 for bosons) in the lowest Chern band, classified by features from ground states including the unique Chern number matrix (inverse of the K matrix), the fractional charge and spin pumpings, and two parallel propagating edge modes. Moreover, we also apply our strategy to two-component fermions at integer fillingmore » factor ν = 2 , where a possible topological Neel antiferromagnetic phase is under intense debate very recently. For the typical π -flux checkerboard lattice, by tuning the onsite Hubbard repulsion, we establish a first-order phase transition directly from a two-component fermionic ν = 2 quantum Hall state at weak interaction to a topologically trivial antiferromagnetic insulator at strong interaction, and therefore exclude the possibility of an intermediate topological phase for our system.« less

Using Experimental Design and Data Analysis to Study the Enlisted Specialty Model for the U.S. Army G1

DTIC Science & Technology

2010-06-01

RECOMMENDATIONS FOR FUTURE STUDY ..................43 APPENDIX. OBJECTIVE FUNTION COEFFICIENTS ...................47 LIST OF REFERENCES...experiments are designed so an analyst can conduct simultaneous examination of multiple factors and explore these factors and their relationship to output...or more components. 46 THIS PAGE INTENTIONALLY LEFT BLANK 47 APPENDIX. OBJECTIVE FUNTION COEFFICIENTS

Construction and Validation of the Career and Educational Decision Self-Efficacy Inventory for Secondary Students (CEDSIS)

ERIC Educational Resources Information Center

Ho, Esther Sui Chu; Sum, Kwok Wing

2018-01-01

This study aims to construct and validate the Career and Educational Decision Self-Efficacy Inventory for Secondary Students (CEDSIS) by using a sample of 2,631 students in Hong Kong. Principal component analysis yielded a three-factor structure, which demonstrated good model fit in confirmatory factor analysis. High reliability was found for the…

Background recovery via motion-based robust principal component analysis with matrix factorization

NASA Astrophysics Data System (ADS)

Pan, Peng; Wang, Yongli; Zhou, Mingyuan; Sun, Zhipeng; He, Guoping

2018-03-01

Background recovery is a key technique in video analysis, but it still suffers from many challenges, such as camouflage, lighting changes, and diverse types of image noise. Robust principal component analysis (RPCA), which aims to recover a low-rank matrix and a sparse matrix, is a general framework for background recovery. The nuclear norm is widely used as a convex surrogate for the rank function in RPCA, which requires computing the singular value decomposition (SVD), a task that is increasingly costly as matrix sizes and ranks increase. However, matrix factorization greatly reduces the dimension of the matrix for which the SVD must be computed. Motion information has been shown to improve low-rank matrix recovery in RPCA, but this method still finds it difficult to handle original video data sets because of its batch-mode formulation and implementation. Hence, in this paper, we propose a motion-assisted RPCA model with matrix factorization (FM-RPCA) for background recovery. Moreover, an efficient linear alternating direction method of multipliers with a matrix factorization (FL-ADM) algorithm is designed for solving the proposed FM-RPCA model. Experimental results illustrate that the method provides stable results and is more efficient than the current state-of-the-art algorithms.

Gender and education impact on brain aging: a general cognitive factor approach.

PubMed

Proust-Lima, Cécile; Amieva, Hélène; Letenneur, Luc; Orgogozo, Jean-Marc; Jacqmin-Gadda, Hélène; Dartigues, Jean-François

2008-09-01

In cognitive aging research, the study of a general cognitive factor has been shown to have a substantial explanatory power over the study of isolated tests. The authors aimed at differentiating the impact of gender and education on global cognitive change with age from their differential impact on 4 psychometric tests using a new latent process approach, which intermediates between a single-factor longitudinal model for sum scores and an item-response theory approach for longitudinal data. The analysis was conducted on a sample of 2,228 subjects from PAQUID, a population-based cohort of older adults followed for 13 years with repeated measures of cognition. Adjusted for vascular factors, the analysis confirmed that women performed better in tests involving verbal components, while men performed better in tests involving visuospatial skills. In addition, the model suggested that women had a slightly steeper global cognitive decline with oldest age than men, even after excluding incident dementia or death. Subjects with higher education exhibited a better mean score for the 4 tests, but this difference tended to attenuate with age for tests involving a speed component. (c) 2008 APA, all rights reserved

Computing the scatter component of mammographic images.

PubMed

Highnam, R P; Brady, J M; Shepstone, B J

1994-01-01

The authors build upon a technical report (Tech. Report OUEL 2009/93, Engng. Sci., Oxford Uni., Oxford, UK, 1993) in which they proposed a model of the mammographic imaging process for which scattered radiation is a key degrading factor. Here, the authors propose a way of estimating the scatter component of the signal at any pixel within a mammographic image, and they use this estimate for model-based image enhancement. The first step is to extend the authors' previous model to divide breast tissue into "interesting" (fibrous/glandular/cancerous) tissue and fat. The scatter model is then based on the idea that the amount of scattered radiation reaching a point is related to the energy imparted to the surrounding neighbourhood. This complex relationship is approximated using published empirical data, and it varies with the size of the breast being imaged. The approximation is further complicated by needing to take account of extra-focal radiation and breast edge effects. The approximation takes the form of a weighting mask which is convolved with the total signal (primary and scatter) to give a value which is input to a "scatter function", approximated using three reference cases, and which returns a scatter estimate. Given a scatter estimate, the more important primary component can be calculated and used to create an image recognizable by a radiologist. The images resulting from this process are clearly enhanced, and model verification tests based on an estimate of the thickness of interesting tissue present proved to be very successful. A good scatter model opens the was for further processing to remove the effects of other degrading factors, such as beam hardening.

Time series analysis of collective motions in proteins

NASA Astrophysics Data System (ADS)

Alakent, Burak; Doruker, Pemra; ćamurdan, Mehmet C.

2004-01-01

The dynamics of α-amylase inhibitor tendamistat around its native state is investigated using time series analysis of the principal components of the Cα atomic displacements obtained from molecular dynamics trajectories. Collective motion along a principal component is modeled as a homogeneous nonstationary process, which is the result of the damped oscillations in local minima superimposed on a random walk. The motion in local minima is described by a stationary autoregressive moving average model, consisting of the frequency, damping factor, moving average parameters and random shock terms. Frequencies for the first 50 principal components are found to be in the 3-25 cm-1 range, which are well correlated with the principal component indices and also with atomistic normal mode analysis results. Damping factors, though their correlation is less pronounced, decrease as principal component indices increase, indicating that low frequency motions are less affected by friction. The existence of a positive moving average parameter indicates that the stochastic force term is likely to disturb the mode in opposite directions for two successive sampling times, showing the modes tendency to stay close to minimum. All these four parameters affect the mean square fluctuations of a principal mode within a single minimum. The inter-minima transitions are described by a random walk model, which is driven by a random shock term considerably smaller than that for the intra-minimum motion. The principal modes are classified into three subspaces based on their dynamics: essential, semiconstrained, and constrained, at least in partial consistency with previous studies. The Gaussian-type distributions of the intermediate modes, called "semiconstrained" modes, are explained by asserting that this random walk behavior is not completely free but between energy barriers.

Development and Validation of the Work-Related Well-Being Index: Analysis of the Federal Employee Viewpoint Survey.

PubMed

Eaton, Jennifer L; Mohr, David C; Hodgson, Michael J; McPhaul, Kathleen M

2018-02-01

To describe development and validation of the work-related well-being (WRWB) index. Principal components analysis was performed using Federal Employee Viewpoint Survey (FEVS) data (N = 392,752) to extract variables representing worker well-being constructs. Confirmatory factor analysis was performed to verify factor structure. To validate the WRWB index, we used multiple regression analysis to examine relationships with burnout associated outcomes. Principal Components Analysis identified three positive psychology constructs: "Work Positivity", "Co-worker Relationships", and "Work Mastery". An 11 item index explaining 63.5% of variance was achieved. The structural equation model provided a very good fit to the data. Higher WRWB scores were positively associated with all three employee experience measures examined in regression models. The new WRWB index shows promise as a valid and widely accessible instrument to assess worker well-being.

Using Separable Nonnegative Matrix Factorization Techniques for the Analysis of Time-Resolved Raman Spectra

NASA Astrophysics Data System (ADS)

Luce, R.; Hildebrandt, P.; Kuhlmann, U.; Liesen, J.

2016-09-01

The key challenge of time-resolved Raman spectroscopy is the identification of the constituent species and the analysis of the kinetics of the underlying reaction network. In this work we present an integral approach that allows for determining both the component spectra and the rate constants simultaneously from a series of vibrational spectra. It is based on an algorithm for non-negative matrix factorization which is applied to the experimental data set following a few pre-processing steps. As a prerequisite for physically unambiguous solutions, each component spectrum must include one vibrational band that does not significantly interfere with vibrational bands of other species. The approach is applied to synthetic "experimental" spectra derived from model systems comprising a set of species with component spectra differing with respect to their degree of spectral interferences and signal-to-noise ratios. In each case, the species involved are connected via monomolecular reaction pathways. The potential and limitations of the approach for recovering the respective rate constants and component spectra are discussed.

Tracking senescence-induced patterns in leaf litter leachate using parallel factor analysis (PARAFAC) modeling and self-organizing maps

NASA Astrophysics Data System (ADS)

Wheeler, K. I.; Levia, D. F.; Hudson, J. E.

2017-09-01

In autumn, the dissolved organic matter (DOM) contribution of leaf litter leachate to streams in forested watersheds changes as trees undergo resorption, senescence, and leaf abscission. Despite its biogeochemical importance, little work has investigated how leaf litter leachate DOM changes throughout autumn and how any changes might differ interspecifically and intraspecifically. Since climate change is expected to cause vegetation migration, it is necessary to learn how changes in forest composition could affect DOM inputs via leaf litter leachate. We examined changes in leaf litter leachate fluorescent DOM (FDOM) from American beech (Fagus grandifolia Ehrh.) leaves in Maryland, Rhode Island, Vermont, and North Carolina and from yellow poplar (Liriodendron tulipifera L.) leaves from Maryland. FDOM in leachate samples was characterized by excitation-emission matrices (EEMs). A six-component parallel factor analysis (PARAFAC) model was created to identify components that accounted for the majority of the variation in the data set. Self-organizing maps (SOM) compared the PARAFAC component proportions of leachate samples. Phenophase and species exerted much stronger influence on the determination of a sample's SOM placement than geographic origin. As expected, FDOM from all trees transitioned from more protein-like components to more humic-like components with senescence. Percent greenness of sampled leaves and the proportion of tyrosine-like component 1 were found to be significantly different between the two genetic beech clusters, suggesting differences in photosynthesis and resorption. Our results highlight the need to account for interspecific and intraspecific variations in leaf litter leachate FDOM throughout autumn when examining the influence of allochthonous inputs to streams.

Does the concept of resilience contribute to understanding good quality of life in the context of epilepsy?

PubMed

Ring, Adele; Jacoby, Ann; Baker, Gus A; Marson, Anthony; Whitehead, Margaret M

2016-03-01

A significant body of research highlights negative impacts of epilepsy for individual quality of life (QOL). Poor seizure control is frequently associated with reporting of poor QOL and good seizure control with good QOL; however, this is not a universal finding. Evidence suggests that some people enjoy good QOL despite ongoing seizures while others report poor QOL despite good seizure control. Understanding the factors that influence QOL for people with epilepsy and the processes via which such factors exert their influence is central to the development of interventions to support people with epilepsy to experience the best possible QOL. We present findings of a qualitative investigation exploring influences and processes on QOL for people with epilepsy. We describe the clinical, psychological, and social factors contributing to QOL. In particular, we focus on the value of the concept of resilience for understanding quality of life in epilepsy. Based on our analysis, we propose a model of resilience wherein four key component sets of factors interact to determine QOL. This model reflects the fluid nature of resilience that, we suggest, is subject to change based on shifts within the individual components and the interactions between them. The model offers a representation of the complex influences that act and interact to either mitigate or further compound the negative impacts of epilepsy on individual QOL. Copyright © 2016 Elsevier Inc. All rights reserved.

[Psychometric properties of the Polish version of the Oldenburg Burnout Inventory (OLBI)].

PubMed

Baka, Łukasz; Basińska, Beata A

2016-01-01

The objective of this study was to test the psychometric properties of the Polish version of the Oldenburg Burnout Inventory (OLBI) - its factor structure, reliability, validity and standard norms. The study was conducted on 3 independent samples of 1804, 366 and 48 workers employed in social service and general service professions. To test the OLBI structure the exploratory factor analysis was conducted. The reliability was assessed by means of Cronbach's α coefficient (the internal consistent) and test-retest (the stability over time) method, with a 6-week follow-up. The construct validity of the OLBI was tested by means of correlation analysis, using perceived stress and work engagement as the criterion variables. The result of the factor analysis confirmed a 2-factor structure of the Inventory but the construction of each factor differed from that in the OLBI original version. Therefore, 2 separate factor analyses - each for the single component of job burnout (exhaustion and disengagement from work) - were conducted. The analyses revealed that each of the components consisted of 2 subscales. The reliability of the OLBI was supported by 2 methods. It was also proved that job burnout and its 2 components, exhaustion and disengagement from work, were positively correlated with perceived stress and negatively correlated with work engagement and its 3 components - vigor, absorption and dedication. Despite certain limitations the Polish version of the OLBI shows satisfactory psychometric properties and it can be used to measure job burnout in Polish conditions. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

Structural analysis of a Petri net model of oxidative stress in atherosclerosis.

PubMed

Kozak, Adam; Formanowicz, Dorota; Formanowicz, Piotr

2018-06-01

Atherosclerosis is a complex process of gathering sub-endothelial plaques decreasing lumen of the blood vessels. This disorder affects people of all ages, but its progression is asymptomatic for many years. It is regulated by many typical and atypical factors including the immune system response, a chronic kidney disease, a diet rich in lipids, a local inflammatory process and a local oxidative stress that is here one of the key factors. In this study, a Petri net model of atherosclerosis regulation is presented. This model includes also some information about stoichiometric relationships between its components and covers all mentioned factors. For the model, a structural analysis based on invariants was made and biological conclusions are presented. Since the model contains inhibitor arcs, a heuristic method for analysis of such cases is presented. This method can be used to extend the concept of feasible t -invariants.

Test-Anchored Vibration Response Predictions for an Acoustically Energized Curved Orthogrid Panel with Mounted Components

NASA Technical Reports Server (NTRS)

Frady, Gregory P.; Duvall, Lowery D.; Fulcher, Clay W. G.; Laverde, Bruce T.; Hunt, Ronald A.

2011-01-01

rich body of vibroacoustic test data was recently generated at Marshall Space Flight Center for component-loaded curved orthogrid panels typical of launch vehicle skin structures. The test data were used to anchor computational predictions of a variety of spatially distributed responses including acceleration, strain and component interface force. Transfer functions relating the responses to the input pressure field were generated from finite element based modal solutions and test-derived damping estimates. A diffuse acoustic field model was applied to correlate the measured input sound pressures across the energized panel. This application quantifies the ability to quickly and accurately predict a variety of responses to acoustically energized skin panels with mounted components. Favorable comparisons between the measured and predicted responses were established. The validated models were used to examine vibration response sensitivities to relevant modeling parameters such as pressure patch density, mesh density, weight of the mounted component and model form. Convergence metrics include spectral densities and cumulative root-mean squared (RMS) functions for acceleration, velocity, displacement, strain and interface force. Minimum frequencies for response convergence were established as well as recommendations for modeling techniques, particularly in the early stages of a component design when accurate structural vibration requirements are needed relatively quickly. The results were compared with long-established guidelines for modeling accuracy of component-loaded panels. A theoretical basis for the Response/Pressure Transfer Function (RPTF) approach provides insight into trends observed in the response predictions and confirmed in the test data. The software developed for the RPTF method allows easy replacement of the diffuse acoustic field with other pressure fields such as a turbulent boundary layer (TBL) model suitable for vehicle ascent. Structural responses using a TBL model were demonstrated, and wind tunnel tests have been proposed to anchor the predictions and provide new insight into modeling approaches for this environment. Finally, design load factors were developed from the measured and predicted responses and compared with those derived from traditional techniques such as historical Mass Acceleration Curves and Barrett scaling methods for acreage and component-loaded panels.

On the source of stochastic volatility: Evidence from CAC40 index options during the subprime crisis

NASA Astrophysics Data System (ADS)

Slim, Skander

2016-12-01

This paper investigates the performance of time-changed Lévy processes with distinct sources of return volatility variation for modeling cross-sectional option prices on the CAC40 index during the subprime crisis. Specifically, we propose a multi-factor stochastic volatility model: one factor captures the diffusion component dynamics and two factors capture positive and negative jump variations. In-sample and out-of-sample tests show that our full-fledged model significantly outperforms nested lower-dimensional specifications. We find that all three sources of return volatility variation, with different persistence, are needed to properly account for market pricing dynamics across moneyness, maturity and volatility level. Besides, the model estimation reveals negative risk premium for both diffusive volatility and downward jump intensity whereas a positive risk premium is found to be attributed to upward jump intensity.

Simultaneous UV and X-ray Spectroscopy of the Seyfert 1 Galaxy NGC 5548. I. Evidence for Dust in the UV Absorbers

NASA Astrophysics Data System (ADS)

Kraemer, S. B.; Crenshaw, D. M.; Gabel, J. R.; Kaastra, J. S.; Steenbrugge, K.; George, I. M.; Turner, T. J.; Yaqoob, T.; Dunn, J. P.

2002-12-01

We present new UV spectra of the nucleus of the Seyfert 1 galaxy NGC 5548, obtained with the Space Telescope Imaging Spectrograph at high spectral resolution (λ /Δ λ = 30,000 - 46,000), simultaneously with Chandra X-ray Observatory spectra. Taking advantage of the low UV continuum and broad emission-line fluxes, we have determined that the deepest UV absorption component covers at least a portion of the inner high-ionization narrow-line region (NLR). Assuming the NLR is fully covered, we find nonunity covering factors in the cores of several components, which increase the column density measurements of N V and C IV by factors of 1.2 to 1.9; however, the revised columns have only a minor effect on the parameters derived from our photoionization models. For the first time, we have simultaneous C IV and N V columns for component 1 (at -1040 km s-1), and find that this component cannot be an X-ray warm absorber, contrary to our previous claim (based on nonsimultaneous observations of N V and C IV). We find that dust-free models of the absorbers severely overpredict the O VI columns previously obtained with the Far Ultraviolet Spectrograph, and present arguments that this is not likely due to variability. However, models that include dust (and thereby heavily deplete carbon) are successful in matching all of the observed ionic columns, and result in substantially lower ionization parameters and total column densities compared to dust-free models. Interestingly, these models yield the exact amount of dust needed to produce the observed reddening of the inner NLR, assuming a Galactic dust to gas ratio. The models produce little O VII and O VIII, indicating that none of the dusty UV absorbers is associated with a classic X-ray warm absorber.

Principal Components Analyses of the MMPI-2 PSY-5 Scales. Identification of Facet Subscales

ERIC Educational Resources Information Center

Arnau, Randolph C.; Handel, Richard W.; Archer, Robert P.

2005-01-01

The Personality Psychopathology Five (PSY-5) is a five-factor personality trait model designed for assessing personality pathology using quantitative dimensions. Harkness, McNulty, and Ben-Porath developed Minnesota Multiphasic Personality Inventory-2 (MMPI-2) scales based on the PSY-5 model, and these scales were recently added to the standard…

The Mediating Role of Intercultural Wonderment: Connecting Programmatic Components to Global Outcomes in Study Abroad

ERIC Educational Resources Information Center

Engberg, Mark E.; Jourian, T. J.; Davidson, Lisa M.

2016-01-01

This study examines the mediating role of intercultural wonderment in relation to students' development of a global perspective. We utilize both confirmatory factor analysis and structural equation modeling to validate the intercultural wonderment construct and test the direct and indirect effects of the structural pathways in the model,…

Developing and Evaluating Creativity Gamification Rehabilitation System: The Application of PCA-ANFIS Based Emotions Model

ERIC Educational Resources Information Center

Su, Chung-Ho; Cheng, Ching-Hsue

2016-01-01

This study aims to explore the factors in a patient's rehabilitation achievement after a total knee replacement (TKR) patient exercises, using a PCA-ANFIS emotion model-based game rehabilitation system, which combines virtual reality (VR) and motion capture technology. The researchers combine a principal component analysis (PCA) and an adaptive…

Toward a Tripartite Model of Research Motivation: Development and Initial Validation of the Research Motivation Scale

ERIC Educational Resources Information Center

Deemer, Eric D.; Martens, Matthew P.; Buboltz, Walter C.

2010-01-01

An instrument designed to measure a 3-factor model of research motivation was developed and psychometrically examined in the present research. Participants were 437 graduate students in biology, chemistry/biochemistry, physics/astronomy, and psychology. A principal components analysis supported the retention of 20 items representing the 3-factor…

Linear degrees of freedom in speech production: analysis of cineradio- and labio-film data and articulatory-acoustic modeling.

PubMed

Beautemps, D; Badin, P; Bailly, G

2001-05-01

The following contribution addresses several issues concerning speech degrees of freedom in French oral vowels, stop, and fricative consonants based on an analysis of tongue and lip shapes extracted from cineradio- and labio-films. The midsagittal tongue shapes have been submitted to a linear decomposition where some of the loading factors were selected such as jaw and larynx position while four other components were derived from principal component analysis (PCA). For the lips, in addition to the more traditional protrusion and opening components, a supplementary component was extracted to explain the upward movement of both the upper and lower lips in [v] production. A linear articulatory model was developed; the six tongue degrees of freedom were used as the articulatory control parameters of the midsagittal tongue contours and explained 96% of the tongue data variance. These control parameters were also used to specify the frontal lip width dimension derived from the labio-film front views. Finally, this model was complemented by a conversion model going from the midsagittal to the area function, based on a fitting of the midsagittal distances and the formant frequencies for both vowels and consonants.

Relative contributions of scattering, diffraction and modal diffusion to focal ratio degradation in optical fibres

NASA Astrophysics Data System (ADS)

Haynes, D. M.; Withford, M. J.; Dawes, J. M.; Lawrence, J. S.; Haynes, R.

2011-06-01

Focal ratio degradation (FRD) is a major contributor to light loss in astronomical instruments employing multimode optical fibres. We present a powerful diagnostic model that uniquely quantifies the various sources of FRD in multimode fibres. There are three main phenomena that can contribute to FRD: scattering, diffraction and modal diffusion. We propose a Voigt FRD model where the diffraction and modal diffusion are modelled by the Gaussian component and the end-face scattering is modelled by the Lorentzian component. The Voigt FRD model can be deconvolved into its Gaussian and Lorentzian components and used to analyse the contribution of each of the three major components. We used the Voigt FRD model to analyse the FRD of modern astronomical grade fibre for variations in (i) end-face surface roughness, (ii) wavelength, (iii) fibre length and (iv) external fibre stress. The elevated FRD we observed was mostly due to external factors, i.e. fibre end effects such as surface roughness, subsurface damage and environmentally induced microbending caused by the epoxy, ferrules and fibre cable design. The Voigt FRD model has numerous applications such as a diagnostic tool for current fibre instrumentation that show elevated FRD, as a quality control method for fibre manufacture and fibre cable assembly and as a research and development tool for the characterization of new fibre technologies.

Diet-to-female and female-to-pup isotopic discrimination in South American sea lions.

PubMed

Drago, Massimiliano; Franco-Trecu, Valentina; Cardona, Luis; Inchausti, Pablo

2015-08-30

The use of accurate, species-specific diet-tissue discrimination factors is a critical requirement when applying stable isotope mixing models to predict consumer diet composition. Thus, diet-to-female and female-to-pup isotopic discrimination factors in several tissues for both captive and wild South American sea lions were estimated to provide appropriate values for quantifying feeding preferences at different timescales in the wild populations of this species. Stable carbon and nitrogen isotope ratios in the blood components of two female-pup pairs and females' prey muscle from captive individuals were determined by elemental analyzer/isotope ratio mass spectrometry (EA/IRMS) to calculate the respective isotopic discrimination factors. The same analysis was carried out in both blood components, and skin and hair tissues for eight female-pup pairs from wild individuals. Mean diet-to-female Δ(13) C and Δ(15) N values were higher than the female-to-pup ones. Pup tissues were more (15) N-enriched than their mothers but (13) C-depleted in serum and plasma tissues. In most of the tissue comparisons, we found differences in both Δ(15) N and Δ(13) C values, supporting tissue-specific discrimination. We found no differences between captive and wild female-to-pup discrimination factors either in Δ(13) C or Δ(15) N values of blood components. Only the stable isotope ratios in pup blood are good proxies of the individual lactating females. Thus, we suggest that blood components are more appropriate to quantify the feeding habits of wild individuals of this species. Furthermore, because female-to-pup discrimination factors for blood components did not differ between captive and wild individuals, we suggest that results for captive experiments can be extrapolated to wild South American sea lion populations. Copyright © 2015 John Wiley & Sons, Ltd.

Behavioral interventions to improve infection control practices.

PubMed

Kretzer, E K; Larson, E L

1998-06-01

No single intervention has been successful in improving and sustaining such infection control practices as universal precautions and handwashing by health care professionals. This paper examines several behavioral theories (Health Belief Model, Theory of Reasoned Action and Theory of Planned Behavior, self-efficacy, and the Transtheoretic Model) and relates them to individual factors, also considering interpersonal and organizational factors. Further, this article includes recommendations of individual and organizational components to be addressed when planning a theoretically based intervention for improving infection control practices. A hypothetic framework to enhance handwashing practice is proposed.

Computer-aided study of key factors determining high mechanical properties of nanostructured surface layers in metal-ceramic composites

NASA Astrophysics Data System (ADS)

Konovalenko, Igor S.; Shilko, Evgeny V.; Ovcharenko, Vladimir E.; Psakhie, Sergey G.

2017-12-01

The paper presents the movable cellular automaton method. It is based on numerical models of surface layers of the metal-ceramic composite NiCr-TiC modified under electron beam irradiation in inert gas plasmas. The models take into account different geometric, concentration and mechanical parameters of ceramic and metallic components. The authors study the contributions of key structural factors in mechanical properties of surface layers and determine the ranges of their variations by providing the optimum balance of strength, strain hardening and fracture toughness.

Fidelity and moderating factors in complex interventions: a case study of a continuum of care program for frail elderly people in health and social care

PubMed Central

2012-01-01

Background Prior studies measuring fidelity of complex interventions have mainly evaluated adherence, and not taken factors affecting adherence into consideration. A need for studies that clarify the concept of fidelity and the function of factors moderating fidelity has been emphasized. The aim of the study was to systematically evaluate implementation fidelity and possible factors influencing fidelity of a complex care continuum intervention for frail elderly people. Methods The intervention was a systematization of the collaboration between a nurse with geriatric expertise situated at the emergency department, the hospital ward staff, and a multi-professional team with a case manager in the municipal care services for older people. Implementation was evaluated between September 2008 and May 2010 with observations of work practices, stakeholder interviews, and document analysis according to a modified version of The Conceptual Framework for Implementation Fidelity. Results A total of 16 of the 18 intervention components were to a great extent delivered as planned, while some new components were added to the model. No changes in the frequency or duration of the 18 components were observed, but the dose of the added components varied over time. Changes in fidelity were caused in a complex, interrelated fashion by all the moderating factors in the framework, i.e., context, staff and participant responsiveness, facilitation, recruitment, and complexity. Discussion The Conceptual Framework for Implementation Fidelity was empirically useful and included comprehensive measures of factors affecting fidelity. Future studies should focus on developing the framework with regard to how to investigate relationships between the moderating factors and fidelity over time. Trial registration ClinicalTrials.gov, NCT01260493. PMID:22436121

Characterization of atrazine binding to dissolved organic matter of soil under different types of land use.

PubMed

Zhu, Long-Ji; Zhao, Yue; Chen, Yan-Ni; Cui, Hong-Yang; Wei, Yu-Quan; Liu, Hai-Long; Chen, Xiao-Meng; Wei, Zi-Min

2018-01-01

Atrazine is widely used in agriculture. In this study, dissolved organic matter (DOM) from soils under four types of land use (forest (F), meadow (M), cropland (C) and wetland (W)) was used to investigate the binding characteristics of atrazine. Fluorescence excitation-emission matrix-parallel factor (EEM-PARAFAC) analysis, two-dimensional correlation spectroscopy (2D-COS) and Stern-Volmer model were combined to explore the complexation between DOM and atrazine. The EEM-PARAFAC indicated that DOM from different sources had different structures, and humic-like components had more obvious quenching effects than protein-like components. The Stern-Volmer model combined with correlation analysis showed that log K values of PARAFAC components had a significant correlation with the humification of DOM, especially for C3 component, and they were all in the same order as follows: meadow soil (5.68)>wetland soil (5.44)>cropland soil (5.35)>forest soil (5.04). The 2D-COS further confirmed that humic-like components firstly combined with atrazine followed by protein-like components. These findings suggest that DOM components can significantly influence the bioavailability, mobility and migration of atrazine in different land uses. Copyright © 2016 Elsevier Inc. All rights reserved.

Screening Active Components from Yu-Ping-Feng-San for Regulating Initiative Key Factors in Allergic Sensitization

PubMed Central

Zhu, Zhijie; Yu, Xi; Liu, Hailiang; Wang, Huizhu; Fan, Hongwei; Wang, Dawei; Jiang, Guorong; Hong, Min

2014-01-01

Yu-ping-feng-san (YPFS) is a Chinese medical formula that is used clinically for allergic diseases and characterized by reducing allergy relapse. Our previous studies demonstrated that YPFS efficiently inhibited T helper 2 cytokines in allergic inflammation. The underlying mechanisms of action of YPFS and its effective components remain unclear. In this study, it was shown that YPFS significantly inhibited production of thymic stromal lymphopoietin (TSLP), an epithelial cell-derived initiative factor in allergic inflammation, in vitro and in vivo. A method of human bronchial epithelial cell (16HBE) binding combined with HPLC-MS (named 16HBE-HPLC-MS) was established to explore potential active components of YPFS. The following five components bound to 16HBE cells: calycosin-7-glucoside, ononin, claycosin, sec-o-glucosylhamaudol and formononetin. Serum from YPFS-treated mice was analyzed and three major components were detected claycosin, formononetin and cimifugin. Among these, claycosin and formononetin were detected by 16HBE-HPLC-MS and in the serum of YPFS-treated mice. Claycosin and formononetin decreased the level of TSLP markedly at the initial stage of allergic inflammation in vivo. Nuclear factor (NF)-κB, a key transcription factor in TSLP production, was also inhibited by claycosin and formononetin, either in terms of transcriptional activation or its nuclear translocation in vitro. Allergic inflammation was reduced by claycosin and formononetin when they are administered only at the initial stage in a murine model of atopic contact dermatitis. Thus, epithelial cell binding combined with HPLC-MS is a valid method for screening active components from complex mixtures of Chinese medicine. It was demonstrated that the compounds screened from YPFS significantly attenuated allergic inflammation probably by reducing TSLP production via regulating NF-κB activation. PMID:25198676

Gender differences in metabolic syndrome components among the Korean 66-year-old population with metabolic syndrome.

PubMed

Lee, Sangjin; Ko, Young; Kwak, Chanyeong; Yim, Eun-Shil

2016-01-23

Gender is thought to be an important factor in metabolic syndrome and its outcomes. Despite a number of studies that have demonstrated differences in metabolism and its components that are dependent on gender, limited information about gender differences on the characteristics of metabolic syndrome and its components is available regarding the Korean old adult population. This study aimed to identify gender differences in characteristics of the metabolic syndrome and other risk factors for cardiovascular disease. Secondary analysis of data from a nationwide cross-sectional survey for health examination at the time of transitioning from midlife to old age was performed. Multiple logistic regression models were used to estimate adjusted odds ratios and 95% confidence intervals for gender differences among the Korean 66-year-old population with metabolic syndrome. Gender differences in metabolic syndrome components that contributed to the diagnosis of metabolic syndrome were identified. In males, the most common component was high blood sugar levels (87.5%), followed by elevated triglyceride levels (83.5%) and high blood pressure (83.1%). In females, the most commonly identified component was elevated triglyceride levels (79.0%), followed by high blood sugar levels (78.6%) and high blood pressure (78.5%). Gender differences for other risk factors for cardiovascular disease, including family history, health habits, and body mass index were observed. Gender-specific public health policies and management strategies to prevent cardiovascular disease among the older adult population should be developed for Koreans undergoing the physiological transition to old age.

