WorldWideScience

Sample records for factor modelling study

  1. Factoring vs linear modeling in rate estimation: a simulation study of relative accuracy.

    Science.gov (United States)

    Maldonado, G; Greenland, S

    1998-07-01

    A common strategy for modeling dose-response in epidemiology is to transform ordered exposures and covariates into sets of dichotomous indicator variables (that is, to factor the variables). Factoring tends to increase estimation variance, but it also tends to decrease bias and thus may increase or decrease total accuracy. We conducted a simulation study to examine the impact of factoring on the accuracy of rate estimation. Factored and unfactored Poisson regression models were fit to follow-up study datasets that were randomly generated from 37,500 population model forms that ranged from subadditive to supramultiplicative. In the situations we examined, factoring sometimes substantially improved accuracy relative to fitting the corresponding unfactored model, sometimes substantially decreased accuracy, and sometimes made little difference. The difference in accuracy between factored and unfactored models depended in a complicated fashion on the difference between the true and fitted model forms, the strength of exposure and covariate effects in the population, and the study size. It may be difficult in practice to predict when factoring is increasing or decreasing accuracy. We recommend, therefore, that the strategy of factoring variables be supplemented with other strategies for modeling dose-response.

  2. Study on visibility evaluation model which is considered field factors; Field factor wo koryoshita shininsei hyoka model ni kansuru kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    Nakanishi, M; Hagiwara, T [Hokkaido University, Sapporo (Japan)

    1997-10-01

    The present study proposes a model to evaluate visual performance of road traffic facilities required for drivers. Two factors were employed to obtain the suitable contrast for drivers under driving situation. One factor is a suitable luminance range, which is derived from minimum required luminance and glare luminance. Another is a field. The model showed capability of providing visibility range in some cases. 8 refs., 4 figs., 2 tabs.

  3. Applying total interpretive structural modeling to study factors affecting construction labour productivity

    Directory of Open Access Journals (Sweden)

    Sayali Shrikrishna Sandbhor

    2014-03-01

    Full Text Available Construction sector has always been dependent on manpower. Most of the activities carried out on any construction site are labour intensive. Since productivity of any project depends directly on productivity of labour, it is a prime responsibility of the employer to enhance labour productivity. Measures to improve the same depend on analysis of positive and negative factors affecting productivity. Major attention should be given to factors that decrease the productivity of labour. Factor analysis thus is an integral part of any study aiming to improve productivity.  Interpretive structural modeling is a methodology for identifying and summarizing relationships among factors which define an issue or problem. It provides a means to arrange the factors in an order as per their complexity. This study attempts to use the latest version of interpretive structural modeling i.e. total interpretive structural modeling to analyze factors negatively affecting construction labour productivity. It establishes interpretive relationship among these factors facilitating improvement in the overall productivity of construction site.

  4. A Comparative Study of CAPM and Seven Factors Risk Adjusted Return Model

    Directory of Open Access Journals (Sweden)

    Madiha Riaz Bhatti

    2014-12-01

    Full Text Available This study is a comparison and contrast of the predictive powers of two asset pricing models: CAPM and seven factor risk-return adjusted model, to explain the cross section of stock rate of returns in the financial sector listed at Karachi Stock Exchange (KSE. To test the models daily returns from January 2013 to February 2014 have been taken and the excess returns of portfolios are regressed on explanatory variables. The results of the tested models indicate that the models are valid and applicable in the financial market of Pakistan during the period under study, as the intercepts are not significantly different from zero. It is consequently established from the findings that all the explanatory variables explain the stock returns in the financial sector of KSE. In addition, the results of this study show that addition of more explanatory variables to the single factor CAPM results in reasonably high values of R2. These results provide substantial support to fund managers, investors and financial analysts in making investment decisions.

  5. An innovation resistance factor model

    Directory of Open Access Journals (Sweden)

    Siti Salwa Mohd Ishak

    2016-09-01

    Full Text Available The process and implementation strategy of information technology in construction is generally considered through the limiting prism of theoretical contexts generated from innovation diffusion and acceptance. This research argues that more attention should be given to understanding the positive effects of resistance. The study develops a theoretical framing for the Integrated Resistance Factor Model (IRFM. The framing uses a combination of diffusion of innovation theory, technology acceptance model and social network perspective. The model is tested to identify the most significant resistance factors using Partial Least Square (PLS technique. All constructs proposed in the model are found to be significant, valid and consistent with the theoretical framework. IRFM is shown to be an effective and appropriate model of user resistance factors. The most critical factors to influence technology resistance in the online project information management system (OPIMS context are: support from leaders and peers, complexity of the technology, compatibility with key work practices; and pre-trial of the technology before it is actually deployed. The study provides a new model for further research in technology innovation specific to the construction industry.

  6. A Study on Influencing Factors of Knowledge Management Systems Adoption: Models Comparison Approach

    OpenAIRE

    Mei-Chun Yeh; Ming-Shu Yuan

    2007-01-01

    Using Linear Structural Relation model (LISREL model) as analysis method and technology acceptance model and decomposed theory of planned behavior as research foundation, this study approachesmainly from the angle of behavioral intention to examine the influential factors of 421 employees adopting knowledge management systems and in the meantime to compare the two method models mentioned on the top. According to the research, there is no, in comparison with technology acceptance model anddeco...

  7. New JLS-Factor Model versus the Standard JLS Model: A Case Study on Chinese Stock Bubbles

    Directory of Open Access Journals (Sweden)

    Zongyi Hu

    2017-01-01

    Full Text Available In this paper, we extend the Johansen-Ledoit-Sornette (JLS model by introducing fundamental economic factors in China (including the interest rate and deposit reserve rate and the historical volatilities of targeted and US equity indices into the original model, which is a flexible tool to detect bubbles and predict regime changes in financial markets. We then derive a general method to incorporate these selected factors in addition to the log-periodic power law signature of herding and compare the prediction accuracy of the critical time between the original and the new JLS models (termed the JLS-factor model by applying these two models to fit two well-known Chinese stock indices in three bubble periods. The results show that the JLS-factor model with Chinese characteristics successfully depicts the evolutions of bubbles and “antibubbles” and constructs efficient end-of-bubble signals for all bubbles in Chinese stock markets. In addition, the results of standard statistical tests demonstrate the excellent explanatory power of these additive factors and confirm that the new JLS model provides useful improvements over the standard JLS model.

  8. The Five-Factor Model: General Overview

    Directory of Open Access Journals (Sweden)

    A A Vorobyeva

    2011-12-01

    Full Text Available The article describes the five-factor model (FFM, giving an overview of its history, basic dimensions, cross-cultural research conducted on the model and highlights some practical studies based on the FFM, including the studies on job performance, leader performance and daily social interactions. An overview of the recent five-factor theory is also provided. According to the theory, the five factors are encoded in human genes, therefore it is almost impossible to change the basic factors themselves, but a person's behavior might be changed due to characteristic adaptations which do not alter personality dimensions, only a person's behavior.

  9. Food hygiene practices and its associated factors among model and non model households in Abobo district, southwestern Ethiopia: Comparative cross-sectional study.

    Science.gov (United States)

    Okugn, Akoma; Woldeyohannes, Demelash

    2018-01-01

    In developing country most of human infectious diseases are caused by eating contaminated food. Estimated nine out ten of the diarrheal disease is attributable to the environment and associated with risk factors of poor food hygiene practice. Understanding the risk of eating unsafe food is the major concern to prevent and control food borne diseases. The main goal of this study was to assessing food hygiene practices and its associated factors among model and non model households at Abobo district. This study was conducted from 18 October 2013 to 13 June 2014. A community-based comparative cross-sectional study design was used. Pretested structured questionnaire was used to collect data. A total of 1247 households (417 model and 830 non model households) were included in the study from Abobo district. Bivariate and multivariate logistic regression analysis was used to identify factors associated with outcome variable. The study revealed that good food hygiene practice was 51%, of which 79% were model and 36.70% were non model households. Type of household [AOR: 2.07, 95% CI: (1.32-3.39)], sex of household head [AOR: 1.63, 95% CI: (1.06-2.48)], Availability of liquid wastes disposal pit [AOR: 2.23, 95% CI: (1.39,3.63)], Knowledge of liquid waste to cause diseases [AOR: 1.95, 95% (1.23,3.08)], and availability of functional hand washing facility [AOR: 3.61, 95% CI: (1.86-7.02)] were the factors associated with food handling practices. This study revealed that good food handling practice is low among model and non model households. While type of household (model versus non model households), sex, knowledge of solid waste to cause diseases, availability of functional hand washing facility, and availability of liquid wastes disposal pit were the factors associated with outcome variable. Health extension workers should play a great role in educating households regarding food hygiene practices to improve their knowledge and practices of the food hygiene.

  10. Studying Term Structure of SHIBOR with the Two-Factor Vasicek Model

    Directory of Open Access Journals (Sweden)

    Chaoqun Ma

    2014-01-01

    Full Text Available With the development of the Chinese interest rate market, SHIBOR is playing an increasingly important role. Based on principal component analysing SHIBOR, a two-factor Vasicek model is established to portray the change in SHIBOR with different terms. And parameters are estimated by using the Kalman filter. The model is also used to fit and forecast SHIBOR with different terms. The results show that two-factor Vasicek model fits SHIBOR well, especially for SHIBOR in terms of three months or more.

  11. Assessment of slip factor models at off-design condition

    International Nuclear Information System (INIS)

    Yoon, Sung Ho; Baek, Je Hyun

    2000-01-01

    Slip factor is defined as an empirical factor being multiplied to theoretical energy transfer for the estimation of real work input of a centrifugal compressor. Researchers have tried to develop a simple empirical model, for a century, to predict a slip factor. However most these models were developed on the condition of design point assuming inviscid flow. So these models often fail to predict a correct slip factor at off-design condition. In this study, we summarized various slip factor models and compared these models with experimental and numerical data at off-design condition. As a result of this study, Wiesner's and Paeng and Chung's models are applicable for radial impeller, but all the models are not suitable for backswept impeller. Finally, the essential avenues for future study is discussed

  12. Linear factor copula models and their properties

    KAUST Repository

    Krupskii, Pavel; Genton, Marc G.

    2018-01-01

    We consider a special case of factor copula models with additive common factors and independent components. These models are flexible and parsimonious with O(d) parameters where d is the dimension. The linear structure allows one to obtain closed form expressions for some copulas and their extreme‐value limits. These copulas can be used to model data with strong tail dependencies, such as extreme data. We study the dependence properties of these linear factor copula models and derive the corresponding limiting extreme‐value copulas with a factor structure. We show how parameter estimates can be obtained for these copulas and apply one of these copulas to analyse a financial data set.

  13. Linear factor copula models and their properties

    KAUST Repository

    Krupskii, Pavel

    2018-04-25

    We consider a special case of factor copula models with additive common factors and independent components. These models are flexible and parsimonious with O(d) parameters where d is the dimension. The linear structure allows one to obtain closed form expressions for some copulas and their extreme‐value limits. These copulas can be used to model data with strong tail dependencies, such as extreme data. We study the dependence properties of these linear factor copula models and derive the corresponding limiting extreme‐value copulas with a factor structure. We show how parameter estimates can be obtained for these copulas and apply one of these copulas to analyse a financial data set.

  14. Dimensional Model for Estimating Factors influencing Childhood Obesity: Path Analysis Based Modeling

    Directory of Open Access Journals (Sweden)

    Maryam Kheirollahpour

    2014-01-01

    Full Text Available The main objective of this study is to identify and develop a comprehensive model which estimates and evaluates the overall relations among the factors that lead to weight gain in children by using structural equation modeling. The proposed models in this study explore the connection among the socioeconomic status of the family, parental feeding practice, and physical activity. Six structural models were tested to identify the direct and indirect relationship between the socioeconomic status and parental feeding practice general level of physical activity, and weight status of children. Finally, a comprehensive model was devised to show how these factors relate to each other as well as to the body mass index (BMI of the children simultaneously. Concerning the methodology of the current study, confirmatory factor analysis (CFA was applied to reveal the hidden (secondary effect of socioeconomic factors on feeding practice and ultimately on the weight status of the children and also to determine the degree of model fit. The comprehensive structural model tested in this study suggested that there are significant direct and indirect relationships among variables of interest. Moreover, the results suggest that parental feeding practice and physical activity are mediators in the structural model.

  15. The Dual-Factor Model of Mental Health: Further Study of the Determinants of Group Differences

    Science.gov (United States)

    Lyons, Michael D.; Huebner, E. Scott; Hills, Kimberly J.; Shinkareva, Svetlana V.