Custodial grandmothers' psychological distress, dysfunctional parenting, and grandchildren's adjustment.

PubMed

Smith, Gregory C; Palmieri, Patrick A; Hancock, Gregory R; Richardson, Rhonda A

2008-01-01

An adaptation of the Family Stress Model (FSM) with hypothesized linkages between family contextual factors, custodial grandmothers' psychological distress, parenting practices, and grandchildren's adjustment was tested with structural equation modeling. Interview data from 733 custodial grandmothers of grandchildren between ages 4-17 revealed that the effect of grandmothers' distress on grandchildren's adjustment was mediated by dysfunctional parenting, especially regarding externalizing problems. The effects of contextual factors on grandchildren's adjustment were also indirect. The model's measurement and structural components were largely invariant across grandmothers' race and age, as well as grandchildren's gender and age. Group differences were more prevalent regarding the magnitude of latent means for model constructs. We conclude that parenting models like the FSM are useful for investigating custodial grandfamilies.

Custodial Grandmothers' Psychological Distress, Dysfunctional Parenting, and Grandchildren's Adjustment*ł

PubMed Central

Smith, Gregory C.; Palmieri, Patrick A.; Hancock, Gregory R.; Richardson, Rhonda A.

2009-01-01

An adaptation of the Family Stress Model (FSM) with hypothesized linkages between family contextual factors, custodial grandmothers' psychological distress, parenting practices, and grandchildren's adjustment was tested with structural equation modeling. Interview data from 733 custodial grandmothers of grandchildren between ages 4-17 revealed that the effect of grandmothers' distress on grandchildren's adjustment was mediated by dysfunctional parenting, especially regarding externalizing problems. The effects of contextual factors on grandchildren's adjustment were also indirect. The model's measurement and structural components were largely invariant across grandmothers' race and age, as well as grandchildren's gender and age. Group differences were more prevalent regarding the magnitude of latent means for model constructs. We conclude that parenting models like the FSM are useful for investigating custodial grandfamilies. PMID:19266869

A heuristic model of enactive compassion.

PubMed

Halifax, Joan

2012-06-01

This article is an investigation of the possibility that compassion is not a discrete feature but an emergent and contingent process that is at its base enactive. Compassion must be primed through the cultivation of various factors. This article endeavors to identify interdependent components of compassion. This is particularly relevant for those in the end-of-life care professions, wherein compassion is an essential factor in the care of those suffering from a catastrophic illness or injury. The Halifax Model of Compassion is presented here as a new vision of compassion with particular relevance for the training of compassion in clinicians. Compassion is generally valued as a prosocial mental quality. The factors that foster compassion are not well understood, and the essential components of compassion have not been sufficiently delineated. Neuroscience research on compassion has only recently begun, and there is little clinical research on the role of compassion in end-of-life care. Compassion is in general seen as having two main components: the affective feeling of caring for one who is suffering and the motivation to relieve suffering. This definition of compassion might impose limitations and will, therefore, have consequences on how one trains compassion in clinicians and others. It is the author's premise that compassion is dispositionally enactive (the interactions between living organisms and their environments, i.e., the propensity toward perception-action in relation to one's surrounds), and it is a process that is contingent and emergent.

Movement Integration and the One-Target Advantage.

PubMed

Hoffmann, Errol R

2017-01-01

The 1-target advantage (OTA) has been found to occur in many circumstances and the current best explanation for this phenomenon is that of the movement integration hypothesis. The author's purpose is twofold: (a) to model the conditions under which there is integration of the movement components in a 2-component movement and (b) to study the factors that determine the magnitude of the OTA for both the first and second component of a 2-component movement. Results indicate that integration of movement components, where times for one component are affected by the geometry of the other component, occurs when 1 of the movement components is made ballistically. Movement components that require ongoing visual control show only weak interaction with the second component, whereas components made ballistically always show movement time dependence on first and second component amplitude, independent of location within the sequence. The OTA is present on both the first and second components of the movement, with a magnitude that is dependent on whether the components are performed ballistically or with ongoing visual control and also on the amplitudes and indexes of difficulty of the component movements.

Strengthening organizations to implement evidence-based clinical practices.

PubMed

VanDeusen Lukas, Carol; Engle, Ryann L; Holmes, Sally K; Parker, Victoria A; Petzel, Robert A; Nealon Seibert, Marjorie; Shwartz, Michael; Sullivan, Jennifer L

2010-01-01

Despite recognition that implementation of evidence-based clinical practices (EBPs) usually depends on the structure and processes of the larger health care organizational context, the dynamics of implementation are not well understood. This project's aim was to deepen that understanding by implementing and evaluating an organizational model hypothesized to strengthen the ability of health care organizations to facilitate EBPs. CONCEPTUAL MODEL: The model posits that implementation of EBPs will be enhanced through the presence of three interacting components: active leadership commitment to quality, robust clinical process redesign incorporating EBPs into routine operations, and use of management structures and processes to support and align redesign. In a mixed-methods longitudinal comparative case study design, seven medical centers in one network in the Department of Veterans Affairs participated in an intervention to implement the organizational model over 3 years. The network was selected randomly from three interested in using the model. The target EBP was hand-hygiene compliance. Measures included ratings of implementation fidelity, observed hand-hygiene compliance, and factors affecting model implementation drawn from interviews. Analyses support the hypothesis that greater fidelity to the organizational model was associated with higher compliance with hand-hygiene guidelines. High-fidelity sites showed larger effect sizes for improvement in hand-hygiene compliance than lower-fidelity sites. Adherence to the organizational model was in turn affected by factors in three categories: urgency to improve, organizational environment, and improvement climate. Implementation of EBPs, particularly those that cut across multiple processes of care, is a complex process with many possibilities for failure. The results provide the basis for a refined understanding of relationships among components of the organizational model and factors in the organizational context affecting them. This understanding suggests practical lessons for future implementation efforts and contributes to theoretical understanding of the dynamics of the implementation of EBPs.

Inter-comparison of receptor models for PM source apportionment: Case study in an industrial area

NASA Astrophysics Data System (ADS)

Viana, M.; Pandolfi, M.; Minguillón, M. C.; Querol, X.; Alastuey, A.; Monfort, E.; Celades, I.

2008-05-01

Receptor modelling techniques are used to identify and quantify the contributions from emission sources to the levels and major and trace components of ambient particulate matter (PM). A wide variety of receptor models are currently available, and consequently the comparability between models should be evaluated if source apportionment data are to be used as input in health effects studies or mitigation plans. Three of the most widespread receptor models (principal component analysis, PCA; positive matrix factorization, PMF; chemical mass balance, CMB) were applied to a single PM10 data set (n=328 samples, 2002-2005) obtained from an industrial area in NE Spain, dedicated to ceramic production. Sensitivity and temporal trend analyses (using the Mann-Kendall test) were applied. Results evidenced the good overall performance of the three models (r2>0.83 and α>0.91×between modelled and measured PM10 mass), with a good agreement regarding source identification and high correlations between input (CMB) and output (PCA, PMF) source profiles. Larger differences were obtained regarding the quantification of source contributions (up to a factor of 4 in some cases). The combined application of different types of receptor models would solve the limitations of each of the models, by constructing a more robust solution based on their strengths. The authors suggest the combined use of factor analysis techniques (PCA, PMF) to identify and interpret emission sources, and to obtain a first quantification of their contributions to the PM mass, and the subsequent application of CMB. Further research is needed to ensure that source apportionment methods are robust enough for application to PM health effects assessments.

Cumulative complexity: a functional, patient-centered model of patient complexity can improve research and practice.

PubMed

Shippee, Nathan D; Shah, Nilay D; May, Carl R; Mair, Frances S; Montori, Victor M

2012-10-01

To design a functional, patient-centered model of patient complexity with practical applicability to analytic design and clinical practice. Existing literature on patient complexity has mainly identified its components descriptively and in isolation, lacking clarity as to their combined functions in disrupting care or to how complexity changes over time. The authors developed a cumulative complexity model, which integrates existing literature and emphasizes how clinical and social factors accumulate and interact to complicate patient care. A narrative literature review is used to explicate the model. The model emphasizes a core, patient-level mechanism whereby complicating factors impact care and outcomes: the balance between patient workload of demands and patient capacity to address demands. Workload encompasses the demands on the patient's time and energy, including demands of treatment, self-care, and life in general. Capacity concerns ability to handle work (e.g., functional morbidity, financial/social resources, literacy). Workload-capacity imbalances comprise the mechanism driving patient complexity. Treatment and illness burdens serve as feedback loops, linking negative outcomes to further imbalances, such that complexity may accumulate over time. With its components largely supported by existing literature, the model has implications for analytic design, clinical epidemiology, and clinical practice. Copyright © 2012 Elsevier Inc. All rights reserved.

Animal models of drug addiction.

PubMed

García Pardo, María Pilar; Roger Sánchez, Concepción; De la Rubia Ortí, José Enrique; Aguilar Calpe, María Asunción

2017-09-29

The development of animal models of drug reward and addiction is an essential factor for progress in understanding the biological basis of this disorder and for the identification of new therapeutic targets. Depending on the component of reward to be studied, one type of animal model or another may be used. There are models of reinforcement based on the primary hedonic effect produced by the consumption of the addictive substance, such as the self-administration (SA) and intracranial self-stimulation (ICSS) paradigms, and there are models based on the component of reward related to associative learning and cognitive ability to make predictions about obtaining reward in the future, such as the conditioned place preference (CPP) paradigm. In recent years these models have incorporated methodological modifications to study extinction, reinstatement and reconsolidation processes, or to model specific aspects of addictive behavior such as motivation to consume drugs, compulsive consumption or drug seeking under punishment situations. There are also models that link different reinforcement components or model voluntary motivation to consume (two-bottle choice, or drinking in the dark tests). In short, innovations in these models allow progress in scientific knowledge regarding the different aspects that lead individuals to consume a drug and develop compulsive consumption, providing a target for future treatments of addiction.

Research on distributed heterogeneous data PCA algorithm based on cloud platform

NASA Astrophysics Data System (ADS)

Zhang, Jin; Huang, Gang

2018-05-01

Principal component analysis (PCA) of heterogeneous data sets can solve the problem that centralized data scalability is limited. In order to reduce the generation of intermediate data and error components of distributed heterogeneous data sets, a principal component analysis algorithm based on heterogeneous data sets under cloud platform is proposed. The algorithm performs eigenvalue processing by using Householder tridiagonalization and QR factorization to calculate the error component of the heterogeneous database associated with the public key to obtain the intermediate data set and the lost information. Experiments on distributed DBM heterogeneous datasets show that the model method has the feasibility and reliability in terms of execution time and accuracy.

Same genetic components underlie different measures of sweet taste preference.

PubMed

Keskitalo, Kaisu; Tuorila, Hely; Spector, Tim D; Cherkas, Lynn F; Knaapila, Antti; Silventoinen, Karri; Perola, Markus

2007-12-01

Sweet taste preferences are measured by several often correlated measures. We examined the relative proportions of genetic and environmental effects on sweet taste preference indicators and their mutual correlations. A total of 663 female twins (324 complete pairs, 149 monozygous and 175 dizygous pairs) aged 17-80 y rated the liking and intensity of a 20% (wt/vol) sucrose solution, reported the liking and the use-frequency of 6 sweet foods (sweet desserts, sweets, sweet pastry, ice cream, hard candy, and chocolate), and completed a questionnaire on cravings of sweet foods. The estimated contributions of genetic factors, environmental factors shared by a twin pair, and environmental factors unique to each twin individual to the variance and covariance of the traits were obtained with the use of linear structural equation modeling. Approximately half of the variation in liking for sweet solution and liking and use-frequency of sweet foods (49-53%) was explained by genetic factors, whereas the rest of the variation was due to environmental factors unique to each twin individual. Sweet taste preference-related traits were correlated. Tetravariate modeling showed that the correlation between liking for the sweet solution and liking for sweet foods was due to genetic factors (genetic r = 0.27). Correlations between liking, use-frequency, and craving for sweet foods were due to both genetic and unshared environmental factors. Detailed information on the associations between preference measures is an important intermediate goal in the determination of the genetic components affecting sweet taste preferences.

What is the role of "nonorganic somatic components" in functional capacity evaluations in patients with chronic nonspecific low back pain undergoing fitness for work evaluation?

PubMed

Oesch, Peter; Meyer, Kathrin; Jansen, Beatrice; Mowinckel, Petter; Bachmann, Stefan; Hagen, Kare Birger

2012-02-15

Analytical cross-sectional study. To assess the association of "nonorganic somatic components" together with physical and other psychosocial factors on functional capacity evaluation (FCE) in patients with chronic nonspecific low back pain (NSLBP) undergoing fitness-for-work evaluation. Functional capacity evaluation is increasingly used for physical fitness-for-work evaluation in patients with chronic NSLBP, but results seem to be influenced by physical as well as psychosocial factors. The influence of nonorganic somatic components together with physical and other psychosocial factors on FCE performance has not yet been investigated. One hundred twenty-six patients with chronic NSLBP referred for physical fitness-for-work evaluation were included. The 4 FCE tests were lifting from floor to waist, forward bend standing, grip strength, and 6-minute walking. Nonorganic somatic components were assessed with the 8 nonorganic somatic signs as defined by Waddell and were adjusted for age, sex, days off work, salary in the previous occupation, pain intensity, fear avoidance belief, and perceived functional ability in multivariate regression analyses. Between 42% and 58% of the variation in the FCE tests was explained in the final multivariate regression models. Nonorganic somatic components were consistent independent predictors for all tests. Their influence was most important on forward bend standing and walking distance, and less on grip strength and lifting performance. The physical factors of age and/or sex were strongly associated with grip strength and lifting, less with walking distance, and not at all with forward bend standing. The influence of at least 1 other psychosocial factor was observed in all FCE tests, having the highest proportion in the 6-minute walking test. Nonorganic somatic components seem to be consistent independent predictors in FCE testing and should be considered for interpretation of test results.

The Influence of Accreditation on the Sustainability of Organizations with the Brazilian Accreditation Methodology

PubMed Central

de Paiva, Anderson Paulo

2018-01-01

This research evaluates the influence of the Brazilian accreditation methodology on the sustainability of the organizations. Critical factors for implementing accreditation were also examined, including measuring the relationships established between these factors in the organization sustainability. The present study was developed based on the survey methodology applied in the organizations accredited by ONA (National Accreditation Organization); 288 responses were received from the top level managers. The analysis of quantitative data of the measurement models was made with factorial analysis from principal components. The final model was evaluated from the confirmatory factorial analysis and structural equation modeling techniques. The results from the research are vital for the definition of factors that interfere in the accreditation processes, providing a better understanding for accredited organizations and for Brazilian accreditation. PMID:29599939

Influence factors and forecast of carbon emission in China: structure adjustment for emission peak

NASA Astrophysics Data System (ADS)

Wang, B.; Cui, C. Q.; Li, Z. P.

2018-02-01

This paper introduced Principal Component Analysis and Multivariate Linear Regression Model to verify long-term balance relationships between Carbon Emissions and the impact factors. The integrated model of improved PCA and multivariate regression analysis model is attainable to figure out the pattern of carbon emission sources. Main empirical results indicate that among all selected variables, the role of energy consumption scale was largest. GDP and Population follow and also have significant impacts on carbon emission. Industrialization rate and fossil fuel proportion, which is the indicator of reflecting the economic structure and energy structure, have a higher importance than the factor of urbanization rate and the dweller consumption level of urban areas. In this way, some suggestions are put forward for government to achieve the peak of carbon emissions.

Assessing the Total Factor Productivity of Cotton Production in Egypt

PubMed Central

Rodríguez, Xosé A.; Elasraag, Yahia H.

2015-01-01

The main objective of this paper is to decompose the productivity growth of Egyptian cotton production. We employ the stochastic frontier approach and decompose the changes in total factor productivity (CTFP) growth into four components: technical progress (TP), changes in scale component (CSC), changes in allocative efficiency (CAE), and changes in technical efficiency (CTE). Considering a situation of scarce statistical information, we propose four alternative empirical models, with the purpose of looking for convergence in the results. The results provide evidence that in this production system total productivity does not increase, which is mainly due to the negative average contributions of CAE and TP. Policy implications are offered in light of the results. PMID:25625318

Assessing the total factor productivity of cotton production in Egypt.

PubMed

Rodríguez, Xosé A; Elasraag, Yahia H

2015-01-01

The main objective of this paper is to decompose the productivity growth of Egyptian cotton production. We employ the stochastic frontier approach and decompose the changes in total factor productivity (CTFP) growth into four components: technical progress (TP), changes in scale component (CSC), changes in allocative efficiency (CAE), and changes in technical efficiency (CTE). Considering a situation of scarce statistical information, we propose four alternative empirical models, with the purpose of looking for convergence in the results. The results provide evidence that in this production system total productivity does not increase, which is mainly due to the negative average contributions of CAE and TP. Policy implications are offered in light of the results.

Construct validation of SF-36 Malay version among type 2 diabetes mellitus patients

NASA Astrophysics Data System (ADS)

Yap, Bee Wah; Jannoo, Zeinab; Razali, Nornadiah Mohd; Ghani, Nor Azura Md.; Lazim, Mohamad Alias

2015-02-01

The Short Form 36 (SF-36) is one of the most widely used generic health status measure. This study used the SF-36 Health Survey instrument to investigate the functional health and well-being of Malay Type 2 Diabetes Mellitus patients in Malaysia. The survey was carried out in three local hospitals in Selangor. The method of questionnaire administration was both self-administered and interviewer administered. A total of 354 questionnaires was returned, but only 295 questionnaires with no missing data were analyzed. Confirmatory Factor Analysis (CFA) was used to confirm the first-order and third-order CFA models. The higher order analyses included a third-order CFA models with two second-order factors (physical and mental component) and three second-order factors (physical, general well-being and mental health) and both showed satisfactory model fit indices. This study confirmed the multidimensional factor structure of the SF-36.

Body composition, muscle capacity, and physical function in older adults: an integrated conceptual model.

PubMed

Brady, Anne O; Straight, Chad R; Evans, Ellen M

2014-07-01

The aging process leads to adverse changes in body composition (increases in fat mass and decreases in skeletal muscle mass), declines in physical function (PF), and ultimately increased risk for disability and loss of independence. Specific components of body composition or muscle capacity (strength and power) may be useful in predicting PF; however, findings have been mixed regarding the most salient predictor of PF. The development of a conceptual model potentially aids in understanding the interrelated factors contributing to PF with the factors of interest being physical activity, body composition, and muscle capacity. This article also highlights sex differences in these domains. Finally, factors known to affect PF, such as sleep, depression, fatigue, and self-efficacy, are discussed. Development of a comprehensive conceptual model is needed to better characterize the most salient factors contributing to PF and to subsequently inform the development of interventions to reduce physical disability in older adults.

Measurement and Modeling of the Optical Scattering Properties of Crop Canopies

NASA Technical Reports Server (NTRS)

Vanderbilt, V. C.; Grant, L.

1984-01-01

Efforts in measuring, analyzing, and mathematically modeling the specular, polarized, and diffuse light scattering properties of several plant canopies and their component parts (leaves, stems, fruit, soil) as a function of view angle and illumination angle are reported. Specific objectives were: (1) to demonstrate a technique for determining the specular and diffuse components of the reflectance factor of plant canopies; (2) to acquire the measurements and begin assembling a data set for developing and testing canopy reflectance models; (3) to design and build a new optical instrument to measure the light scattering properties of individual leaves; and (4) to use this instrument to survey and investigate the information in the light scattering properties of individual leaves of crops, forests, weeds, and horticulture.

Reducing equifinality of hydrological models by integrating Functional Streamflow Disaggregation

NASA Astrophysics Data System (ADS)

Lüdtke, Stefan; Apel, Heiko; Nied, Manuela; Carl, Peter; Merz, Bruno

2014-05-01

A universal problem of the calibration of hydrological models is the equifinality of different parameter sets derived from the calibration of models against total runoff values. This is an intrinsic problem stemming from the quality of the calibration data and the simplified process representation by the model. However, discharge data contains additional information which can be extracted by signal processing methods. An analysis specifically developed for the disaggregation of runoff time series into flow components is the Functional Streamflow Disaggregation (FSD; Carl & Behrendt, 2008). This method is used in the calibration of an implementation of the hydrological model SWIM in a medium sized watershed in Thailand. FSD is applied to disaggregate the discharge time series into three flow components which are interpreted as base flow, inter-flow and surface runoff. In addition to total runoff, the model is calibrated against these three components in a modified GLUE analysis, with the aim to identify structural model deficiencies, assess the internal process representation and to tackle equifinality. We developed a model dependent (MDA) approach calibrating the model runoff components against the FSD components, and a model independent (MIA) approach comparing the FSD of the model results and the FSD of calibration data. The results indicate, that the decomposition provides valuable information for the calibration. Particularly MDA highlights and discards a number of standard GLUE behavioural models underestimating the contribution of soil water to river discharge. Both, MDA and MIA yield to a reduction of the parameter ranges by a factor up to 3 in comparison to standard GLUE. Based on these results, we conclude that the developed calibration approach is able to reduce the equifinality of hydrological model parameterizations. The effect on the uncertainty of the model predictions is strongest by applying MDA and shows only minor reductions for MIA. Besides further validation of FSD, the next steps include an extension of the study to different catchments and other hydrological models with a similar structure.

From concept to content: assessing the implementation fidelity of a chronic care model for frail, older people who live at home.

PubMed

Muntinga, Maaike E; Van Leeuwen, Karen M; Schellevis, François G; Nijpels, Giel; Jansen, Aaltje P D

2015-01-22

Implementation fidelity, the degree to which a care program is implemented as intended, can influence program impact. Since results of trials that aim to implement comprehensive care programs for frail, older people have been conflicting, assessing implementation fidelity alongside these trials is essential to differentiate between flaws inherent to the program and implementation issues. This study demonstrates how a theory-based assessment of fidelity can increase insight in the implementation process of a complex intervention in primary elderly care. The Geriatric Care Model was implemented among 35 primary care practices in the Netherlands. During home visits, practice nurses conducted a comprehensive geriatric assessment and wrote a tailored care plan. Multidisciplinary team consultations were organized with the aim to enhance the coordination between professionals caring for a single patient with complex needs. To assess fidelity, we identified 5 key intervention components and formulated corresponding research questions using Carroll's framework for fidelity. Adherence (coverage, frequency, duration, content) was assessed per intervention component during and at the end of the intervention period. Two moderating factors (participant responsiveness and facilitation strategies) were assessed at the end of the intervention. Adherence to the geriatric assessments and care plans was high, but decreased over time. Adherence to multidisciplinary consultations was initially poor, but increased over time. We found that individual differences in adherence between practice nurses and primary care physicians were moderate, while differences in participant responsiveness (satisfaction, involvement) were more distinct. Nurses deviated from protocol due to contextual factors and personal work routines. Adherence to the Geriatric Care Model was high for most of the essential intervention components. Study limitations include the limited number of assessed moderating factors. We argue that a longitudinal investigation of adherence per intervention component is essential for a complete understanding of the implementation process, but that such investigations may be complicated by practical and methodological challenges. The Netherlands National Trial Register (NTR). 2160 .

The Use of Probabilistic Methods to Evaluate the Systems Impact of Component Design Improvements on Large Turbofan Engines

NASA Technical Reports Server (NTRS)

Packard, Michael H.

2002-01-01

Probabilistic Structural Analysis (PSA) is now commonly used for predicting the distribution of time/cycles to failure of turbine blades and other engine components. These distributions are typically based on fatigue/fracture and creep failure modes of these components. Additionally, reliability analysis is used for taking test data related to particular failure modes and calculating failure rate distributions of electronic and electromechanical components. How can these individual failure time distributions of structural, electronic and electromechanical component failure modes be effectively combined into a top level model for overall system evaluation of component upgrades, changes in maintenance intervals, or line replaceable unit (LRU) redesign? This paper shows an example of how various probabilistic failure predictions for turbine engine components can be evaluated and combined to show their effect on overall engine performance. A generic model of a turbofan engine was modeled using various Probabilistic Risk Assessment (PRA) tools (Quantitative Risk Assessment Software (QRAS) etc.). Hypothetical PSA results for a number of structural components along with mitigation factors that would restrict the failure mode from propagating to a Loss of Mission (LOM) failure were used in the models. The output of this program includes an overall failure distribution for LOM of the system. The rank and contribution to the overall Mission Success (MS) is also given for each failure mode and each subsystem. This application methodology demonstrates the effectiveness of PRA for assessing the performance of large turbine engines. Additionally, the effects of system changes and upgrades, the application of different maintenance intervals, inclusion of new sensor detection of faults and other upgrades were evaluated in determining overall turbine engine reliability.

Genetic and Psychosocial Predictors of Aggression: Variable Selection and Model Building With Component-Wise Gradient Boosting.

PubMed

Suchting, Robert; Gowin, Joshua L; Green, Charles E; Walss-Bass, Consuelo; Lane, Scott D

2018-01-01

Rationale : Given datasets with a large or diverse set of predictors of aggression, machine learning (ML) provides efficient tools for identifying the most salient variables and building a parsimonious statistical model. ML techniques permit efficient exploration of data, have not been widely used in aggression research, and may have utility for those seeking prediction of aggressive behavior. Objectives : The present study examined predictors of aggression and constructed an optimized model using ML techniques. Predictors were derived from a dataset that included demographic, psychometric and genetic predictors, specifically FK506 binding protein 5 (FKBP5) polymorphisms, which have been shown to alter response to threatening stimuli, but have not been tested as predictors of aggressive behavior in adults. Methods : The data analysis approach utilized component-wise gradient boosting and model reduction via backward elimination to: (a) select variables from an initial set of 20 to build a model of trait aggression; and then (b) reduce that model to maximize parsimony and generalizability. Results : From a dataset of N = 47 participants, component-wise gradient boosting selected 8 of 20 possible predictors to model Buss-Perry Aggression Questionnaire (BPAQ) total score, with R 2 = 0.66. This model was simplified using backward elimination, retaining six predictors: smoking status, psychopathy (interpersonal manipulation and callous affect), childhood trauma (physical abuse and neglect), and the FKBP5_13 gene (rs1360780). The six-factor model approximated the initial eight-factor model at 99.4% of R 2 . Conclusions : Using an inductive data science approach, the gradient boosting model identified predictors consistent with previous experimental work in aggression; specifically psychopathy and trauma exposure. Additionally, allelic variants in FKBP5 were identified for the first time, but the relatively small sample size limits generality of results and calls for replication. This approach provides utility for the prediction of aggression behavior, particularly in the context of large multivariate datasets.

Comparative statistical component analysis of transgenic, cyanophycin-producing potatoes in greenhouse and field trials.

PubMed

Schmidt, Kerstin; Schmidtke, Jörg; Mast, Yvonne; Waldvogel, Eva; Wohlleben, Wolfgang; Klemke, Friederike; Lockau, Wolfgang; Hausmann, Tina; Hühns, Maja; Broer, Inge

2017-08-01

Potatoes are a promising system for industrial production of the biopolymer cyanophycin as a second compound in addition to starch. To assess the efficiency in the field, we analysed the stability of the system, specifically its sensitivity to environmental factors. Field and greenhouse trials with transgenic potatoes (two independent events) were carried out for three years. The influence of environmental factors was measured and target compounds in the transgenic plants (cyanophycin, amino acids) were analysed for differences to control plants. Furthermore, non-target parameters (starch content, number, weight and size of tubers) were analysed for equivalence with control plants. The huge amount of data received was handled using modern statistical approaches to model the correlation between influencing environmental factors (year of cultivation, nitrogen fertilization, origin of plants, greenhouse or field cultivation) and key components (starch, amino acids, cyanophycin) and agronomic characteristics. General linear models were used for modelling, and standard effect sizes were applied to compare conventional and genetically modified plants. Altogether, the field trials prove that significant cyanophycin production is possible without reduction of starch content. Non-target compound composition seems to be equivalent under varying environmental conditions. Additionally, a quick test to measure cyanophycin content gives similar results compared to the extensive enzymatic test. This work facilitates the commercial cultivation of cyanophycin potatoes.

The evolution of nucleotides

NASA Technical Reports Server (NTRS)

Usher, D. A.; Needels, M. C.

1986-01-01

Examples of chiral selection in nonenzymatic aminoacylation of internal 2-prime hydroxyl groups of oligo- and polynucleotides are discussed as an evidence for the early evolution of bionucleotides. Some factors that could influence the degree of this chiral selection and its direction are discussed. These include the structure of the aminoacyl component, the structure of the nucleoside component, and the reaction conditions. Investigation of the mechanism of this reaction was aided by the use of 3-prime inosine methyl phosphate (as a simplified model for a dinucleoside monophosphate) and proton NMR spectroscopy of t-butoxycarbonyl-alanyl esters of nucleosides as models for the transition state of the aminoacylation reaction itself.

Positive influences of home food environment on primary-school children's diet and weight status: a structural equation model approach.

PubMed

Ong, Jia Xin; Ullah, Shahid; Magarey, Anthea; Leslie, Eva

2016-10-01

The mechanism by which the home food environment (HFE) influences childhood obesity is unclear. The present study aimed to investigate the relationship between HFE and childhood obesity as mediated by diet in primary-school children. Cross-sectional data collected from parents and primary-school children participating in the Obesity Prevention and Lifestyle Evaluation Project. Only children aged 9-11 years participated in the study. Matched parent/child data (n 3323) were analysed. Exploratory factor analysis underlined components of twenty-one HFE items; these were linked to child diet (meeting guidelines for fruit, vegetable and non-core food intakes) and measured child BMI, in structural equation modelling, adjusting for confounders. Twenty geographically bounded metropolitan and regional South Australian communities. School children and their parents from primary schools in selected communities. In the initial exploratory factor analysis, nineteen items remaining extracted eight factors with eigenvalues >1·0 (72·4 % of total variance). A five-factor structure incorporating ten items described HFE. After adjusting for age, gender, socio-economic status and physical activity all associations in the model were significant (P<0·05), explaining 9·3 % and 4·5 % of the variance in child diet and BMI, respectively. A more positive HFE was directly and indirectly associated with a lower BMI in children through child diet. The robust statistical methodology used in the present study provides support for a model of direct and indirect dynamics between the HFE and childhood obesity. The model can be tested in future longitudinal and intervention studies to identify the most effective components of the HFE to target in childhood obesity prevention efforts.

Vestibular coriolis effect differences modeled with three-dimensional linear-angular interactions.

PubMed

Holly, Jan E

2004-01-01

The vestibular coriolis (or "cross-coupling") effect is traditionally explained by cross-coupled angular vectors, which, however, do not explain the differences in perceptual disturbance under different acceleration conditions. For example, during head roll tilt in a rotating chair, the magnitude of perceptual disturbance is affected by a number of factors, including acceleration or deceleration of the chair rotation or a zero-g environment. Therefore, it has been suggested that linear-angular interactions play a role. The present research investigated whether these perceptual differences and others involving linear coriolis accelerations could be explained under one common framework: the laws of motion in three dimensions, which include all linear-angular interactions among all six components of motion (three angular and three linear). The results show that the three-dimensional laws of motion predict the differences in perceptual disturbance. No special properties of the vestibular system or nervous system are required. In addition, simulations were performed with angular, linear, and tilt time constants inserted into the model, giving the same predictions. Three-dimensional graphics were used to highlight the manner in which linear-angular interaction causes perceptual disturbance, and a crucial component is the Stretch Factor, which measures the "unexpected" linear component.

A model marine-science curriculum for fourth-grade pupils in Florida

NASA Astrophysics Data System (ADS)

Schulte, Philip James

This dissertation focused on the development of a model marine-science curriculum for fourth-grade pupils in the State of Florida. The curriculum was developed using grounded theory research method, including a component of data collected from an on-line survey administered to 106 professional educators and marine biologists. The results of the data collection and analysis showed a definitive necessity for teacher preparedness, multidisciplinary content, and inquiry-based science instruction. Further, three important factors emerged: (a) collaborative grouping increases achievement; (b) field excursions significantly impact student motivation; (c) standardized testing influences curriculum development. The curriculum is organized as an 11-day unit, with detailed lesson plans presented in standard curricular format and with all components correlated to the Florida State Educational Standards. The curriculum incorporates teacher preparation, multimedia presentations, computer-assisted instruction, scientific art appreciation, and replication as well as assessment factors. The curriculum addresses topics of ichthyology, marine animal identification, environmental conservation and protection, marine animal anatomy, water safety, environmental stewardship, and responsible angling techniques. The components of the curriculum were discussed with reference to the literature on which it was based and recommendations for future research were addressed.

Exploring factors related to metastasis free survival in breast cancer patients using Bayesian cure models.

PubMed

Jafari-Koshki, Tohid; Mansourian, Marjan; Mokarian, Fariborz

2014-01-01

Breast cancer is a fatal disease and the most frequently diagnosed cancer in women with an increasing pattern worldwide. The burden is mostly attributed to metastatic cancers that occur in one-third of patients and the treatments are palliative. It is of great interest to determine factors affecting time from cancer diagnosis to secondary metastasis. Cure rate models assume a Poisson distribution for the number of unobservable metastatic-component cells that are completely deleted from the non-metastasis patient body but some may remain and result in metastasis. Time to metastasis is defined as a function of the number of these cells and the time for each cell to develop a detectable sign of metastasis. Covariates are introduced to the model via the rate of metastatic-component cells. We used non-mixture cure rate models with Weibull and log-logistic distributions in a Bayesian setting to assess the relationship between metastasis free survival and covariates. The median of metastasis free survival was 76.9 months. Various models showed that from covariates in the study, lymph node involvement ratio and being progesterone receptor positive were significant, with an adverse and a beneficial effect on metastasis free survival, respectively. The estimated fraction of patients cured from metastasis was almost 48%. The Weibull model had a slightly better performance than log-logistic. Cure rate models are popular in survival studies and outperform other models under certain conditions. We explored the prognostic factors of metastatic breast cancer from a different viewpoint. In this study, metastasis sites were analyzed all together. Conducting similar studies in a larger sample of cancer patients as well as evaluating the prognostic value of covariates in metastasis to each site separately are recommended.

Hierarchical modularization of biochemical pathways using fuzzy-c means clustering.

PubMed

de Luis Balaguer, Maria A; Williams, Cranos M

2014-08-01

Biological systems that are representative of regulatory, metabolic, or signaling pathways can be highly complex. Mathematical models that describe such systems inherit this complexity. As a result, these models can often fail to provide a path toward the intuitive comprehension of these systems. More coarse information that allows a perceptive insight of the system is sometimes needed in combination with the model to understand control hierarchies or lower level functional relationships. In this paper, we present a method to identify relationships between components of dynamic models of biochemical pathways that reside in different functional groups. We find primary relationships and secondary relationships. The secondary relationships reveal connections that are present in the system, which current techniques that only identify primary relationships are unable to show. We also identify how relationships between components dynamically change over time. This results in a method that provides the hierarchy of the relationships among components, which can help us to understand the low level functional structure of the system and to elucidate potential hierarchical control. As a proof of concept, we apply the algorithm to the epidermal growth factor signal transduction pathway, and to the C3 photosynthesis pathway. We identify primary relationships among components that are in agreement with previous computational decomposition studies, and identify secondary relationships that uncover connections among components that current computational approaches were unable to reveal.

Internet Addiction of Young Greek Adults: Psychological Aspects and Information Privacy.

PubMed

Grammenos, P; Syrengela, N A; Magkos, E; Tsohou, A

2017-01-01

The main goal of this study is to examine the Internet addiction status of Greek young adults, aged from 18 to 25, using Young's Internet Addiction Test (IAT) and self-administered questionnaires. In addition this paper assesses the psychological traits of addicted persons per addiction category, using the big five factor model tool to study the user's personality and analyze the components that lead a person to become Internet addicted. Furthermore, we found an association between addicted people and the five factors from the Big Five Factor Model; i.e., extraversion, agreeableness, conscientiousness, neuroticism, openness to experience. Moreover, this paper discusses information privacy awareness issues related to Internet Addiction treatment.

Roads in landscape modeling: a case study of a road data layer and use in the interior northwest landscape analysis system.

Treesearch

Marti Aitken; Jane L. Hayes

2006-01-01

Roads are important ecological features of forest landscapes, but their cause-and effect relationships with other ecosystem components are only recently becoming included in integrated landscape analyses. Simulation models can help us to understand how forested landscapes respond over time to disturbance and socioeconomic factors, and potentially to address the...

A Qualitative Study of Systemic Factors Contributing to Successful Implementation of Response to Intervention Programs in Elementary Schools

ERIC Educational Resources Information Center

White, Sheila B.

2017-01-01

Response to intervention (RTI), an educational reform effort designed to meet the needs of struggling learners, has been adopted by an increasing number of states as a primary component of their educational service delivery model for low-achieving students (Burns et al., 2013; Castillo & Batsche, 2012). RTI models are multi-tiered…

Revisit to the RXTE and ASCA Data for GRO J1655-40: Effects of Radiative Transfer in Corona and Color Hardening in the Disk

NASA Technical Reports Server (NTRS)

Zhang, S. Nan; Zhang, Xiaoling; Wu, Xuebing; Yao, Yangsen; Sun, Xuejun; Xu, Haiguang; Cui, Wei; Chen, Wan; Harmon, B. A.; Robinson, C. R.

1999-01-01

The results of spectral modeling of the data for a series of RXTE observations and four ASCA observations of GRO J1655-40 are presented. The thermal Comptonization model is used instead of the power-law model for the hard component of the two-component continuum spectra. The previously reported dramatic variations of the apparent inner disk radius of GRO J1655-40 during its outburst may be due to the inverse Compton scattering in the hot corona. A procedure is developed for making the radiative transfer correction to the fitting parameters from RXTE data and a more stable inner disk radius is obtained. A practical process of determining the color correction (hardening) factor from observational data is proposed and applied to the four ASCA observations of GRO J1655-40. We found that the color correction factor may vary significantly between different observations and the finally corrected physical inner disk radius remains reasonably stable over a large range of luminosity and spectral states.

The impact of case specificity and generalisable skills on clinical performance: a correlated traits-correlated methods approach.

PubMed

Wimmers, Paul F; Fung, Cha-Chi

2008-06-01

The finding of case or content specificity in medical problem solving moved the focus of research away from generalisable skills towards the importance of content knowledge. However, controversy about the content dependency of clinical performance and the generalisability of skills remains. This study aimed to explore the relative impact of both perspectives (case specificity and generalisable skills) on different components (history taking, physical examination, communication) of clinical performance within and across cases. Data from a clinical performance examination (CPX) taken by 350 Year 3 students were used in a correlated traits-correlated methods (CTCM) approach using confirmatory factor analysis, whereby 'traits' refers to generalisable skills and 'methods' to individual cases. The baseline CTCM model was analysed and compared with four nested models using structural equation modelling techniques. The CPX consisted of three skills components and five cases. Comparison of the four different models with the least-restricted baseline CTCM model revealed that a model with uncorrelated generalisable skills factors and correlated case-specific knowledge factors represented the data best. The generalisable processes found in history taking, physical examination and communication were responsible for half the explained variance, in comparison with the variance related to case specificity. Conclusions Pure knowledge-based and pure skill-based perspectives on clinical performance both seem too one-dimensional and new evidence supports the idea that a substantial amount of variance contributes to both aspects of performance. It could be concluded that generalisable skills and specialised knowledge go hand in hand: both are essential aspects of clinical performance.

Comparison of current and paleorecharge on the Yucatan Peninsula, Mexico

NASA Astrophysics Data System (ADS)

Van Pelt, S.; Allen, D. M.; Kohfeld, K. E.

2016-12-01

During the Terminal Classic Period (TCP) 800-1000 AD, the Yucatan Peninsula is thought to have experienced a 150-year long series of droughts that contributed to the demise of the Mayan civilization. The occurrence of this type of event suggests that similar precipitation extremes could occur again, and severely impact water supplies. Studying the past occurrence of droughts may provide more insight into the possible timing and intensity of droughts. However, observed data of the past climate is limited to proxy records, which are not detailed enough for groundwater modeling. The goals of this study were two-fold: (a) to generate a daily paleoclimate time series for use in a recharge model, and (b) to compare current and past recharge on the Yucatan Peninsula. Past temperature and precipitation were reconstructed using a novel backwards shift factor approach using output from two experiments of the Community Climate System Model Version 4 (CCSM4). Shift factors were applied using two approaches: (1) application of shift factors to a stochastic weather series based on the observed climate, and (2) application of shift factors directly to the observed climate. The second method (direct shift factor approach) was found to be more suitable for the Yucatan Peninsula, as the observed median annual precipitation was poorly reproduced in the stochastic data. The reconstructed precipitation was used in the recharge model, which used the unsaturated component of the modeling program MIKE SHE. The comparison of the TCP and the current climate models indicated that on average, 1.74% more recharge occurred annually during the TCP. The seasonal water balance components showed that the majority of this higher recharge occurred during the wet season, with little to no increase in recharge during the dry season. Due to issues with the CCSM4 model data, changes in climate variability were not able to be incorporated into this study. If variability were incorporated, the TCP climate may have had more extreme precipitation values which are not represented in the recharge model, and the Yucatan Peninsula may have been susceptible to dry season droughts.

Outcomes research in cancer clinical trial cooperative groups: the RTOG model.

PubMed

Bruner, D W; Movsas, B; Konski, A; Roach, M; Bondy, M; Scarintino, C; Scott, C; Curran, W

2004-08-01

The Radiation Therapy Oncology Group (RTOG), a National Cancer Institute sponsored cancer clinical trials research cooperative, has recently formed an Outcomes Committee to assess a comprehensive array of clinical trial endpoints and factors impacting the net effect of therapy. To study outcomes in a consistent, comprehensive and coordinated manner, the RTOG Outcomes Committee developed a model to assess clinical, humanistic, and economic outcomes important in clinical trials. This paper reviews how the RTOG incorporates outcomes research into cancer clinical trials, and demonstrates utilization of the RTOG Outcomes Model to test hypotheses related to non-small-cell lung cancer (NSCLC). In this example, the clinical component of the model indicates that the addition of chemotherapy to radiotherapy (RT) improves survival but increases the risk of toxicity. The humanistic component indicates that esophagitis is the symptom impacting quality of life the greatest and may outweigh the benefits in elderly (> or =70 years) patients. The economic component of the model indicates that accounting for quality-adjusted survival, concurrent chemoRT for the treatment of NSCLC is within the range of economically acceptable recommendations. The RTOG Outcomes Model guides a comprehensive program of research that systematically measures a triad of endpoints considered important to clinical trials research.

Empirical evidence for an invariant three-factor structure of the Parental Bonding Instrument in six European countries.

PubMed

Heider, Dirk; Matschinger, Herbert; Bernert, Sebastian; Vilagut, Gemma; Martínez-Alonso, Montserrat; Dietrich, Sandra; Angermeyer, Matthias C

2005-06-30

The objective of the present study was to test the Parental Bonding Instrument's (PBI) three-factor structure (care, overprotection, and authoritarianism) found by [Cox, B.J., Enns, M.W., Clara, I.P. 2000, The Parental Bonding Instrument: confirmatory evidence for a three-factor model in a psychiatric clinical sample and in the National Comorbidity Survey, Social Psychiatry and Psychiatric Epidemiology 35 (2000) 353-357.] on an eight-item short form of the scale. A total of 8813 respondents from the six European countries participating in the ESEMeD project (Belgium, France, Germany, Italy, The Netherlands, and Spain) completed either the PBI-paternal or the PBI-maternal scale. Maximum likelihood confirmatory factor analysis was used to compare the original factor model of Cox et al. with a three-factor solution that emerged from an exploration of the structure with principal component factor analysis. When gender and age subgroups, as well as different countries, were taken into account, the accuracy of the model was confirmed. The fit indices for the new model indicated a generally better model fit than the ones for the model originally developed by Cox et al. Further efforts should be directed to the modeling of the dimension authoritarianism. The results provide the opportunity to estimate the influence of the extracted factors on mental disorders in different countries. The application of the short form of the PBI seems suitable primarily for large epidemiological studies.

Temporal dynamic of malaria in a suburban area along the Niger River.

PubMed

Sissoko, Mahamadou Soumana; Sissoko, Kourane; Kamate, Bourama; Samake, Yacouba; Goita, Siaka; Dabo, Abdoulaye; Yena, Mama; Dessay, Nadine; Piarroux, Renaud; Doumbo, Ogobara K; Gaudart, Jean

2017-10-23

Even if rainfall and temperature are factors classically associated to malaria, little is known about other meteorological factors, their variability and combinations related to malaria, in association with river height variations. Furthermore, in suburban area, urbanization and growing population density should be assessed in relation to these environmental factors. The aim of this study was to assess the impact of combined environmental, meteorological and hydrological factors on malaria incidence through time in the context of urbanization. Population observational data were prospectively collected. Clinical malaria was defined as the presence of parasites in addition to clinical symptoms. Meteorological and hydrological factors were measured daily. For each factors variation indices were estimated. Urbanization was yearly estimated assessing satellite imaging and field investigations. Principal component analysis was used for dimension reduction and factors combination. Lags between malaria incidences and the main components were assessed by cross-correlation functions. Generalized additive model was used to assess relative impact of different environmental components, taking into account lags, and modelling non-linear relationships. Change-point analysis was used to determine transmission periods within years. Malaria incidences were dominated by annual periodicity and varied through time without modification of the dynamic, with no impact of the urbanization. The main meteorological factor associated with malaria was a combination of evaporation, humidity and rainfall, with a lag of 3 months. The relationship between combined temperature factors showed a linear impact until reaching high temperatures limiting malaria incidence, with a lag 3.25 months. Height and variation of the river were related to malaria incidence (respectively 6 week lag and no lag). The study emphasizes no decreasing trend of malaria incidence despite accurate access to care and control strategies in accordance to international recommendations. Furthermore, no decreasing trend was showed despite the urbanization of the area. Malaria transmission remain increase 3 months after the beginning of the dry season. Addition to evaporation versus humidity/rainfall, nonlinear relationship for temperature and river height and variations have to be taken into account when implementing malaria control programmes.

A model for nematode locomotion in soil

USGS Publications Warehouse

Hunt, H. William; Wall, Diana H.; DeCrappeo, Nicole; Brenner, John S.

2001-01-01

Locomotion of nematodes in soil is important for both practical and theoretical reasons. We constructed a model for rate of locomotion. The first model component is a simple simulation of nematode movement among finite cells by both random and directed behaviours. Optimisation procedures were used to fit the simulation output to data from published experiments on movement along columns of soil or washed sand, and thus to estimate the values of the model's movement coefficients. The coefficients then provided an objective means to compare rates of locomotion among studies done under different experimental conditions. The second component of the model is an equation to predict the movement coefficients as a function of controlling factors that have been addressed experimentally: soil texture, bulk density, water potential, temperature, trophic group of nematode, presence of an attractant or physical gradient and the duration of the experiment. Parameters of the equation were estimated by optimisation to achieve a good fit to the estimated movement coefficients. Bulk density, which has been reported in a minority of published studies, is predicted to have an important effect on rate of locomotion, at least in fine-textured soils. Soil sieving, which appears to be a universal practice in laboratory studies of nematode movement, is predicted to negatively affect locomotion. Slower movement in finer textured soils would be expected to increase isolation among local populations, and thus to promote species richness. Future additions to the model that might improve its utility include representing heterogeneity within populations in rate of movement, development of gradients of chemical attractants, trade-offs between random and directed components of movement, species differences in optimal temperature and water potential, and interactions among factors controlling locomotion.

Genetic and other risk factors for suicidal ideation and the relationship with depression.

PubMed

Dutta, R; Ball, H A; Siribaddana, S H; Sumathipala, A; Samaraweera, S; McGuffin, P; Hotopf, M

2017-10-01

There is a genetic contribution to the risk of suicide, but sparse prior research on the genetics of suicidal ideation. Active and passive suicidal ideation were assessed in a Sri Lankan population-based twin registry (n = 3906 twins) and a matched non-twin sample (n = 2016). Logistic regression models were used to examine associations with socio-demographic factors, environmental exposures and psychiatric symptoms. The heritability of suicidal ideation was assessed using structural equation modelling. The lifetime prevalence of any suicidal ideation was 13.0% (11.7-14.3%) for men; 21.8% (20.3-23.2%) for women, with no significant difference between twins and non-twins. Factors that predicted suicidal ideation included female gender, termination of marital relationship, low education level, urban residence, losing a parent whilst young, low standard of living and stressful life events in the preceding 12 months. Suicidal ideation was strongly associated with depression, but also with abnormal fatigue and alcohol and tobacco use. The best fitting structural equation model indicated a substantial contribution from genetic factors (57%; CI 47-66) and from non-shared environmental factors (43%; CI 34-53) in both men and women. In women this genetic component was largely mediated through depression, but in men there was a significant heritable component to suicidal ideation that was independent of depression. These are the first results to show a genetic contribution to suicidal ideation that is independent of depression outside of a high-income country. These phenomena may be generalizable, because previous research highlights similarities between the aetiology of mental disorders in Sri Lanka and higher-income countries.

Self-consistent asset pricing models

NASA Astrophysics Data System (ADS)

Malevergne, Y.; Sornette, D.

2007-08-01

We discuss the foundations of factor or regression models in the light of the self-consistency condition that the market portfolio (and more generally the risk factors) is (are) constituted of the assets whose returns it is (they are) supposed to explain. As already reported in several articles, self-consistency implies correlations between the return disturbances. As a consequence, the alphas and betas of the factor model are unobservable. Self-consistency leads to renormalized betas with zero effective alphas, which are observable with standard OLS regressions. When the conditions derived from internal consistency are not met, the model is necessarily incomplete, which means that some sources of risk cannot be replicated (or hedged) by a portfolio of stocks traded on the market, even for infinite economies. Analytical derivations and numerical simulations show that, for arbitrary choices of the proxy which are different from the true market portfolio, a modified linear regression holds with a non-zero value αi at the origin between an asset i's return and the proxy's return. Self-consistency also introduces “orthogonality” and “normality” conditions linking the betas, alphas (as well as the residuals) and the weights of the proxy portfolio. Two diagnostics based on these orthogonality and normality conditions are implemented on a basket of 323 assets which have been components of the S&P500 in the period from January 1990 to February 2005. These two diagnostics show interesting departures from dynamical self-consistency starting about 2 years before the end of the Internet bubble. Assuming that the CAPM holds with the self-consistency condition, the OLS method automatically obeys the resulting orthogonality and normality conditions and therefore provides a simple way to self-consistently assess the parameters of the model by using proxy portfolios made only of the assets which are used in the CAPM regressions. Finally, the factor decomposition with the self-consistency condition derives a risk-factor decomposition in the multi-factor case which is identical to the principal component analysis (PCA), thus providing a direct link between model-driven and data-driven constructions of risk factors. This correspondence shows that PCA will therefore suffer from the same limitations as the CAPM and its multi-factor generalization, namely lack of out-of-sample explanatory power and predictability. In the multi-period context, the self-consistency conditions force the betas to be time-dependent with specific constraints.

Italian regional health system structure and expected cancer survival.

PubMed

Vercelli, Marina; Lillini, Roberto; Quaglia, Alberto; Capocaccia, Riccardo

2014-01-01

Few studies deal with the association of socioeconomic and health system resource variables with cancer survival at the Italian regional level, where the greatest number of decisions about social and health policies and resource allocations are taken. The present study aimed to describe the causal relationships between socioeconomic and health system resource factors and regional cancer survival and to compute the expected cancer survival at provincial, regional and area levels. Age-standardized relative survival at 5 years from diagnosis of cases incident in 1995-1998 and followed up to 2004 were derived by gender for 11 sites from the Italian Association of Cancer Registries data bank. The socioeconomic and health system resource variables, describing at a regional level the macro-economy, demography, labor market, and health resources for 1995-2005, came from the Health for All database. A principal components factor analysis was applied to the socioeconomic and health system resource variables. For every site, linear regression models were computed considering the relative survival at 5 years as a dependent variable and the principal components factor analysis factors as independent variables. The factors described the socioeconomic and health-related features of the regional systems and were causally related to the characteristics of the patient taken in charge. The models built by the factors allowed computation of the expected relative survival at 5 years with very good concordance with those observed at regional, macro-regional and national levels. In the regions without any cancer registry, survival was coherent with that of neighboring regions with similar socioeconomic and health system resources characteristics. The models highlighted the causal correlations between socioeconomic and health system resources and cancer survival, suggesting that they could be good evaluation tools for the efficiency of the resources allocation and use.

Exploration and confirmation of the latent variable structure of the Jefferson scale of empathy

PubMed Central

LaNoue, Marianna

2014-01-01

Objectives: To reaffirm the underlying components of the JSE by using exploratory factor analysis (EFA), and to confirm its latent variable structure by using confirmatory factor analysis (CFA). Methods Research participants included 2,612 medical students who entered Jefferson Medical College between 2002 and 2012. This sample was divided into two groups: Matriculants between 2002 and 2007 (n=1,380) and between 2008 and 2012 (n=1,232). Data for 2002-2007 matriculants were subjected to EFA (principal component factor extraction), and data for matriculants of 2008-2012 were used for CFA (structural equation modeling, and root mean square error for approximation). Results The EFA resulted in three factors: “perspective-taking,” “compassionate care” and “walking in patient’s shoes” replicating the 3-factor model reported in most of the previous studies. The CFA showed that the 3-factor model was an acceptable fit, thus confirming the latent variable structure emerged in the EFA. Corrected item-total score correlations for the total sample were all positive and statistically significant, ranging from 0.13 to 0.61 with a median of 0.44 (p<0.01). The item discrimination effect size indices (contrasting item mean scores for the top-third versus bottom-third JSE scorers) ranged from 0.50 to 1.4 indicating that the differences in item mean scores between top and bottom scorers on the JSE were of practical importance. Cronbach’s alpha coefficient of the JSE for the total sample was 0.80, ranging from 0.75 to 0.84 for matriculatnts of different years. Conclusions Findings provided further support for underlying constructs of the JSE, adding to its credibility. PMID:25341215

Optical properties of mineral dust aerosol including analysis of particle size, composition, and shape effects, and the impact of physical and chemical processing

NASA Astrophysics Data System (ADS)

Alexander, Jennifer Mary

Atmospheric mineral dust has a large impact on the earth's radiation balance and climate. The radiative effects of mineral dust depend on factors including, particle size, shape, and composition which can all be extremely complex. Mineral dust particles are typically irregular in shape and can include sharp edges, voids, and fine scale surface roughness. Particle shape can also depend on the type of mineral and can vary as a function of particle size. In addition, atmospheric mineral dust is a complex mixture of different minerals as well as other, possibly organic, components that have been mixed in while these particles are suspended in the atmosphere. Aerosol optical properties are investigated in this work, including studies of the effect of particle size, shape, and composition on the infrared (IR) extinction and visible scattering properties in order to achieve more accurate modeling methods. Studies of particle shape effects on dust optical properties for single component mineral samples of silicate clay and diatomaceous earth are carried out here first. Experimental measurements are modeled using T-matrix theory in a uniform spheroid approximation. Previous efforts to simulate the measured optical properties of silicate clay, using models that assumed particle shape was independent of particle size, have achieved only limited success. However, a model which accounts for a correlation between particle size and shape for the silicate clays offers a large improvement over earlier modeling approaches. Diatomaceous earth is also studied as an example of a single component mineral dust aerosol with extreme particle shapes. A particle shape distribution, determined by fitting the experimental IR extinction data, used as a basis for modeling the visible light scattering properties. While the visible simulations show only modestly good agreement with the scattering data, the fits are generally better than those obtained using more commonly invoked particle shape distributions. The next goal of this work is to investigate if modeling methods developed in the studies of single mineral components can be generalized to predict the optical properties of more authentic aerosol samples which are complex mixtures of different minerals. Samples of Saharan sand, Iowa loess, and Arizona road dust are used here as test cases. T-matrix based simulations of the authentic samples, using measured particle size distributions, empirical mineralogies, and a priori particle shape models for each mineral component are directly compared with the measured IR extinction spectra and visible scattering profiles. This modeling approach offers a significant improvement over more commonly applied models that ignore variations in particle shape with size or mineralogy and include only a moderate range of shape parameters. Mineral dust samples processed with organic acids and humic material are also studied in order to explore how the optical properties of dust can change after being aged in the atmosphere. Processed samples include quartz mixed with humic material, and calcite reacted with acetic and oxalic acid. Clear differences in the light scattering properties are observed for all three processed mineral dust samples when compared to the unprocessed mineral dust or organic salt products. These interactions result in both internal and external mixtures depending on the sample. In addition, the presence of these organic materials can alter the mineral dust particle shape. Overall, however, these results demonstrate the need to account for the effects of atmospheric aging of mineral dust on aerosol optical properties. Particle shape can also affect the aerodynamic properties of mineral dust aerosol. In order to account for these effects, the dynamic shape factor is used to give a measure of particle asphericity. Dynamic shape factors of quartz are measured by mass and mobility selecting particles and measuring their vacuum aerodynamic diameter. From this, dynamic shape factors in both the transition and vacuum regime can be derived. The measured dynamic shape factors of quartz agree quite well with the spheroidal shape distributions derived through studies of the optical properties.

Item response theory and factor analysis as a mean to characterize occurrence of response shift in a longitudinal quality of life study in breast cancer patients

PubMed Central

2014-01-01

Background The occurrence of response shift (RS) in longitudinal health-related quality of life (HRQoL) studies, reflecting patient adaptation to disease, has already been demonstrated. Several methods have been developed to detect the three different types of response shift (RS), i.e. recalibration RS, 2) reprioritization RS, and 3) reconceptualization RS. We investigated two complementary methods that characterize the occurrence of RS: factor analysis, comprising Principal Component Analysis (PCA) and Multiple Correspondence Analysis (MCA), and a method of Item Response Theory (IRT). Methods Breast cancer patients (n = 381) completed the EORTC QLQ-C30 and EORTC QLQ-BR23 questionnaires at baseline, immediately following surgery, and three and six months after surgery, according to the “then-test/post-test” design. Recalibration was explored using MCA and a model of IRT, called the Linear Logistic Model with Relaxed Assumptions (LLRA) using the then-test method. Principal Component Analysis (PCA) was used to explore reconceptualization and reprioritization. Results MCA highlighted the main profiles of recalibration: patients with high HRQoL level report a slightly worse HRQoL level retrospectively and vice versa. The LLRA model indicated a downward or upward recalibration for each dimension. At six months, the recalibration effect was statistically significant for 11/22 dimensions of the QLQ-C30 and BR23 according to the LLRA model (p ≤ 0.001). Regarding the QLQ-C30, PCA indicated a reprioritization of symptom scales and reconceptualization via an increased correlation between functional scales. Conclusions Our findings demonstrate the usefulness of these analyses in characterizing the occurrence of RS. MCA and IRT model had convergent results with then-test method to characterize recalibration component of RS. PCA is an indirect method in investigating the reprioritization and reconceptualization components of RS. PMID:24606836

Simultaneous Ultraviolet and X-Ray Spectroscopy of the Seyfert 1 Galaxy NGC 5548. I. Physical Conditions in the Ultraviolet Absorbers

NASA Astrophysics Data System (ADS)

Crenshaw, D. M.; Kraemer, S. B.; Gabel, J. R.; Kaastra, J. S.; Steenbrugge, K. C.; Brinkman, A. C.; Dunn, J. P.; George, I. M.; Liedahl, D. A.; Paerels, F. B. S.; Turner, T. J.; Yaqoob, T.

2003-09-01

We present new UV spectra of the nucleus of the Seyfert 1 galaxy NGC 5548, which we obtained with the Space Telescope Imaging Spectrograph at high spectral resolution, in conjunction with simultaneous Chandra X-Ray Observatory spectra. Taking advantage of the low UV continuum and broad emission-line fluxes, we have determined that the deepest UV absorption component covers at least a portion of the inner, high-ionization narrow-line region (NLR). We find nonunity covering factors in the cores of several kinematic components, which increase the column density measurements of N V and C IV by factors of 1.2-1.9 over the full-covering case; however, the revised columns have only a minor effect on the parameters derived from our photoionization models. For the first time, we have simultaneous N V and C IV columns for component 1 (at -1040 km s-1) and find that this component cannot be an X-ray warm absorber, contrary to our previous claim based on nonsimultaneous observations. We find that models of the absorbers based on solar abundances severely overpredict the O VI columns previously obtained with the Far Ultraviolet Spectroscopic Explorer and present arguments that this is not likely due to variability. However, models that include either enhanced nitrogen (twice solar) or dust, with strong depletion of carbon in either case, are successful in matching all of the observed ionic columns. These models result in substantially lower ionization parameters and total column densities compared to dust-free solar-abundance models and produce little O VII or O VIII, indicating that none of the UV absorbers are X-ray warm absorbers. Based on observations made with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. These observations are associated with proposal 9279.

Patterns in longitudinal growth of refraction in Southern Chinese children: cluster and principal component analysis.

PubMed

Chen, Yanxian; Chang, Billy Heung Wing; Ding, Xiaohu; He, Mingguang

2016-11-22

In the present study we attempt to use hypothesis-independent analysis in investigating the patterns in refraction growth in Chinese children, and to explore the possible risk factors affecting the different components of progression, as defined by Principal Component Analysis (PCA). A total of 637 first-born twins in Guangzhou Twin Eye Study with 6-year annual visits (baseline age 7-15 years) were available in the analysis. Cluster 1 to 3 were classified after a partitioning clustering, representing stable, slow and fast progressing groups of refraction respectively. Baseline age and refraction, paternal refraction, maternal refraction and proportion of two myopic parents showed significant differences across the three groups. Three major components of progression were extracted using PCA: "Average refraction", "Acceleration" and the combination of "Myopia stabilization" and "Late onset of refraction progress". In regression models, younger children with more severe myopia were associated with larger "Acceleration". The risk factors of "Acceleration" included change of height and weight, near work, and parental myopia, while female gender, change of height and weight were associated with "Stabilization", and increased outdoor time was related to "Late onset of refraction progress". We therefore concluded that genetic and environmental risk factors have different impacts on patterns of refraction progression.

Patterns in longitudinal growth of refraction in Southern Chinese children: cluster and principal component analysis

PubMed Central

Chen, Yanxian; Chang, Billy Heung Wing; Ding, Xiaohu; He, Mingguang

2016-01-01

In the present study we attempt to use hypothesis-independent analysis in investigating the patterns in refraction growth in Chinese children, and to explore the possible risk factors affecting the different components of progression, as defined by Principal Component Analysis (PCA). A total of 637 first-born twins in Guangzhou Twin Eye Study with 6-year annual visits (baseline age 7–15 years) were available in the analysis. Cluster 1 to 3 were classified after a partitioning clustering, representing stable, slow and fast progressing groups of refraction respectively. Baseline age and refraction, paternal refraction, maternal refraction and proportion of two myopic parents showed significant differences across the three groups. Three major components of progression were extracted using PCA: “Average refraction”, “Acceleration” and the combination of “Myopia stabilization” and “Late onset of refraction progress”. In regression models, younger children with more severe myopia were associated with larger “Acceleration”. The risk factors of “Acceleration” included change of height and weight, near work, and parental myopia, while female gender, change of height and weight were associated with “Stabilization”, and increased outdoor time was related to “Late onset of refraction progress”. We therefore concluded that genetic and environmental risk factors have different impacts on patterns of refraction progression. PMID:27874105

Phases of female sexual response cycle among Malaysian women with infertility: a factor analysis study.