    2012-01-01

    Consistent with a positive psychology framework, this study examined the contributions of personality, environmental, and perceived social support variables in classifying adolescents using Greenspoon and Saklofske's Dual-Factor model of mental health. This model incorporates information about positive subjective well-being (SWB), along with…

  16. Factors contributing to academic achievement: a Bayesian structure equation modelling study

    Science.gov (United States)

    Payandeh Najafabadi, Amir T.; Omidi Najafabadi, Maryam; Farid-Rohani, Mohammad Reza

    2013-06-01

    In Iran, high school graduates enter university after taking a very difficult entrance exam called the Konkoor. Therefore, only the top-performing students are admitted by universities to continue their bachelor's education in statistics. Surprisingly, statistically, most of such students fall into the following categories: (1) do not succeed in their education despite their excellent performance on the Konkoor and in high school; (2) graduate with a grade point average (GPA) that is considerably lower than their high school GPA; (3) continue their master's education in majors other than statistics and (4) try to find jobs unrelated to statistics. This article employs the well-known and powerful statistical technique, the Bayesian structural equation modelling (SEM), to study the academic success of recent graduates who have studied statistics at Shahid Beheshti University in Iran. This research: (i) considered academic success as a latent variable, which was measured by GPA and other academic success (see below) of students in the target population; (ii) employed the Bayesian SEM, which works properly for small sample sizes and ordinal variables; (iii), which is taken from the literature, developed five main factors that affected academic success and (iv) considered several standard psychological tests and measured characteristics such as 'self-esteem' and 'anxiety'. We then study the impact of such factors on the academic success of the target population. Six factors that positively impact student academic success were identified in the following order of relative impact (from greatest to least): 'Teaching-Evaluation', 'Learner', 'Environment', 'Family', 'Curriculum' and 'Teaching Knowledge'. Particularly, influential variables within each factor have also been noted.

  17. PENGUJIAN FAMA-FRENCH THREE-FACTOR MODEL DI INDONESIA

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    Damar Hardianto

    2017-03-01

    Full Text Available This study empirically examined the Fama-French three factor model of stock returnsfor Indonesia over the period 2000-2004. We found evidence for pervasive market, size, andbook-to-market factors in Indonesian stock returns. We found that cross-sectional mean returnswere explained by exposures to these three factors, and not by the market factor alone. Theempirical results were reasonably consistent with the Fama-French three factor model.

  18. Moderating Factors of Video-Modeling with Other as Model: A Meta-Analysis of Single-Case Studies

    Science.gov (United States)

    Mason, Rose A.; Ganz, Jennifer B.; Parker, Richard I.; Burke, Mack D.; Camargo, Siglia P.

    2012-01-01

    Video modeling with other as model (VMO) is a more practical method for implementing video-based modeling techniques, such as video self-modeling, which requires significantly more editing. Despite this, identification of contextual factors such as participant characteristics and targeted outcomes that moderate the effectiveness of VMO has not…

  19. Comparison of Transcription Factor Binding Site Models

    KAUST Repository

    Bhuyan, Sharifulislam

    2012-05-01

    Modeling of transcription factor binding sites (TFBSs) and TFBS prediction on genomic sequences are important steps to elucidate transcription regulatory mechanism. Dependency of transcription regulation on a great number of factors such as chemical specificity, molecular structure, genomic and epigenetic characteristics, long distance interaction, makes this a challenging problem. Different experimental procedures generate evidence that DNA-binding domains of transcription factors show considerable DNA sequence specificity. Probabilistic modeling of TFBSs has been moderately successful in identifying patterns from a family of sequences. In this study, we compare performances of different probabilistic models and try to estimate their efficacy over experimental TFBSs data. We build a pipeline to calculate sensitivity and specificity from aligned TFBS sequences for several probabilistic models, such as Markov chains, hidden Markov models, Bayesian networks. Our work, containing relevant statistics and evaluation for the models, can help researchers to choose the most appropriate model for the problem at hand.

  20. Modeling of Individual and Organizational Factors Affecting Traumatic Occupational Injuries Based on the Structural Equation Modeling: A Case Study in Large Construction Industries.

    Science.gov (United States)

    Mohammadfam, Iraj; Soltanzadeh, Ahmad; Moghimbeigi, Abbas; Akbarzadeh, Mehdi

    2016-09-01

    Individual and organizational factors are the factors influencing traumatic occupational injuries. The aim of the present study was the short path analysis of the severity of occupational injuries based on individual and organizational factors. The present cross-sectional analytical study was implemented on traumatic occupational injuries within a ten-year timeframe in 13 large Iranian construction industries. Modeling and data analysis were done using the structural equation modeling (SEM) approach and the IBM SPSS AMOS statistical software version 22.0, respectively. The mean age and working experience of the injured workers were 28.03 ± 5.33 and 4.53 ± 3.82 years, respectively. The portions of construction and installation activities of traumatic occupational injuries were 64.4% and 18.1%, respectively. The SEM findings showed that the individual, organizational and accident type factors significantly were considered as effective factors on occupational injuries' severity (P accidents' severity in large construction industries.

  1. Skewed factor models using selection mechanisms

    KAUST Repository

    Kim, Hyoung-Moon

    2015-12-21

    Traditional factor models explicitly or implicitly assume that the factors follow a multivariate normal distribution; that is, only moments up to order two are involved. However, it may happen in real data problems that the first two moments cannot explain the factors. Based on this motivation, here we devise three new skewed factor models, the skew-normal, the skew-tt, and the generalized skew-normal factor models depending on a selection mechanism on the factors. The ECME algorithms are adopted to estimate related parameters for statistical inference. Monte Carlo simulations validate our new models and we demonstrate the need for skewed factor models using the classic open/closed book exam scores dataset.

  2. Skewed factor models using selection mechanisms

    KAUST Repository

    Kim, Hyoung-Moon; Maadooliat, Mehdi; Arellano-Valle, Reinaldo B.; Genton, Marc G.

    2015-01-01

    Traditional factor models explicitly or implicitly assume that the factors follow a multivariate normal distribution; that is, only moments up to order two are involved. However, it may happen in real data problems that the first two moments cannot explain the factors. Based on this motivation, here we devise three new skewed factor models, the skew-normal, the skew-tt, and the generalized skew-normal factor models depending on a selection mechanism on the factors. The ECME algorithms are adopted to estimate related parameters for statistical inference. Monte Carlo simulations validate our new models and we demonstrate the need for skewed factor models using the classic open/closed book exam scores dataset.

  3. Interpersonal success factors for strategy implementation: a case study using group model building

    OpenAIRE

    Rodney J Scott; Robert Y Cavana; Donald Cameron

    2015-01-01

    Strategy implementation has been identified as an area of system dynamics literature requiring greater attention. Most strategies fail to be implemented successfully, and processes for effectively implementing strategy are yet to be fully explained and explored. The reported interpersonal success factors for strategy implementation are reported outcomes for group model building, suggesting potential applicability. A case study using validated survey methods yielded promising results, and sugg...

  4. Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel

    2016-12-19

    We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.

  5. Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel; Huser, Raphaë l; Genton, Marc G.

    2016-01-01

    We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.

  6. Modeling Ability Differentiation in the Second-Order Factor Model

    Science.gov (United States)

    Molenaar, Dylan; Dolan, Conor V.; van der Maas, Han L. J.

    2011-01-01

    In this article we present factor models to test for ability differentiation. Ability differentiation predicts that the size of IQ subtest correlations decreases as a function of the general intelligence factor. In the Schmid-Leiman decomposition of the second-order factor model, we model differentiation by introducing heteroscedastic residuals,…

  7. Bayes Factor Covariance Testing in Item Response Models.

    Science.gov (United States)

    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.

  8. Modeling the influence of local environmental factors on malaria transmission in Benin and its implications for cohort study.

    Science.gov (United States)

    Cottrell, Gilles; Kouwaye, Bienvenue; Pierrat, Charlotte; le Port, Agnès; Bouraïma, Aziz; Fonton, Noël; Hounkonnou, Mahouton Norbert; Massougbodji, Achille; Corbel, Vincent; Garcia, André

    2012-01-01

    Malaria remains endemic in tropical areas, especially in Africa. For the evaluation of new tools and to further our understanding of host-parasite interactions, knowing the environmental risk of transmission--even at a very local scale--is essential. The aim of this study was to assess how malaria transmission is influenced and can be predicted by local climatic and environmental factors.As the entomological part of a cohort study of 650 newborn babies in nine villages in the Tori Bossito district of Southern Benin between June 2007 and February 2010, human landing catches were performed to assess the density of malaria vectors and transmission intensity. Climatic factors as well as household characteristics were recorded throughout the study. Statistical correlations between Anopheles density and environmental and climatic factors were tested using a three-level Poisson mixed regression model. The results showed both temporal variations in vector density (related to season and rainfall), and spatial variations at the level of both village and house. These spatial variations could be largely explained by factors associated with the house's immediate surroundings, namely soil type, vegetation index and the proximity of a watercourse. Based on these results, a predictive regression model was developed using a leave-one-out method, to predict the spatiotemporal variability of malaria transmission in the nine villages.This study points up the importance of local environmental factors in malaria transmission and describes a model to predict the transmission risk of individual children, based on environmental and behavioral characteristics.

  9. Model of key success factors for Business Intelligence implementation

    Directory of Open Access Journals (Sweden)

    Peter Mesaros

    2016-07-01

    Full Text Available New progressive technologies recorded growth in every area. Information-communication technologies facilitate the exchange of information and it facilitates management of everyday activities in enterprises. Specific modules (such as Business Intelligence facilitate decision-making. Several studies have demonstrated the positive impact of Business Intelligence to decision-making. The first step is to put in place the enterprise. The implementation process is influenced by many factors. This article discusses the issue of key success factors affecting to successful implementation of Business Intelligence. The article describes the key success factors for successful implementation and use of Business Intelligence based on multiple studies. The main objective of this study is to verify the effects and dependence of selected factors and proposes a model of key success factors for successful implementation of Business Intelligence. Key success factors and the proposed model are studied in Slovak enterprises.

  10. Identifying the important factors in simulation models with many factors

    NARCIS (Netherlands)

    Bettonvil, B.; Kleijnen, J.P.C.

    1994-01-01

    Simulation models may have many parameters and input variables (together called factors), while only a few factors are really important (parsimony principle). For such models this paper presents an effective and efficient screening technique to identify and estimate those important factors. The

  11. Sensitivity Analysis of b-factor in Microwave Emission Model for Soil Moisture Retrieval: A Case Study for SMAP Mission

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    Dugwon Seo

    2010-05-01

    Full Text Available Sensitivity analysis is critically needed to better understand the microwave emission model for soil moisture retrieval using passive microwave remote sensing data. The vegetation b-factor along with vegetation water content and surface characteristics has significant impact in model prediction. This study evaluates the sensitivity of the b-factor, which is function of vegetation type. The analysis is carried out using Passive and Active L and S-band airborne sensor (PALS and measured field soil moisture from Southern Great Plains experiment (SGP99. The results show that the relative sensitivity of the b-factor is 86% in wet soil condition and 88% in high vegetated condition compared to the sensitivity of the soil moisture. Apparently, the b-factor is found to be more sensitive than the vegetation water content, surface roughness and surface temperature; therefore, the effect of the b-factor is fairly large to the microwave emission in certain conditions. Understanding the dependence of the b-factor on the soil and vegetation is important in studying the soil moisture retrieval algorithm, which can lead to potential improvements in model development for the Soil Moisture Active-Passive (SMAP mission.

  12. A Dynamic Multi-Level Factor Model with Long-Range Dependence

    DEFF Research Database (Denmark)

    Ergemen, Yunus Emre; Rodríguez-Caballero, Carlos Vladimir

    A dynamic multi-level factor model with stationary or nonstationary global and regional factors is proposed. In the model, persistence in global and regional common factors as well as innovations allows for the study of fractional cointegrating relationships. Estimation of global and regional...

  13. Hierarchical and coupling model of factors influencing vessel traffic flow.

    Science.gov (United States)

    Liu, Zhao; Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

    2017-01-01

    Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

  14. Analysis of significance of environmental factors in landslide susceptibility modeling: Case study Jemma drainage network, Ethiopia

    Directory of Open Access Journals (Sweden)

    Vít Maca

    2017-06-01

    Full Text Available Aim of the paper is to describe methodology for calculating significance of environmental factors in landslide susceptibility modeling and present result of selected one. As a study area part of a Jemma basin in Ethiopian Highland is used. This locality is highly affected by mass movement processes. In the first part all major factors and their influence are described briefly. Majority of the work focuses on research of other methodologies used in susceptibility models and design of own methodology. This method is unlike most of the methods used completely objective, therefore it is not possible to intervene in the results. In article all inputs and outputs of the method are described as well as all stages of calculations. Results are illustrated on specific examples. In study area most important factor for landslide susceptibility is slope, on the other hand least important is land cover. At the end of article landslide susceptibility map is created. Part of the article is discussion of results and possible improvements of the methodology.

  15. Study of depression influencing factors with zero-inflated regression models in a large-scale population survey

    OpenAIRE

    Xu, Tao; Zhu, Guangjin; Han, Shaomei

    2017-01-01

    Objectives The number of depression symptoms can be considered as count data in order to get complete and accurate analyses findings in studies of depression. This study aims to compare the goodness of fit of four count outcomes models by a large survey sample to identify the optimum model for a risk factor study of the number of depression symptoms. Methods 15 820 subjects, aged 10 to 80 years old, who were not suffering from serious chronic diseases and had not run a high fever in the past ...