PubMed

Seen Heng, Yeoh; Sidi, Hatta; Nik Jaafar, Nik Ruzyanei; Razali, Rosdinom; Ram, Hari

2013-04-01

This cross-sectional study aimed to determine the construct of the phases of the female sexual response cycle (SRC) among women attending an infertility clinic in a Malaysian tertiary center. The sexual response phases were measured with a validated Malay version of the Female Sexual Function Index (FSFI). The correlation structure of the items of the SRC phases (i.e. desire, arousal, orgasm, satisfaction and pain) was determined using principal component analysis (PCA), with varimax rotation method. The number of factors obtained was decided using Kaiser's criteria. A total of 150 married women with a mean age of 32 years participated in this study. Factor loadings using PCA with varimax rotation divided the sexual domains into three components. The first construct comprised sexual arousal, lubrication and pain (suggesting a mechanical component). The second construct were orgasm and sexual satisfaction (suggesting a physical achievement). Sexual desire, suggesting a psychological component, stood on its own as the third. The findings suggest that three constructs could be identified and in favor of the Basson model (a non-linear concept of SRC) for Malaysian women's sexual functioning. Understanding this would help clinicians to strategize the treatment approach of sexual dysfunction in women with infertility. Copyright © 2013 Wiley Publishing Asia Pty Ltd.

A qualitative assessment of a community pharmacy cognitive pharmaceutical services program, using a work system approach.

PubMed

Chui, Michelle A; Mott, David A; Maxwell, Leigh

2012-01-01

Although lack of time, trained personnel, and reimbursement have been identified as barriers to pharmacists providing cognitive pharmaceutical services (CPS) in community pharmacies, the underlying contributing factors of these barriers have not been explored. One approach to better understand barriers and facilitators to providing CPS is to use a work system approach to examine different components of a work system and how the components may impact care processes. The goals of this study were to identify and describe pharmacy work system characteristics that pharmacists identified and changed to provide CPS in a demonstration program. A qualitative approach was used for data collection. A purposive sample of 8 pharmacists at 6 community pharmacies participating in a demonstration program was selected to be interviewed. Each semistructured interview was audio recorded and transcribed, and the text was analyzed in a descriptive and interpretive manner by 3 analysts. Themes were identified in the text and aligned with 1 of 5 components of the Systems Engineering Initiative for Patient Safety (SEIPS) work system model (organization, tasks, tools/technology, people, and environment). A total of 21 themes were identified from the interviews, and 7 themes were identified across all 6 interviews. The organization component of the SEIPS model contained the most (n=10) themes. Numerous factors within a pharmacy work system appear important to enable pharmacists to provide CPS. Leadership and foresight by the organization to implement processes (communication, coordination, planning, etc.) to facilitate providing CPS was a key finding across the interviews. Expanding technician responsibilities was reported to be essential for successfully implementing CPS. To be successful in providing CPS, pharmacists must be cognizant of the different components of the pharmacy work system and how these components influence providing CPS. Copyright © 2012 Elsevier Inc. All rights reserved.

A qualitative assessment of a community pharmacy cognitive pharmaceutical services program, using a work system approach

PubMed Central

Chui, Michelle A.; Mott, David A.; Maxwell, Leigh

2012-01-01

Background Although lack of time, trained personnel, and reimbursement have been identified as barriers to pharmacists providing cognitive pharmaceutical services (CPS) in community pharmacies, the underlying contributing factors of these barriers have not been explored. One approach to better understand barriers and facilitators to providing CPS is to use a work system approach to examine different components of a work system and how the components may impact care processes. Objectives The goals of this study were to identify and describe pharmacy work system characteristics that pharmacists identified and changed to provide CPS in a demonstration program. Methods A qualitative approach was used for data collection. A purposive sample of 8 pharmacists at 6 community pharmacies participating in a demonstration program was selected to be interviewed. Each semistructured interview was audio recorded and transcribed, and the text was analyzed in a descriptive and interpretive manner by 3 analysts. Themes were identified in the text and aligned with 1 of 5 components of the Systems Engineering Initiative for Patient Safety (SEIPS) work system model (organization, tasks, tools/technology, people, and environment). Results A total of 21 themes were identified from the interviews, and 7 themes were identified across all 6 interviews. The organization component of the SEIPS model contained the most (n = 10) themes. Numerous factors within a pharmacy work system appear important to enable pharmacists to provide CPS. Leadership and foresight by the organization to implement processes (communication, coordination, planning, etc.) to facilitate providing CPS was a key finding across the interviews. Expanding technician responsibilities was reported to be essential for successfully implementing CPS. Conclusions To be successful in providing CPS, pharmacists must be cognizant of the different components of the pharmacy work system and how these components influence providing CPS. PMID:21824822

Sociodemographic Factors Associated With Changes in Successful Aging in Spain: A Follow-Up Study.

PubMed

Domènech-Abella, Joan; Perales, Jaime; Lara, Elvira; Moneta, Maria Victoria; Izquierdo, Ana; Rico-Uribe, Laura Alejandra; Mundó, Jordi; Haro, Josep Maria

2017-06-01

Successful aging (SA) refers to maintaining well-being in old age. Several definitions or models of SA exist (biomedical, psychosocial, and mixed). We examined the longitudinal association between various SA models and sociodemographic factors, and analyzed the patterns of change within these models. This was a nationally representative follow-up in Spain including 3,625 individuals aged ≥50 years. Some 1,970 individuals were interviewed after 3 years. Linear regression models were used to analyze the survey data. Age, sex, and occupation predicted SA in the biomedical model, while marital status, educational level, and urbanicity predicted SA in the psychosocial model. The remaining models included different sets of these predictors as significant. In the psychosocial model, individuals tended to improve over time but this was not the case in the biomedical model. The biomedical and psychosocial components of SA need to be addressed specifically to achieve the best aging trajectories.

Reliability and Validity of the Sexual Pressure Scale for Women-Revised

PubMed Central

Jones, Rachel; Gulick, Elsie

2008-01-01

Sexual pressure among young urban women represents adherence to gender stereotypical expectations to engage in sex. Revision of the original 5-factor Sexual Pressure Scale was undertaken in two studies to improve reliabilities in two of the five factors. In Study 1 the reliability of the Sexual Pressure Scale for Women-Revised (SPSW-R) was tested, and principal components analysis was performed in a sample of 325 young, urban women. A parsimonious 18-item, 4-factor model explained 61% of the variance. In Study 2 the theory underlying sexual pressure was supported by confirmatory factor analysis using structural equation modeling in a sample of 181 women. Reliabilities of the SPSW-R total and subscales were very satisfactory, suggesting it may be used in intervention research. PMID:18666222

Social–Emotional Factors Affecting Achievement Outcomes Among Disadvantaged Students: Closing the Achievement Gap

PubMed Central

Becker, Bronwyn E.; Luthar, Suniya S.

2012-01-01

Despite concentrated efforts at improving inferior academic outcomes among disadvantaged students, a substantial achievement gap between the test scores of these students and others remains (Jencks & Phillips, 1998; National Center for Education Statistics, 2000a, 2000b; Valencia & Suzuki, 2000). Existing research used ecological models to document social–emotional factors at multiple levels of influence that undermine academic performance. This article integrates ideas from various perspectives in a comprehensive and interdisciplinary model that will inform policy makers, administrators, and schools about the social–emotional factors that act as both risk and protective factors for disadvantaged students’ learning and opportunities for academic success. Four critical social–emotional components that influence achievement performance (academic and school attachment, teacher support, peer values, and mental health) are reviewed. PMID:23255834

Social-Emotional Factors Affecting Achievement Outcomes Among Disadvantaged Students: Closing the Achievement Gap.

PubMed

Becker, Bronwyn E; Luthar, Suniya S

2002-01-01

Despite concentrated efforts at improving inferior academic outcomes among disadvantaged students, a substantial achievement gap between the test scores of these students and others remains (Jencks & Phillips, 1998; National Center for Education Statistics, 2000a, 2000b; Valencia & Suzuki, 2000). Existing research used ecological models to document social-emotional factors at multiple levels of influence that undermine academic performance. This article integrates ideas from various perspectives in a comprehensive and interdisciplinary model that will inform policy makers, administrators, and schools about the social-emotional factors that act as both risk and protective factors for disadvantaged students' learning and opportunities for academic success. Four critical social-emotional components that influence achievement performance (academic and school attachment, teacher support, peer values, and mental health) are reviewed.

Isolating the anthropogenic component of Arctic warming

DOE PAGES

Chylek, Petr; Hengartner, Nicholas; Lesins, Glen; ...

2014-05-28

Structural equation modeling is used in statistical applications as both confirmatory and exploratory modeling to test models and to suggest the most plausible explanation for a relationship between the independent and the dependent variables. Although structural analysis cannot prove causation, it can suggest the most plausible set of factors that influence the observed variable. Here, we apply structural model analysis to the annual mean Arctic surface air temperature from 1900 to 2012 to find the most effective set of predictors and to isolate the anthropogenic component of the recent Arctic warming by subtracting the effects of natural forcing and variabilitymore » from the observed temperature. We also find that anthropogenic greenhouse gases and aerosols radiative forcing and the Atlantic Multidecadal Oscillation internal mode dominate Arctic temperature variability. Finally, our structural model analysis of observational data suggests that about half of the recent Arctic warming of 0.64 K/decade may have anthropogenic causes.« less

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing.

PubMed

Leong, Siow Hoo; Ong, Seng Huat

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index.

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing

PubMed Central

Leong, Siow Hoo

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index. PMID:28686634

Can Coolness Predict Technology Adoption? Effects of Perceived Coolness on User Acceptance of Smartphones with Curved Screens.

PubMed

Kim, Ki Joon; Shin, Dong-Hee; Park, Eunil

2015-09-01

This study proposes an acceptance model for curved-screen smartphones, and explores how the sense of coolness induced by attractiveness, originality, subcultural appeal, and the utility of the curved screen promotes smartphone adoption. The results of structural equation modeling analyses (N = 246) show that these components of coolness (except utility) increase the acceptance of the technology by enhancing the smartphones' affectively driven qualities rather than their utilitarian ones. The proposed coolness model is then compared with the original technology acceptance model to validate that the coolness factors are indeed equally effective determinants of usage intention, as are the extensively studied usability factors such as perceived ease of use and usefulness.

Evaluating the Bulk Lorentz Factors of Outflow Material: Lessons Learned from the Extremely Energetic Outburst GRB 160625B

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

Wang, Yuan-Zhu; Wang, Hao; Zhang, Shuai

2017-02-10

GRB 160625B is an extremely bright outburst with well-monitored afterglow emission. The geometry-corrected energy is high, up to ∼5.2 × 10{sup 52} erg or even ∼8 × 10{sup 52} erg, rendering it the most energetic GRB prompt emission recorded so far. We analyzed the time-resolved spectra of the prompt emission and found that in some intervals there were likely thermal-radiation components and the high energy emission was characterized by significant cutoff. The bulk Lorentz factors of the outflow material are estimated accordingly. We found out that the Lorentz factors derived in the thermal-radiation model are consistent with the luminosity-Lorentz factormore » correlation found in other bursts, as well as in GRB 090902B for the time-resolved thermal-radiation components, while the spectral cutoff model yields much lower Lorentz factors that are in tension with the constraints set by the electron pair Compton scattering process. We then suggest that these spectral cutoffs are more likely related to the particle acceleration process and that one should be careful in estimating the Lorentz factors if the spectrum cuts at a rather low energy (e.g., ∼tens of MeV). The nature of the central engine has also been discussed, and a stellar-mass black hole is favored.« less

Analyzing endocrine system conservation and evolution.

PubMed

Bonett, Ronald M

2016-08-01

Analyzing variation in rates of evolution can provide important insights into the factors that constrain trait evolution, as well as those that promote diversification. Metazoan endocrine systems exhibit apparent variation in evolutionary rates of their constituent components at multiple levels, yet relatively few studies have quantified these patterns and analyzed them in a phylogenetic context. This may be in part due to historical and current data limitations for many endocrine components and taxonomic groups. However, recent technological advancements such as high-throughput sequencing provide the opportunity to collect large-scale comparative data sets for even non-model species. Such ventures will produce a fertile data landscape for evolutionary analyses of nucleic acid and amino acid based endocrine components. Here I summarize evolutionary rate analyses that can be applied to categorical and continuous endocrine traits, and also those for nucleic acid and protein-based components. I emphasize analyses that could be used to test whether other variables (e.g., ecology, ontogenetic timing of expression, etc.) are related to patterns of rate variation and endocrine component diversification. The application of phylogenetic-based rate analyses to comparative endocrine data will greatly enhance our understanding of the factors that have shaped endocrine system evolution. Copyright © 2016 Elsevier Inc. All rights reserved.

Determination of effective loss factors in reduced SEA models

NASA Astrophysics Data System (ADS)

Chimeno Manguán, M.; Fernández de las Heras, M. J.; Roibás Millán, E.; Simón Hidalgo, F.

2017-01-01

The definition of Statistical Energy Analysis (SEA) models for large complex structures is highly conditioned by the classification of the structure elements into a set of coupled subsystems and the subsequent determination of the loss factors representing both the internal damping and the coupling between subsystems. The accurate definition of the complete system can lead to excessively large models as the size and complexity increases. This fact can also rise practical issues for the experimental determination of the loss factors. This work presents a formulation of reduced SEA models for incomplete systems defined by a set of effective loss factors. This reduced SEA model provides a feasible number of subsystems for the application of the Power Injection Method (PIM). For structures of high complexity, their components accessibility can be restricted, for instance internal equipments or panels. For these cases the use of PIM to carry out an experimental SEA analysis is not possible. New methods are presented for this case in combination with the reduced SEA models. These methods allow defining some of the model loss factors that could not be obtained through PIM. The methods are validated with a numerical analysis case and they are also applied to an actual spacecraft structure with accessibility restrictions: a solar wing in folded configuration.

Light-meson masses in an unquenched quark model

NASA Astrophysics Data System (ADS)

Chen, Xiaoyun; Ping, Jialun; Roberts, Craig D.; Segovia, Jorge

2018-05-01

We perform a coupled-channels calculation of the masses of light mesons with the quantum numbers I JP =-, (I ,J )=0 , 1, by including q q ¯ and (q q ¯)2 components in a nonrelativistic chiral quark model. The coupling between two- and four-quark configurations is realized through a 3P0 quark-pair creation model. With the usual form of this operator, the mass shifts are large and negative, an outcome which raises serious issues of validity for the quenched quark model. Herein, therefore, we introduce some improvements of the 3P0 operator in order to reduce the size of the mass shifts. By introducing two simple factors, physically well motivated, the coupling between q q ¯ and (q q ¯)2 components is weakened, producing mass shifts that are around 10%-20% of hadron bare masses.

Engineering model of the electric drives of separation device for simulation of automatic control systems of reactive power compensation by means of serially connected capacitors

NASA Astrophysics Data System (ADS)

Juromskiy, V. M.

2016-09-01

It is developed a mathematical model for an electric drive of high-speed separation device in terms of the modeling dynamic systems Simulink, MATLAB. The model is focused on the study of the automatic control systems of the power factor (Cosφ) of an actuator by compensating the reactive component of the total power by switching a capacitor bank in series with the actuator. The model is based on the methodology of the structural modeling of dynamic processes.

An Analysis of Viable Financial Negotiations Processes and Related Internal Controls for Procurement in Pakistan

DTIC Science & Technology

2016-06-01

regulations are in accordance with UNCITRAL Model Law and are based on principles of “ accountability , transparency, fairness, efficiency and value for... account certain factors about the firm(s) for pre-qualification. These factors include past performance and experience; financial health; managerial...internal control components, along with associated principles , were discussed in detail to develop a suitable internal control system for the financial

Simulations of Highway Traffic With Various Degrees of Automation

DOT National Transportation Integrated Search

1996-01-01

A traffic simulator to study highway traffic under various degrees of automation is being developed at Argonne National Laboratory. The key components of this simulator include a global and a local Expert Driver Model, a human factor study and a grap...

RECENT APPLICATIONS OF SOURCE APPORTIONMENT METHODS AND RELATED NEEDS

EPA Science Inventory

Traditional receptor modeling studies have utilized factor analysis (like principal component analysis, PCA) and/or Chemical Mass Balance (CMB) to assess source influences. The limitations with these approaches is that PCA is qualitative and CMB requires the input of source pr...

Uncontrolled eating in adolescents: The role of impulsivity and automatic approach bias for food.

PubMed

Booth, Charlotte; Spronk, Desiree; Grol, Maud; Fox, Elaine

2018-01-01

Obesity is a global problem reaching epidemic proportions and can be explained by unhealthy eating and sedentary lifestyles. Understanding the psychological processes underlying unhealthy eating behaviour is crucial for the development of effective obesity prevention programmes. Dual-process models implicate the interplay between impaired cognitive control and enhanced automatic responsivity to rewarding food cues as key risk factors. The current study assessed the influence of four different components of trait impulsivity (reflecting impaired cognitive control) and automatic approach bias for food (reflecting automatic responsivity to food) on uncontrolled eating in a large sample (N = 504) of young adolescents. Of the four impulsivity factors, negative urgency was found to be the strongest predictor of uncontrolled eating. Interestingly, we found that lack of premeditation was a key risk factor for uncontrolled eating, but only when approach bias for food was high, supporting a dual-process model. Lack of perseverance showed a similar interactive pattern to a lesser degree and sensation-seeking did not predict uncontrolled eating. Together, our results show that distinct components of trait impulsivity are differentially associated with uncontrolled eating behaviour in adolescents, and that automatic processing of food cues may be an important factor in modulating this relationship. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Study on nondestructive discrimination of genuine and counterfeit wild ginsengs using NIRS

NASA Astrophysics Data System (ADS)

Lu, Q.; Fan, Y.; Peng, Z.; Ding, H.; Gao, H.

2012-07-01

A new approach for the nondestructive discrimination between genuine wild ginsengs and the counterfeit ones by near infrared spectroscopy (NIRS) was developed. Both discriminant analysis and back propagation artificial neural network (BP-ANN) were applied to the model establishment for discrimination. Optimal modeling wavelengths were determined based on the anomalous spectral information of counterfeit samples. Through principal component analysis (PCA) of various wild ginseng samples, genuine and counterfeit, the cumulative percentages of variance of the principal components were obtained, serving as a reference for principal component (PC) factor determination. Discriminant analysis achieved an identification ratio of 88.46%. With sample' truth values as its outputs, a three-layer BP-ANN model was built, which yielded a higher discrimination accuracy of 100%. The overall results sufficiently demonstrate that NIRS combined with BP-ANN classification algorithm performs better on ginseng discrimination than discriminant analysis, and can be used as a rapid and nondestructive method for the detection of counterfeit wild ginsengs in food and pharmaceutical industry.

Distillation and Air Stripping Designs for the Lunar Surface

NASA Technical Reports Server (NTRS)

Boul, Peter J.; Lange, Kevin E.; Conger, Bruce; Anderson, Molly

2009-01-01

Air stripping and distillation are two different gravity-based methods, which may be applied to the purification of wastewater on the lunar base. These gravity-based solutions to water processing are robust physical separation techniques, which may be advantageous to many other techniques for their simplicity in design and operation. The two techniques can be used in conjunction with each other to obtain high purity water. The components and feed compositions for modeling waste water streams are presented in conjunction with the Aspen property system for traditional stage distillation models and air stripping models. While the individual components for each of the waste streams will vary naturally within certain bounds, an analog model for waste water processing is suggested based on typical concentration ranges for these components. Target purity levels for the for recycled water are determined for each individual component based on NASA s required maximum contaminant levels for potable water Distillation processes are modeled separately and in tandem with air stripping to demonstrate the potential effectiveness and utility of these methods in recycling wastewater on the Moon. Optimum parameters such as reflux ratio, feed stage location, and processing rates are determined with respect to the power consumption of the process. Multistage distillation is evaluated for components in wastewater to determine the minimum number of stages necessary for each of 65 components in humidity condensate and urine wastewater mixed streams. Components of the wastewater streams are ranked by Henry s Law Constant and the suitability of air stripping in the purification of wastewater in terms of component removal is evaluated. Scaling factors for distillation and air stripping columns are presented to account for the difference in the lunar gravitation environment. Commercially available distillation and air stripping units which are considered suitable for Exploration Life Support are presented. The advantages to the various designs are summarized with respect to water purity levels, power consumption, and processing rates.

Figures of merit for present and future dark energy probes

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

Mortonson, Michael J.; Huterer, Dragan; Hu, Wayne

2010-09-15

We compare current and forecasted constraints on dynamical dark energy models from Type Ia supernovae and the cosmic microwave background using figures of merit based on the volume of the allowed dark energy parameter space. For a two-parameter dark energy equation of state that varies linearly with the scale factor, and assuming a flat universe, the area of the error ellipse can be reduced by a factor of {approx}10 relative to current constraints by future space-based supernova data and CMB measurements from the Planck satellite. If the dark energy equation of state is described by a more general basis ofmore » principal components, the expected improvement in volume-based figures of merit is much greater. While the forecasted precision for any single parameter is only a factor of 2-5 smaller than current uncertainties, the constraints on dark energy models bounded by -1{<=}w{<=}1 improve for approximately 6 independent dark energy parameters resulting in a reduction of the total allowed volume of principal component parameter space by a factor of {approx}100. Typical quintessence models can be adequately described by just 2-3 of these parameters even given the precision of future data, leading to a more modest but still significant improvement. In addition to advances in supernova and CMB data, percent-level measurement of absolute distance and/or the expansion rate is required to ensure that dark energy constraints remain robust to variations in spatial curvature.« less

A new state space model for the NASA/JPL 70-meter antenna servo controls

NASA Technical Reports Server (NTRS)

Hill, R. E.

1987-01-01

A control axis referenced model of the NASA/JPL 70-m antenna structure is combined with the dynamic equations of servo components to produce a comprehansive state variable (matrix) model of the coupled system. An interactive Fortran program for generating the linear system model and computing its salient parameters is described. Results are produced in a state variable, block diagram, and in factored transfer function forms to facilitate design and analysis by classical as well as modern control methods.

The development of a fear of falling interdisciplinary intervention program

PubMed Central

Gomez, Fernando; Curcio, Carmen-Lucia

2007-01-01

Objective: To describe the development process of a protocol for a fear of falling interdisciplinary intervention program based on the main factors associated with fear of falling. Design/methods: The process of developing a protocol consisted of defining the target population, selecting the initial assessment components, adapting the intervention program based on findings about fear of falling and restriction of activities in this population. Settings: University-affiliated outpatient vertigo, dizziness and falls clinic in coffee-growers zone of Colombian Andes Mountains. Results: An intervention program was developed based on three main falling conceptual models. A medical intervention, based on a biomedical and pathophysiological model, a physiotherapeutic intervention based on a postural control model and a psychological intervention based on a biological-behavioral model. Conclusion: This interdisciplinary fear of falling intervention program developed is based on particular characteristics of target population, with differences in the inclusion criteria and the program intervention components; with emphasis on medical (recurrent falls and dizziness evaluation and management), psychological (cognitive-behavioral therapy) and physiotherapeutic (balance and transfers training) components. PMID:18225468

Modeling homeorhetic trajectories of milk component yields, body composition and dry-matter intake in dairy cows: Influence of parity, milk production potential and breed.

PubMed

Daniel, J B; Friggens, N C; van Laar, H; Ingvartsen, K L; Sauvant, D

2018-06-01

The control of nutrient partitioning is complex and affected by many factors, among them physiological state and production potential. Therefore, the current model aims to provide for dairy cows a dynamic framework to predict a consistent set of reference performance patterns (milk component yields, body composition change, dry-matter intake) sensitive to physiological status across a range of milk production potentials (within and between breeds). Flows and partition of net energy toward maintenance, growth, gestation, body reserves and milk components are described in the model. The structure of the model is characterized by two sub-models, a regulating sub-model of homeorhetic control which sets dynamic partitioning rules along the lactation, and an operating sub-model that translates this into animal performance. The regulating sub-model describes lactation as the result of three driving forces: (1) use of previously acquired resources through mobilization, (2) acquisition of new resources with a priority of partition towards milk and (3) subsequent use of resources towards body reserves gain. The dynamics of these three driving forces were adjusted separately for fat (milk and body), protein (milk and body) and lactose (milk). Milk yield is predicted from lactose and protein yields with an empirical equation developed from literature data. The model predicts desired dry-matter intake as an outcome of net energy requirements for a given dietary net energy content. The parameters controlling milk component yields and body composition changes were calibrated using two data sets in which the diet was the same for all animals. Weekly data from Holstein dairy cows was used to calibrate the model within-breed across milk production potentials. A second data set was used to evaluate the model and to calibrate it for breed differences (Holstein, Danish Red and Jersey) on the mobilization/reconstitution of body composition and on the yield of individual milk components. These calibrations showed that the model framework was able to adequately simulate milk yield, milk component yields, body composition changes and dry-matter intake throughout lactation for primiparous and multiparous cows differing in their production level.

The Analysis of the Contribution of Human Factors to the In-Flight Loss of Control Accidents

NASA Technical Reports Server (NTRS)

Ancel, Ersin; Shih, Ann T.

2012-01-01

In-flight loss of control (LOC) is currently the leading cause of fatal accidents based on various commercial aircraft accident statistics. As the Next Generation Air Transportation System (NextGen) emerges, new contributing factors leading to LOC are anticipated. The NASA Aviation Safety Program (AvSP), along with other aviation agencies and communities are actively developing safety products to mitigate the LOC risk. This paper discusses the approach used to construct a generic integrated LOC accident framework (LOCAF) model based on a detailed review of LOC accidents over the past two decades. The LOCAF model is comprised of causal factors from the domain of human factors, aircraft system component failures, and atmospheric environment. The multiple interdependent causal factors are expressed in an Object-Oriented Bayesian belief network. In addition to predicting the likelihood of LOC accident occurrence, the system-level integrated LOCAF model is able to evaluate the impact of new safety technology products developed in AvSP. This provides valuable information to decision makers in strategizing NASA's aviation safety technology portfolio. The focus of this paper is on the analysis of human causal factors in the model, including the contributions from flight crew and maintenance workers. The Human Factors Analysis and Classification System (HFACS) taxonomy was used to develop human related causal factors. The preliminary results from the baseline LOCAF model are also presented.

Probing the structure of the gas in the Milky Way through X-ray high-resolution spectroscopy

NASA Astrophysics Data System (ADS)

Gatuzz, Efraín; Churazov, Eugene

2018-02-01

We have developed a new X-ray absorption model, called IONeq, which computes the optical depth τ(E) simultaneously for ions of all abundant elements, assuming ionization equilibrium and taking into account turbulent broadening. We use this model to analyse the interstellar medium (ISM) absorption features in the Milky Way for a sample of 18 Galactic (LMXBs) and 42 extragalactic sources (mainly Blazars). The absorbing ISM was modelled as a combination of three components/phases - neutral (T ≲ 1 × 104 K), warm (T ˜ 5 × 104 K) and hot (T ˜ 2 × 106 K). We found that the spatial distribution of both, neutral and warm components, are difficult to describe using smooth profiles due to non-uniform distribution of the column densities over the sky. For the hot phase we used a combination of a flattened disc and a halo, finding comparable column densities for both spatial components, of the order of ˜6-7 × 1018 cm-2, although this conclusion depends on the adopted parametrization. If the halo component has sub-solar abundance Z, then the column density has to be scaled up by a factor of Z_{⊙}/Z. The vertically integrated column densities of the disc components suggest the following mass fractions for these three ISM phases in the Galactic disc: neutral ˜ 89 per cent, warm ˜ 8 per cent and hot ˜ 3 per cent components, respectively. The constraints on the radial distribution of the halo component of the hot component are weak.

A community-based validation study of the short-form 36 version 2 Philippines (Tagalog) in two cities in the Philippines.

PubMed

Castillo-Carandang, Nina T; Sison, Olivia T; Grefal, Mary Lenore; Sy, Rody G; Alix, Oliver C; Llanes, Elmer Jasper B; Reganit, Paul Ferdinand M; Gumatay, Allan Wilbert G; Punzalan, Felix Eduardo R; Velandria, Felicidad V; Tai, E Shyong; Wee, Hwee-Lin

2013-01-01

To evaluate the validity and reliability of the Philippines (Tagalog) Short Form 36 Health Survey version 2 (SF-36v2(®)) standard questionnaire among Filipinos residing in two cities. The official Philippines (Tagalog) SF-36v2 standard (4-week recall) version was pretested on 30 participants followed by formal and informal cognitive debriefing. To obtain the feedback on translation by bilingual respondents, each SF-36v2 question was stated first in English followed by Tagalog. No revisions to the original questionnaire were needed except that participants thought it was appropriate to incorporate "po" in the instructions to make it more polite. Face-to-face interviews of 562 participants aged 20-50 years living in two barangays (villages) in the highly urbanized city of Makati City (Metro Manila) and in urban and rural barangays in Tanauan City (province of Batangas) were subsequently conducted. Content validity, item level validity, reliability and factor structure of the SF-36v2 (Tagalog) were examined. Content validity of the SF-36v2 was assessed to be adequate for assessing health status among Filipinos. Item means of Philippines (Tagalog) SF-36v2 were similar with comparable scales in the US English, Singapore (English and Chinese) and Thai SF-36 version 1. Item-scale correlation exceeded 0.4 for all items except the bathing item in PF (correlation: 0.31). In exploratory factor analysis, the US two-component model was supported. However, in confirmatory factor analysis, the Japanese three-component model fit the Tagalog data better than the US two-component model. The Philippines (Tagalog) SF-36v2 is a valid and reliable instrument for measuring health status among residents of Makati City (Metro Manila) and Tanauan City (Province of Batangas).

Development of a Pressure Sensitive Paint System with Correction for Temperature Variation

NASA Technical Reports Server (NTRS)

Simmons, Kantis A.

1995-01-01

Pressure Sensitive Paint (PSP) is known to provide a global image of pressure over a model surface. However, improvements in its accuracy and reliability are needed. Several factors contribute to the inaccuracy of PSP. One major factor is that luminescence is temperature dependent. To correct the luminescence of the pressure sensing component for changes in temperature, a temperature sensitive luminophore incorporated in the paint allows the user to measure both pressure and temperature simultaneously on the surface of a model. Magnesium Octaethylporphine (MgOEP) was used as a temperature sensing luminophore, with the pressure sensing luminophore, Platinum Octaethylporphine (PtOEP), to correct for temperature variations in model surface pressure measurements.

Solar array electrical performance assessment for Space Station Freedom

NASA Technical Reports Server (NTRS)

Smith, Bryan K.; Brisco, Holly

1993-01-01

Electrical power for Space Station Freedom will be generated by large Photovoltaic arrays with a beginning of life power requirement of 30.8 kW per array. The solar arrays will operate in a Low Earth Orbit (LEO) over a design life of fifteen years. This paper provides an analysis of the predicted solar array electrical performance over the design life and presents a summary of supporting analysis and test data for the assigned model parameters and performance loss factors. Each model parameter and loss factor is assessed based upon program requirements, component analysis, and test data to date. A description of the LMSC performance model, future test plans, and predicted performance ranges are also given.

Solar array electrical performance assessment for Space Station Freedom

NASA Technical Reports Server (NTRS)

Smith, Bryan K.; Brisco, Holly

1993-01-01

Electrical power for Space Station Freedom will be generated by large photovoltaic arrays with a beginning of life power requirement of 30.8 kW per array. The solar arrays will operate in a Low Earth Orbit (LEO) over a design life of fifteen years. This paper provides an analysis of the predicted solar array electrical performance over the design life and presents a summary of supporting analysis and test data for the assigned model parameters and performance loss factors. Each model parameter and loss factor is assessed based upon program requirements, component analysis and test data to date. A description of the LMSC performance model future test plans and predicted performance ranges are also given.

Beryllium and titanium cost-adjustment report

NASA Astrophysics Data System (ADS)

Owen, John; Ulph, Eric, Sr.