  16. Online revenue models in the media sector: an exploratory study on their success factors and adoption

    OpenAIRE

    Stienstra, Martin R.; Ruel, Hubertus Johannes Maria; Boerrigter, Thomas

    2010-01-01

    Especially for companies in the media sector such as publishers, the Internet has created new strategic and commercial opportunities. However, many companies in the media sector are struggling with how to adapt their business and revenue model for doing profitable business online. This exploratory study goes into the success factors and the level of adoption of online revenue models by media sector companies. We use Chaffey (2002) in determining online revenue models in which we included Oste...

  17. Modeling the influence of local environmental factors on malaria transmission in Benin and its implications for cohort study.

    Directory of Open Access Journals (Sweden)

    Gilles Cottrell

    Full Text Available Malaria remains endemic in tropical areas, especially in Africa. For the evaluation of new tools and to further our understanding of host-parasite interactions, knowing the environmental risk of transmission--even at a very local scale--is essential. The aim of this study was to assess how malaria transmission is influenced and can be predicted by local climatic and environmental factors.As the entomological part of a cohort study of 650 newborn babies in nine villages in the Tori Bossito district of Southern Benin between June 2007 and February 2010, human landing catches were performed to assess the density of malaria vectors and transmission intensity. Climatic factors as well as household characteristics were recorded throughout the study. Statistical correlations between Anopheles density and environmental and climatic factors were tested using a three-level Poisson mixed regression model. The results showed both temporal variations in vector density (related to season and rainfall, and spatial variations at the level of both village and house. These spatial variations could be largely explained by factors associated with the house's immediate surroundings, namely soil type, vegetation index and the proximity of a watercourse. Based on these results, a predictive regression model was developed using a leave-one-out method, to predict the spatiotemporal variability of malaria transmission in the nine villages.This study points up the importance of local environmental factors in malaria transmission and describes a model to predict the transmission risk of individual children, based on environmental and behavioral characteristics.

  18. Scale factor management in the studies of affine models of shockproof garment elements

    Directory of Open Access Journals (Sweden)

    Denisov Oleg

    2018-01-01

    Full Text Available New samples of protective garment for performing construction work at height require numerous tests in conditions close to real conditions of extreme vital activity. The article presents some results of shockproof garment element studies and a description of a patented prototype. The tests were carried out on a model which geometric dimensions were convenient for manufacturing it in a limited batch. In addition, the used laboratory equipment (for example, a unique power pendulum, blanks made of a titanium-nickel alloy with a shape memory effect also imposed their limitations. The problem of the adequacy of the obtained experimental results transfer to mass-produced products was solved using tools of the classical similarity theory. Scale factor management influence in the affine modeling of the shockproof element, studied on the basis of the equiatomic titanium-nickel alloy with the shape memory effect, allowed us to assume, with a sufficient degree of reliability, the technical possibility of extrapolating the results of experimental studies to full-scale objects for the formation of the initial data of the mathematical model of shockproof garment dynamics elastoplastic deformation (while observing the similarity of the features of external loading.

  19. Scale factor management in the studies of affine models of shockproof garment elements

    Science.gov (United States)

    Denisov, Oleg; Pleshko, Mikhail; Ponomareva, Irina; Merenyashev, Vitaliy

    2018-03-01

    New samples of protective garment for performing construction work at height require numerous tests in conditions close to real conditions of extreme vital activity. The article presents some results of shockproof garment element studies and a description of a patented prototype. The tests were carried out on a model which geometric dimensions were convenient for manufacturing it in a limited batch. In addition, the used laboratory equipment (for example, a unique power pendulum), blanks made of a titanium-nickel alloy with a shape memory effect also imposed their limitations. The problem of the adequacy of the obtained experimental results transfer to mass-produced products was solved using tools of the classical similarity theory. Scale factor management influence in the affine modeling of the shockproof element, studied on the basis of the equiatomic titanium-nickel alloy with the shape memory effect, allowed us to assume, with a sufficient degree of reliability, the technical possibility of extrapolating the results of experimental studies to full-scale objects for the formation of the initial data of the mathematical model of shockproof garment dynamics elastoplastic deformation (while observing the similarity of the features of external loading).

  20. Dynamic Factor Models for the Volatility Surface

    DEFF Research Database (Denmark)

    van der Wel, Michel; Ozturk, Sait R.; Dijk, Dick van

    The implied volatility surface is the collection of volatilities implied by option contracts for different strike prices and time-to-maturity. We study factor models to capture the dynamics of this three-dimensional implied volatility surface. Three model types are considered to examine desirable...

  1. Factors accounting for youth suicide attempt in Hong Kong: a model building.

    Science.gov (United States)

    Wan, Gloria W Y; Leung, Patrick W L

    2010-10-01

    This study aimed at proposing and testing a conceptual model of youth suicide attempt. We proposed a model that began with family factors such as a history of physical abuse and parental divorce/separation. Family relationship, presence of psychopathology, life stressors, and suicide ideation were postulated as mediators, leading to youth suicide attempt. The stepwise entry of the risk factors to a logistic regression model defined their proximity as related to suicide attempt. Path analysis further refined our proposed model of youth suicide attempt. Our originally proposed model was largely confirmed. The main revision was dropping parental divorce/separation as a risk factor in the model due to lack of significant contribution when examined alongside with other risk factors. This model was cross-validated by gender. This study moved research on youth suicide from identification of individual risk factors to model building, integrating separate findings of the past studies.

  2. Modeling the Factors Associated with Children's Mental Health Difficulties in Primary School: A Multilevel Study

    Science.gov (United States)

    Humphrey, Neil; Wigelsworth, Michael

    2012-01-01

    The current study explores some of the factors associated with children's mental health difficulties in primary school. Multilevel modeling with data from 628 children from 36 schools was used to determine how much variation in mental health difficulties exists between and within schools, and to identify characteristics at the school and…

  3. Hierarchical and coupling model of factors influencing vessel traffic flow.

    Directory of Open Access Journals (Sweden)

    Zhao Liu

    Full Text Available Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

  4. Dependent defaults and losses with factor copula models

    Directory of Open Access Journals (Sweden)

    Ackerer Damien

    2017-12-01

    Full Text Available We present a class of flexible and tractable static factor models for the term structure of joint default probabilities, the factor copula models. These high-dimensional models remain parsimonious with paircopula constructions, and nest many standard models as special cases. The loss distribution of a portfolio of contingent claims can be exactly and efficiently computed when individual losses are discretely supported on a finite grid. Numerical examples study the key features affecting the loss distribution and multi-name credit derivatives prices. An empirical exercise illustrates the flexibility of our approach by fitting credit index tranche prices.

  5. Study of risk factors affecting both hypertension and obesity outcome by using multivariate multilevel logistic regression models

    Directory of Open Access Journals (Sweden)

    Sepedeh Gholizadeh

    2016-07-01

    Full Text Available Background:Obesity and hypertension are the most important non-communicable diseases thatin many studies, the prevalence and their risk factors have been performedin each geographic region univariately.Study of factors affecting both obesity and hypertension may have an important role which to be adrressed in this study. Materials &Methods:This cross-sectional study was conducted on 1000 men aged 20-70 living in Bushehr province. Blood pressure was measured three times and the average of them was considered as one of the response variables. Hypertension was defined as systolic blood pressure ≥140 (and-or diastolic blood pressure ≥90 and obesity was defined as body mass index ≥25. Data was analyzed by using multilevel, multivariate logistic regression model by MlwiNsoftware. Results:Intra class correlations in cluster level obtained 33% for high blood pressure and 37% for obesity, so two level model was fitted to data. The prevalence of obesity and hypertension obtained 43.6% (0.95%CI; 40.6-46.5, 29.4% (0.95%CI; 26.6-32.1 respectively. Age, gender, smoking, hyperlipidemia, diabetes, fruit and vegetable consumption and physical activity were the factors affecting blood pressure (p≤0.05. Age, gender, hyperlipidemia, diabetes, fruit and vegetable consumption, physical activity and place of residence are effective on obesity (p≤0.05. Conclusion: The multilevel models with considering levels distribution provide more precise estimates. As regards obesity and hypertension are the major risk factors for cardiovascular disease, by knowing the high-risk groups we can d careful planning to prevention of non-communicable diseases and promotion of society health.

  6. Confirmatory Factor Analysis of WAIS-IV in a Clinical Sample: Examining a Bi-Factor Model

    Directory of Open Access Journals (Sweden)

    Rachel Collinson

    2016-12-01

    Full Text Available There have been a number of studies that have examined the factor structure of the Wechsler Adult Intelligence Scale IV (WAIS-IV using the standardization sample. In this study, we investigate its factor structure on a clinical neuropsychology sample of mixed aetiology. Correlated factor, higher-order and bi-factor models are all tested. Overall, the results suggest that the WAIS-IV will be suitable for use with this population.

  7. An alternative method for centrifugal compressor loading factor modelling

    Science.gov (United States)

    Galerkin, Y.; Drozdov, A.; Rekstin, A.; Soldatova, K.

    2017-08-01

    The loading factor at design point is calculated by one or other empirical formula in classical design methods. Performance modelling as a whole is out of consideration. Test data of compressor stages demonstrates that loading factor versus flow coefficient at the impeller exit has a linear character independent of compressibility. Known Universal Modelling Method exploits this fact. Two points define the function - loading factor at design point and at zero flow rate. The proper formulae include empirical coefficients. A good modelling result is possible if the choice of coefficients is based on experience and close analogs. Earlier Y. Galerkin and K. Soldatova had proposed to define loading factor performance by the angle of its inclination to the ordinate axis and by the loading factor at zero flow rate. Simple and definite equations with four geometry parameters were proposed for loading factor performance calculated for inviscid flow. The authors of this publication have studied the test performance of thirteen stages of different types. The equations are proposed with universal empirical coefficients. The calculation error lies in the range of plus to minus 1,5%. The alternative model of a loading factor performance modelling is included in new versions of the Universal Modelling Method.

  8. Modeling Factors with Influence on Sustainable University Management

    Directory of Open Access Journals (Sweden)

    Oana Dumitrascu

    2015-01-01

    Full Text Available The main objective of this paper is to present the factors with influence on the sustainable university management and the relationships between them. In the scientific approach we begin from a graphical model, according to which the extracurricular activities together with internal environmental factors influence students’ involvement in such activities, the university attractiveness, their academic performance and their integration into the socially-economic and natural environment (components related with sustainable development. The model emphasizes that individual performances, related to students’ participation in extracurricular activities, have a positive influence on the sustainability of university management. The results of the study have shown that the university sustainability may be influenced by a number of factors, such as students’ performance, students’ involvement in extracurricular activities or university’s attractiveness and can in turn influence implicitly also the sustainability of university management. The originality of the paper consists in the relationships study using the modeling method in general and informatics tools of modeling in particular, as well as through graphical visualization of some influences, on the sustainability university management.

  9. Testing alternative factor models of PTSD and the robustness of the dysphoria factor.

    Science.gov (United States)

    Elklit, Ask; Armour, Cherie; Shevlin, Mark

    2010-01-01

    This study first aimed to examine the structure of self-reported posttraumatic stress disorder (PTSD) symptoms using three different samples. The second aim of the paper was to test the robustness of the factor analytic model when depression scores were controlled for. Based on previous factor analytic findings and the DSM-IV formulation, six confirmatory factor models were specified and estimated that reflected different symptom clusters. The best fitting model was subsequently re-fitted to the data after including a depression variable. The analyses were based on responses from 973 participants across three samples. Sample 1 consisted of 633 parents who were members of 'The National Association of Infant Death' and who had lost a child. Sample 2 consisted of 227 victims of rape, who completed a questionnaire within 4 weeks of the rape. Each respondent had been in contact with the Centre for Rape Victims (CRV) at the Aarhus University Hospital, Denmark. Sample 3 consisted of 113 refugees resident in Denmark. All participants had been referred to a treatment centre which focused on rehabilitating refugees through treatment for psychosocial integration problems (RRCF: Rehabliterings og Revliderings Centre for Flygtninge). In total 500 participants received a diagnosis of PTSD/sub-clinical PTSD (Sample 1, N=214; 2, N=176; 3, N=110). A correlated four-factor model with re-experiencing, avoidance, dysphoria, and arousal factors provided the best fit to the sample data. The average attenuation in the factor loadings was highest for the dysphoria factor (M=-.26, SD=.11) compared to the re-experiencing (M=-.14, SD=.18), avoidance (M=-.10, SD=.21), and arousal (M=-.09, SD=.13) factors. With regards to the best fitting factor model these results concur with previous research findings using different trauma populations but do not reflect the current DSM-IV symptom groupings. The attenuation of dysphoria factor loadings suggests that dysphoria is a non-specific component of

  10. Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

    Directory of Open Access Journals (Sweden)

    Hong Xue

    2018-01-01

    Full Text Available High capital cost is a significant hindrance to the promotion of prefabrication. In order to optimize cost management and reduce capital cost, this study aims to explore the latent factors and factor analysis evaluation model. Semi-structured interviews were conducted to explore potential variables and then questionnaire survey was employed to collect professionals’ views on their effects. After data collection, exploratory factor analysis was adopted to explore the latent factors. Seven latent factors were identified, including “Management Index”, “Construction Dissipation Index”, “Productivity Index”, “Design Efficiency Index”, “Transport Dissipation Index”, “Material increment Index” and “Depreciation amortization Index”. With these latent factors, a factor analysis evaluation model (FAEM, divided into factor analysis model (FAM and comprehensive evaluation model (CEM, was established. The FAM was used to explore the effect of observed variables on the high capital cost of prefabrication, while the CEM was used to evaluate comprehensive cost management level on prefabrication projects. Case studies were conducted to verify the models. The results revealed that collaborative management had a positive effect on capital cost of prefabrication. Material increment costs and labor costs had significant impacts on production cost. This study demonstrated the potential of on-site management and standardization design to reduce capital cost. Hence, collaborative management is necessary for cost management of prefabrication. Innovation and detailed design were needed to improve cost performance. The new form of precast component factories can be explored to reduce transportation cost. Meanwhile, targeted strategies can be adopted for different prefabrication projects. The findings optimized the capital cost and improved the cost performance through providing an evaluation and optimization model, which helps managers to

  11. Model Correction Factor Method

    DEFF Research Database (Denmark)

    Christensen, Claus; Randrup-Thomsen, Søren; Morsing Johannesen, Johannes

    1997-01-01

    The model correction factor method is proposed as an alternative to traditional polynomial based response surface techniques in structural reliability considering a computationally time consuming limit state procedure as a 'black box'. The class of polynomial functions is replaced by a limit...... of the model correction factor method, is that in simpler form not using gradient information on the original limit state function or only using this information once, a drastic reduction of the number of limit state evaluation is obtained together with good approximations on the reliability. Methods...