1991-09-01

This report summarizes cost adjustment factors for beryllium (Be, S200) and titanium (Ti, 6Al-4V) that were derived relative to aluminum (Al, 7075-T6). Aluminum is traditionally the material upon which many of the Cost Analysis Office, Missile Division cost estimating relationships (CERs) are based. The adjustment factors address both research and development and production (Q > 100) quantities. In addition, the factors derived include optical elements, normal structure, and structure with special requirements for minimal microcreep, such as sensor assembly parts and supporting components. Since booster cost per payload pound is an even larger factor in total missile launch costs than was initially presumed, the primary cost driver for all materials compared was the missiles' booster cost per payload pound for both R&D and production quantities. Al and Ti are 1.5 and 2.4 times more dense, respectively, than Be, and the cost to lift the heavier materials results in greater booster expense. In addition, Al and Ti must be 2.1 and 2.8, respectively, times the weight of a Be component to provide equivalent stiffness, based on the example component addressed in the report. These factors also increase booster costs. After review of the relative factors cited above, especially the lower costs for Be when stiffness and booster costs are taken into consideration, affordability becomes an important issue. When this study was initiated, both government and contractor engineers said that Be was the material to be used as a last resort because of its prohibitive cost and extreme toxicity. Although the initial price of Be may lead one to believe that any Be product would be extremely expensive, the total cost of Be used for space applications is actually competitive with or less costly than either Al or Ti. Also, the Be toxicity problem has turned out to be a non-issue for purchasers of finished Be components since no machining or grinding operations are required on the finished components. Several new costing techniques are developed which provide quantitative measures of the cost of material stiffness, costs related to payload weight, and costs associated with the relative temperature stability of different materials. In addition, use is made of the Design/Cost Trade Model developed by Applied Research, Inc., to determine the booster cost differential relative to changes in payload weight, and a mirror fabrication cost model, developed by OCA Applied Optics, was used for mirror costing. This report is a summary of an extensive study done by the U.S. Army Strategic Defense Command, Huntsville, Alabama.

Single-trial event-related potentials to significant stimuli.

PubMed

Rushby, Jacqueline A; Barry, Robert J

2009-11-01

The stimulus-response pattern of the skin conductance response (SCR) was used as a model of the Orienting Reflex (OR) to assess the P1, N1, P2, N2 and late positive complex (LPC/P300) components of the ERP in a simple habituation paradigm, in which a single series of 12 innocuous tones were presented at a very long interstimulus interval (2 min). To maintain their waking state during this boring task, participants were instructed to alternately close or open their eyes to each stimulus. None of the baseline-to-peak ERP measures showed trials effects comparable with the marked habituation over trials shown by the SCRs. Principal Components Analysis was used to decompose the ERP, yielding factors identified as the N1, N2, P3a, P3b and Novelty P3 components. An additional factor represented later eye-movement activity. No trial effects were apparent for the N1, N2, P3a or P3b components. The Novelty P3 showed marked response decrement over trials. These results are discussed in relation to current conceptualisations of the OR.

Using Separable Nonnegative Matrix Factorization Techniques for the Analysis of Time-Resolved Raman Spectra.

PubMed

Luce, Robert; Hildebrandt, Peter; Kuhlmann, Uwe; Liesen, Jörg

2016-09-01

The key challenge of time-resolved Raman spectroscopy is the identification of the constituent species and the analysis of the kinetics of the underlying reaction network. In this work we present an integral approach that allows for determining both the component spectra and the rate constants simultaneously from a series of vibrational spectra. It is based on an algorithm for nonnegative matrix factorization that is applied to the experimental data set following a few pre-processing steps. As a prerequisite for physically unambiguous solutions, each component spectrum must include one vibrational band that does not significantly interfere with the vibrational bands of other species. The approach is applied to synthetic "experimental" spectra derived from model systems comprising a set of species with component spectra differing with respect to their degree of spectral interferences and signal-to-noise ratios. In each case, the species involved are connected via monomolecular reaction pathways. The potential and limitations of the approach for recovering the respective rate constants and component spectra are discussed. © The Author(s) 2016.

The Development and Validation of the Online Shopping Addiction Scale.

PubMed

Zhao, Haiyan; Tian, Wei; Xin, Tao

2017-01-01

We report the development and validation of a scale to measure online shopping addiction. Inspired by previous theories and research on behavioral addiction, the Griffiths's widely accepted six-factor component model was referred to and an 18-item scale was constructed, with each component measured by three items. The results of exploratory factor analysis, based on Sample 1 (999 college students) and confirmatory factor analysis, based on Sample 2 (854 college students) showed the Griffiths's substantive six-factor structure underlay the online shopping addiction scale. Cronbach's alpha suggested that the resulting scale was highly reliable. Concurrent validity, based on Sample 3 (328 college students), was also satisfactory as indicated by correlations between the scale and measures of similar constructs. Finally, self-perceived online shopping addiction can be predicted to a relatively high degree. The present 18-item scale is a solid theory-based instrument to empirically measure online shopping addiction and can be used for understanding the phenomena among young adults.

The Development and Validation of the Online Shopping Addiction Scale

PubMed Central

Zhao, Haiyan; Tian, Wei; Xin, Tao

2017-01-01

We report the development and validation of a scale to measure online shopping addiction. Inspired by previous theories and research on behavioral addiction, the Griffiths's widely accepted six-factor component model was referred to and an 18-item scale was constructed, with each component measured by three items. The results of exploratory factor analysis, based on Sample 1 (999 college students) and confirmatory factor analysis, based on Sample 2 (854 college students) showed the Griffiths's substantive six-factor structure underlay the online shopping addiction scale. Cronbach's alpha suggested that the resulting scale was highly reliable. Concurrent validity, based on Sample 3 (328 college students), was also satisfactory as indicated by correlations between the scale and measures of similar constructs. Finally, self-perceived online shopping addiction can be predicted to a relatively high degree. The present 18-item scale is a solid theory-based instrument to empirically measure online shopping addiction and can be used for understanding the phenomena among young adults. PMID:28559864

A dynamic social systems model for considering structural factors in HIV prevention and detection

PubMed Central

Latkin, Carl; Weeks, Margaret; Glasman, Laura; Galletly, Carol; Albarracin, Dolores

2010-01-01

We present a model for HIV-related behaviors that emphasizes the dynamic and social nature of the structural factors that influence HIV prevention and detection. Key structural dimensions of the model include resources, science and technology, formal social control, informal social influences and control, social interconnectedness, and settings. These six dimensions can be conceptualized on macro, meso, and micro levels. Given the inherent complexity of structural factors and their interrelatedness, HIV prevention interventions may focus on different levels and dimensions. We employ a systems perspective to describe the interconnected and dynamic processes of change among social systems and their components. The topics of HIV testing and safer injection facilities are analyzed using this structural framework. Finally, we discuss methodological issues in the development and evaluation of structural interventions for HIV prevention and detection. PMID:20838871

Determining the optimal number of independent components for reproducible transcriptomic data analysis.

PubMed

Kairov, Ulykbek; Cantini, Laura; Greco, Alessandro; Molkenov, Askhat; Czerwinska, Urszula; Barillot, Emmanuel; Zinovyev, Andrei

2017-09-11

Independent Component Analysis (ICA) is a method that models gene expression data as an action of a set of statistically independent hidden factors. The output of ICA depends on a fundamental parameter: the number of components (factors) to compute. The optimal choice of this parameter, related to determining the effective data dimension, remains an open question in the application of blind source separation techniques to transcriptomic data. Here we address the question of optimizing the number of statistically independent components in the analysis of transcriptomic data for reproducibility of the components in multiple runs of ICA (within the same or within varying effective dimensions) and in multiple independent datasets. To this end, we introduce ranking of independent components based on their stability in multiple ICA computation runs and define a distinguished number of components (Most Stable Transcriptome Dimension, MSTD) corresponding to the point of the qualitative change of the stability profile. Based on a large body of data, we demonstrate that a sufficient number of dimensions is required for biological interpretability of the ICA decomposition and that the most stable components with ranks below MSTD have more chances to be reproduced in independent studies compared to the less stable ones. At the same time, we show that a transcriptomics dataset can be reduced to a relatively high number of dimensions without losing the interpretability of ICA, even though higher dimensions give rise to components driven by small gene sets. We suggest a protocol of ICA application to transcriptomics data with a possibility of prioritizing components with respect to their reproducibility that strengthens the biological interpretation. Computing too few components (much less than MSTD) is not optimal for interpretability of the results. The components ranked within MSTD range have more chances to be reproduced in independent studies.

Factor IX assay

MedlinePlus

... factor assay; Serum factor IX; Hemophilic factor B; Plasma thromboplastin component; PTC ... BJ. Factor IX (Christmas factor, hemophilic factor B, plasma thromboplastin component, PTC) - blood. In: Chernecky CC, Berger ...

Conceptual model for dietary behaviour change at household level: a 'best-fit' qualitative study using primary data.

PubMed

Daivadanam, Meena; Wahlström, Rolf; Ravindran, T K Sundari; Thankappan, K R; Ramanathan, Mala

2014-06-09

Interventions having a strong theoretical basis are more efficacious, providing a strong argument for incorporating theory into intervention planning. The objective of this study was to develop a conceptual model to facilitate the planning of dietary intervention strategies at the household level in rural Kerala. Three focus group discussions and 17 individual interviews were conducted among men and women, aged between 23 and 75 years. An interview guide facilitated the process to understand: 1) feasibility and acceptability of a proposed dietary behaviour change intervention; 2) beliefs about foods, particularly fruits and vegetables; 3) decision-making in households with reference to food choices and access; and 4) to gain insights into the kind of intervention strategies that may be practical at community and household level. The data were analysed using a modified form of qualitative framework analysis, which combined both deductive and inductive reasoning. A priori themes were identified from relevant behaviour change theories using construct definitions, and used to index the meaning units identified from the primary qualitative data. In addition, new themes emerging from the data were included. The associations between the themes were mapped into four main factors and its components, which contributed to construction of the conceptual model. Thirteen of the a priori themes from three behaviour change theories (Trans-theoretical model, Health Belief model and Theory of Planned Behaviour) were confirmed or slightly modified, while four new themes emerged from the data. The conceptual model had four main factors and its components: impact factors (decisional balance, risk perception, attitude); change processes (action-oriented, cognitive); background factors (personal modifiers, societal norms); and overarching factors (accessibility, perceived needs and preferences), built around a three-stage change spiral (pre-contemplation, intention, action). Decisional balance was the strongest in terms of impacting the process of behaviour change, while household efficacy and perceived household cooperation were identified as 'markers' for stages-of-change at the household level. This type of framework analysis made it possible to develop a conceptual model that could facilitate the design of intervention strategies to aid a household-level dietary behaviour change process.

Conceptual model for dietary behaviour change at household level: a ‘best-fit’ qualitative study using primary data

PubMed Central

2014-01-01

Background Interventions having a strong theoretical basis are more efficacious, providing a strong argument for incorporating theory into intervention planning. The objective of this study was to develop a conceptual model to facilitate the planning of dietary intervention strategies at the household level in rural Kerala. Methods Three focus group discussions and 17 individual interviews were conducted among men and women, aged between 23 and 75 years. An interview guide facilitated the process to understand: 1) feasibility and acceptability of a proposed dietary behaviour change intervention; 2) beliefs about foods, particularly fruits and vegetables; 3) decision-making in households with reference to food choices and access; and 4) to gain insights into the kind of intervention strategies that may be practical at community and household level. The data were analysed using a modified form of qualitative framework analysis, which combined both deductive and inductive reasoning. A priori themes were identified from relevant behaviour change theories using construct definitions, and used to index the meaning units identified from the primary qualitative data. In addition, new themes emerging from the data were included. The associations between the themes were mapped into four main factors and its components, which contributed to construction of the conceptual model. Results Thirteen of the a priori themes from three behaviour change theories (Trans-theoretical model, Health Belief model and Theory of Planned Behaviour) were confirmed or slightly modified, while four new themes emerged from the data. The conceptual model had four main factors and its components: impact factors (decisional balance, risk perception, attitude); change processes (action-oriented, cognitive); background factors (personal modifiers, societal norms); and overarching factors (accessibility, perceived needs and preferences), built around a three-stage change spiral (pre-contemplation, intention, action). Decisional balance was the strongest in terms of impacting the process of behaviour change, while household efficacy and perceived household cooperation were identified as ‘markers’ for stages-of-change at the household level. Conclusions This type of framework analysis made it possible to develop a conceptual model that could facilitate the design of intervention strategies to aid a household-level dietary behaviour change process. PMID:24912496

Kottamia 74-inch telescope discovery of the new eclipsing binary KAO-EGYPT J225702.44+523222.1.: First CCD photometry and light curve analysis

NASA Astrophysics Data System (ADS)

Shokry, A.; Darwish, M. S.; Saad, S. M.; Eldepsy, M.; Zead, I.

2017-08-01

We present the first multicolor CCD photometry for the newly discovered binary system KAO-EGYPT J225702.44+523222.1. New times of light minimum and new ephemeris were obtained. The VR I light curves were analyzed using WD code, the difference in maximum light at phase 0.25 is modeled with a cool spot on the secondary component. The solution show that the system is A-subtype, overcontact binary with fill-out factor = 42% and low mass ratio, q = 0.275. The two components of spectral types K0 and K1 and the primary component is the massive one. The position of both components on the M-L and M-R relations revealed that the primary component is a main sequence star while the secondary is an evolved component.

Craving's place in addiction theory: contributions of the major models.

PubMed

Skinner, Marilyn D; Aubin, Henri-Jean

2010-03-01

We examine in this paper the unfolding of craving concepts within 18 models that span roughly 60 years (1948-2009). The amassed evidence suggests that craving is an indispensable construct, useful as a research area because it has continued to destabilize patients seeking treatment for substances. The models fall into four categories: the conditioning-based models, the cognitive models, the psychobiological models, and the motivation models. In the conditioning models, craving is assumed to be an automatic, unconscious reaction to a stimulus. In the cognitive models, craving arises from the operation of information processing systems. In the psychobiological models, craving can be explained at least in part by biological factors with an emphasis on motivational components. Finally, in the motivation models, craving is viewed as a component of a larger decision-making framework. It is well accepted that no single model explains craving completely, suggesting that a solid understanding of the phenomenon will only occur with consideration from multiple angles. A reformulated definition of craving is proposed. (c) 2009 Elsevier Ltd. All rights reserved.

Reliability and maintainability assessment factors for reliable fault-tolerant systems

NASA Technical Reports Server (NTRS)

Bavuso, S. J.

1984-01-01

A long term goal of the NASA Langley Research Center is the development of a reliability assessment methodology of sufficient power to enable the credible comparison of the stochastic attributes of one ultrareliable system design against others. This methodology, developed over a 10 year period, is a combined analytic and simulative technique. An analytic component is the Computer Aided Reliability Estimation capability, third generation, or simply CARE III. A simulative component is the Gate Logic Software Simulator capability, or GLOSS. The numerous factors that potentially have a degrading effect on system reliability and the ways in which these factors that are peculiar to highly reliable fault tolerant systems are accounted for in credible reliability assessments. Also presented are the modeling difficulties that result from their inclusion and the ways in which CARE III and GLOSS mitigate the intractability of the heretofore unworkable mathematics.

Metabolic Profiles Predict Adverse Events Following Coronary Artery Bypass Grafting

PubMed Central

Shah, Asad A.; Craig, Damian M.; Sebek, Jacqueline K.; Haynes, Carol; Stevens, Robert C.; Muehlbauer, Michael J.; Granger, Christopher B.; Hauser, Elizabeth R.; Newby, L. Kristin; Newgard, Christopher B.; Kraus, William E.; Hughes, G. Chad; Shah, Svati H.

2012-01-01

Objectives Clinical models incompletely predict outcomes following coronary artery bypass grafting. Novel molecular technologies may identify biomarkers to improve risk stratification. We examined whether metabolic profiles can predict adverse events in patients undergoing coronary artery bypass grafting. Methods The study population comprised 478 subjects from the CATHGEN biorepository of patients referred for cardiac catheterization who underwent coronary artery bypass grafting after enrollment. Targeted mass spectrometry-based profiling of 69 metabolites was performed in frozen, fasting plasma samples collected prior to surgery. Principal-components analysis and Cox proportional hazards regression modeling were used to assess the relation between metabolite factor levels and a composite outcome of post-coronary artery bypass grafting myocardial infarction, need for percutaneous coronary intervention, repeat coronary artery bypass grafting, or death. Results Over a mean follow-up of 4.3 ± 2.4 years, 126 subjects (26.4%) suffered an adverse event. Three principal-components analysis-derived factors were significantly associated with adverse outcome in univariable analysis: short-chain dicarboxylacylcarnitines (factor 2, P=0.001); ketone-related metabolites (factor 5, P=0.02); and short-chain acylcarnitines (factor 6, P=0.004). These three factors remained independently predictive of adverse outcome after multivariable adjustment: factor 2 (adjusted hazard ratio 1.23; 95% confidence interval [1.10-1.38]; P<0.001), factor 5 (1.17 [1.01-1.37], P=0.04), and factor 6 (1.14 [1.02-1.27], P=0.03). Conclusions Metabolic profiles are independently associated with adverse outcomes following coronary artery bypass grafting. These profiles may represent novel biomarkers of risk that augment existing tools for risk stratification of coronary artery bypass grafting patients and may elucidate novel biochemical pathways that mediate risk. PMID:22306227

Disassemblability modeling technology of configurable product based on disassembly constraint relation weighted design structure matrix(DSM)

NASA Astrophysics Data System (ADS)

Qiu, Lemiao; Liu, Xiaojian; Zhang, Shuyou; Sun, Liangfeng

2014-05-01

The current research of configurable product disassemblability focuses on disassemblability evaluation and disassembly sequence planning. Little work has been done on quantitative analysis of configurable product disassemblability. The disassemblability modeling technology for configurable product based on disassembly constraint relation weighted design structure matrix (DSM) is proposed. Major factors affecting the disassemblability of configurable product are analyzed, and the disassembling degrees between components in configurable product are obtained by calculating disassembly entropies such as joint type, joint quantity, disassembly path, disassembly accessibility and material compatibility. The disassembly constraint relation weighted DSM of configurable product is constructed and configuration modules are formed by matrix decomposition and tearing operations. The disassembly constraint relation in configuration modules is strong coupling, and the disassembly constraint relation between modules is weak coupling, and the disassemblability configuration model is constructed based on configuration module. Finally, taking a hydraulic forging press as an example, the decomposed weak coupling components are used as configuration modules alone, components with a strong coupling are aggregated into configuration modules, and the disassembly sequence of components inside configuration modules is optimized by tearing operation. A disassemblability configuration model of the hydraulic forging press is constructed. By researching the disassemblability modeling technology of product configuration design based on disassembly constraint relation weighted DSM, the disassembly property in maintenance, recycling and reuse of configurable product are optimized.

A Facility and Architecture for Autonomy Research

NASA Technical Reports Server (NTRS)

Pisanich, Greg; Clancy, Daniel (Technical Monitor)

2002-01-01

Autonomy is a key enabling factor in the advancement of the remote robotic exploration. There is currently a large gap between autonomy software at the research level and software that is ready for insertion into near-term space missions. The Mission Simulation Facility (MST) will bridge this gap by providing a simulation framework and suite of simulation tools to support research in autonomy for remote exploration. This system will allow developers of autonomy software to test their models in a high-fidelity simulation and evaluate their system's performance against a set of integrated, standardized simulations. The Mission Simulation ToolKit (MST) uses a distributed architecture with a communication layer that is built on top of the standardized High Level Architecture (HLA). This architecture enables the use of existing high fidelity models, allows mixing simulation components from various computing platforms and enforces the use of a standardized high-level interface among components. The components needed to achieve a realistic simulation can be grouped into four categories: environment generation (terrain, environmental features), robotic platform behavior (robot dynamics), instrument models (camera/spectrometer/etc.), and data analysis. The MST will provide basic components in these areas but allows users to plug-in easily any refined model by means of a communication protocol. Finally, a description file defines the robot and environment parameters for easy configuration and ensures that all the simulation models share the same information.

Fracture mechanics criteria for turbine engine hot section components

NASA Technical Reports Server (NTRS)

Meyers, G. J.

1982-01-01

The application of several fracture mechanics data correlation parameters to predicting the crack propagation life of turbine engine hot section components was evaluated. An engine survey was conducted to determine the locations where conventional fracture mechanics approaches may not be adequate to characterize cracking behavior. Both linear and nonlinear fracture mechanics analyses of a cracked annular combustor liner configuration were performed. Isothermal and variable temperature crack propagation tests were performed on Hastelloy X combustor liner material. The crack growth data was reduced using the stress intensity factor, the strain intensity factor, the J integral, crack opening displacement, and Tomkins' model. The parameter which showed the most effectiveness in correlation high temperature and variable temperature Hastelloy X crack growth data was crack opening displacement.

Protocol and Demonstrations of Probabilistic Reliability Assessment for Structural Health Monitoring Systems (Preprint)

DTIC Science & Technology

2011-11-01

assessment to quality of localization/characterization estimates. This protocol includes four critical components: (1) a procedure to identify the...critical factors impacting SHM system performance; (2) a multistage or hierarchical approach to SHM system validation; (3) a model -assisted evaluation...Lindgren, E. A ., Buynak, C. F., Steffes, G., Derriso, M., “ Model -assisted Probabilistic Reliability Assessment for Structural Health Monitoring

Human Factors in the Design and Evaluation of Air Traffic Control Systems

DTIC Science & Technology

1995-04-01

the controller must filter through and decipher. Fortunately, some of this is done without the need for conscious attention ; fcr example, a clear...components of an information-processing model ? ...................... 166 5.3 ATTENTION ......................................... 172 0 5.3.1 What is...processing? support of our performance of daily activities, including our (,) job tasks. Two models of attention currently in use assume that human infor

Chaotic component obscured by strong periodicity in voice production system

NASA Astrophysics Data System (ADS)

Tao, Chao; Jiang, Jack J.

2008-06-01

The effect of glottal aerodynamics in producing the nonlinear characteristics of voice is investigated by comparing the outputs of the asymmetric composite model and the two-mass model. The two-mass model assumes the glottal airflow to be laminar, nonviscous, and incompressible. In this model, when the asymmetric factor is decreased from 0.65 to 0.35, only 1:1 and 1:2 modes are detectable. However, with the same parameters, four vibratory modes (1:1, 1:2, 2:4, 2:6) are found in the asymmetric composite model using the Navier-Stokes equations to describe the complex aerodynamics in the glottis. Moreover, the amplitude of the waveform is modulated by a small-amplitude noiselike series. The nonlinear detection method reveals that this noiselike modulation is not random, but rather it is deterministic chaos. This result agrees with the phenomenon often seen in voice, in which the voice signal is strongly periodic but modulated by a small-amplitude chaotic component. The only difference between the two-mass model and the composite model is in their descriptions of glottal airflow. Therefore, the complex aerodynamic characteristics of glottal airflow could be important in generating the nonlinear dynamic behavior of voice production, including bifurcation and a small-amplitude chaotic component obscured by strong periodicity.

Chaotic component obscured by strong periodicity in voice production system

PubMed Central

Tao, Chao; Jiang, Jack J.

2010-01-01

The effect of glottal aerodynamics in producing the nonlinear characteristics of voice is investigated by comparing the outputs of the asymmetric composite model and the two-mass model. The two-mass model assumes the glottal airflow to be laminar, nonviscous, and incompressible. In this model, when the asymmetric factor is decreased from 0.65 to 0.35, only 1:1 and 1:2 modes are detectable. However, with the same parameters, four vibratory modes (1:1, 1:2, 2:4, 2:6) are found in the asymmetric composite model using the Navier-Stokes equations to describe the complex aerodynamics in the glottis. Moreover, the amplitude of the waveform is modulated by a small-amplitude noiselike series. The nonlinear detection method reveals that this noiselike modulation is not random, but rather it is deterministic chaos. This result agrees with the phenomenon often seen in voice, in which the voice signal is strongly periodic but modulated by a small-amplitude chaotic component. The only difference between the two-mass model and the composite model is in their descriptions of glottal airflow. Therefore, the complex aerodynamic characteristics of glottal airflow could be important in generating the nonlinear dynamic behavior of voice production, including bifurcation and a small-amplitude chaotic component obscured by strong periodicity. PMID:18643315

Further Evaluation of the Tripartite Structure of Subjective Well-Being: Evidence From Longitudinal and Experimental Studies.

PubMed

Metler, Samantha J; Busseri, Michael A

2017-04-01

Subjective well-being (SWB; Diener, 1984) comprises three primary components: life satisfaction (LS), positive affect (PA), and negative affect (NA). Multiple competing conceptualizations of the tripartite structure of SWB have been employed, resulting in widespread ambiguity concerning the definition, operationalization, analysis, and synthesis of SWB-related findings (Busseri & Sadava, 2011). We report two studies evaluating two predominant structural models (as recently identified by Busseri, 2015): a hierarchical model comprising a higher-order latent SWB factor with LS, PA, and NA as indicators; and a causal systems model specifying unidirectional effects of PA and NA on LS. A longitudinal study (N = 452; M age  = 18.54; 76.5% female) and a lab-based experiment (N = 195; M age  = 20.42 years; 87.6% female; 81.5% Caucasian) were undertaken. Structural models were evaluated with respect to (a) associations among SWB components across time (three months, three years in Study 1; one week in Study 2) and (b) the impact of manipulating the individual SWB components (Study 2). A hierarchical structural model was supported in both studies; conflicting evidence was found for the causal systems model. A hierarchical model provides a robust conceptualization for the tripartite structure of SWB. © 2015 Wiley Periodicals, Inc.

A survey on the measure of combat readiness

NASA Astrophysics Data System (ADS)

Wen, Kwong Fook; Nor, Norazman Mohamad; Soon, Lee Lai

2014-09-01

Measuring the combat readiness in military forces involves the measures of tangible and intangible elements of combat power. Though these measures are applicable, the mathematical models and formulae used focus mainly on either the tangible or the intangible elements. In this paper, a review is done to highlight the research gap in the formulation of a mathematical model that incorporates tangible elements with intangible elements to measure the combat readiness of a military force. It highlights the missing link between the tangible and intangible elements of combat power. To bridge the gap and missing link, a mathematical model could be formulated that measures both the tangible and intangible aspects of combat readiness by establishing the relationship between the causal (tangible and intangible) elements and its effects on the measure of combat readiness. The model uses multiple regression analysis as well as mathematical modeling and simulation which digest the capability component reflecting its assets and resources, the morale component reflecting human needs, and the quality of life component reflecting soldiers' state of satisfaction in life. The results of the review provide a mean to bridge the research gap through the formulation of a mathematical model that shows the total measure of a military force's combat readiness. The results also significantly identify parameters for each of the variables and factors in the model.

77 FR 67007 - Federal Reserve Bank Services Private Sector Adjustment Factor

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-08

... had characteristics most analogous to correspondent banks, clearing balances held by depository institutions at Reserve Banks were a primary component in computing the PSAF. The clearing balance program was largely modeled after similar programs offered by correspondent banks, wherein banks maintain balances...

Perceived risks of HIV/AIDS and first sexual intercourse among youth in Cape Town, South Africa.

PubMed

Tenkorang, Eric Y; Rajulton, Fernando; Maticka-Tyndale, Eleanor

2009-04-01

The 'Health Belief Model' (HBM) identifies perception of HIV/AIDS risks, recognition of its seriousness, and knowledge about prevention as predictors of safer sexual activity. Using data from the Cape Area Panel Survey (CAPS) and hazard models, this study examines the impact of risk perception, considered the first step in HIV prevention, set within the context of the HBM and socio-economic, familial and school factors, on the timing of first sexual intercourse among youth aged 14-22 in Cape Town, South Africa. Of the HBM components, female youth who perceive their risk as 'very small' and males with higher knowledge, experience their sexual debut later than comparison groups, net of other influences. For both males and females socio-economic and familial factors also influence timing of sexual debut, confirming the need to consider the social embeddedness of this sexual behavior as well as the rational components of decision making when designing prevention programs.

The holistic claims of the biopsychosocial conception of WHO's International Classification of Functioning, Disability, and Health (ICF): a conceptual analysis on the basis of a pluralistic-holistic ontology and multidimensional view of the human being.

PubMed

Solli, Hans Magnus; da Silva, António Barbosa

2012-06-01

The International Classification of Functioning, Disability and Health (ICF), designed by the WHO, attempts to provide a holistic model of functioning and disability by integrating a medical model with a social one. The aim of this article is to analyze the ICF's claim to holism. The following components of the ICF's complexity are analyzed: (1) health condition, (2) body functions and structures, (3) activity, (4) participation, (5) environmental factors, (6) personal factors, and (7) health. Although the ICF claims to be holistic, it presupposes a monistic materialistic ontology. We indicate some limitations of this ontology, proposing instead: (a) a pluralistic-holistic ontology (PHO) and (b) a multidimensional view of the human being, with individual and environmental aspects, in relation to three levels of reality implied by the PHO. For the ICF to attain its holistic claim, the interactions between its components should be based on (a) and (b).

Synchronous orbit power technology needs

NASA Technical Reports Server (NTRS)

Slifer, L. W., Jr.; Billerbeck, W. J.

1979-01-01

The needs are defined for future geosynchronous orbit spacecraft power subsystem components, including power generation, energy storage, and power processing. A review of the rapid expansion of the satellite communications field provides a basis for projection into the future. Three projected models, a mission model, an orbit transfer vehicle model, and a mass model for power subsystem components are used to define power requirements and mass limitations for future spacecraft. Based upon these three models, the power subsystems for a 10 kw, 10 year life, dedicated spacecraft and for a 20 kw, 20 year life, multi-mission platform are analyzed in further detail to establish power density requirements for the generation, storage and processing components of power subsystems as related to orbit transfer vehicle capabilities. Comparison of these requirements to state of the art design values shows that major improvements, by a factor of 2 or more, are needed to accomplish the near term missions. However, with the advent of large transfer vehicles, these requirements are significantly reduced, leaving the long lifetime requirement, associated with reliability and/or refurbishment, as the primary development need. A few technology advances, currently under development, are noted with regard to their impacts on future capability.

Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis

NASA Astrophysics Data System (ADS)

E, Jianwei; Bao, Yanling; Ye, Jimin

2017-10-01

As one of the most vital energy resources in the world, crude oil plays a significant role in international economic market. The fluctuation of crude oil price has attracted academic and commercial attention. There exist many methods in forecasting the trend of crude oil price. However, traditional models failed in predicting accurately. Based on this, a hybrid method will be proposed in this paper, which combines variational mode decomposition (VMD), independent component analysis (ICA) and autoregressive integrated moving average (ARIMA), called VMD-ICA-ARIMA. The purpose of this study is to analyze the influence factors of crude oil price and predict the future crude oil price. Major steps can be concluded as follows: Firstly, applying the VMD model on the original signal (crude oil price), the modes function can be decomposed adaptively. Secondly, independent components are separated by the ICA, and how the independent components affect the crude oil price is analyzed. Finally, forecasting the price of crude oil price by the ARIMA model, the forecasting trend demonstrates that crude oil price declines periodically. Comparing with benchmark ARIMA and EEMD-ICA-ARIMA, VMD-ICA-ARIMA can forecast the crude oil price more accurately.

Ω-slow Solutions and Be Star Disks

NASA Astrophysics Data System (ADS)

Araya, I.; Jones, C. E.; Curé, M.; Silaj, J.; Cidale, L.; Granada, A.; Jiménez, A.

2017-09-01

As the disk formation mechanism(s) in Be stars is(are) as yet unknown, we investigate the role of rapidly rotating radiation-driven winds in this process. We implemented the effects of high stellar rotation on m-CAK models accounting for the shape of the star, the oblate finite disk correction factor, and gravity darkening. For a fast rotating star, we obtain a two-component wind model, I.e., a fast, thin wind in the polar latitudes and an Ω-slow, dense wind in the equatorial regions. We use the equatorial mass densities to explore Hα emission profiles for the following scenarios: (1) a spherically symmetric star, (2) an oblate star with constant temperature, and (3) an oblate star with gravity darkening. One result of this work is that we have developed a novel method for solving the gravity-darkened, oblate m-CAK equation of motion. Furthermore, from our modeling we find that (a) the oblate finite disk correction factor, for the scenario considering the gravity darkening, can vary by at least a factor of two between the equatorial and polar directions, influencing the velocity profile and mass-loss rate accordingly, (b) the Hα profiles predicted by our model are in agreement with those predicted by a standard power-law model for following values of the line-force parameters: 1.5≲ k≲ 3,α ˜ 0.6, and δ ≳ 0.1, and (c) the contribution of the fast wind component to the Hα emission line profile is negligible; therefore, the line profiles arise mainly from the equatorial disks of Be stars.