  12. Shell model and spectroscopic factors

    International Nuclear Information System (INIS)

    Poves, P.

    2007-01-01

    In these lectures, I introduce the notion of spectroscopic factor in the shell model context. A brief review is given of the present status of the large scale applications of the Interacting Shell Model. The spectroscopic factors and the spectroscopic strength are discussed for nuclei in the vicinity of magic closures and for deformed nuclei. (author)

  13. Study of Factors Preventing Children from Enrolment in Primary School in the Republic of Honduras: Analysis Using Structural Equation Modelling

    Science.gov (United States)

    Ashida, Akemi

    2015-01-01

    Studies have investigated factors that impede enrolment in Honduras. However, they have not analysed individual factors as a whole or identified the relationships among them. This study used longitudinal data for 1971 children who entered primary schools from 1986 to 2000, and employed structural equation modelling to examine the factors…

  14. Ressac program plants analytical experiments study of a code modelling the soil to plant transfer factor of cesium

    International Nuclear Information System (INIS)

    Jouve, A.; Troesch, O.; Legrand, B.

    1989-10-01

    The available data about the soil to plant transfer factor of cesium are numerous but very variable. The variation conditions of the transfer factor are studied with the help of laboratory experiments and the results analysed with the help of a multiple linear regression calculation. The results are applied to the soils and plants types the most frequently present around the French nuclear sites. A calculation model including the plant life conditions such as pH, water-soluble potassium and the available part of cesium in the water of the soil, is proposed. This model allows to predict the transfer factor with a better accuracy (up to ten times) than using the single ratio issue from the experimental data [fr

  15. The five-factor model in schizotypal personality disorder

    OpenAIRE

    Gurrera, Ronald J.; Dickey, Chandlee C.; Niznikiewicz, Margaret A.; Voglmaier, Martina M.; Shenton, Martha E.; McCarley, Robert W.

    2005-01-01

    Studies of the five-factor model of personality in schizotypal personality disorder (SPD) have produced inconsistent results, particularly with respect to openness. In the present study, the NEO-FFI was used to measure five-factor personality dimensions in 28 community volunteers with SPD and 24 psychiatrically healthy individuals. Standard multivariate statistical analyses were used to evaluate personality differences as a function of diagnosis and gender. Individuals with SPD had significan...

  16. Model of a ternary complex between activated factor VII, tissue factor and factor IX.

    Science.gov (United States)

    Chen, Shu-wen W; Pellequer, Jean-Luc; Schved, Jean-François; Giansily-Blaizot, Muriel

    2002-07-01

    Upon binding to tissue factor, FVIIa triggers coagulation by activating vitamin K-dependent zymogens, factor IX (FIX) and factor X (FX). To understand recognition mechanisms in the initiation step of the coagulation cascade, we present a three-dimensional model of the ternary complex between FVIIa:TF:FIX. This model was built using a full-space search algorithm in combination with computational graphics. With the known crystallographic complex FVIIa:TF kept fixed, the FIX docking was performed first with FIX Gla-EGF1 domains, followed by the FIX protease/EGF2 domains. Because the FIXa crystal structure lacks electron density for the Gla domain, we constructed a chimeric FIX molecule that contains the Gla-EGF1 domains of FVIIa and the EGF2-protease domains of FIXa. The FVIIa:TF:FIX complex has been extensively challenged against experimental data including site-directed mutagenesis, inhibitory peptide data, haemophilia B database mutations, inhibitor antibodies and a novel exosite binding inhibitor peptide. This FVIIa:TF:FIX complex provides a powerful tool to study the regulation of FVIIa production and presents new avenues for developing therapeutic inhibitory compounds of FVIIa:TF:substrate complex.

  17. Dynamic structure factor for liquid He4 and quantum lattice model

    International Nuclear Information System (INIS)

    Lee, M.H.

    1975-01-01

    It has been realized for some time now that the quantum lattice model (or the anisotropic Heisenberg antiferromagnetic model) is a useful model for studying the properties of quantum liquids especially near the lambda transition. The static critical values calculated from the quantum lattice model are in good agreement with the observed values. Furthermore, it was shown recently that there are collective modes in the quantum lattice model which are equivalent to the plasmons. Hence, it would seem to be interesting to study the dynamic structure factor for the quantum lattice model and to make a comparison with experiment. Work on the dynamic structure factor is reported here. (Auth.)

  18. Studying the Impacts of Environmental Factors and Agricultural Management on Methane Emissions from Rice Paddies Using a Land Surface Model

    Science.gov (United States)

    Lin, T. S.; Gahlot, S.; Shu, S.; Jain, A. K.; Kheshgi, H. S.

    2017-12-01

    Continued growth in population is projected to drive increased future demand for rice and the methane emissions associated with its production. However, observational studies of methane emissions from rice have reported seemingly conflicting results and do not all support this projection. In this study we couple an ecophysiological process-based rice paddy module and a methane emission module with a land surface model, Integrated Science Assessment Model (ISAM), to study the impacts of various environmental factors and agricultural management practices on rice production and methane emissions from rice fields. This coupled modeling framework accounts for dynamic rice growth processes with adaptation of photosynthesis, rice-specific phenology, biomass accumulation, leaf area development and structures responses to water, temperature, light and nutrient stresses. The coupled model is calibrated and validated with observations from various rice cultivation fields. We find that the differing results of observational studies can be caused by the interactions of environmental factors, including climate, atmospheric CO2 concentration, and N deposition, and agricultural management practices, such as irrigation and N fertilizer applications, with rice production at spatial and temporal scales.

  19. Toward a Two-Dimensional Model of Social Cognition in Clinical Neuropsychology: A Systematic Review of Factor Structure Studies.

    Science.gov (United States)

    Etchepare, Aurore; Prouteau, Antoinette

    2018-04-01

    Social cognition has received growing interest in many conditions in recent years. However, this construct still suffers from a considerable lack of consensus, especially regarding the dimensions to be studied and the resulting methodology of clinical assessment. Our review aims to clarify the distinctiveness of the dimensions of social cognition. Based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statements, a systematic review was conducted to explore the factor structure of social cognition in the adult general and clinical populations. The initial search provided 441 articles published between January 1982 and March 2017. Eleven studies were included, all conducted in psychiatric populations and/or healthy participants. Most studies were in favor of a two-factor solution. Four studies drew a distinction between low-level (e.g., facial emotion/prosody recognition) and high-level (e.g., theory of mind) information processing. Four others reported a distinction between affective (e.g., facial emotion/prosody recognition) and cognitive (e.g., false beliefs) information processing. Interestingly, attributional style was frequently reported as an additional separate factor of social cognition. Results of factor analyses add further support for the relevance of models differentiating level of information processing (low- vs. high-level) from nature of processed information (affective vs. cognitive). These results add to a significant body of empirical evidence from developmental, clinical research and neuroimaging studies. We argue the relevance of integrating low- versus high-level processing with affective and cognitive processing in a two-dimensional model of social cognition that would be useful for future research and clinical practice. (JINS, 2018, 24, 391-404).

  20. Adolescent Girls' Self-Concept and Its Related Factors Based on Roy Adaptation Model

    OpenAIRE

    M. Basiri Moghadam; SH. Khosravan; L. Sadeghmoghadam; N. Ebrahimi Senoo

    2017-01-01

    Aims: One of the most important factors of individual health in the adolescents is the self-concept. As a nursing model, the Roy adaptation model mainly investigates the factor. The aim of the study was to investigate the self-concept and its related factors in the adolescent girls in Gonabad Township, based on the Roy adaptation model. Instrument & Methods: In the descriptive cross-sectional study, 270 adolescent girls were studied in Gonabad Township, Iran, in 2015. The subjects were s...

  1. System Dynamics Modeling of interactive cost factors for small modular reactors

    International Nuclear Information System (INIS)

    Ahn, Nam Sung; Lee, Keun Dae; Yoon, Suk Ho

    2011-01-01

    As a part of the Study on Economic Efficiency and Marketability of small modular reactors project, we at Nemo partners NEC consulting corporation were studying the various cost factors on small modular reactors (SMRs). To have a better knowledge of the interaction between the cost factors, System Dynamics Modeling has been developed. This model will contribute to our understanding of the interaction on the major factors effecting on the unit cost of SMRs to the SMRs' market share in the market economics as competition

  2. Change management in Iranian hospitals: social factors model

    Directory of Open Access Journals (Sweden)

    B. Delgoshaei

    2012-02-01

    Full Text Available Background: Continuous change in the complex health care environments is a major challenge for administrative managers. This study aimed to design a change model to facilitate change implementation in the Iranian hospitals. Methods: This is a descriptive and comparative study. The data were collected through library search and in-depth interview with 15 hospital managers. Nine well-established change theories developed by Lewin, Action Research, Kotter, Ackerman- Anderson and Anderson, Prosci , Kilman, Beer, Continuum, and Gelicher were compared. Common denominators of the theories were identified and tabulated. Experienced hospital managers’ suggestions about social factors were acquired. The initial model was designed and validated using the Delphi Technique. Results: The majority of the selected change models emphasize the significance of social factors in change implementation such as effective communication, organizational climate and culture, and leadership. The results from the interviews indicate that low readiness to change, lack of confidence (or trust for change, and autocratic leadership style ,and poor communication could hinder the change process. Conclusion: Based on the model developed in the study, effective communication, readiness of employees, and a contingency leadership/management combined could lead to successful implementation of change in the hospital.

  3. Modeling of Alpine Grassland Cover Based on Unmanned Aerial Vehicle Technology and Multi-Factor Methods: A Case Study in the East of Tibetan Plateau, China

    Directory of Open Access Journals (Sweden)

    Baoping Meng

    2018-02-01

    Full Text Available Grassland cover and its temporal changes are key parameters in the estimation and monitoring of ecosystems and their functions, especially via remote sensing. However, the most suitable model for estimating grassland cover and the differences between models has rarely been studied in alpine meadow grasslands. In this study, field measurements of grassland cover in Gannan Prefecture, from 2014 to 2016, were acquired using unmanned aerial vehicle (UAV technology. Single-factor parametric and multi-factor parametric/non-parametric cover inversion models were then constructed based on 14 factors related to grassland cover, and the dynamic variation of the annual maximum cover was analyzed. The results show that (1 nine out of 14 factors (longitude, latitude, elevation, the concentrations of clay and sand in the surface and bottom soils, temperature, precipitation, enhanced vegetation index (EVI and normalized difference vegetation index (NDVI exert a significant effect on grassland cover in the study area. The logarithmic model based on EVI presents the best performance, with an R2 and RMSE of 0.52 and 16.96%, respectively. Single-factor grassland cover inversion models account for only 1–49% of the variation in cover during the growth season. (2 The optimum grassland cover inversion model is the artificial neural network (BP-ANN, with an R2 and RMSE of 0.72 and 13.38%, and SDs of 0.062% and 1.615%, respectively. Both the accuracy and the stability of the BP-ANN model are higher than those of the single-factor parametric models and multi-factor parametric/non-parametric models. (3 The annual maximum cover in Gannan Prefecture presents an increasing trend over 60.60% of the entire study area, while 36.54% is presently stable and 2.86% exhibits a decreasing trend.

  4. A 3-factor model for the FACIT-Sp.

    Science.gov (United States)

    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

  5. First International Workshop on Human Factors in Modeling (HuFaMo 2015)

    DEFF Research Database (Denmark)

    Störrle, Harald; Chaudron, Michel R. V.; Amaral, Vasco

    2015-01-01

    human factors in modeling. Our goal is to improve the state of the science and professionalism in empirical research in the Model Based Engineering community. Typical examples of research questions might consider the usability of a certain approach, such as a method or language, or the emotional states......Modeling is a human-intensive enterprise. As such, many research questions related to modeling can only be answered by empirical studies employing human factors. The International Workshop Series on Human Factors in Modeling (HuFaMo) is dedicated to the discussion of empirical research involving...... or personal judgements of modelers. While concerned with foundations and framework support for modeling, the community has been somehow neglecting the issue of human factors in this context. There is a growing need from the community concerned with quality factors to understand the best practices...

  6. Study of the validity of a job-exposure matrix for the job strain model factors: an update and a study of changes over time.

    Science.gov (United States)

    Niedhammer, Isabelle; Milner, Allison; LaMontagne, Anthony D; Chastang, Jean-François

    2018-03-08

    The objectives of the study were to construct a job-exposure matrix (JEM) for psychosocial work factors of the job strain model, to evaluate its validity, and to compare the results over time. The study was based on national representative data of the French working population with samples of 46,962 employees (2010 SUMER survey) and 24,486 employees (2003 SUMER survey). Psychosocial work factors included the job strain model factors (Job Content Questionnaire): psychological demands, decision latitude, social support, job strain and iso-strain. Job title was defined by three variables: occupation and economic activity coded using standard classifications, and company size. A JEM was constructed using a segmentation method (Classification and Regression Tree-CART) and cross-validation. The best quality JEM was found using occupation and company size for social support. For decision latitude and psychological demands, there was not much difference using occupation and company size with or without economic activity. The validity of the JEM estimates was higher for decision latitude, job strain and iso-strain, and lower for social support and psychological demands. Differential changes over time were observed for psychosocial work factors according to occupation, economic activity and company size. This study demonstrated that company size in addition to occupation may improve the validity of JEMs for psychosocial work factors. These matrices may be time-dependent and may need to be updated over time. More research is needed to assess the validity of JEMs given that these matrices may be able to provide exposure assessments to study a range of health outcomes.

  7. Determining factors influencing survival of breast cancer by fuzzy logistic regression model.

    Science.gov (United States)

    Nikbakht, Roya; Bahrampour, Abbas

    2017-01-01

    Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM). The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86). Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.

  8. A rough multi-factor model of electricity spot prices

    International Nuclear Information System (INIS)

    Bennedsen, Mikkel

    2017-01-01

    We introduce a new continuous-time mathematical model of electricity spot prices which accounts for the most important stylized facts of these time series: seasonality, spikes, stochastic volatility, and mean reversion. Empirical studies have found a possible fifth stylized fact, roughness, and our approach explicitly incorporates this into the model of the prices. Our setup generalizes the popular Ornstein–Uhlenbeck-based multi-factor framework of and allows us to perform statistical tests to distinguish between an Ornstein–Uhlenbeck-based model and a rough model. Further, through the multi-factor approach we account for seasonality and spikes before estimating – and making inference on – the degree of roughness. This is novel in the literature and we present simulation evidence showing that these precautions are crucial for accurate estimation. Lastly, we estimate our model on recent data from six European energy exchanges and find statistical evidence of roughness in five out of six markets. As an application of our model, we show how, in these five markets, a rough component improves short term forecasting of the prices. - Highlights: • Statistical modeling of electricity spot prices • Multi-factor decomposition • Roughness • Electricity price forecasting

  9. The effect of modifiable risk factors on geographic mortality differentials: a modelling study

    Directory of Open Access Journals (Sweden)

    Stevenson Christopher E

    2012-01-01

    Full Text Available Abstract Background Australian mortality rates are higher in regional and remote areas than in major cities. The degree to which this is driven by variation in modifiable risk factors is unknown. Methods We applied a risk prediction equation incorporating smoking, cholesterol and blood pressure to a national, population based survey to project all-causes mortality risk by geographic region. We then modelled life expectancies at different levels of mortality risk by geographic region using a risk percentiles model. Finally we set high values of each risk factor to a target level and modelled the subsequent shift in the population to lower levels of mortality risk and longer life expectancy. Results Survival is poorer in both Inner Regional and Outer Regional/Remote areas compared to Major Cities for men and women at both high and low levels of predicted mortality risk. For men smoking, high cholesterol and high systolic blood pressure were each associated with the mortality difference between Major Cities and Outer Regional/Remote areas--accounting for 21.4%, 20.3% and 7.7% of the difference respectively. For women smoking and high cholesterol accounted for 29.4% and 24.0% of the difference respectively but high blood pressure did not contribute to the observed mortality differences. The three risk factors taken together accounted for 45.4% (men and 35.6% (women of the mortality difference. The contribution of risk factors to the corresponding differences for inner regional areas was smaller, with only high cholesterol and smoking contributing to the difference in men-- accounting for 8.8% and 6.3% respectively-- and only smoking contributing to the difference in women--accounting for 12.3%. Conclusions These results suggest that health intervention programs aimed at smoking, blood pressure and total cholesterol could have a substantial impact on mortality inequities for Outer Regional/Remote areas.

  10. Chou-Yang model and PHI form factor

    Energy Technology Data Exchange (ETDEWEB)

    Fazal-e-Aleem; Saleem, M.; Rafique, M.

    1988-03-01

    By using the deduced differential cross-section data for PHIp elastic scattering at 175 GeV/c in the Chou-Yang model, the PHI form factor has been computed and parametrized. Then in conjunction with the proton form factor this form factor is used in the pristine Chou-Yang model to obtain differential cross-section data at Fermilab energies. The theoretical results agree with the experimental measurements, endorsing the conjecture that the hadronic form factor of neutral particle is proportional to its magnetic form factor.

  11. Modelling impulsive factors for electronics and restaurant coupons’ e-store display

    Science.gov (United States)

    Ariningsih, P. K.; Nainggolan, M.; Sandy, I. A.

    2018-04-01

    In many times, the increment of e-store visitors does not followed by sales increment. Most purchases through e-commerce are impulsive buying, however only small amount of study is available to understand impulsive factors of e-store display. This paper suggests a preliminary concept on understanding the impulsive factors in Electronics and Restaurant Coupons e-store display, which are two among few popular group products sold through e-commerce. By conducting literature study and survey, 31 attributes were identified as impulsive factors in electronics e-store display and 20 attributes were identified as impulsive factors for restaurant coupon e-store. The attributes were then grouped into comprehensive impulsive factors by factor analysis. Each group of impulsive attributes were generated into 3 factors. Accessibility Factors and Trust Factors appeared for each group products. The other factors are Internal Factors for electronics e-store and Marketing factors for restaurant coupons e-store. Structural Equation Model of the impulsive factors was developed for each type of e-store, which stated the covariance between Trust Factors and Accessibility Factors. Based on preliminary model, Internal Factor and Trust Factor are influencing impulsive buying in electronics store. Special factor for electronics e-store is Internal Factor, while for restaurant coupons e-store is Marketing Factor.

  12. Evidence for a General ADHD Factor from a Longitudinal General School Population Study

    Science.gov (United States)

    Normand, Sebastien; Flora, David B.; Toplak, Maggie E.; Tannock, Rosemary

    2012-01-01

    Recent factor analytic studies in Attention-Deficit/Hyperactivity Disorder (ADHD) have shown that hierarchical models provide a better fit of ADHD symptoms than correlated models. A hierarchical model includes a general ADHD factor and specific factors for inattention, and hyperactivity/impulsivity. The aim of this 12-month longitudinal study was…

  13. Supplementary Material for: Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel; Huser, Raphaë l; Genton, Marc G.

    2016-01-01

    We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.

  14. Predisposing, precipitating and perpetuating factors and the common sense model of illness

    DEFF Research Database (Denmark)

    Carstensen, Tina; Kasch, Helge; Frostholm, Lisbeth

    2017-01-01

    Background: Various predisposing, precipitating and perpetuating factors are found to be associated with development of persistent symptoms and disability after whiplash trauma. According to the commonsense model of illness, people use commonsense knowledge to develop individual illness models when...... facing health threat. Question: Can we use the common-sense model as a unifying model to encompass the impact of predisposing, precipitating, and perpetuating factors in the development of chronic whiplash? Looking into specific factors and their interaction: Do illness perceptions mediate the effect...... of precollision sick leave on chronic whiplash? Methods: This presentation will integrate findings from research on predisposing, precipitating, perpetuating factors that are associated with poor outcome after whiplash trauma and propose the common-sense model as a unifying model. Data from a study including 740...

  15. EMPIRICAL STUDY OF DIFFERENT FACTORS EFFECTS ON ARTICLES PUBLICATION REGARDING SURVEY INTERVIEWER CHARACTERISTICS USING MULTILEVEL REGRESSION MODEL

    Directory of Open Access Journals (Sweden)

    Alina MOROŞANU

    2013-06-01

    Full Text Available The purpose of this research work is to evaluate the effects which some factors could have on articles publication regarding survey interviewer characteristics. For this, the author studied the existing literature from the various fields in which articles on survey interviewer characteristics has been published and which can be found in online articles database. The analysis was performed on 243 articles achieved by researchers in the time period 1949-2012. Using statistical software R and applying multilevel regression model, the results showed that the time period when the studied articles are made and the interaction between the number of authors and the number of pages affect the most their publication in journals with a certain level of impact factor.

  16. Separating form factor and nuclear model effects in quasielastic neutrino-nucleus scattering

    Science.gov (United States)

    Wieske, Joseph

    2017-09-01

    When studying neutrino oscillations an understanding of charged current quasielastic (CCQE) neutrino-nucleus scattering is imperative. This interaction depends on a nuclear model as well as knowledge of form factors. In the past, CCQE data from the MiniBooNE experiment was analyzed assuming the Relativistic Fermi Gas (RFG) nuclear model, an axial dipole form factor in, and using the the z-expansion for the axial form factor in. We present the first analysis that combines a non-RFG nuclear model, in particular the Correlated Fermi Gas nuclear model (CFG) of, and the z expansion for the axial form factor. This will allow us to separate form factor and nuclear model effects in CCQE scattering. This project was supported through the Wayne State University REU program under NSF Grant PHY-1460853 and by the DOE Grant DE-SC0007983.

  17. Model of relationship between personal factors and Occupational Health and Safety (OHS) management toward unsafe actions: a case study

    Science.gov (United States)

    Syamtinningrum, M. D. P.; Partiwi, S. G.; Dewi, D. S.

    2018-04-01

    One indicator of a good company is when a safe business environment can be well maintained. In this work environment, the number of industrial accidents is minimum. Industrial accidents are the incidents that occurred in the workplace, especially in industrial area. Industrial accidents are generally caused by two main reasons, unsafe actions & unsafe conditions. Some research indicates that unsafe actions significantly affect the incidence in the workplace. Unsafe action is a failure to follow the proper procedures and requirements, which is led into accidents. From several previous studies it can be concluded that personal factors & OHS management are two most influential factors that affect unsafe actions. However, their relationship in influencing unsafe actions is not fully understood. Based on this reason the authors want to investigate the effect of personal factors and OHS management toward unsafe actions to workers. For this purpose, a company is selected as a case study. In this research, analyses were done by using univariate test, bivariate correlation and linear regression. The results of this study proves that two indicators of personal factors (i.e. knowledge of OHS & OHS training) and OHS management have significant effect on unsafe actions but in negative direction, while two indicators of personal factors (i.e. workload & fatigue) have positive direction of effect on unsafe actions. In addition, this research has developed a mathematical model that can be used to calculate and predict the value of unsafe actions performed by the worker. By using this model, the company will able to take preventive actions toward unsafe actions to reduce workers accidents.

  18. HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.

    Science.gov (United States)

    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.

  19. Are Fit Indices Biased in Favor of Bi-Factor Models in Cognitive Ability Research?: A Comparison of Fit in Correlated Factors, Higher-Order, and Bi-Factor Models via Monte Carlo Simulations

    Directory of Open Access Journals (Sweden)

    Grant B. Morgan

    2015-02-01

    Full Text Available Bi-factor confirmatory factor models have been influential in research on cognitive abilities because they often better fit the data than correlated factors and higher-order models. They also instantiate a perspective that differs from that offered by other models. Motivated by previous work that hypothesized an inherent statistical bias of fit indices favoring the bi-factor model, we compared the fit of correlated factors, higher-order, and bi-factor models via Monte Carlo methods. When data were sampled from a true bi-factor structure, each of the approximate fit indices was more likely than not to identify the bi-factor solution as the best fitting. When samples were selected from a true multiple correlated factors structure, approximate fit indices were more likely overall to identify the correlated factors solution as the best fitting. In contrast, when samples were generated from a true higher-order structure, approximate fit indices tended to identify the bi-factor solution as best fitting. There was extensive overlap of fit values across the models regardless of true structure. Although one model may fit a given dataset best relative to the other models, each of the models tended to fit the data well in absolute terms. Given this variability, models must also be judged on substantive and conceptual grounds.