Comparison of human radiation exchange models in outdoor areas

NASA Astrophysics Data System (ADS)

Park, Sookuk; Tuller, Stanton E.

2011-10-01

Results from the radiation components of seven different human thermal exchange models/methods are compared. These include the Burt, COMFA, MENEX, OUT_SET* and RayMan models, the six-directional method and the new Park and Tuller model employing projected area factors ( f p) and effective radiation area factors ( f eff) determined from a sample of normal- and over-weight Canadian Caucasian adults. Input data include solar and longwave radiation measured during a clear summer day in southern Ontario. Variations between models came from differences in f p and f eff and different estimates of longwave radiation from the open sky. The ranges between models for absorbed solar, net longwave and net all-wave radiation were 164, 31 and 187 W m-2, respectively. These differentials between models can be significant in total human thermal exchange. Therefore, proper f p and f eff values should be used to make accurate estimation of radiation on the human body surface.

In vivo gene manipulation reveals the impact of stress-responsive MAPK pathways on tumor progression

PubMed Central

Kamiyama, Miki; Naguro, Isao; Ichijo, Hidenori

2015-01-01

It has been widely accepted that tumor cells and normal stromal cells in the host environment coordinately modulate tumor progression. Mitogen-activated protein kinase pathways are the representative stress-responsive cascades that exert proper cellular responses to divergent environmental stimuli. Genetically engineered mouse models and chemically induced tumorigenesis models have revealed that components of the MAPK pathway not only regulate the behavior of tumor cells themselves but also that of surrounding normal stromal cells in the host environment during cancer pathogenesis. The individual functions of MAPK pathway components in tumor initiation and progression vary depending on the stimuli and the stromal cell types involved in tumor progression, in addition to the molecular isoforms of the components and the origins of the tumor. Recent studies have indicated that MAPK pathway components synergize with environmental factors (e.g. tobacco smoke and diet) to affect tumor initiation and progression. Moreover, some components play distinct roles in the course of tumor progression, such as before and after the establishment of tumors. Hence, a comprehensive understanding of the multifaceted functions of MAPK pathway components in tumor initiation and progression is essential for the improvement of cancer therapy. In this review, we focus on the reports that utilized knockout, conditional knockout, and transgenic mice of MAPK pathway components to investigate the effects of MAPK pathway components on tumor initiation and progression in the host environment. PMID:25880821

Infrared and X-Ray Spectroscopy of the KES 75 Supernova Remnant Shell: Characterizing the Dust and Gas Properties

NASA Technical Reports Server (NTRS)

Temim, Tea; Dwek, Eli; Slane, Patrick; Arendt, Richard G.

2009-01-01

We present deep Chandra observations and Spitzer Space Telescope infrared (IR) spectroscopy of the shell in the composite supernova remnant (SNR) Kes 75 (G29.7-0.3). The remnant is composed of a central pulsar wind nebula and a bright partial shell in the south that is visible at radio, IR, and X-ray wavelengths. The X-ray emission can be modeled by either a single thermal component with a temperature of 1.5 keV, or with two thermal components with temperatures of 1.5 and 0.2 keV. Previous studies suggest that the hot component may originate from reverse-shocked SN ejecta. However, our new analysis shows no definitive evidence for enhanced abundances of Si, S, Ar, Mg, and Fe, as expected from supernova (SN) ejecta, or for the IR spectral signatures characteristic of confirmed SN condensed dust, thus favoring a circumstellar or interstellar origin for the X-ray and IR emission. The X-ray and ill emission in the shell are spatially correlated, suggesting that the dust particles are collisionally heated by the X-ray emitting gas. The IR spectrum of the shell is dominated by continuum emission from dust with little, or no line emission. Modeling the IR spectrum shows that the dust is heated to a temperature of 140 K by a relatively dense, hot plasma, that also gives rise to the hot X-ray emission component. The density inferred from the IR emission is significantly higher than the density inferred from the X-ray models, suggesting a low filling factor for this X-ray emitting gas. The total mass of the warm dust component is at least 1.3 x 10(exp -2) solar mass, assuming no significant dust destruction has occurred in the shell. The IR data also reveal the presence of an additional plasma component with a cooler temperature, consistent with the 0.2 keV gas component. Our IR analysis therefore provides an independent verification of the cooler component of the X-ray emission. The complementary analyses of the X-ray and IR emission provide quantitative estimates of density and filling factors of the clumpy medium swept up by the SNR.

Infrared and X-Ray Spectroscopy of the Kes 75 Supernova Remnant Shell: Characterizing the Dust and Gas Properties

NASA Technical Reports Server (NTRS)

Temim, Tea; Slane, Patrick; Arendt, Richard G.; Dwek, Eli

2011-01-01

We present deep Chandra observations and Spitzer Space Telescope infrared (IR) spectroscopy of the shell in the composite supernova remnant (SNR) Kes 75 (G29.7-0.3). The remnant is composed of a central pulsar wind nebula and a bright partial shell in the south that is visible at radio, IR, and X-ray wavelengths. The X-ray emission can be modeled by either a single thermal component with a temperature of approximately 1.5 keY, or with two thermal components with temperatures of 1.5 and 0.2 keY. Previous studies suggest that the hot component may originate from reverse-shocked supernova (SN) ejecta. However, our new analysis shows no definitive evidence for enhanced abundances of Si, S, Ar, Mg, and Fe, as expected from SN ejecta, or for the IR spectral signatures characteristic of confirmed SN condensed dust, thus favoring a circumstellar or interstellar origin for the X-ray and IR emission. The X-ray and IR emission in the shell are spatially correlated, suggesting that the dust particles are collisionally heated by the X-ray emitting gas. The IR spectrum of the shell is dominated by continuum emission from dust with little, or no line emission. Modeling the IR spectrum shows that the dust is heated to a temperature of approximately 140 K by a relatively dense, hot plasma that also gives rise to the hot X-my emission component. The density inferred from the IR emission is significantly higher than the density inferred from the X-ray models, suggesting a low filling factor for this X-my emitting gas. The total mass of the warm dust component is at least 1.3 x 10(exp -2) x solar mass, assuming no significant dust destruction has occurred in the shell. The IR data also reveal the presence of an additional plasma component with a cooler temperature, consistent with the 0.2 keV gas component. Our IR analysis therefore provides an independent verification of the cooler component of the X-ray emission. The complementary analyses of the X-ray and IR emission provide quantitative estimates of density and filling factors of the clumpy medium swept up by the SNR.

Infrared and X-Ray Spectroscopy of the Kes 75 Supernova Shell Characterizing the Dust and Gas Properties

NASA Technical Reports Server (NTRS)

Temim, Tea; Arendt, Richard G.; Dwek, Eli; Slane, Patrick

2012-01-01

We present deep Chandra observations and Spitzer Space Telescope infrared (IR) spectroscopy of the shell in the composite supernova remnant (SNR) Kes 75 (G29.7-0.3). The remnant is composed of a central pulsar wind nebula and a bright partial shell in the south that is visible at radio, IR, and X-ray wavelengths. The X-ray emission can be modeled by either a single thermal component with a temperature of approx 1.5 keV, or with two thermal components with temperatures of 1.5 and 0.2 keY. Previous studies suggest that the hot component may originate from reverse-shocked SN ejecta. However, our new analysis shows no definitive evidence for enhanced abundances of Si, S, Ar, Mg, and Fe, as expected from supernova (SN) ejecta, or for the IR spectral signatures characteristic of confirmed SN condensed dust, thus favoring a circumstellar or interstellar origin for the X-ray and IR emission. The X-ray and IR emission in the shell are spatially correlated, suggesting that the dust particles are collisionally heated by the X-ray emitting gas. The IR spectrum of the shell is dominated by continuum emission from dust with little, or no line emission. Modeling the IR spectrum shows that the dust is heated to a temperature of approx 140 K by a relatively dense, hot plasma, that also gives rise to the hot X-ray emission component. The density inferred from the IR emission is significantly higher than the density inferred from the X-ray models, suggesting a low filling factor for this X-ray emitting gas. The total mass of the warm dust component is at least 1.3 x 10(exp -2) Solar Mass, assuming no significant dust destruction has occurred in the shell. The IR data also reveal the presence of an additional plasma component with a cooler temperature, consistent with the 0.2 keV gas component. Our IR analysis therefore provides an independent verification of the cooler component of the X-ray emission. The complementary analyses of the X-ray and IR emission provide quantitative estimates of density and filling factors of the clumpy medium swept up by the SNR.

Infrared and X-Ray Spectroscopy of the Kes 75 Supernova Remnant Shell: Characterizing the Dust and Gas Properties

NASA Astrophysics Data System (ADS)

Temim, Tea; Slane, Patrick; Arendt, Richard G.; Dwek, Eli

2012-01-01

We present deep Chandra observations and Spitzer Space Telescope infrared (IR) spectroscopy of the shell in the composite supernova remnant (SNR) Kes 75 (G29.7-0.3). The remnant is composed of a central pulsar wind nebula and a bright partial shell in the south that is visible at radio, IR, and X-ray wavelengths. The X-ray emission can be modeled by either a single thermal component with a temperature of ~1.5 keV, or with two thermal components with temperatures of 1.5 and 0.2 keV. Previous studies suggest that the hot component may originate from reverse-shocked supernova (SN) ejecta. However, our new analysis shows no definitive evidence for enhanced abundances of Si, S, Ar, Mg, and Fe, as expected from SN ejecta, or for the IR spectral signatures characteristic of confirmed SN condensed dust, thus favoring a circumstellar or interstellar origin for the X-ray and IR emission. The X-ray and IR emission in the shell are spatially correlated, suggesting that the dust particles are collisionally heated by the X-ray emitting gas. The IR spectrum of the shell is dominated by continuum emission from dust with little, or no line emission. Modeling the IR spectrum shows that the dust is heated to a temperature of ~140 K by a relatively dense, hot plasma that also gives rise to the hot X-ray emission component. The density inferred from the IR emission is significantly higher than the density inferred from the X-ray models, suggesting a low filling factor for this X-ray emitting gas. The total mass of the warm dust component is at least 1.3 × 10-2 M ⊙, assuming no significant dust destruction has occurred in the shell. The IR data also reveal the presence of an additional plasma component with a cooler temperature, consistent with the 0.2 keV gas component. Our IR analysis therefore provides an independent verification of the cooler component of the X-ray emission. The complementary analyses of the X-ray and IR emission provide quantitative estimates of density and filling factors of the clumpy medium swept up by the SNR.

Bone fracture healing in mechanobiological modeling: A review of principles and methods.

PubMed

Ghiasi, Mohammad S; Chen, Jason; Vaziri, Ashkan; Rodriguez, Edward K; Nazarian, Ara

2017-06-01

Bone fracture is a very common body injury. The healing process is physiologically complex, involving both biological and mechanical aspects. Following a fracture, cell migration, cell/tissue differentiation, tissue synthesis, and cytokine and growth factor release occur, regulated by the mechanical environment. Over the past decade, bone healing simulation and modeling has been employed to understand its details and mechanisms, to investigate specific clinical questions, and to design healing strategies. The goal of this effort is to review the history and the most recent work in bone healing simulations with an emphasis on both biological and mechanical properties. Therefore, we provide a brief review of the biology of bone fracture repair, followed by an outline of the key growth factors and mechanical factors influencing it. We then compare different methodologies of bone healing simulation, including conceptual modeling (qualitative modeling of bone healing to understand the general mechanisms), biological modeling (considering only the biological factors and processes), and mechanobiological modeling (considering both biological aspects and mechanical environment). Finally we evaluate different components and clinical applications of bone healing simulation such as mechanical stimuli, phases of bone healing, and angiogenesis.

Assessing sources of airborne mineral dust and other aerosols, in Iraq

NASA Astrophysics Data System (ADS)

Engelbrecht, Johann P.; Jayanty, R. K. M.

2013-06-01

Most airborne particulate matter in Iraq comes from mineral dust sources. This paper describes the statistics and modeling of chemical results, specifically those from Teflon® filter samples collected at Tikrit, Balad, Taji, Baghdad, Tallil and Al Asad, in Iraq, in 2006/2007. Methodologies applied to the analytical results include calculation of correlation coefficients, Principal Components Analysis (PCA), and Positive Matrix Factorization (PMF) modeling. PCA provided a measure of the covariance within the data set, thereby identifying likely point sources and events. These include airborne mineral dusts of silicate and carbonate minerals, gypsum and salts, as well as anthropogenic sources of metallic fumes, possibly from battery smelting operations, and emissions of leaded gasoline vehicles. Five individual PMF factors (source categories) were modeled, four of which being assigned to components of geological dust, and the fifth to gasoline vehicle emissions together with battery smelting operations. The four modeled geological components, dust-siliceous, dust-calcic, dust-gypsum, and evaporate occur in variable ratios for each site and size fraction (TSP, PM10, and PM2.5), and also vary by season. In general, Tikrit and Taji have the largest and Al Asad the smallest percentages of siliceous dust. In contrast, Al Asad has the largest proportion of gypsum, in part representing the gypsiferous soils in that region. Baghdad has the highest proportions of evaporite in both size fractions, ascribed to the highly salinized agricultural soils, following millennia of irrigation along the Tigris River valley. Although dust storms along the Tigris and Euphrates River valleys originate from distal sources, the mineralogy bears signatures of local soils and air pollutants.

Extending Our Understanding of Compliant Thermal Barrier Performance

NASA Technical Reports Server (NTRS)

Demange, Jeffrey J.; Finkbeiner, Joshua R.; Dunlap, Patrick H.

2014-01-01

Thermal barriers and seals are integral components in the thermal protection systems (TPS) of nearly all aerospace vehicles. They are used to minimize the flow of hot gases through interfaces and protect underlying temperature-sensitive components and systems. Although thermal barriers have been used extensively on many aerospace vehicles, the factors affecting their thermal and mechanical performance are not well-understood. Because of this, vehicle TPS designers are often left with little guidance on how to properly design and optimize these barriers. An ongoing effort to better understand thermal barrier performance and develop models and design tools is in progress at the NASA Glenn Research Center. Testing has been conducted to understand the degree to which insulation density influences structural performance and permeability. In addition, the development of both thermal and mechanical models is ongoing with the goal of providing an improved ability to design and implement these critical TPS components.

Analysis of fatigue reliability for high temperature and high pressure multi-stage decompression control valve

NASA Astrophysics Data System (ADS)

Yu, Long; Xu, Juanjuan; Zhang, Lifang; Xu, Xiaogang

2018-03-01

Based on stress-strength interference theory to establish the reliability mathematical model for high temperature and high pressure multi-stage decompression control valve (HMDCV), and introduced to the temperature correction coefficient for revising material fatigue limit at high temperature. Reliability of key dangerous components and fatigue sensitivity curve of each component are calculated and analyzed by the means, which are analyzed the fatigue life of control valve and combined with reliability theory of control valve model. The impact proportion of each component on the control valve system fatigue failure was obtained. The results is shown that temperature correction factor makes the theoretical calculations of reliability more accurate, prediction life expectancy of main pressure parts accords with the technical requirements, and valve body and the sleeve have obvious influence on control system reliability, the stress concentration in key part of control valve can be reduced in the design process by improving structure.

Rank estimation and the multivariate analysis of in vivo fast-scan cyclic voltammetric data

PubMed Central

Keithley, Richard B.; Carelli, Regina M.; Wightman, R. Mark

2010-01-01

Principal component regression has been used in the past to separate current contributions from different neuromodulators measured with in vivo fast-scan cyclic voltammetry. Traditionally, a percent cumulative variance approach has been used to determine the rank of the training set voltammetric matrix during model development, however this approach suffers from several disadvantages including the use of arbitrary percentages and the requirement of extreme precision of training sets. Here we propose that Malinowski’s F-test, a method based on a statistical analysis of the variance contained within the training set, can be used to improve factor selection for the analysis of in vivo fast-scan cyclic voltammetric data. These two methods of rank estimation were compared at all steps in the calibration protocol including the number of principal components retained, overall noise levels, model validation as determined using a residual analysis procedure, and predicted concentration information. By analyzing 119 training sets from two different laboratories amassed over several years, we were able to gain insight into the heterogeneity of in vivo fast-scan cyclic voltammetric data and study how differences in factor selection propagate throughout the entire principal component regression analysis procedure. Visualizing cyclic voltammetric representations of the data contained in the retained and discarded principal components showed that using Malinowski’s F-test for rank estimation of in vivo training sets allowed for noise to be more accurately removed. Malinowski’s F-test also improved the robustness of our criterion for judging multivariate model validity, even though signal-to-noise ratios of the data varied. In addition, pH change was the majority noise carrier of in vivo training sets while dopamine prediction was more sensitive to noise. PMID:20527815

Measuring Filial Piety in the 21st Century: Development, Factor Structure, and Reliability of the 10-Item Contemporary Filial Piety Scale.

PubMed

Lum, Terry Y S; Yan, Elsie C W; Ho, Andy H Y; Shum, Michelle H Y; Wong, Gloria H Y; Lau, Mandy M Y; Wang, Junfang

2016-11-01

The experience and practice of filial piety have evolved in modern Chinese societies, and existing measures fail to capture these important changes. Based on a conceptual analysis on current literature, 42 items were initially compiled to form a Contemporary Filial Piety Scale (CFPS), and 1,080 individuals from a representative sample in Hong Kong were surveyed. Principal component analysis generated a 16-item three-factor model: Pragmatic Obligations (Factor 1; 10 items), Compassionate Reverence (Factor 2; 4 items), and Family Continuity (Factor 3; 2 items). Confirmatory factor analysis revealed strong factor loadings for Factors 1 and 2, while removing Factor 3 and conceptually duplicated items increased total variance explained from 58.02% to 60.09% and internal consistency from .84 to .88. A final 10-item two-factor structure model was adopted with a goodness of fit of 0.95. The CFPS-10 is a data-driven, simple, and efficient instrument with strong psychometric properties for assessing contemporary filial piety. © The Author(s) 2015.

Polychlorinated Biphenyl (PCB) Bioaccumulation in Fish: A Look at Michigan's Upper Peninsula

NASA Astrophysics Data System (ADS)

Sokol, E. C.; Urban, N. R.; Perlinger, J. A.; Khan, T.; Friedman, C. L.

2014-12-01

Fish consumption is an important economic, social and cultural component of Michigan's UpperPeninsula, where safe fish consumption is threatened due to polychlorinated biphenyl (PCB)contamination. Despite its predominantly rural nature, the Upper Peninsula has a history of industrialPCB use. PCB congener concentrations in fish vary 50-fold in Upper Peninsula lakes. Several factors maycontribute to this high variability including local point sources, unique watershed and lakecharacteristics, and food web structure. It was hypothesized that the variability in congener distributionscould be used to identify factors controlling concentrations in fish, and then to use those factors topredict PCB contamination in fish from lakes that had not been monitored. Watershed and lakecharacteristics were acquired from several databases for 16 lakes sampled in the State's fishcontaminant survey. Species congener distributions were compared using Principal Component Analysis(PCA) to distinguish between lakes with local vs. regional, atmospheric sources; six lakes were predictedto have local sources and half of those have confirmed local PCB use. For lakes without local PCBsources, PCA indicated that lake size was the primary factor influencing PCB concentrations. The EPA'sbioaccumulation model, BASS, was used to predict PCB contamination in lakes without local sources as afunction of food web characteristics. The model was used to evaluate the hypothesis that deep,oligotrophic lakes have longer food webs and higher PCB concentrations in top predator fish. Based onthese findings, we will develop a mechanistic watershed-lake model to predict PCB concentrations infish as a function of atmospheric PCB concentrations, lake size, and trophic state. Future atmosphericconcentrations, predicted by modeling potential primary and secondary emission scenarios, will be usedto predict the time horizon for safe fish consumption.

Time-invariant component-based normalization for a simultaneous PET-MR scanner.

PubMed

Belzunce, M A; Reader, A J

2016-05-07

Component-based normalization is a method used to compensate for the sensitivity of each of the lines of response acquired in positron emission tomography. This method consists of modelling the sensitivity of each line of response as a product of multiple factors, which can be classified as time-invariant, time-variant and acquisition-dependent components. Typical time-variant factors are the intrinsic crystal efficiencies, which are needed to be updated by a regular normalization scan. Failure to do so would in principle generate artifacts in the reconstructed images due to the use of out of date time-variant factors. For this reason, an assessment of the variability and the impact of the crystal efficiencies in the reconstructed images is important to determine the frequency needed for the normalization scans, as well as to estimate the error obtained when an inappropriate normalization is used. Furthermore, if the fluctuations of these components are low enough, they could be neglected and nearly artifact-free reconstructions become achievable without performing a regular normalization scan. In this work, we analyse the impact of the time-variant factors in the component-based normalization used in the Biograph mMR scanner, but the work is applicable to other PET scanners. These factors are the intrinsic crystal efficiencies and the axial factors. For the latter, we propose a new method to obtain fixed axial factors that was validated with simulated data. Regarding the crystal efficiencies, we assessed their fluctuations during a period of 230 d and we found that they had good stability and low dispersion. We studied the impact of not including the intrinsic crystal efficiencies in the normalization when reconstructing simulated and real data. Based on this assessment and using the fixed axial factors, we propose the use of a time-invariant normalization that is able to achieve comparable results to the standard, daily updated, normalization factors used in this scanner. Moreover, to extend the analysis to other scanners, we generated distributions of crystal efficiencies with greater fluctuations than those found in the Biograph mMR scanner and evaluated their impact in simulations with a wide variety of noise levels. An important finding of this work is that a regular normalization scan is not needed in scanners with photodetectors with relatively low dispersion in their efficiencies.

Time-invariant component-based normalization for a simultaneous PET-MR scanner

NASA Astrophysics Data System (ADS)

Belzunce, M. A.; Reader, A. J.

2016-05-01

Component-based normalization is a method used to compensate for the sensitivity of each of the lines of response acquired in positron emission tomography. This method consists of modelling the sensitivity of each line of response as a product of multiple factors, which can be classified as time-invariant, time-variant and acquisition-dependent components. Typical time-variant factors are the intrinsic crystal efficiencies, which are needed to be updated by a regular normalization scan. Failure to do so would in principle generate artifacts in the reconstructed images due to the use of out of date time-variant factors. For this reason, an assessment of the variability and the impact of the crystal efficiencies in the reconstructed images is important to determine the frequency needed for the normalization scans, as well as to estimate the error obtained when an inappropriate normalization is used. Furthermore, if the fluctuations of these components are low enough, they could be neglected and nearly artifact-free reconstructions become achievable without performing a regular normalization scan. In this work, we analyse the impact of the time-variant factors in the component-based normalization used in the Biograph mMR scanner, but the work is applicable to other PET scanners. These factors are the intrinsic crystal efficiencies and the axial factors. For the latter, we propose a new method to obtain fixed axial factors that was validated with simulated data. Regarding the crystal efficiencies, we assessed their fluctuations during a period of 230 d and we found that they had good stability and low dispersion. We studied the impact of not including the intrinsic crystal efficiencies in the normalization when reconstructing simulated and real data. Based on this assessment and using the fixed axial factors, we propose the use of a time-invariant normalization that is able to achieve comparable results to the standard, daily updated, normalization factors used in this scanner. Moreover, to extend the analysis to other scanners, we generated distributions of crystal efficiencies with greater fluctuations than those found in the Biograph mMR scanner and evaluated their impact in simulations with a wide variety of noise levels. An important finding of this work is that a regular normalization scan is not needed in scanners with photodetectors with relatively low dispersion in their efficiencies.

Change Theory for Accounting System Reform in Health Sector: A Case Study of Kerman University of Medical Sciences in Iran

PubMed Central

Mehrolhassani, Mohammad Hossein; Emami, Mozhgan

2013-01-01

Background: Change theories provide an opportunity for organizational managers to plan, monitor and evaluate changes using a framework which enable them, among others, to show a fast response to environmental fluctuations and to predict the changing patterns of individuals and technology. The current study aimed to explore whether the change in the public accounting system of the Iranian health sector has followed Kurt Lewin’s change theory or not. Methods: This study which adopted a mixed methodology approach, qualitative and quantitative methods, was conducted in 2012. In the first phase of the study, 41 participants using purposive sampling and in the second phase, 32 affiliated units of Kerman University of Medical Sciences (KUMS) were selected as the study sample. Also, in phase one, we used face-to-face in-depth interviews (6 participants) and the quote method (35 participants) for data collection. We used a thematic framework analysis for analyzing data. In phase two, a questionnaire with a ten-point Likert scale was designed and then, data were analyzed using descriptive indicators, principal component and factorial analyses. Results: The results of phase one yielded a model consisting of four categories of superstructure, apparent infrastructure, hidden infrastructure and common factors. By linking all factors, totally, 12 components based on the quantitative results showed that the state of all components were not satisfactory at KUMS (5.06±2.16). Leadership and management; and technology components played the lowest and the greatest roles in implementing the accrual accounting system respectively. Conclusion: The results showed that the unfreezing stage did not occur well and the components were immature, mainly because the emphasis was placed on superstructure components rather than the components of hidden infrastructure. The study suggests that a road map should be developed in the financial system based on Kurt Lewin’s change theory and the model presented in this paper underpins the change management in any organizations. PMID:24596885

Change theory for accounting system reform in health sector: a case study of kerman university of medical sciences in iran.

PubMed

Mehrolhassani, Mohammad Hossein; Emami, Mozhgan

2013-11-01

Change theories provide an opportunity for organizational managers to plan, monitor and evaluate changes using a framework which enable them, among others, to show a fast response to environmental fluctuations and to predict the changing patterns of individuals and technology. The current study aimed to explore whether the change in the public accounting system of the Iranian health sector has followed Kurt Lewin's change theory or not. This study which adopted a mixed methodology approach, qualitative and quantitative methods, was conducted in 2012. In the first phase of the study, 41 participants using purposive sampling and in the second phase, 32 affiliated units of Kerman University of Medical Sciences (KUMS) were selected as the study sample. Also, in phase one, we used face-to-face in-depth interviews (6 participants) and the quote method (35 participants) for data collection. We used a thematic framework analysis for analyzing data. In phase two, a questionnaire with a ten-point Likert scale was designed and then, data were analyzed using descriptive indicators, principal component and factorial analyses. The results of phase one yielded a model consisting of four categories of superstructure, apparent infrastructure, hidden infrastructure and common factors. By linking all factors, totally, 12 components based on the quantitative results showed that the state of all components were not satisfactory at KUMS (5.06±2.16). Leadership and management; and technology components played the lowest and the greatest roles in implementing the accrual accounting system respectively. The results showed that the unfreezing stage did not occur well and the components were immature, mainly because the emphasis was placed on superstructure components rather than the components of hidden infrastructure. The study suggests that a road map should be developed in the financial system based on Kurt Lewin's change theory and the model presented in this paper underpins the change management in any organizations.

Comprehensive dynamic analysis of a bladed disk-turborotor-bearing system

NASA Astrophysics Data System (ADS)

Kaushal, Ashok

The dynamic behavior of a bladed disk-turborotor-bearing system is studied employing analytical, numerical, and experimental methods. The system consists of several subsystems such as turbine disk, blades, bearings, support pedestals etc. In order to completely understand the dynamic behavior of the turborotor system an appropriate model for each individual component of the system is first developed. The individual components are modeled to include various design parameters and the effect of these parameters on the vibrational behavior is studied. The vibration studies on the individual components are carried out using Rayleigh-Ritz method boundary characteristic orthogonal polynomials as assumed shape functions. The individual components are then assembled using the finite element technique. The turborotor system is studied from a system point of view and the natural frequencies and mode shapes are obtained for various rotational speeds. The results show that the natural frequencies of the system are different from those obtained by analyzing individual components, suggesting that a system approach must be adopted for proper design of a turborotor system. The amplitude of vibration and stresses due to harmonic and centrifugal loading on the blades and the disk are also obtained. The results indicate that for the turborotor speed of operation, the centrifugal loading is the major factor in determining the critical stresses in comparison to the gas forces on the blade modeled as harmonic loading. Experimental validation of the analytical model is carried out and suggestions for future work are given.

Usefulness of an ability-based health model in work ability assessments provided by psychiatrists and psychology specialists writing social security certificates.

PubMed

Solli, Hans Magnus; Barbosa da Silva, António; Egeland, Jens

2015-01-01

To investigate whether adding descriptions of the health factors "ability," "environment" and "intentions/goals" to the officially sanctioned biomedical disability model (BDM) would improve assessments of work ability for social security purposes. The study was based on a theoretical design consisting of textual analysis and interpretation. Two further work ability models were defined: the mixed health model (MHM), which describes health factors without assessing a person's abilities in context, and the ability-based health model (AHM), which assesses abilities in a concrete context of environment and intention. Eighty-six social security certificates, written by psychiatrists and psychology specialists in a Norwegian hospital-based mental health clinic, were analysed in relation to the three work ability/disability models. In certificates based on the BDM, a general pattern was found of "gradual work training". The MHM added health factors, but without linking them together in a concrete way. With the AHM, work ability was assessed in terms of a concrete unified evaluation of the claimant's abilities, environments and intentions/goals. Applying the AHM in work ability assessments, in comparison with the BDM and the MHM, is useful because this foregrounds claimants' abilities in a context of concrete goals and work-related opportunities, as a unity. Implications for Rehabilitation A concept of health should include ability, environment and intentions/goals as components. When all three of these components are described in concrete terms in a work ability assessment, an integrated picture of the individual's abilities in the context of his/her particular intentions/goals and work opportunities comes to the fore. This kind of assessment makes it possible to meet the individual's needs for individual follow-up in a work environment.

Structural Similitude and Scaling Laws

NASA Technical Reports Server (NTRS)

Simitses, George J.

1998-01-01

Aircraft and spacecraft comprise the class of aerospace structures that require efficiency and wisdom in design, sophistication and accuracy in analysis and numerous and careful experimental evaluations of components and prototype, in order to achieve the necessary system reliability, performance and safety. Preliminary and/or concept design entails the assemblage of system mission requirements, system expected performance and identification of components and their connections as well as of manufacturing and system assembly techniques. This is accomplished through experience based on previous similar designs, and through the possible use of models to simulate the entire system characteristics. Detail design is heavily dependent on information and concepts derived from the previous steps. This information identifies critical design areas which need sophisticated analyses, and design and redesign procedures to achieve the expected component performance. This step may require several independent analysis models, which, in many instances, require component testing. The last step in the design process, before going to production, is the verification of the design. This step necessitates the production of large components and prototypes in order to test component and system analytical predictions and verify strength and performance requirements under the worst loading conditions that the system is expected to encounter in service. Clearly then, full-scale testing is in many cases necessary and always very expensive. In the aircraft industry, in addition to full-scale tests, certification and safety necessitate large component static and dynamic testing. Such tests are extremely difficult, time consuming and definitely absolutely necessary. Clearly, one should not expect that prototype testing will be totally eliminated in the aircraft industry. It is hoped, though, that we can reduce full-scale testing to a minimum. Full-scale large component testing is necessary in other industries as well, Ship building, automobile and railway car construction all rely heavily on testing. Regardless of the application, a scaled-down (by a large factor) model (scale model) which closely represents the structural behavior of the full-scale system (prototype) can prove to be an extremely beneficial tool. This possible development must be based on the existence of certain structural parameters that control the behavior of a structural system when acted upon by static and/or dynamic loads. If such structural parameters exist, a scaled-down replica can be built, which will duplicate the response of the full-scale system. The two systems are then said to be structurally similar. The term, then, that best describes this similarity is structural similitude. Similarity of systems requires that the relevant system parameters be identical and these systems be governed by a unique set of characteristic equations. Thus, if a relation or equation of variables is written for a system, it is valid for all systems which are similar to it. Each variable in a model is proportional to the corresponding variable of the prototype. This ratio, which plays an essential role in predicting the relationship between the model and its prototype, is called the scale factor.

Similarly shaped letters evoke similar colors in grapheme-color synesthesia.

PubMed

Brang, David; Rouw, Romke; Ramachandran, V S; Coulson, Seana

2011-04-01

Grapheme-color synesthesia is a neurological condition in which viewing numbers or letters (graphemes) results in the concurrent sensation of color. While the anatomical substrates underlying this experience are well understood, little research to date has investigated factors influencing the particular colors associated with particular graphemes or how synesthesia occurs developmentally. A recent suggestion of such an interaction has been proposed in the cascaded cross-tuning (CCT) model of synesthesia, which posits that in synesthetes connections between grapheme regions and color area V4 participate in a competitive activation process, with synesthetic colors arising during the component-stage of grapheme processing. This model more directly suggests that graphemes sharing similar component features (lines, curves, etc.) should accordingly activate more similar synesthetic colors. To test this proposal, we created and regressed synesthetic color-similarity matrices for each of 52 synesthetes against a letter-confusability matrix, an unbiased measure of visual similarity among graphemes. Results of synesthetes' grapheme-color correspondences indeed revealed that more similarly shaped graphemes corresponded with more similar synesthetic colors, with stronger effects observed in individuals with more intense synesthetic experiences (projector synesthetes). These results support the CCT model of synesthesia, implicate early perceptual mechanisms as driving factors in the elicitation of synesthetic hues, and further highlight the relationship between conceptual and perceptual factors in this phenomenon. Copyright © 2011 Elsevier Ltd. All rights reserved.

Light-meson masses in an unquenched quark model

DOE PAGES

Chen, Xiaoyun; Ping, Jialun; Roberts, Craig D.; ...

2018-05-17

We perform a coupled-channels calculation of the masses of light mesons with the quantum numbers IJ P=-, (I,J) = 0,1, by includingmore » $$q\\bar{q}$$ and ($$q\\bar{q}$$) 2 components in a nonrelativistic chiral quark model. The coupling between two- and four-quark configurations is realized through a 3P 0 quark-pair creation model. With the usual form of this operator, the mass shifts are large and negative, an outcome which raises serious issues of validity for the quenched quark model. Therefore, we introduce some improvements of the 3P 0 operator in order to reduce the size of the mass shifts. By introducing two simple factors, physically well motivated, the coupling between $$q\\bar{q}$$ and ($$q\\bar{q}$$) 2 components is weakened, producing mass shifts that are around 10%–20% of hadron bare masses.« less

Light-meson masses in an unquenched quark model

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

Chen, Xiaoyun; Ping, Jialun; Roberts, Craig D.

We perform a coupled-channels calculation of the masses of light mesons with the quantum numbers IJ P=-, (I,J) = 0,1, by includingmore » $$q\\bar{q}$$ and ($$q\\bar{q}$$) 2 components in a nonrelativistic chiral quark model. The coupling between two- and four-quark configurations is realized through a 3P 0 quark-pair creation model. With the usual form of this operator, the mass shifts are large and negative, an outcome which raises serious issues of validity for the quenched quark model. Therefore, we introduce some improvements of the 3P 0 operator in order to reduce the size of the mass shifts. By introducing two simple factors, physically well motivated, the coupling between $$q\\bar{q}$$ and ($$q\\bar{q}$$) 2 components is weakened, producing mass shifts that are around 10%–20% of hadron bare masses.« less

School Climate Factors Relating to Teacher Burnout: A Mediator Model

ERIC Educational Resources Information Center

Grayson, Jessica L.; Alvarez, Heather K.

2008-01-01

The present study investigated components of school climate (i.e. parent/community relations, administration, student behavioral values) and assessed their influence on the core burnout dimensions of Emotional Exhaustion, Depersonalization, and feelings of low Personal Accomplishment. The study weighed the relative contributions of demographic…

Early College High Schools: Model Policy Components. Policy Analysis

ERIC Educational Resources Information Center

Zinth, Jennifer

2016-01-01

An alarming convergence of factors--diminishing percentages of high school graduates enrolling immediately in postsecondary education, traditionally underserved students comprising a growing proportion of the overall U.S. school population, and projections that more occupations in the future will need education beyond high school--suggest that…

Component-based model to predict aerodynamic noise from high-speed train pantographs

NASA Astrophysics Data System (ADS)

Latorre Iglesias, E.; Thompson, D. J.; Smith, M. G.

2017-04-01

At typical speeds of modern high-speed trains the aerodynamic noise produced by the airflow over the pantograph is a significant source of noise. Although numerical models can be used to predict this they are still very computationally intensive. A semi-empirical component-based prediction model is proposed to predict the aerodynamic noise from train pantographs. The pantograph is approximated as an assembly of cylinders and bars with particular cross-sections. An empirical database is used to obtain the coefficients of the model to account for various factors: incident flow speed, diameter, cross-sectional shape, yaw angle, rounded edges, length-to-width ratio, incoming turbulence and directivity. The overall noise from the pantograph is obtained as the incoherent sum of the predicted noise from the different pantograph struts. The model is validated using available wind tunnel noise measurements of two full-size pantographs. The results show the potential of the semi-empirical model to be used as a rapid tool to predict aerodynamic noise from train pantographs.

Improvements to a Response Surface Thermal Model for Orion Mated to the International Space Station

NASA Technical Reports Server (NTRS)

Miller, StephenW.; Walker, William Q.

2011-01-01

This study is an extension of previous work to evaluate the applicability of Design of Experiments (DOE)/Response Surface Methodology to on-orbit thermal analysis. The goal was to determine if the methodology could produce a Response Surface Equation (RSE) that predicted the thermal model temperature results within +/-10 F. An RSE is a polynomial expression that can then be used to predict temperatures for a defined range of factor combinations. Based on suggestions received from the previous work, this study used a model with simpler geometry, considered polynomials up to fifth order, and evaluated orbital temperature variations to establish a minimum and maximum temperature for each component. A simplified Outer Mold Line (OML) thermal model of the Orion spacecraft was used in this study. The factors chosen were the vehicle's Yaw, Pitch, and Roll (defining the on-orbit attitude), the Beta angle (restricted to positive beta angles from 0 to 75), and the environmental constants (varying from cold to hot). All factors were normalized from their native ranges to a non-dimensional range from -1.0 to 1.0. Twenty-three components from the OML were chosen and the minimum and maximum orbital temperatures were calculated for each to produce forty-six responses for the DOE model. A customized DOE case matrix of 145 analysis cases was developed which used analysis points at the factor corners, mid-points, and center. From this data set, RSE s were developed which consisted of cubic, quartic, and fifth order polynomials. The results presented are for the fifth order RSE. The RSE results were then evaluated for agreement with the analytical model predictions to produce a +/-3(sigma) error band. Forty of the 46 responses had a +/-3(sigma) value of 10 F or less. Encouraged by this initial success, two additional sets of verification cases were selected. One contained 20 cases, the other 50 cases. These cases were evaluated both with the fifth order RSE and with the analytical model. For the maximum temperature predictions, 12 of the 23 components had all predictions within +/-10 F and 17 were within +/-20 F. For the minimum temperature predictions, only 4 of the 23 components (the four radiator temperatures), were within the 10 F goal. The maximum temperature RSEs were then run through 59,049 screening cases. The RSE predictions were then filtered to find 55 cases that produced the hottest temperatures. These 55 cases were then analyzed using the thermal model and the results compared against the RSE predictions. As noted earlier, 12 of the 23 responses were within +/-10 F at 17 within +/-20 F. These results demonstrate that if properly formulated, an RSE can provide a reliable, fast temperature prediction. Despite this progress, additional work is needed to determine why the minimum temperatures responses and 6 of the hot temperature responses did not produce reliable RSEs. Recommend focus areas are the model itself (arithmetic vs. diffusion nodes) and seeking consultations with statistical application experts.

The patient work system: An analysis of self-care performance barriers among elderly heart failure patients and their informal caregivers

PubMed Central

Holden, Richard J.; Schubert, Christiane C.; Mickelson, Robin S.

2014-01-01

Human factors and ergonomics approaches have been successfully applied to study and improve the work performance of healthcare professionals. However, there has been relatively little work in “patient-engaged human factors,” or the application of human factors to the health-related work of patients and other nonprofessionals. This study applied a foundational human factors tool, the systems model, to investigate the barriers to self-care performance among chronically ill elderly patients and their informal (family) caregivers. A Patient Work System model was developed to guide the collection and analysis of interviews, surveys, and observations of patients with heart failure (n=30) and their informal caregivers (n=14). Iterative analyses revealed the nature and prevalence of self-care barriers across components of the Patient Work System. Person-related barriers were common and stemmed from patients’ biomedical conditions, limitations, knowledge deficits, preferences, and perceptions as well as the characteristics of informal caregivers and healthcare professionals. Task barriers were also highly prevalent and included task difficulty, timing, complexity, ambiguity, conflict, and undesirable consequences. Tool barriers were related to both availability and access of tools and technologies and their design, usability, and impact. Context barriers were found across three domains—physical-spatial, social-cultural, and organizational—and multiple “spaces” such as “at home,” “on the go,” and “in the community.” Barriers often stemmed not from single factors but from the interaction of several work system components. Study findings suggest the need to further explore multiple actors, context, and interactions in the patient work system during research and intervention design, as well as the need to develop new models and measures for studying patient and family work. PMID:25479983

The patient work system: an analysis of self-care performance barriers among elderly heart failure patients and their informal caregivers.

PubMed

Holden, Richard J; Schubert, Christiane C; Mickelson, Robin S

2015-03-01

Human factors and ergonomics approaches have been successfully applied to study and improve the work performance of healthcare professionals. However, there has been relatively little work in "patient-engaged human factors," or the application of human factors to the health-related work of patients and other nonprofessionals. This study applied a foundational human factors tool, the systems model, to investigate the barriers to self-care performance among chronically ill elderly patients and their informal (family) caregivers. A Patient Work System model was developed to guide the collection and analysis of interviews, surveys, and observations of patients with heart failure (n = 30) and their informal caregivers (n = 14). Iterative analyses revealed the nature and prevalence of self-care barriers across components of the Patient Work System. Person-related barriers were common and stemmed from patients' biomedical conditions, limitations, knowledge deficits, preferences, and perceptions as well as the characteristics of informal caregivers and healthcare professionals. Task barriers were also highly prevalent and included task difficulty, timing, complexity, ambiguity, conflict, and undesirable consequences. Tool barriers were related to both availability and access of tools and technologies and their design, usability, and impact. Context barriers were found across three domains-physical-spatial, social-cultural, and organizational-and multiple "spaces" such as "at home," "on the go," and "in the community." Barriers often stemmed not from single factors but from the interaction of several work system components. Study findings suggest the need to further explore multiple actors, contexts, and interactions in the patient work system during research and intervention design, as well as the need to develop new models and measures for studying patient and family work. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Quantifying the impacts of climatic trend and fluctuation on crop yields in northern China.

PubMed

Qiao, Jianmin; Yu, Deyong; Liu, Yupeng

2017-10-01

Climate change plays a critical role in crop yield variations, which has attracted a great deal of concern worldwide. However, the mechanisms of how climatic trend and fluctuations affect crop yields are not well understood and need to be further investigated. Thus, using the GIS-based Environmental Policy Integrated Climate (EPIC) model, we simulated the yields of major crops (i.e., wheat, maize, and rice) and evaluated the impacts of climatic factors on crop yields in the Agro-Pastoral Transitional Zone (APTZ) of northern China between 1980 and 2010. The partial least squares regression model was used to assess the contribution rates of climatic factors (i.e., precipitation, photosynthetically active radiation (PAR), minimum temperature (T min ), maximum temperature (T max )) to the variation of crop yields. The Breaks for Additive Season and Trend (BFAST) model was adopted to decompose the climate factors into trend and fluctuation components, and the relative contributions of climate trend and fluctuation were then evaluated. The results indicated that the contributions of climatic factors to yield variations of wheat, maize, and rice were 31.7, 37.7, and 23.1%, respectively. That is, climate change had larger impacts on maize than wheat and rice. More cultivated areas were significantly and positively correlated with precipitation than with other climatic factors due to the limited precipitation in the APTZ. Also, climatic trend component had positive impacts on crop yields in the whole region, whereas the climate fluctuation was associated mainly with the areas where the crop yields decreased. This study helps improve our understanding of the mechanisms of climate change impacts on crop yields, and provides useful scientific information for designing regional-scale strategies of adaptation to climate change.

Spectral factorization of wavefields and wave operators

NASA Astrophysics Data System (ADS)

Rickett, James Edward

Spectral factorization is the problem of finding a minimum-phase function with a given power spectrum. Minimum phase functions have the property that they are causal with a causal (stable) inverse. In this thesis, I factor multidimensional systems into their minimum-phase components. Helical boundary conditions resolve any ambiguities over causality, allowing me to factor multi-dimensional systems with conventional one-dimensional spectral factorization algorithms. In the first part, I factor passive seismic wavefields recorded in two-dimensional spatial arrays. The result provides an estimate of the acoustic impulse response of the medium that has higher bandwidth than autocorrelation-derived estimates. Also, the function's minimum-phase nature mimics the physics of the system better than the zero-phase autocorrelation model. I demonstrate this on helioseismic data recorded by the satellite-based Michelson Doppler Imager (MDI) instrument, and shallow seismic data recorded at Long Beach, California. In the second part of this thesis, I take advantage of the stable-inverse property of minimum-phase functions to solve wave-equation partial differential equations. By factoring multi-dimensional finite-difference stencils into minimum-phase components, I can invert them efficiently, facilitating rapid implicit extrapolation without the azimuthal anisotropy that is observed with splitting approximations. The final part of this thesis describes how to calculate diagonal weighting functions that approximate the combined operation of seismic modeling and migration. These weighting functions capture the effects of irregular subsurface illumination, which can be the result of either the surface-recording geometry, or focusing and defocusing of the seismic wavefield as it propagates through the earth. Since they are diagonal, they can be easily both factored and inverted to compensate for uneven subsurface illumination in migrated images. Experimental results show that applying these weighting functions after migration leads to significantly improved estimates of seismic reflectivity.

Micropollutants throughout an integrated urban drainage model: Sensitivity and uncertainty analysis

NASA Astrophysics Data System (ADS)

Mannina, Giorgio; Cosenza, Alida; Viviani, Gaspare

2017-11-01

The paper presents the sensitivity and uncertainty analysis of an integrated urban drainage model which includes micropollutants. Specifically, a bespoke integrated model developed in previous studies has been modified in order to include the micropollutant assessment (namely, sulfamethoxazole - SMX). The model takes into account also the interactions between the three components of the system: sewer system (SS), wastewater treatment plant (WWTP) and receiving water body (RWB). The analysis has been applied to an experimental catchment nearby Palermo (Italy): the Nocella catchment. Overall, five scenarios, each characterized by different uncertainty combinations of sub-systems (i.e., SS, WWTP and RWB), have been considered applying, for the sensitivity analysis, the Extended-FAST method in order to select the key factors affecting the RWB quality and to design a reliable/useful experimental campaign. Results have demonstrated that sensitivity analysis is a powerful tool for increasing operator confidence in the modelling results. The approach adopted here can be used for blocking some non-identifiable factors, thus wisely modifying the structure of the model and reducing the related uncertainty. The model factors related to the SS have been found to be the most relevant factors affecting the SMX modeling in the RWB when all model factors (scenario 1) or model factors of SS (scenarios 2 and 3) are varied. If the only factors related to the WWTP are changed (scenarios 4 and 5), the SMX concentration in the RWB is mainly influenced (till to 95% influence of the total variance for SSMX,max) by the aerobic sorption coefficient. A progressive uncertainty reduction from the upstream to downstream was found for the soluble fraction of SMX in the RWB.

What Do We Mean By Sensitivity Analysis? The Need For A Comprehensive Characterization Of Sensitivity In Earth System Models

NASA Astrophysics Data System (ADS)

Razavi, S.; Gupta, H. V.

2014-12-01

Sensitivity analysis (SA) is an important paradigm in the context of Earth System model development and application, and provides a powerful tool that serves several essential functions in modelling practice, including 1) Uncertainty Apportionment - attribution of total uncertainty to different uncertainty sources, 2) Assessment of Similarity - diagnostic testing and evaluation of similarities between the functioning of the model and the real system, 3) Factor and Model Reduction - identification of non-influential factors and/or insensitive components of model structure, and 4) Factor Interdependence - investigation of the nature and strength of interactions between the factors, and the degree to which factors intensify, cancel, or compensate for the effects of each other. A variety of sensitivity analysis approaches have been proposed, each of which formally characterizes a different "intuitive" understanding of what is meant by the "sensitivity" of one or more model responses to its dependent factors (such as model parameters or forcings). These approaches are based on different philosophies and theoretical definitions of sensitivity, and range from simple local derivatives and one-factor-at-a-time procedures to rigorous variance-based (Sobol-type) approaches. In general, each approach focuses on, and identifies, different features and properties of the model response and may therefore lead to different (even conflicting) conclusions about the underlying sensitivity. This presentation revisits the theoretical basis for sensitivity analysis, and critically evaluates existing approaches so as to demonstrate their flaws and shortcomings. With this background, we discuss several important properties of response surfaces that are associated with the understanding and interpretation of sensitivity. Finally, a new approach towards global sensitivity assessment is developed that is consistent with important properties of Earth System model response surfaces.

Efficient system modeling for a small animal PET scanner with tapered DOI detectors.

PubMed

Zhang, Mengxi; Zhou, Jian; Yang, Yongfeng; Rodríguez-Villafuerte, Mercedes; Qi, Jinyi

2016-01-21

A prototype small animal positron emission tomography (PET) scanner for mouse brain imaging has been developed at UC Davis. The new scanner uses tapered detector arrays with depth of interaction (DOI) measurement. In this paper, we present an efficient system model for the tapered PET scanner using matrix factorization and a virtual scanner geometry. The factored system matrix mainly consists of two components: a sinogram blurring matrix and a geometrical matrix. The geometric matrix is based on a virtual scanner geometry. The sinogram blurring matrix is estimated by matrix factorization. We investigate the performance of different virtual scanner geometries. Both simulation study and real data experiments are performed in the fully 3D mode to study the image quality under different system models. The results indicate that the proposed matrix factorization can maintain image quality while substantially reduce the image reconstruction time and system matrix storage cost. The proposed method can be also applied to other PET scanners with DOI measurement.

Emergent Writing in Preschoolers: Preliminary Evidence for a Theoretical Framework

PubMed Central

Puranik, Cynthia S.; Lonigan, Christopher J.

2014-01-01

Researchers and educators use the term emergent literacy to refer to a broad set of skills and attitudes that serve as foundational skills for acquiring success in later reading and writing; however, models of emergent literacy have generally focused on reading and reading-related behaviors. Hence, the primary aim of this study was to articulate and evaluate a theoretical model of the components of emergent writing. Alternative models of the structure of individual and developmental differences of emergent writing and writing-related skills were examined in 372 preschool children who ranged in age from 3- to 5-years using confirmatory factor analysis. Results from a confirmatory factor analysis provide evidence that these emergent writing skills are best described by three correlated but distinct factors, (a) Conceptual Knowledge, (b) Procedural Knowledge, and (c) Generative Knowledge. Evidence that these three emergent writing factors show different patterns of relations to emergent literacy constructs is presented. Implications for understanding the development of writing and assessment of early writing skills are discussed. PMID:25316955

Diffuse nutrient losses and the impact factors determining their regional differences in four catchments from North to South China

NASA Astrophysics Data System (ADS)

Zhang, Yongyong; Zhou, Yujian; Shao, Quanxi; Liu, Hongbin; Lei, Qiuliang; Zhai, Xiaoyan; Wang, Xuelei

2016-12-01

Diffuse nutrient loss mechanism is complicated and shows remarkably regional differences due to spatial heterogeneities of underlying surface conditions, climate and agricultural practices. Moreover, current available observations are still hard to support the identification of impact factors due to different time or space steps. In this study, an integrated water system model (HEQM) was adopted to obtain the simulated loads of diffuse components (carriers: runoff and sediment; nutrient: total nitrogen (TN) and total phosphorous (TP)) with synchronous scales. Multivariable statistical analysis approaches (Analysis of Similarity and redundancy analysis) were used to assess the regional differences, and to identify impact factors as well as their contributions. Four catchments were selected as our study areas, i.e., Xiahui and Zhangjiafen Catchments of Miyun Basin in North China, Yuliang and Tunxi Catchments of Xin'anjiang Basin in South China. Results showed that the model performances of monthly processes were very good for runoff and good for sediment, TN and TP. The annual average coefficients of all the diffuse components in Xin'anjiang Basin were much greater than those in Miyun Basin, and showed significantly regional differences. All the selected impact factors interpreted 72.87-82.16% of the regional differences of carriers, and 62.72-71.62% of those of nutrient coefficients, respectively. For individual impact factor categories, the critical category was geography, followed by land-use/cover, carriers, climate, as well as soil and agricultural practices in Miyun Basin, or agricultural practices and soil in Xin'anjiang Basin. For individual factors, the critical factors were locations for the carrier regional differences, and carriers or chemical fertilizer for the nutrient regional differences. This study is expected to promote further applications of integrated water system model and multivariable statistical analysis in the diffuse nutrient studies, and provide a scientific support for the diffuse pollution control and management in China.

Decoding and modelling of time series count data using Poisson hidden Markov model and Markov ordinal logistic regression models.

PubMed

Sebastian, Tunny; Jeyaseelan, Visalakshi; Jeyaseelan, Lakshmanan; Anandan, Shalini; George, Sebastian; Bangdiwala, Shrikant I

2018-01-01

Hidden Markov models are stochastic models in which the observations are assumed to follow a mixture distribution, but the parameters of the components are governed by a Markov chain which is unobservable. The issues related to the estimation of Poisson-hidden Markov models in which the observations are coming from mixture of Poisson distributions and the parameters of the component Poisson distributions are governed by an m-state Markov chain with an unknown transition probability matrix are explained here. These methods were applied to the data on Vibrio cholerae counts reported every month for 11-year span at Christian Medical College, Vellore, India. Using Viterbi algorithm, the best estimate of the state sequence was obtained and hence the transition probability matrix. The mean passage time between the states were estimated. The 95% confidence interval for the mean passage time was estimated via Monte Carlo simulation. The three hidden states of the estimated Markov chain are labelled as 'Low', 'Moderate' and 'High' with the mean counts of 1.4, 6.6 and 20.2 and the estimated average duration of stay of 3, 3 and 4 months, respectively. Environmental risk factors were studied using Markov ordinal logistic regression analysis. No significant association was found between disease severity levels and climate components.

Relationship between uric acid and arterial stiffness in the elderly with metabolic syndrome components.

PubMed

Sun, Ning; Zhang, Yun; Tian, Jian-li; Wang, Hui

2013-08-01

High uric acid (UA) levels and metabolic syndrome (MS) are risk factors for atherosclerotic diseases. Brachial-ankle pulse wave velocity (baPWV) is a valid and reproducible measurement by which to assess arterial stiffness and a surrogate marker of atherosclerosis. However, little is known about the relationship between them, especially in elderly Chinese with MS components who are at high risk for atherosclerotic diseases. One thousand and twenty Chinese subjects (159 women) older than 60 years of age (mean age (70.6 ± 5.7) years) with at least one MS component underwent routine laboratory tests, and baPWV measurements were analyzed. Participants were divided into four groups by MS components. The mean age did not significantly differ among the MS component groups. We found that not only the diagnostic factors (blood pressure, body mass index (BMI), lipids, glucose) of MS but also baPWV, UA, insulin, homeostasis model of assessment for insulin resistence index (HOMAIR) levels increased, and high density lipoprotein (HDL)-C decreased with an increased number of MS components (test for trend P < 0.05). The association between UA and baPWV was observed after adjustment for gender, age, blood pressure, BMI, serum creatinine and high density lipoprotein, and insulin resistance (r = 0.186, P < 0.0001). There were increases in the odds ratios for the association between the number of components of MS, UA and baPWV, even after adjustment for traditional risk factors. However, after adjustment for insulin or HOMA-IR, there were no significant differences in the multivariate odds ratios among the number of MS components for UA. The UA level is positively associated with baPWV and MS, but the association between UA and MS is dependent on insulin resistance. Furthermore, baPWV is independently associated with MS in our study population.

An integrated system for rainfall induced shallow landslides modeling

NASA Astrophysics Data System (ADS)

Formetta, Giuseppe; Capparelli, Giovanna; Rigon, Riccardo; Versace, Pasquale

2014-05-01

Rainfall induced shallow landslides (RISL) cause significant damages involving loss of life and properties. Predict susceptible locations for RISL is a complex task that involves many disciplines: hydrology, geotechnical science, geomorphology, statistic. Usually to accomplish this task two main approaches are used: statistical or physically based model. In this work an open source (OS), 3-D, fully distributed hydrological model was integrated in an OS modeling framework (Object Modeling System). The chain is closed by linking the system to a component for safety factor computation with infinite slope approximation able to take into account layered soils and suction contribution to hillslope stability. The model composition was tested for a case study in Calabria (Italy) in order to simulate the triggering of a landslide happened in the Cosenza Province. The integration in OMS allows the use of other components such as a GIS to manage inputs-output processes, and automatic calibration algorithms to estimate model parameters. Finally, model performances were quantified by comparing modelled and simulated trigger time. This research is supported by Ambito/Settore AMBIENTE E SICUREZZA (PON01_01503) project.

A Conceptual Model of Childhood Adaptation to Type 1 Diabetes

PubMed Central

Whittemore, Robin; Jaser, Sarah; Guo, Jia; Grey, Margaret

2010-01-01

The Childhood Adaptation Model to Chronic Illness: Diabetes Mellitus was developed to identify factors that influence childhood adaptation to type 1 diabetes (T1D). Since this model was proposed, considerable research has been completed. The purpose of this paper is to update the model on childhood adaptation to T1D using research conducted since the original model was proposed. The framework suggests that individual and family characteristics, such as age, socioeconomic status, and in children with T1D, treatment modality (pump vs. injections), psychosocial responses (depressive symptoms and anxiety), and individual and family responses (self-management, coping, self-efficacy, family functioning, social competence) influence the level of adaptation. Adaptation has both physiologic (metabolic control) and psychosocial (QOL) components. This revised model provides greater specificity to the factors that influence adaptation to chronic illness in children. Research and clinical implications are discussed. PMID:20934079

Modeling Insurgency, Counter-Insurgency, and Coalition Strategies and Operations

DTIC Science & Technology

2012-01-01

these structures to analyze the components of leadership, promotion , recruitment, financial resources, operational techniques, network communications...processes into account: promotion of junior leaders (j), loss of senior leaders to internal factors (l), recruitment of senior leaders (o), rate that senior...is modeled in a similar manner as senior lead- ers, using: promotion of foot soldiers to junior leaders (β1f), the loss of junior leaders promoted to

Construct validity and factor structure of the pittsburgh sleep quality index and epworth sleepiness scale in a multi-national study of African, South East Asian and South American college students.

PubMed

Gelaye, Bizu; Lohsoonthorn, Vitool; Lertmeharit, Somrat; Pensuksan, Wipawan C; Sanchez, Sixto E; Lemma, Seblewengel; Berhane, Yemane; Zhu, Xiaotong; Vélez, Juan Carlos; Barbosa, Clarita; Anderade, Asterio; Tadesse, Mahlet G; Williams, Michelle A

2014-01-01

The Pittsburgh Sleep Quality Index (PSQI) and the Epworth Sleepiness Scale (ESS) are questionnaires used to assess sleep quality and excessive daytime sleepiness in clinical and population-based studies. The present study aimed to evaluate the construct validity and factor structure of the PSQI and ESS questionnaires among young adults in four countries (Chile, Ethiopia, Peru and Thailand). A cross-sectional study was conducted among 8,481 undergraduate students. Students were invited to complete a self-administered questionnaire that collected information about lifestyle, demographic, and sleep characteristics. In each country, the construct validity and factorial structures of PSQI and ESS questionnaires were tested through exploratory and confirmatory factor analyses (EFA and CFA). The largest component-total correlation coefficient for sleep quality as assessed using PSQI was noted in Chile (r = 0.71) while the smallest component-total correlation coefficient was noted for sleep medication use in Peru (r = 0.28). The largest component-total correlation coefficient for excessive daytime sleepiness as assessed using ESS was found for item 1 (sitting/reading) in Chile (r = 0.65) while the lowest item-total correlation was observed for item 6 (sitting and talking to someone) in Thailand (r = 0.35). Using both EFA and CFA a two-factor model was found for PSQI questionnaire in Chile, Ethiopia and Thailand while a three-factor model was found for Peru. For the ESS questionnaire, we noted two factors for all four countries. Overall, we documented cross-cultural comparability of sleep quality and excessive daytime sleepiness measures using the PSQI and ESS questionnaires among Asian, South American and African young adults. Although both the PSQI and ESS were originally developed as single-factor questionnaires, the results of our EFA and CFA revealed the multi- dimensionality of the scales suggesting limited usefulness of the global PSQI and ESS scores to assess sleep quality and excessive daytime sleepiness.

Race and Gender Matter: A Multidimensional Approach to Conceptualizing and Measuring Stress in African American Women

PubMed Central

Woods-Giscombé, Cheryl L.; Lobel, Marci

2008-01-01

Based on prior research and theory, the authors constructed a multidimensional model of stress in African American women comprised of race-related, gender-related, and generic stress. Exposure to and appraisal of these three types of stress were combined into a higher-order global stress factor. Using structural equation modeling, the fit of this stress factor and its ability to predict distress symptoms were examined in 189 socioeconomically diverse African American women aged 21 to 78. Results support the multidimensional conceptualization and operationalization of stress. Race-related, gender-related, and generic stress contributed equally to the global stress factor, and global stress predicted a significant amount of variance in distress symptoms and intensity. This model exhibited better fit than a model without a global stress factor, in which each stress component predicted distress directly. Furthermore, race-related, gender-related, and generic stress did not contribute to distress beyond their representation in the global stress factor. These findings illustrate that stress related to central elements of identity, namely race and gender, cohere with generic stress to define the stress experience of African American women. PMID:18624581

Race and gender matter: a multidimensional approach to conceptualizing and measuring stress in African American women.

PubMed

Woods-Giscombé, Cheryl L; Lobel, Marci

2008-07-01

Based on prior research and theory, the authors constructed a multidimensional model of stress in African American women comprised of race-related, gender-related, and generic stress. Exposure to and appraisal of these three types of stress were combined into a higher-order global stress factor. Using structural equation modeling, the fit of this stress factor and its ability to predict distress symptoms were examined in 189 socioeconomically diverse African American women aged 21 to 78. Results support the multidimensional conceptualization and operationalization of stress. Race-related, gender-related, and generic stress contributed equally to the global stress factor, and global stress predicted a significant amount of variance in distress symptoms and intensity. This model exhibited better fit than a model without a global stress factor, in which each stress component predicted distress directly. Furthermore, race-related, gender-related, and generic stress did not contribute to distress beyond their representation in the global stress factor. These findings illustrate that stress related to central elements of identity, namely race and gender, cohere with generic stress to define the stress experience of African American women. Copyright (c) 2008 APA, all rights reserved.

A Factor Analytic Investigation of the Person-in-Recovery and Provider Versions of the Revised Recovery Self-Assessment (RSA-R).

PubMed

Konkolÿ Thege, Barna; Ham, Elke; Ball, Laura C

2017-12-01

Recovery is understood as living a life with hope, purpose, autonomy, productivity, and community engagement despite a mental illness. The aim of this study was to provide further information on the psychometric properties of the Person-in-Recovery and Provider versions of the Revised Recovery Self-Assessment (RSA-R), a widely used measure of recovery orientation. Data from 654 individuals were analyzed, 519 of whom were treatment providers (63.6% female), while 135 were inpatients (10.4% female) of a Canadian tertiary-level psychiatric hospital. Confirmatory and exploratory techniques were used to investigate the factor structure of both versions of the instrument. Results of the confirmatory factor analyses showed that none of the four theoretically plausible models fit the data well. Principal component analyses could not replicate the structure obtained by the scale developers either and instead resulted in a five-component solution for the Provider and a four-component solution for the Person-in-Recovery version. When considering the results of a parallel analysis, the number of components to retain dropped to two for the Provider version and one for the Person-in-Recovery version. We can conclude that the RSA-R requires further revision to become a psychometrically sound instrument for assessing recovery-oriented practices in an inpatient mental health-care setting.

Robust categorization of microfacet BRDF models to enable flexible application-specific BRDF adaptation

NASA Astrophysics Data System (ADS)

Butler, Samuel D.; Marciniak, Michael A.