  20. Stochastic factor model for electricity spot price-the case of the Nordic market

    International Nuclear Information System (INIS)

    Vehvilaeinen, Iivo; Pyykkoenen, Tuomas

    2005-01-01

    This paper presents a stochastic factor based approach to mid-term modeling of spot prices in deregulated electricity markets. The fundamentals affecting the spot price are modeled independently and a market equilibrium model combines them to form spot price. Main advantage of the model is the transparency of the generated prices because each underlying factor and the dynamics between factors can be modeled and studied in detail. Paper shows realistic numerical examples on the forerunner Scandinavian electricity market. The model is used to price an exotic electricity derivative

  1. Stochastic factor model for electricity spot price - the case of the Nordic market

    International Nuclear Information System (INIS)

    Vehvilainen, I.; Pyykkoenen, T.

    2005-01-01

    This paper presents a stochastic factor based approach to mid-term modeling of spot prices in deregulated electricity markets. The fundamentals affecting the spot price are modeled independently and a market equilibrium model combines them to form spot price. Main advantage of the model is the transparency of the generated prices because each underlying factor and the dynamics between factors can be modeled and studied in detail. Paper shows realistic numerical examples on the forerunner Scandinavian electricity market. The model is used to price an exotic electricity derivative. (author)

  2. Lexical studies of indigenous personality factors: premises, products, and prospects.

    Science.gov (United States)

    Saucier, G; Goldberg, L R; Institute, O R

    2001-12-01

    The rationale for lexical studies rests on the assumption that the most meaningful personality attributes tend to become encoded in language as single-word descriptors. We articulate some key premises of the lexical approach and then review a number of studies that have been conducted examining the factor structure of personality descriptors extracted from dictionaries. We compare lexical studies in English and 12 other languages, with attention to delineating consistencies between the structures found in diverse languages. Our review suggests that the Anglo-Germanic Big Five is reproduced better in some languages than in others. We propose some organizing rules for lexical factor structures that may be more generalizable than the contemporary Big-Five model. And, we propose several candidate structural models that should be compared with the Big Five in future studies, including structures with one, two, and three very broad factors, an alternative five-factor structure identified in Italian and Hungarian studies, and a seven-factor structure represented in Hebrew and Philippine studies. We recommend that in future studies more attention be paid to middle-level personality constructs and to examining the effects of methodological variations on the resulting factor structures.

  3. Reformulation of Crop and Management Factor in ANSWERS Model

    Directory of Open Access Journals (Sweden)

    Yayat Hidayat

    2008-05-01

    Full Text Available Crop and management factor value is significantly corelated with outputs of ANSWERS model especially on soil erosion. Using daily crop and management factors (daily C factors, the ANSWERS model performs well in predicting soil erosion which is showed by determination coeffient (R2 = 0.89, model efficiency (0.86, and average of percentage model deviations (24.1%. Whereas using USLE C factor (2 cropping systems, predicted is much higher than measured soil erosion (over estimate. Output of the model is not statisfy; it is represented by model coefficient (0.40 and average of percentage model deviations (63.6%.

  4. Model of separated form factors for unilamellar vesicles

    International Nuclear Information System (INIS)

    Kiselev, M.A.; Aksenov, V.L.; Lesieur, P.; Lombardo, D.; Kiselev, A.M.

    2001-01-01

    A new model of separated form factors is proposed for the evaluation of small-angle neutron scattering curves from large unilamellar vesicles. The validity of the model was checked via comparison with the model of a hollow sphere. The model of separated form factors and the hollow sphere model give a reasonable agreement in the evaluation of vesicle parameters

  5. An integrated model of environmental factors in adult asthma lung function and disease severity: a cross-sectional study

    Directory of Open Access Journals (Sweden)

    Katz Patricia P

    2010-05-01

    Full Text Available Abstract Background Diverse environmental exposures, studied separately, have been linked to health outcomes in adult asthma, but integrated multi-factorial effects have not been modeled. We sought to evaluate the contribution of combined social and physical environmental exposures to adult asthma lung function and disease severity. Methods Data on 176 subjects with asthma and/or rhinitis were collected via telephone interviews for sociodemographic factors and asthma severity (scored on a 0-28 point range. Dust, indoor air quality, antigen-specific IgE antibodies, and lung function (percent predicted FEV1 were assessed through home visits. Neighborhood socioeconomic status, proximity to traffic, land use, and ambient air quality data were linked to the individual-level data via residential geocoding. Multiple linear regression separately tested the explanatory power of five groups of environmental factors for the outcomes, percent predicted FEV1 and asthma severity. Final models retained all variables statistically associated (p Results Mean FEV1 was 85.0 ± 18.6%; mean asthma severity score was 6.9 ± 5.6. Of 29 variables screened, 13 were retained in the final model of FEV1 (R2 = 0.30; p 2 = 0.16; p 1 as an independent variable to the severity model further increased its explanatory power (R2 = 0.25. Conclusions Multivariate models covering a range of individual and environmental factors explained nearly a third of FEV1 variability and, taking into account lung function, one quarter of variability in asthma severity. These data support an integrated approach to modeling adult asthma outcomes, including both the physical and the social environment.

  6. Collapsing Factors in Multitrait-Multimethod Models: Examining Consequences of a Mismatch Between Measurement Design and Model

    Directory of Open Access Journals (Sweden)

    Christian eGeiser

    2015-08-01

    Full Text Available Models of confirmatory factor analysis (CFA are frequently applied to examine the convergent validity of scores obtained from multiple raters or methods in so-called multitrait-multimethod (MTMM investigations. Many applications of CFA-MTMM and similarly structured models result in solutions in which at least one method (or specific factor shows non-significant loading or variance estimates. Eid et al. (2008 distinguished between MTMM measurement designs with interchangeable (randomly selected versus structurally different (fixed methods and showed that each type of measurement design implies specific CFA-MTMM measurement models. In the current study, we hypothesized that some of the problems that are commonly seen in applications of CFA-MTMM models may be due to a mismatch between the underlying measurement design and fitted models. Using simulations, we found that models with M method factors (where M is the total number of methods and unconstrained loadings led to a higher proportion of solutions in which at least one method factor became empirically unstable when these models were fit to data generated from structurally different methods. The simulations also revealed that commonly used model goodness-of-fit criteria frequently failed to identify incorrectly specified CFA-MTMM models. We discuss implications of these findings for other complex CFA models in which similar issues occur, including nested (bifactor and latent state-trait models.

  7. [Psychosocial factors at work and cardiovascular diseases: contribution of the Effort-Reward Imbalance model].

    Science.gov (United States)

    Niedhammer, I; Siegrist, J

    1998-11-01

    The effect of psychosocial factors at work on health, especially cardiovascular health, has given rise to growing concern in occupational epidemiology over the last few years. Two theoretical models, Karasek's model and the Effort-Reward Imbalance model, have been developed to evaluate psychosocial factors at work within specific conceptual frameworks in an attempt to take into account the serious methodological difficulties inherent in the evaluation of such factors. Karasek's model, the most widely used model, measures three factors: psychological demands, decision latitude and social support at work. Many studies have shown the predictive effects of these factors on cardiovascular diseases independently of well-known cardiovascular risk factors. More recently, the Effort-Reward Imbalance model takes into account the role of individual coping characteristics which was neglected in the Karasek model. The effort-reward imbalance model focuses on the reciprocity of exchange in occupational life where high-cost/low-gain conditions are considered particularly stressful. Three dimensions of rewards are distinguished: money, esteem and gratifications in terms of promotion prospects and job security. Some studies already support that high-effort/low reward-conditions are predictive of cardiovascular diseases.

  8. The Five-Factor Model and Self-Determination Theory

    DEFF Research Database (Denmark)

    Olesen, Martin Hammershøj; Thomsen, Dorthe Kirkegaard; Schnieber, Anette

    This study investigates conceptual overlap vs. distinction between individual differences in personality traits, i.e. the Five-Factor Model; and Self-determination Theory, i.e. general causality orientations. Twelve-hundred-and-eighty-seven freshmen (mean age 21.71; 64% women) completed electronic...

  9. Constructing a unique two-phase compressibility factor model for lean gas condensates

    Energy Technology Data Exchange (ETDEWEB)

    Moayyedi, Mahmood; Gharesheikhlou, Aliashghar [Research Institute of Petroleum Industry (RIPI), Tehran (Iran, Islamic Republic of); Azamifard, Arash; Mosaferi, Emadoddin [Amirkabir University of Technology (AUT), Tehran (Iran, Islamic Republic of)

    2015-02-15

    Generating a reliable experimental model for two-phase compressibility factor in lean gas condensate reservoirs has always been demanding, but it was neglected due to lack of required experimental data. This study presents the main results of constructing the first two-phase compressibility factor model that is completely valid for Iranian lean gas condensate reservoirs. Based on a wide range of experimental data bank for Iranian lean gas condensate reservoirs, a unique two-phase compressibility factor model was generated using design of experiments (DOE) method and neural network technique (ANN). Using DOE, a swift cubic response surface model was generated for two-phase compressibility factor as a function of some selected fluid parameters for lean gas condensate fluids. The proposed DOE and ANN models were finally validated using four new independent data series. The results showed that there is a good agreement between experimental data and the proposed models. In the end, a detailed comparison was made between the results of proposed models.

  10. Constructing a unique two-phase compressibility factor model for lean gas condensates

    International Nuclear Information System (INIS)

    Moayyedi, Mahmood; Gharesheikhlou, Aliashghar; Azamifard, Arash; Mosaferi, Emadoddin

    2015-01-01

    Generating a reliable experimental model for two-phase compressibility factor in lean gas condensate reservoirs has always been demanding, but it was neglected due to lack of required experimental data. This study presents the main results of constructing the first two-phase compressibility factor model that is completely valid for Iranian lean gas condensate reservoirs. Based on a wide range of experimental data bank for Iranian lean gas condensate reservoirs, a unique two-phase compressibility factor model was generated using design of experiments (DOE) method and neural network technique (ANN). Using DOE, a swift cubic response surface model was generated for two-phase compressibility factor as a function of some selected fluid parameters for lean gas condensate fluids. The proposed DOE and ANN models were finally validated using four new independent data series. The results showed that there is a good agreement between experimental data and the proposed models. In the end, a detailed comparison was made between the results of proposed models

  11. A multi-factor model of panic disorder: results of a preliminary study integrating the role of perfectionism, stress, physiological anxiety and anxiety sensitivity

    Directory of Open Access Journals (Sweden)

    Cristina M. Wood

    2015-05-01

    Full Text Available Background: Panic disorder (PD is a highly prevalent and disabling mental health problem associated with different factors including perfectionism, stress, physiological anxiety, and anxiety sensitivity regarding physical concerns; however, no studies have analyzed the joint relationship between these factors and PD in a multi-factor model using structural equation modeling. Method: A cross-sectional study was carried out to collect data on these factors and self-reported DSM-IV past-year PD symptoms in a large sample of the general population (N=936. Results: Perceived stress had a significant effect in increasing physiological anxiety, which in turn had an important association with physical concerns. Perfectionism and perceived stress had an indirect relation with past year PD via the mediator role of physiological anxiety and physical concerns. Physical concerns, on one hand, seemed to mediate the impact between perfectionism and PD and, on the other, partially mediated the role between physiological anxiety and PD. Conclusions: Although there is considerable evidence on the association between each of these factors and PD, this model can be considered a broader and productive framework of research on the nature and treatment of PD.

  12. Free-free Gaunt factors: comparison of various models

    International Nuclear Information System (INIS)

    Collins, L.A.; Merts, A.L.

    1986-01-01

    We develop the general theory of free-free absorption processes in terms of basic quantum mechanical principles. We perform calculations of the free-free Gaunt factor for several models of the electron-atom (ion) interaction in a variety of systems including rare gases, alkali, and aluminum. In addition, we investigate plasma-screening effects in such models as the Yukawa potential. Our calculations compare well with those of other authors, and our comparative study of various models allows a more thorough understanding of their range of validity. 38 refs., 2 figs., 14 tabs

  13. The asset pricing model of musharakah factors

    Science.gov (United States)

    Simon, Shahril; Omar, Mohd; Lazam, Norazliani Md

    2015-02-01

    The existing three-factor model developed by Fama and French for conventional investment was formulated based on risk-free rates element in which contradict with Shariah principles. We note that the underlying principles that govern Shariah investment were mutual risk and profit sharing between parties, the assurance of fairness for all and that transactions were based on an underlying asset. In addition, the three-factor model did not exclude stock that was not permissible by Shariah such as financial services based on riba (interest), gambling operator, manufacture or sale of non-halal products or related products and other activities deemed non-permissible according to Shariah. Our approach to construct the factor model for Shariah investment was based on the basic tenets of musharakah in tabulating the factors. We start by noting that Islamic stocks with similar characteristics should have similar returns and risks. This similarity between Islamic stocks was defined by the similarity of musharakah attributes such as business, management, profitability and capital. These attributes define factor exposures (or betas) to factors. The main takeaways were that musharakah attributes we chose had explain stock returns well in cross section and were significant in different market environments. The management factor seemed to be responsible for the general dynamics of the explanatory power.

  14. Type D Personality : a five-factor model perspective

    NARCIS (Netherlands)

    de Fruyt, F.; Denollet, J.K.L.

    2002-01-01

    This study investigated the position of Type D (high Negative Affectivity and high Social Inhibition) within the Five-Factor Model (FFM) of personality. A sample of 155 healthy subjects were administered the Type D Scale and the NEO-FFI, assessing the FFM traits. Subjects also filled out the General

  15. Talent identification model for sprinter using discriminant factor

    Science.gov (United States)

    Kusnanik, N. W.; Hariyanto, A.; Herdyanto, Y.; Satia, A.

    2018-01-01

    The main purpose of this study was to identify young talented sprinter using discriminant factor. The research was conducted in 3 steps including item pool, screening of item pool, and trial of instruments at the small and big size of samples. 315 male elementary school students participated in this study with mean age of 11-13 years old. Data were collected by measuring anthropometry (standing height, sitting height, body mass, and leg length); testing physical fitness (40m sprint for speed, shuttle run for agility, standing broad jump for power, multistage fitness test for endurance). Data were analyzed using discriminant factor. The result of this study found that there were 5 items that selected as an instrument to identify young talented sprinter: sitting height, body mass, leg length, sprint 40m, and multistage fitness test. Model of Discriminant for talent identification in sprinter was D = -24,497 + (0,155 sitting height) + (0,080 body mass) + (0,148 leg length) + (-1,225 Sprint 40m) + (0,563 MFT). The conclusion of this study: instrument tests that have been selected and discriminant model that have been found can be applied to identify young talented as a sprinter.

  16. Extracting the Evaluations of Stereotypes: Bi-factor Model of the Stereotype Content Structure

    Directory of Open Access Journals (Sweden)

    Pablo Sayans-Jiménez

    2017-10-01

    Full Text Available Stereotype dimensions—competence, morality and sociability—are fundamental to studying the perception of other groups. These dimensions have shown moderate/high positive correlations with each other that do not reflect the theoretical expectations. The explanation for this (e.g., halo effect undervalues the utility of the shared variance identified. In contrast, in this work we propose that this common variance could represent the global evaluation of the perceived group. Bi-factor models are proposed to improve the internal structure and to take advantage of the information representing the shared variance among dimensions. Bi-factor models were compared with first order models and other alternative models in three large samples (300–309 participants. The relationships among the global and specific bi-factor dimensions with a global evaluation dimension (measured through a semantic differential were estimated. The results support the use of bi-factor models rather than first order models (and other alternative models. Bi-factor models also show a greater utility to directly and more easily explore the stereotype content including its evaluative content.

  17. Extracting the Evaluations of Stereotypes: Bi-factor Model of the Stereotype Content Structure.

    Science.gov (United States)

    Sayans-Jiménez, Pablo; Cuadrado, Isabel; Rojas, Antonio J; Barrada, Juan R

    2017-01-01

    Stereotype dimensions-competence, morality and sociability-are fundamental to studying the perception of other groups. These dimensions have shown moderate/high positive correlations with each other that do not reflect the theoretical expectations. The explanation for this (e.g., halo effect) undervalues the utility of the shared variance identified. In contrast, in this work we propose that this common variance could represent the global evaluation of the perceived group. Bi-factor models are proposed to improve the internal structure and to take advantage of the information representing the shared variance among dimensions. Bi-factor models were compared with first order models and other alternative models in three large samples (300-309 participants). The relationships among the global and specific bi-factor dimensions with a global evaluation dimension (measured through a semantic differential) were estimated. The results support the use of bi-factor models rather than first order models (and other alternative models). Bi-factor models also show a greater utility to directly and more easily explore the stereotype content including its evaluative content.

  18. Structural Equation Model for Evaluating Factors Affecting Quality of Social Infrastructure Projects

    Directory of Open Access Journals (Sweden)

    Shahid Hussain

    2018-05-01

    Full Text Available The quality of the constructed social infrastructure project has been considered a necessary measure for the sustainability of projects. Studies on factors affecting project quality have used various techniques and methods to explain the relationships between particular variables. Unexpectedly, Structural Equation Modeling (SEM has acquired very little concern in factors affecting project quality studies. To address this limitation in the body of knowledge, the objective of this study was to apply the SEM approach and build a model that explained and identified the critical factors affecting quality in social infrastructure projects. The authors developed a quantitative approach using smart-PLS version 3.2.7. This study shed light on the views of different experts based on their experience in public construction projects in Pakistan. Particularly, the authors aimed to find out the relationships between construction, stakeholders, materials, design, and external factors, and how these relate to project quality. The findings of this study revealed that the R2 value of the model was scored at 0.749, which meant that the five exogenous latent constructs collectively explained 74.9% of the variance in project quality. The Goodness-of-Fit of the model was 0.458. The construction related factor was the most important out of the five constructs. This study determined that better planning and monitoring and evaluation should be developed to better address and control the quality defects by decision-makers, project managers as well as contractors. These findings might support practitioners and decision makers to focus on quality related problems that might occur in their current or future projects.

  19. The capital asset pricing model versus the three factor model: A United Kingdom Perspective

    Directory of Open Access Journals (Sweden)

    Chandra Shekhar Bhatnagar

    2013-07-01

    Full Text Available The Sharpe (1964, Lintner (1965 and Black (1972 Capital Asset Pricing Model (CAPM postulates that the equilibrium rates of return on all risky assets are a linear function of their covariance with the market portfolio. Recent work by Fama and French (1996, 2006 introduce a Three Factor Model that questions the “real world application” of the CAPM Theorem and its ability to explain stock returns as well as value premium effects in the United States market. This paper provides an out-of-sample perspective to the work of Fama and French (1996, 2006. Multiple regression is used to compare the performance of the CAPM, a split sample CAPM and the Three Factor Model in explaining observed stock returns and value premium effects in the United Kingdom market. The methodology of Fama and French (2006 was used as the framework for this study. The findings show that the Three Factor Model holds for the United Kingdom Market and is superior to the CAPM and the split sample CAPM in explaining both stock returns and value premium effects. The “real world application” of the CAPM is therefore not supported by the United Kingdom data.

  20. A temperature dependent slip factor based thermal model for friction

    Indian Academy of Sciences (India)

    This paper proposes a new slip factor based three-dimensional thermal model to predict the temperature distribution during friction stir welding of 304L stainless steel plates. The proposed model employs temperature and radius dependent heat source to study the thermal cycle, temperature distribution, power required, the ...

  1. Empirical Model for Mobile Learning and their Factors. Case Study: Universities Located in the Urban City of Guadalajara, México

    Directory of Open Access Journals (Sweden)

    Juan Mejía Trejo

    2015-10-01

    Full Text Available Information and communication technologies (ICT are producing new and innovative teaching-learning processes. The research question we focused on is: Which is the empirical model and the factors for mobile learning at universities located within the Metropolitan Zone of Guadalajara, in Jalisco, México? Our research is grounded on a documentary study that chose variables used by specialists in m-learning using Analytic Hierarchy Process (AHP. The factors discovered were three: Technology (TECH; Contents Teaching-Learning Management and Styles (CTLMS; and Professor and Student Role (PSR. We used 13 dimensions and 60 variables. 20 professors and 800 students in social sciences courses participated in the study; they came from 7 universities located in the Urban City of Guadalajara, during 2013-2014 school cycles (24 months. We applied questionnaires and the data were analyzed by structural equations modeling (SEM, using EQS 6.1 software. The results suggest that there are 9/60 variables that have the most influence to improve the interaction with m-Learning model within the universities.

  2. Studies on kinetics of water quality factors to establish water transparency model in Neijiang River, China.

    Science.gov (United States)

    Li, Ronghui; Pan, Wei; Guo, Jinchuan; Pang, Yong; Wu, Jianqiang; Li, Yiping; Pan, Baozhu; Ji, Yong; Ding, Ling

    2014-05-01

    The basis for submerged plant restoration in surface water is to research the complicated dynamic mechanism of water transparency. In this paper, through the impact factor analysis of water transparency, the suspended sediment, dissolved organic matter, algae were determined as three main impactfactors for water transparency of Neijiang River in Eastern China. And the multiple regression equation of water transparency and sediment concentration, permanganate index, chlorophyll-a concentration was developed. Considering the complicated transport and transformation of suspended sediment, dissolved organic matter and algae, numerical model of them were developed respectively for simulating the dynamic process. Water transparency numerical model was finally developed by coupling the sediment, water quality, and algae model. These results showed that suspended sediment was a key factor influencing water transparency of Neijiang River, the influence of water quality indicated by chemical oxygen demand and algal concentration indicated by chlorophyll a were indeterminate when their concentrations were lower, the influence was more obvious when high concentrations are available, such three factors showed direct influence on water transparency.

  3. Macroeconomic factors and oil futures prices. A data-rich model

    International Nuclear Information System (INIS)

    Zagaglia, Paolo

    2010-01-01

    I study the dynamics of oil futures prices in the NYMEX using a large panel dataset that includes global macroeconomic indicators, financial market indices, quantities and prices of energy products. I extract common factors from the panel data series and estimate a Factor-Augmented Vector Autoregression for the maturity structure of oil futures prices. I find that latent factors generate information that, once combined with that of the yields, improves the forecasting performance for oil prices. Furthermore, I show that a factor correlated to purely financial developments contributes to the model performance, in addition to factors related to energy quantities and prices. (author)

  4. Dynamic Multi-Factor Credit Risk Model with Fat-Tailed Factors

    Czech Academy of Sciences Publication Activity Database

    Gapko, Petr; Šmíd, Martin

    2012-01-01

    Roč. 62, č. 2 (2012), s. 125-140 ISSN 0015-1920 R&D Projects: GA ČR GD402/09/H045; GA ČR GA402/09/0965 Grant - others:Univerzita Karlova(CZ) GAUK 46108 Institutional research plan: CEZ:AV0Z10750506 Keywords : credit risk * probability of default * loss given default * credit loss * credit loss distribution * Basel II Subject RIV: AH - Economics Impact factor: 0.340, year: 2012 http://library.utia.cas.cz/separaty/2012/E/smid-dynamic multi-factor credit risk model with fat-tailed factors.pdf

  5. Factors influencing a problem-based learning implementation: A case study of IT courses

    Science.gov (United States)

    Darus, Norida Muhd; Mohd, Haslina; Baharom, Fauziah; Saip, Mohamed Ali; Puteh, Nurnasran; Marzuki @ Matt, Zaharin; Husain, Mohd Zabidin; Yasin, Azman

    2016-08-01

    IT students must be trained to work efficiently as teamwork. One of the techniques that can be used to train them is through Problem-Based Learning (PBL) approach. The PBL implementation can be influenced by various factors depending on the ultimate goal of the study. This study is focusing on the IT students' perception of the PBL implementation. The student's perception is important to ensure the successfulness of the PBL implementation. Therefore, it is important to identify the factors that might influence the implementation of PBL of IT courses. This study aims to identify some catalyst factors that may influence the PBL implementation of IT courses. The study involved three (3) main phases: identifying PBL implementation factors, constructing a PBL model, and PBL model validation using statistical analysis. Four main factors are identified: PBL Characteristics, PBL Course Assessment, PBL Practices, and PBL Perception. Based on these four factors, a PBL model is constructed. Then, based on the proposed PBL model, four hypotheses are formulated and analyzed to validate the model. All hypotheses are significantly acceptable. The result shows that the PBL Characteristics and PBL Course Assessment factors are significantly influenced the PBL Practices and indirectly influenced the Students' Perception of the PBL Implementation for IT courses. This PBL model can assist decision makers in enhancing the PBL teaching and learning strategy for IT courses. It is also can be tested to other courses in the future.

  6. Application of the Value Optimization Model of Key Factors Based on DSEM

    Directory of Open Access Journals (Sweden)

    Chao Su

    2016-01-01

    Full Text Available The key factors of the damping solvent extraction method (DSEM for the analysis of the unbounded medium are the size of bounded domain, the artificial damping ratio, and the finite element mesh density. To control the simulation accuracy and computational efficiency of the soil-structure interaction, this study establishes a value optimization model of key factors that is composed of the design variables, the objective function, and the constraint function system. Then the optimum solutions of key factors are obtained by the optimization model. According to some comparisons of the results provided by the different initial conditions, the value optimization model of key factors is feasible to govern the simulation accuracy and computational efficiency and to analyze the practical unbounded medium-structure interaction.

  7. A dynamic factor model of the evaluation of the financial crisis in Turkey.

    Science.gov (United States)

    Sezgin, F; Kinay, B

    2010-01-01

    Factor analysis has been widely used in economics and finance in situations where a relatively large number of variables are believed to be driven by few common causes of variation. Dynamic factor analysis (DFA) which is a combination of factor and time series analysis, involves autocorrelation matrices calculated from multivariate time series. Dynamic factor models were traditionally used to construct economic indicators, macroeconomic analysis, business cycles and forecasting. In recent years, dynamic factor models have become more popular in empirical macroeconomics. They have more advantages than other methods in various respects. Factor models can for instance cope with many variables without running into scarce degrees of freedom problems often faced in regression-based analysis. In this study, a model which determines the effect of the global crisis on Turkey is proposed. The main aim of the paper is to analyze how several macroeconomic quantities show an alteration before the evolution of the crisis and to decide if a crisis can be forecasted or not.