2014-09-01

Since the development of the Torrance-Sparrow bidirectional re ectance distribution function (BRDF) model in 1967, several BRDF models have been created. Previous attempts to categorize BRDF models have relied upon somewhat vague descriptors, such as empirical, semi-empirical, and experimental. Our approach is to instead categorize BRDF models based on functional form: microfacet normal distribution, geometric attenua- tion, directional-volumetric and Fresnel terms, and cross section conversion factor. Several popular microfacet models are compared to a standardized notation for a microfacet BRDF model. A library of microfacet model components is developed, allowing for creation of unique microfacet models driven by experimentally measured BRDFs.

Longitudinal Links Between Identity Consolidation and Psychosocial Problems in Adolescence: Using Bi-Factor Latent Change and Cross-Lagged Effect Models.

PubMed

Hatano, Kai; Sugimura, Kazumi; Schwartz, Seth J

2018-04-01

Most previous identity research has focused on relationships between identity synthesis, confusion, and psychosocial problems. However, these studies did not take into account Erikson's notion of identity consolidation, that is, the dynamic interplay between identity synthesis and confusion. This study aimed to examine longitudinal relationships and the directionality of the effects between identity consolidation and psychosocial problems during adolescence, using two waves of longitudinal data from 793 Japanese adolescents (49.7% girls; ages 13-14 and 16-17 at Time 1). A bi-factor latent change model revealed that levels and changes in identity consolidation were negatively associated with levels and changes in psychosocial problems. Furthermore, a bi-factor cross-lagged effects model provided evidence that identity consolidation negatively predicted psychosocial problems, and vice versa. Our study facilitates a better understanding of the importance of identity consolidation in the relations between identity components and psychosocial problems.

Predicting Software Suitability Using a Bayesian Belief Network

NASA Technical Reports Server (NTRS)

Beaver, Justin M.; Schiavone, Guy A.; Berrios, Joseph S.

2005-01-01

The ability to reliably predict the end quality of software under development presents a significant advantage for a development team. It provides an opportunity to address high risk components earlier in the development life cycle, when their impact is minimized. This research proposes a model that captures the evolution of the quality of a software product, and provides reliable forecasts of the end quality of the software being developed in terms of product suitability. Development team skill, software process maturity, and software problem complexity are hypothesized as driving factors of software product quality. The cause-effect relationships between these factors and the elements of software suitability are modeled using Bayesian Belief Networks, a machine learning method. This research presents a Bayesian Network for software quality, and the techniques used to quantify the factors that influence and represent software quality. The developed model is found to be effective in predicting the end product quality of small-scale software development efforts.

Attribution of Observed Streamflow Changes in Key British Columbia Drainage Basins

NASA Astrophysics Data System (ADS)

Najafi, Mohammad Reza; Zwiers, Francis W.; Gillett, Nathan P.

2017-11-01

We study the observed decline in summer streamflow in four key river basins in British Columbia (BC), Canada, using a formal detection and attribution (D&A) analysis procedure. Reconstructed and simulated streamflow is generated using the semidistributed variable infiltration capacity hydrologic model, which is driven by 1/16° gridded observations and downscaled climate model data from the Coupled Model Intercomparison Project phase 5 (CMIP5), respectively. The internal variability of the regional hydrologic components using 5100 years of streamflow was simulated using CMIP5 preindustrial control runs. Results show that the observed changes in summer streamflow are inconsistent with simulations representing the responses to natural forcing factors alone, while the response to anthropogenic and natural forcing factors combined is detected in these changes. A two-signal D&A analysis indicates that the effects of anthropogenic (ANT) forcing factors are discernable from natural forcing in BC, albeit with large uncertainties.

Influence of uncertainties of the empirical models for inferring the E-region electric fields at the dip equator

NASA Astrophysics Data System (ADS)

Moro, Juliano; Denardini, Clezio Marcos; Resende, Laysa Cristina Araújo; Chen, Sony Su; Schuch, Nelson Jorge

2016-06-01

Daytime E-region electric fields play a crucial role in the ionospheric dynamics at the geomagnetic dip latitudes. Due to their importance, there is an interest in accurately measuring and modeling the electric fields for both climatological and near real-time studies. In this work, we present the daytime vertical ( Ez) and eastward ( Ey) electric fields for a reference quiet day (February 7, 2001) at the São Luís Space Observatory, Brazil (SLZ, 2.31°S, 44.16°W). The component Ez is inferred from Doppler shifts of type II echoes (gradient drift instability) and the anisotropic factor, which is computed from ion and electron gyro frequencies as well as ion and electron collision frequencies with neutral molecules. The component Ey depends on the ratio of Hall and Pedersen conductivities and Ez. A magnetic field-line-integrated conductivity model is used to obtain the anisotropic factor for calculating Ez and the ionospheric conductivities for calculating Ey. This model uses the NRLMSISE-00, IRI-2007, and IGRF-11 empirical models as input parameters for neutral atmosphere, ionosphere, and geomagnetic field, respectively. Consequently, it is worth determining the uncertainties (or errors) in Ey and Ez associated with these empirical model outputs in order to precisely define the confidence limit for the estimated electric field components. For this purpose, errors of ±10 % were artificially introduced in the magnitude of each empirical model output before estimating Ey and Ez. The corresponding uncertainties in the ionospheric conductivity and electric field are evaluated considering the individual and cumulative contribution of the artificial errors. The results show that the neutral densities and temperature may be responsible for the largest changes in Ey and Ez, followed by changes in the geomagnetic field intensity and electron and ions compositions.

The S factor--a new derived hemodynamic oxygenation parameter--a useful tool for simplified mathematical modeling of global problems of oxygen transport.

PubMed

Farrell, K; Wasser, T

1997-01-01

We describe a new derived hemodynamic oxygenation parameter, the S factor (S). The factor is based on oxygen delivery and oxygen consumption and can range from -3 to 1. It allows simplified mathematical modeling of clinical problems of oxygen transport and can be applied to many clinical situations. A new hemodynamic oxygenation parameter, the S factor (S), is introduced as an aid to mathematical modeling. It is defined as follows: [formula: see text] (DO2 = oxygen delivery, VO2 = oxygen consumption) S can theoretically vary from -3 (DO2 = VO2) to +1 (VO2 = 0). When DO2/VO2 = 4 (ie. OER = 0.25), S = 0. An S < 0 implies utilization of reserve oxygen transport capacity. An S > 0 implies increased oxygen delivery in relation to oxygen consumption (ie. "shunted oxygen delivery"). By algebraic manipulation and substitution of the components of DO2 into Equation 1: DO2 = Q x Ca x 10 DO2 = Q [(Hb)(Sat)(1.36) + PaO2(.0031)] 10 (2) the following equations can be derived: [formula: see text] [formula: see text] Ca - Cv (Ca = arterial content, Cv = venous content) can be determined by substituting components of oxygen consumption: VO2 = Q (Ca - Cv) x 10 (5) into equation 1 and solving for Ca - Cv. [formula: see text] Equation 6 can be simplified to: [formula: see text] A previously defined relationship between mixed venous PO2 (PvO2) and DO2/VO2 (where calculated P50 is 26.6 +/- 1.0) can be used to modify S in a clinically relevant manner. PvO2 = 5.44D O2/VO2 + 18.16 (8) The relationship between S and PvO2 can be defined by substituting Equation 4 into Equation 1 and solving for PvO2 PvO2 = [21.76/(1-S)] + 18.16 (9) As an example, at a PvO2 of 28 torr (anaerobic threshold), S = -1.2. The relationship between PvO2 and S is shown in Figure 1. S, which can also be defined as 1-4(VO2/DO2) or 1-4(OER), is a useful tool for mathematical modeling of global problems of oxygen transport because the previously derived equations with the S value allow the components of oxygen transport to be interrelated in a clinically relevant manner. Additional advantages of using S in mathematical modeling are: 1. Conceptually it 'fits' in that in regards to the sign (+ or -), as a -S implies utilization of reserve oxygen transport capacity and a +S implies wasted or excess oxygen delivery (shunted). 2. These concepts are easily quantified using the S factor. 3. It 'spreads out' the difference between values for parameters (OER or S) integrating components of oxygen transport, ie. in the 'normal state' regarding oxygen transport, OER = 0.25 and S = 0. At the anaerobic threshold (PvO2 = 28 torr), OER = 0.55 and S = -1.2. Thus, the change in OER from 'normal state' to anaerobic threshold is 0.3 (0.55-0.25) and the change in S is 1.2. This represents a four-fold increase. Four examples of mathematical modeling of global problems of oxygen transport using the S factor are described below.

Insights into the interaction between carbamazepine and natural dissolved organic matter in the Yangtze Estuary using fluorescence excitation-emission matrix spectra coupled with parallel factor analysis.

PubMed

Wang, Ying; Zhang, Manman; Fu, Jun; Li, Tingting; Wang, Jinggang; Fu, Yingyu

2016-10-01

The interaction between carbamazepine (CBZ) and dissolved organic matter (DOM) from three zones (the nearshore, the river channel, and the coastal areas) in the Yangtze Estuary was investigated using fluorescence quenching titration combined with excitation emission matrix spectra and parallel factor analysis (PARAFAC). The complexation between CBZ and DOM was demonstrated by the increase in hydrogen bonding and the disappearance of the C=O stretch obtained from the Fourier transform infrared spectroscopy analysis. The results indicated that two protein-like substances (component 2 and component3) and two humic-like substances (component 1 and 4) were identified in the DOM from the Yangtze Estuary. The fluorescence quenching curves of each component with the addition of CBZ and the Ryan and Weber model calculation results both demonstrated that the different components exhibited different complexation activities with CBZ. The protein-like components had a stronger affinity with CBZ than did the humic-like substances. On the other hand, the autochthonous tyrosine-like C2 played an important role in the complexation with DOM from the river channel and coastal areas, while C3 influenced by anthropogenic activities showed an obvious effect in the nearshore area. DOMs from the river channel have the highest binding capacity for CBZ, which may ascribe to the relatively high phenol content group in the DOM.

Initial retrieval sequence and blending strategy

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

Pemwell, D.L.; Grenard, C.E.

1996-09-01

This report documents the initial retrieval sequence and the methodology used to select it. Waste retrieval, storage, pretreatment and vitrification were modeled for candidate single-shell tank retrieval sequences. Performance of the sequences was measured by a set of metrics (for example,high-level waste glass volume, relative risk and schedule).Computer models were used to evaluate estimated glass volumes,process rates, retrieval dates, and blending strategy effects.The models were based on estimates of component inventories and concentrations, sludge wash factors and timing, retrieval annex limitations, etc.

Dynamics of short-pulse generation via spectral filtering from intensely excited gain-switched 1.55-μm distributed-feedback laser diodes.

PubMed

Chen, Shaoqiang; Yoshita, Masahiro; Sato, Aya; Ito, Takashi; Akiyama, Hidefumi; Yokoyama, Hiroyuki

2013-05-06

Picosecond-pulse-generation dynamics and pulse-width limiting factors via spectral filtering from intensely pulse-excited gain-switched 1.55-μm distributed-feedback laser diodes were studied. The spectral and temporal characteristics of the spectrally filtered pulses indicated that the short-wavelength component stems from the initial part of the gain-switched main pulse and has a nearly linear down-chirp of 5.2 ps/nm, whereas long-wavelength components include chirped pulse-lasing components and steady-state-lasing components. Rate-equation calculations with a model of linear change in refractive index with carrier density explained the major features of the experimental results. The analysis of the expected pulse widths with optimum spectral widths was also consistent with the experimental data.

Comparison of receptor models for source apportionment of the PM10 in Zaragoza (Spain).

PubMed

Callén, M S; de la Cruz, M T; López, J M; Navarro, M V; Mastral, A M

2009-08-01

Receptor models are useful to understand the chemical and physical characteristics of air pollutants by identifying their sources and by estimating contributions of each source to receptor concentrations. In this work, three receptor models based on principal component analysis with absolute principal component scores (PCA-APCS), Unmix and positive matrix factorization (PMF) were applied to study for the first time the apportionment of the airborne particulate matter less or equal than 10microm (PM10) in Zaragoza, Spain, during 1year sampling campaign (2003-2004). The PM10 samples were characterized regarding their concentrations in inorganic components: trace elements and ions and also organic components: polycyclic aromatic hydrocarbons (PAH) not only in the solid phase but also in the gas phase. A comparison of the three receptor models was carried out in order to do a more robust characterization of the PM10. The three models predicted that the major sources of PM10 in Zaragoza were related to natural sources (60%, 75% and 47%, respectively, for PCA-APCS, Unmix and PMF) although anthropogenic sources also contributed to PM10 (28%, 25% and 39%). With regard to the anthropogenic sources, while PCA and PMF allowed high discrimination in the sources identification associated with different combustion sources such as traffic and industry, fossil fuel, biomass and fuel-oil combustion, heavy traffic and evaporative emissions, the Unmix model only allowed the identification of industry and traffic emissions, evaporative emissions and heavy-duty vehicles. The three models provided good correlations between the experimental and modelled PM10 concentrations with major precision and the closest agreement between the PMF and PCA models.

Reliability prediction of large fuel cell stack based on structure stress analysis

NASA Astrophysics Data System (ADS)

Liu, L. F.; Liu, B.; Wu, C. W.

2017-09-01

The aim of this paper is to improve the reliability of Proton Electrolyte Membrane Fuel Cell (PEMFC) stack by designing the clamping force and the thickness difference between the membrane electrode assembly (MEA) and the gasket. The stack reliability is directly determined by the component reliability, which is affected by the material property and contact stress. The component contact stress is a random variable because it is usually affected by many uncertain factors in the production and clamping process. We have investigated the influences of parameter variation coefficient on the probability distribution of contact stress using the equivalent stiffness model and the first-order second moment method. The optimal contact stress to make the component stay in the highest level reliability is obtained by the stress-strength interference model. To obtain the optimal contact stress between the contact components, the optimal thickness of the component and the stack clamping force are optimally designed. Finally, a detailed description is given how to design the MEA and gasket dimensions to obtain the highest stack reliability. This work can provide a valuable guidance in the design of stack structure for a high reliability of fuel cell stack.

Disease modeling and drug screening for neurological diseases using human induced pluripotent stem cells.

PubMed

Xu, Xiao-hong; Zhong, Zhong

2013-06-01

With the general decline of pharmaceutical research productivity, there are concerns that many components of the drug discovery process need to be redesigned and optimized. For example, the human immortalized cell lines or animal primary cells commonly used in traditional drug screening may not faithfully recapitulate the pathological mechanisms of human diseases, leading to biases in assays, targets, or compounds that do not effectively address disease mechanisms. Recent advances in stem cell research, especially in the development of induced pluripotent stem cell (iPSC) technology, provide a new paradigm for drug screening by permitting the use of human cells with the same genetic makeup as the patients without the typical quantity constraints associated with patient primary cells. In this article, we will review the progress made to date on cellular disease models using human stem cells, with a focus on patient-specific iPSCs for neurological diseases. We will discuss the key challenges and the factors that associated with the success of using stem cell models for drug discovery through examples from monogenic diseases, diseases with various known genetic components, and complex diseases caused by a combination of genetic, environmental and other factors.

Testing the Technology Acceptance Model: HIV case managers' intention to use a continuity of care record with context-specific links.

PubMed

Schnall, Rebecca; Bakken, Suzanne

2011-09-01

To assess the applicability of the Technology Acceptance Model (TAM) constructs in explaining HIV case managers' behavioural intention to use a continuity of care record (CCR) with context-specific links designed to meet their information needs. Data were collected from 94 case managers who provide care to persons living with HIV (PLWH) using an online survey comprising three components: (1) demographic information: age, gender, ethnicity, race, Internet usage and computer experience; (2) mock-up of CCR with context-specific links; and items related to TAM constructs. Data analysis included: principal components factor analysis (PCA), assessment of internal consistency reliability and univariate and multivariate analysis. PCA extracted three factors (Perceived Ease of Use, Perceived Usefulness and Perceived Barriers to Use), explained variance = 84.9%, Cronbach's ά = 0.69-0.91. In a linear regression model, Perceived Ease of Use, Perceived Usefulness and Perceived Barriers to Use explained 43.6% (p < 0.001) of the variance in Behavioural Intention to use a CCR with context-specific links. Our study contributes to the evidence base regarding TAM in health care through expanding the type of professional surveyed, study setting and Health Information Technology assessed.

Dairy cow culling strategies: making economical culling decisions.

PubMed

Lehenbauer, T W; Oltjen, J W

1998-01-01

The purpose of this report was to examine important economic elements of culling decisions, to review progress in development of culling decision support systems, and to discern some of the potentially rewarding areas for future research on culling models. Culling decisions have an important influence on the economic performance of the dairy but are often made in a nonprogrammed fashion and based partly on the intuition of the decision maker. The computer technology that is available for dairy herd management has made feasible the use of economic models to support culling decisions. Financial components--including profit, cash flow, and risk--are major economic factors affecting culling decisions. Culling strategies are further influenced by short-term fluctuations in cow numbers as well as by planned herd expansion. Changes in herd size affect the opportunity cost for postponed replacement and may alter the relevance of optimization strategies that assume a fixed herd size. Improvements in model components related to biological factors affecting future cow performance, including milk production, reproductive status, and mastitis, appear to offer the greatest economic potential for enhancing culling decision support systems. The ultimate value of any culling decision support system for developing economic culling strategies will be determined by its results under field conditions.

Predictors of recent HIV testing among male street laborers in urban Vietnam.

PubMed

Nguyen, Huy V; Dunne, Michael P; Debattista, Joseph

2014-08-01

This study assessed the prevalence of and factors associated with HIV testing among male street laborers. In a cross-sectional survey, social mapping was done to recruit and interview 450 men aged 18-59 years in Hanoi. Although many of these men engaged in multiple risk behaviors for HIV, only 19.8 percent had been tested for HIV. A modified theoretical model provided better fit than the conventional Information-Motivation-Behavioral Skills model, as it explained much more variance in HIV testing. This model included three Information-Motivation-Behavioral components and four additional factors, namely, the origin of residence, sexual orientation, the number of sexual partners, and the status of condom use. © The Author(s) 2013.

Addressing the Hard Factors for Command File Errors by Probabilistic Reasoning

NASA Technical Reports Server (NTRS)

Meshkat, Leila; Bryant, Larry

2014-01-01

Command File Errors (CFE) are managed using standard risk management approaches at the Jet Propulsion Laboratory. Over the last few years, more emphasis has been made on the collection, organization, and analysis of these errors for the purpose of reducing the CFE rates. More recently, probabilistic modeling techniques have been used for more in depth analysis of the perceived error rates of the DAWN mission and for managing the soft factors in the upcoming phases of the mission. We broadly classify the factors that can lead to CFE's as soft factors, which relate to the cognition of the operators and hard factors which relate to the Mission System which is composed of the hardware, software and procedures used for the generation, verification & validation and execution of commands. The focus of this paper is to use probabilistic models that represent multiple missions at JPL to determine the root cause and sensitivities of the various components of the mission system and develop recommendations and techniques for addressing them. The customization of these multi-mission models to a sample interplanetary spacecraft is done for this purpose.

Psychometric analysis of the Swedish version of the General Medical Council's multi source feedback questionnaires.

PubMed

Olsson, Jan-Eric; Wallentin, Fan Yang; Toth-Pal, Eva; Ekblad, Solvig; Bertilson, Bo Christer

2017-07-10

To determine the internal consistency and the underlying components of our translated and adapted Swedish version of the General Medical Council's multisource feedback questionnaires (GMC questionnaires) for physicians and to confirm which aspects of good medical practice the latent variable structure reflected. From October 2015 to March 2016, residents in family medicine in Sweden were invited to participate in the study and to use the Swedish version to perform self-evaluations and acquire feedback from both their patients and colleagues. The validation focused on internal consistency and construct validity. Main outcome measures were Cronbach's alpha coefficients, Principal Component Analysis, and Confirmatory Factor Analysis indices. A total of 752 completed questionnaires from patients, colleagues, and residents were analysed. Of these, 213 comprised resident self-evaluations, 336 were feedback from residents' patients, and 203 were feedback from residents' colleagues. Cronbach's alpha coefficients of the scores were 0.88 from patients, 0.93 from colleagues, and 0.84 in the self-evaluations. The Confirmatory Factor Analysis validated two models that fit the data reasonably well and reflected important aspects of good medical practice. The first model had two latent factors for patient-related items concerning empathy and consultation management, and the second model had five latent factors for colleague-related items, including knowledge and skills, attitude and approach, reflection and development, teaching, and trust. The current Swedish version seems to be a reliable and valid tool for formative assessment for resident physicians and their supervisors. This needs to be verified in larger samples.

Psychometric analysis of the Swedish version of the General Medical Council's multi source feedback questionnaires

PubMed Central

Wallentin, Fan Yang; Toth-Pal, Eva; Ekblad, Solvig; Bertilson, Bo Christer

2017-01-01

Objectives To determine the internal consistency and the underlying components of our translated and adapted Swedish version of the General Medical Council's multisource feedback questionnaires (GMC questionnaires) for physicians and to confirm which aspects of good medical practice the latent variable structure reflected. Methods From October 2015 to March 2016, residents in family medicine in Sweden were invited to participate in the study and to use the Swedish version to perform self-evaluations and acquire feedback from both their patients and colleagues. The validation focused on internal consistency and construct validity. Main outcome measures were Cronbach’s alpha coefficients, Principal Component Analysis, and Confirmatory Factor Analysis indices. Results A total of 752 completed questionnaires from patients, colleagues, and residents were analysed. Of these, 213 comprised resident self-evaluations, 336 were feedback from residents’ patients, and 203 were feedback from residents’ colleagues. Cronbach’s alpha coefficients of the scores were 0.88 from patients, 0.93 from colleagues, and 0.84 in the self-evaluations. The Confirmatory Factor Analysis validated two models that fit the data reasonably well and reflected important aspects of good medical practice. The first model had two latent factors for patient-related items concerning empathy and consultation management, and the second model had five latent factors for colleague-related items, including knowledge and skills, attitude and approach, reflection and development, teaching, and trust. Conclusions The current Swedish version seems to be a reliable and valid tool for formative assessment for resident physicians and their supervisors. This needs to be verified in larger samples. PMID:28704204

The relationship between brain behavioral systems and the characteristics of the five factor model of personality with aggression among Iranian students.

PubMed

Komasi, Saeid; Saeidi, Mozhgan; Soroush, Ali; Zakiei, Ali

2016-07-01

Aggression is one of the negative components of emotion and it is usually considered to be the outcome of the activity of the Behavioral Inhibition and the Behavioral Activation System (BIS/BAS): components which can be considered as predisposing factors for personality differences. Therefore, the purpose of this study was to investigate the relationship between brain behavioral systems and the characteristics of the five factor model of personality with aggression among students. The present study has a correlation descriptive design. The research population included all of the Razi University students in the academic year of 2012-2013. The sampling was carried out with a random stratified method and 360 people (308 female and 52 male) were studied according to a table of Morgan. The study instruments were Buss and Perry Aggression Questionnaire, NEO Personality Inventory (Short Form), and Carver and White scale for BAS/BIS. Finally, SPSS20 was utilized to analyze the data using Pearson correlation, regression analysis, and canonical correlation. The data showed a significant positive relationship between the neurosis and agreeableness personality factors with aggression; but there is a significant negative relationship between the extroversion, openness, and conscientiousness personality factors with aggression. Furthermore, there is a significant positive relationship between all the components of brain behavioral systems (impulsivity, novelty seeking, sensitivity, tender) and aggression. The results of regression analysis indicated the personality characteristics and the brain behavioral systems which can predict 29 percent of the changes to aggression, simultaneously. According to a predictable level of aggressiveness by the personality characteristics and brain behavioral systems, it is possible to identify the personality characteristics and template patterns of brain behavioral systems for the students which be presented to them as a necessary training in order to control and manage of anger and aggression. © 2016 KUMS, All rights reserved.

A predictive model of human performance.

NASA Technical Reports Server (NTRS)

Walters, R. F.; Carlson, L. D.

1971-01-01

An attempt is made to develop a model describing the overall responses of humans to exercise and environmental stresses for prediction of exhaustion vs an individual's physical characteristics. The principal components of the model are a steady state description of circulation and a dynamic description of thermal regulation. The circulatory portion of the system accepts changes in work load and oxygen pressure, while the thermal portion is influenced by external factors of ambient temperature, humidity and air movement, affecting skin blood flow. The operation of the model is discussed and its structural details are given.

Comparison of three-dimensional fluorescence analysis methods for predicting formation of trihalomethanes and haloacetic acids.

PubMed

Peleato, Nicolás M; Andrews, Robert C

2015-01-01

This work investigated the application of several fluorescence excitation-emission matrix analysis methods as natural organic matter (NOM) indicators for use in predicting the formation of trihalomethanes (THMs) and haloacetic acids (HAAs). Waters from four different sources (two rivers and two lakes) were subjected to jar testing followed by 24hr disinfection by-product formation tests using chlorine. NOM was quantified using three common measures: dissolved organic carbon, ultraviolet absorbance at 254 nm, and specific ultraviolet absorbance as well as by principal component analysis, peak picking, and parallel factor analysis of fluorescence spectra. Based on multi-linear modeling of THMs and HAAs, principle component (PC) scores resulted in the lowest mean squared prediction error of cross-folded test sets (THMs: 43.7 (μg/L)(2), HAAs: 233.3 (μg/L)(2)). Inclusion of principle components representative of protein-like material significantly decreased prediction error for both THMs and HAAs. Parallel factor analysis did not identify a protein-like component and resulted in prediction errors similar to traditional NOM surrogates as well as fluorescence peak picking. These results support the value of fluorescence excitation-emission matrix-principal component analysis as a suitable NOM indicator in predicting the formation of THMs and HAAs for the water sources studied. Copyright © 2014. Published by Elsevier B.V.

Coherent and incoherent ultrasound backscatter from cell aggregates.

PubMed

de Monchy, Romain; Destrempes, François; Saha, Ratan K; Cloutier, Guy; Franceschini, Emilie

2016-09-01

The effective medium theory (EMT) was recently developed to model the ultrasound backscatter from aggregating red blood cells [Franceschini, Metzger, and Cloutier, IEEE Trans. Ultrason. Ferroelectr. Freq. Control 58, 2668-2679 (2011)]. The EMT assumes that aggregates can be treated as homogeneous effective scatterers, which have effective properties determined by the aggregate compactness and the acoustical characteristics of the cells and the surrounding medium. In this study, the EMT is further developed to decompose the differential backscattering cross section of a single cell aggregate into coherent and incoherent components. The coherent component corresponds to the squared norm of the average scattering amplitude from the effective scatterer, and the incoherent component considers the variance of the scattering amplitude (i.e., the mean squared norm of the fluctuation of the scattering amplitude around its mean) within the effective scatterer. A theoretical expression for the incoherent component based on the structure factor is proposed and compared with another formulation based on the Gaussian direct correlation function. This theoretical improvement is assessed using computer simulations of ultrasound backscatter from aggregating cells. The consideration of the incoherent component based on the structure factor allows us to approximate the simulations satisfactorily for a product of the wavenumber times the aggregate radius kr ag around 2.

A Model of Objective Weighting for EIA.

ERIC Educational Resources Information Center

Ying, Long Gen; Liu, You Ci

1995-01-01

In the research of environmental impact assessment (EIA), the problem of weight distribution for a set of parameters has not yet been properly solved. Presents an approach of objective weighting by using a procedure of Pij principal component-factor analysis (Pij PCFA), which suits specifically those parameters measured directly by physical…

A Confirmatory Factor Analysis of Teaching Presence within Online Professional Development

ERIC Educational Resources Information Center

Miller, Melinda G.; Hahs-Vaughn, Debbie L.; Zygouris-Coe, Vicky

2014-01-01

The Community of Inquiry model provides a framework for recognizing and evaluating interpersonal behaviors in online educational settings. One of its three components, teaching presence, describes behaviors that are under the auspices of the online instructor. By examining behaviors through the theoretical lens provided by teaching presence, and…

Evaluation of Formal Training Programmes in Greek Organisations

ERIC Educational Resources Information Center

Diamantidis, Anastasios D.; Chatzoglou, Prodromos D.

2012-01-01

Purpose: The purpose of the paper is to highlight the training factors that mostly affect trainees' perception of learning and training usefulness. Design/methodology/approach: A new research model is proposed exploring the relationships between a trainer's performance, training programme components, outcomes of the learning process and training…

Outdoor Leader Career Development: Exploration of a Career Path

ERIC Educational Resources Information Center

Wagstaff, Mark

2016-01-01

The purpose of this study was to assess the efficacy of the proposed Outdoor Leader Career Development Model (OLCDM) through the development of the Outdoor Leader Career Development Inventory (OLCDI). I assessed the reliability and validity of the OLCDI through exploratory factor analysis, principal component analysis, and varimax rotation, based…

Making the Monday Connection: Teaching Business Ethics in the Congregation.

ERIC Educational Resources Information Center

Van Buren, Harry J., III

1998-01-01

Discusses three factors that have contributed to the decline of eccelsiastical influences on the ethical decisions of Christians in the workplace. Considers the components of a business-ethics curriculum. Outlines one model for both teaching theological/philosophical bases for moral action and providing support groups for business people…

Factors associated with feed intake of Angus steers

USDA-ARS?s Scientific Manuscript database

Estimates of variance components were obtained from 475 records of average (AFI) and residual feed intake (RFI). Covariates in various (8) models included average daily gain (G), age (A) and weight (W) on test, and slaughter (S) and ultrasound (U) carcass measures (fat thickness, ribeye area and ma...

Modeling Hospital Discharge and Placement Decision Making: Whither the Elderly.

ERIC Educational Resources Information Center

Clark, William F.; Pelham, Anabel O.

This paper examines the hospital discharge decision making process for elderly patients, based on observations of the operations of a long term care agency, the California Multipurpose Senior Services Project. The analysis is divided into four components: actors, factors, processes, and strategy critique. The first section discusses the major…

Identifying data gaps and prioritizing restoration strategies for Fremont cottonwood using linked geomorphic and population models

NASA Astrophysics Data System (ADS)

Harper, E. B.; Stella, J. C.; Fremier, A. K.

2009-12-01

Fremont cottonwood (Populus fremontii) is an important component of semi-arid riparian ecosystems throughout western North America, but its populations are in decline due to flow regulation. Achieving a balance between human resource needs and riparian ecosystem function requires a mechanistic understanding of the multiple geomorphic and biological factors affecting tree recruitment and survival, including the timing and magnitude of river flows, and the concomitant influence on suitable habitat creation and mortality from scour and sedimentation burial. Despite a great deal of empirical research on some components of the system, such as factors affecting cottonwood recruitment, other key components are less studied. Yet understanding the relative influence of the full suite of physical and life-history drivers is critical to modeling whole-population dynamics under changing environmental conditions. We addressed these issues for the Fremont cottonwood population along the Sacramento River, CA using a sensitivity analysis approach to quantify uncertainty in parameters on the outcomes of a patch-based, dynamic population model. Using a broad range of plausible values for 15 model parameters that represent key physical, biological and climatic components of the ecosystem, we ran 1,000 population simulations that consisted of a subset of 14.3 million possible combinations of parameter estimates to predict the frequency of patch colonization and total forest habitat predicted to occur under current hydrologic conditions after 175 years. Results indicate that Fremont cottonwood populations are highly sensitive to the interactions among flow regime, sedimentation rate and the depth of the capillary fringe (Fig. 1). Estimates of long-term floodplain sedimentation rate would substantially improve model accuracy. Spatial variation in sediment texture was also important to the extent that it determines the depth of the capillary fringe, which regulates the availability of water for germination and adult tree growth. Our sensitivity analyses suggest that models of future scenarios should incorporate regional climate change projections because changes in temperature and the timing and volume of precipitation affects sensitive aspects of the system, including the timing of seed release and spring snowmelt runoff. Figure 1. The relative effects on model predictions of uncertainty around each parameter included in the patch-based population model for Fremont cottonwood.

7 CFR 1000.50 - Class prices, component prices, and advanced pricing factors.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing... advanced pricing factors. Class prices per hundredweight of milk containing 3.5 percent butterfat, component prices, and advanced pricing factors shall be as follows. The prices and pricing factors described...