  8. Spatial scale effects in environmental risk-factor modelling for diseases

    Directory of Open Access Journals (Sweden)

    Ram K. Raghavan

    2013-05-01

    Full Text Available Studies attempting to identify environmental risk factors for diseases can be seen to extract candidate variables from remotely sensed datasets, using a single buffer-zone surrounding locations from where disease status are recorded. A retrospective case-control study using canine leptospirosis data was conducted to verify the effects of changing buffer-zones (spatial extents on the risk factors derived. The case-control study included 94 case dogs predominantly selected based on positive polymerase chain reaction (PCR test for leptospires in urine, and 185 control dogs based on negative PCR. Land cover features from National Land Cover Dataset (NLCD and Kansas Gap Analysis Program (KS GAP around geocoded addresses of cases/controls were extracted using multiple buffers at every 500 m up to 5,000 m, and multivariable logistic models were used to estimate the risk of different land cover variables to dogs. The types and statistical significance of risk factors identified changed with an increase in spatial extent in both datasets. Leptospirosis status in dogs was significantly associated with developed high-intensity areas in models that used variables extracted from spatial extents of 500-2000 m, developed medium-intensity areas beyond 2,000 m and up to 3,000 m, and evergreen forests beyond 3,500 m and up to 5,000 m in individual models in the NLCD. Significant associations were seen in urban areas in models that used variables extracted from spatial extents of 500-2,500 m and forest/woodland areas beyond 2,500 m and up to 5,000 m in individual models in Kansas gap analysis programme datasets. The use of ad hoc spatial extents can be misleading or wrong, and the determination of an appropriate spatial extent is critical when extracting environmental variables for studies. Potential work-arounds for this problem are discussed.

  9. A general psychopathology factor (P factor) in children: Structural model analysis and external validation through familial risk and child global executive function.

    Science.gov (United States)

    Martel, Michelle M; Pan, Pedro M; Hoffmann, Maurício S; Gadelha, Ary; do Rosário, Maria C; Mari, Jair J; Manfro, Gisele G; Miguel, Eurípedes C; Paus, Tomás; Bressan, Rodrigo A; Rohde, Luis A; Salum, Giovanni A

    2017-01-01

    High rates of comorbidities and poor validity of disorder diagnostic criteria for mental disorders hamper advances in mental health research. Recent work has suggested the utility of continuous cross-cutting dimensions, including general psychopathology and specific factors of externalizing and internalizing (e.g., distress and fear) syndromes. The current study evaluated the reliability of competing structural models of psychopathology and examined external validity of the best fitting model on the basis of family risk and child global executive function (EF). A community sample of 8,012 families from Brazil with children ages 6-12 years completed structured interviews about the child and parental psychiatric syndromes, and a subsample of 2,395 children completed tasks assessing EF (i.e., working memory, inhibitory control, and time processing). Confirmatory factor analyses tested a series of structural models of psychopathology in both parents and children. The model with a general psychopathology factor ("P factor") with 3 specific factors (fear, distress, and externalizing) exhibited the best fit. The general P factor accounted for most of the variance in all models, with little residual variance explained by each of the 3 specific factors. In addition, associations between child and parental factors were mainly significant for the P factors and nonsignificant for the specific factors from the respective models. Likewise, the child P factor-but not the specific factors-was significantly associated with global child EF. Overall, our results provide support for a latent overarching P factor characterizing child psychopathology, supported by familial associations and child EF. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  10. Application of zero-inflated poisson mixed models in prognostic factors of hepatitis C.

    Science.gov (United States)

    Akbarzadeh Baghban, Alireza; Pourhoseingholi, Asma; Zayeri, Farid; Jafari, Ali Akbar; Alavian, Seyed Moayed

    2013-01-01

    In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C. The data was collected from a longitudinal study during 2005-2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the proposed mixed model, standard errors of estimators were compared. The results obtained from mixed PR showed that genotype 3 and treatment protocol were statistically significant. Results of zero-inflated Poisson mixed model showed that age, sex, genotypes 2 and 3, the treatment protocol, and having risk factors had significant effects on viral load of HCV patients. Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors. The results showed that a mixed zero-inflated Poisson model was the almost best fit. The proposed model can capture serial dependence, additional overdispersion, and excess zeros in the longitudinal count data.

  11. A Parametric Factor Model of the Term Structure of Mortality

    DEFF Research Database (Denmark)

    Haldrup, Niels; Rosenskjold, Carsten Paysen T.

    The prototypical Lee-Carter mortality model is characterized by a single common time factor that loads differently across age groups. In this paper we propose a factor model for the term structure of mortality where multiple factors are designed to influence the age groups differently via...... on the loading functions, the factors are not designed to be orthogonal but can be dependent and can possibly cointegrate when the factors have unit roots. We suggest two estimation procedures similar to the estimation of the dynamic Nelson-Siegel term structure model. First, a two-step nonlinear least squares...... procedure based on cross-section regressions together with a separate model to estimate the dynamics of the factors. Second, we suggest a fully specified model estimated by maximum likelihood via the Kalman filter recursions after the model is put on state space form. We demonstrate the methodology for US...

  12. [Lake eutrophication modeling in considering climatic factors change: a review].

    Science.gov (United States)

    Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng

    2012-11-01

    Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.

  13. The structure of musical preferences: a five-factor model.

    Science.gov (United States)

    Rentfrow, Peter J; Goldberg, Lewis R; Levitin, Daniel J

    2011-06-01

    Music is a cross-cultural universal, a ubiquitous activity found in every known human culture. Individuals demonstrate manifestly different preferences in music, and yet relatively little is known about the underlying structure of those preferences. Here, we introduce a model of musical preferences based on listeners' affective reactions to excerpts of music from a wide variety of musical genres. The findings from 3 independent studies converged to suggest that there exists a latent 5-factor structure underlying music preferences that is genre free and reflects primarily emotional/affective responses to music. We have interpreted and labeled these factors as (a) a Mellow factor comprising smooth and relaxing styles; (b) an Unpretentious factor comprising a variety of different styles of sincere and rootsy music such as is often found in country and singer-songwriter genres; (c) a Sophisticated factor that includes classical, operatic, world, and jazz; (d) an Intense factor defined by loud, forceful, and energetic music; and (e) a Contemporary factor defined largely by rhythmic and percussive music, such as is found in rap, funk, and acid jazz. The findings from a fourth study suggest that preferences for the MUSIC factors are affected by both the social and the auditory characteristics of the music. 2011 APA, all rights reserved

  14. Modeling the factors affecting unsafe behavior in the construction industry from safety supervisors' perspective.

    Science.gov (United States)

    Khosravi, Yahya; Asilian-Mahabadi, Hassan; Hajizadeh, Ebrahim; Hassanzadeh-Rangi, Narmin; Bastani, Hamid; Khavanin, Ali; Mortazavi, Seyed Bagher

    2014-01-01

    There can be little doubt that the construction is the most hazardous industry in the worldwide. This study was designed to modeling the factors affecting unsafe behavior from the perspective of safety supervisors. The qualitative research was conducted to extract a conceptual model. A structural model was then developed based on a questionnaire survey (n=266) by two stage Structural Equation Model (SEM) approach. An excellent confirmed 12-factors structure explained about 62% of variances unsafe behavior in the construction industry. A good fit structural model indicated that safety climate factors were positively correlated with safety individual factors (Pconstruction workers' engagement in safe or unsafe behavior. In order to improve construction safety performance, more focus on the workplace condition is required.

  15. Structural Model of psychological risk and protective factors affecting on quality of life in patients with coronary heart disease: A psychocardiology model

    Directory of Open Access Journals (Sweden)

    Zohreh Khayyam Nekouei

    2014-01-01

    Full Text Available Background: Conducted researches show that psychological factors may have a very important role in the etiology, continuity and consequences of coronary heart diseases. This study has drawn the psychological risk and protective factors and their effects in patients with coronary heart diseases (CHD in a structural model. It aims to determine the structural relations between psychological risk and protective factors with quality of life in patients with coronary heart disease. Materials and Methods: The present cross-sectional and correlational studies were conducted using structural equation modeling. The study sample included 398 patients of coronary heart disease in the university referral Hospital, as well as other city health care centers in Isfahan city. They were selected based on random sampling method. Then, in case, they were executed the following questionnaires: Coping with stressful situations (CISS- 21, life orientation (LOT-10, general self-efficacy (GSE-10, depression, anxiety and stress (DASS-21, perceived stress (PSS-14, multidimensional social support (MSPSS-12, alexithymia (TAS-20, spiritual intelligence (SQ-23 and quality of life (WHOQOL-26. Results: The results showed that protective and risk factors could affect the quality of life in patients with CHD with factor loadings of 0.35 and −0.60, respectively. Moreover, based on the values of the framework of the model such as relative chi-square (CMIN/DF = 3.25, the Comparative Fit Index (CFI = 0.93, the Parsimony Comparative Fit Index (PCFI = 0.68, the Root Mean Square Error of Approximation (RMSEA = 0.07 and details of the model (significance of the relationships it has been confirmed that the psychocardiological structural model of the study is the good fitting model. Conclusion: This study was among the first to research the different psychological risk and protective factors of coronary heart diseases in the form of a structural model. The results of this study have

  16. Caenorhabditis elegans: A Useful Model for Studying Metabolic Disorders in Which Oxidative Stress Is a Contributing Factor

    Directory of Open Access Journals (Sweden)

    Elizabeth Moreno-Arriola

    2014-01-01

    Full Text Available Caenorhabditis elegans is a powerful model organism that is invaluable for experimental research because it can be used to recapitulate most human diseases at either the metabolic or genomic level in vivo. This organism contains many key components related to metabolic and oxidative stress networks that could conceivably allow us to increase and integrate information to understand the causes and mechanisms of complex diseases. Oxidative stress is an etiological factor that influences numerous human diseases, including diabetes. C. elegans displays remarkably similar molecular bases and cellular pathways to those of mammals. Defects in the insulin/insulin-like growth factor-1 signaling pathway or increased ROS levels induce the conserved phase II detoxification response via the SKN-1 pathway to fight against oxidative stress. However, it is noteworthy that, aside from the detrimental effects of ROS, they have been proposed as second messengers that trigger the mitohormetic response to attenuate the adverse effects of oxidative stress. Herein, we briefly describe the importance of C. elegans as an experimental model system for studying metabolic disorders related to oxidative stress and the molecular mechanisms that underlie their pathophysiology.

  17. Differences in within- and between-person factor structure of positive and negative affect: analysis of two intensive measurement studies using multilevel structural equation modeling.

    Science.gov (United States)

    Rush, Jonathan; Hofer, Scott M

    2014-06-01

    The Positive and Negative Affect Schedule (PANAS) is a widely used measure of emotional experience. The factor structure of the PANAS has been examined predominantly with cross-sectional designs, which fails to disaggregate within-person variation from between-person differences. There is still uncertainty as to the factor structure of positive and negative affect and whether they constitute 2 distinct independent factors. The present study examined the within-person and between-person factor structure of the PANAS in 2 independent samples that reported daily affect over 7 and 14 occasions, respectively. Results from multilevel confirmatory factor analyses revealed that a 2-factor structure at both the within-person and between-person levels, with correlated specific factors for overlapping items, provided good model fit. The best-fitting solution was one where within-person factors of positive and negative affect were inversely correlated, but between-person factors were independent. The structure was further validated through multilevel structural equation modeling examining the effects of cognitive interference, daily stress, physical symptoms, and physical activity on positive and negative affect factors.

  18. Condensation in models with factorized and pair-factorized stationary states

    International Nuclear Information System (INIS)

    Evans, M R; Waclaw, B

    2015-01-01

    Non-equilibrium real-space condensation is a phenomenon in which a finite fraction of some conserved quantity (mass, particles, etc) becomes spatially localized. We review two popular stochastic models of hopping particles that lead to condensation and whose stationary states assume a factorized form: the zero-range process and the misanthrope process, and their various generalizations. We also introduce a new model—a misanthrope process with parallel dynamics—that exhibits condensation and has a pair-factorized stationary state

  19. Latent factor modeling of four schizotypy dimensions with theory of mind and empathy.

    Directory of Open Access Journals (Sweden)

    Jeffrey S Bedwell

    Full Text Available Preliminary evidence suggests that theory of mind and empathy relate differentially to factors of schizotypy. The current study assessed 686 undergraduate students and used structural equation modeling to examine links between a four-factor model of schizotypy with performance on measures of theory of mind (Reading the Mind in the Eyes Test [MIE] and empathy (Interpersonal Reactivity Index [IRI]. Schizotypy was assessed using three self-report measures which were simultaneously entered into the model. Results revealed that the Negative factor of schizotypy showed a negative relationship with the Empathy factor, which was primarily driven by the Empathic Concern subscale of the IRI and the No Close Friends and Constricted Affect subscales of the Schizotypal Personality Questionnaire. These findings are consistent with a growing body of literature suggesting a relatively specific relationship between negative schizotypy and empathy, and are consistent with several previous studies that found no relationship between MIE performance and schizotypy.

  20. A quantitative assessment of organizational factors affecting safety using system dynamics model

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Jae Kook; Ahn, Nam Sung [Korea Electric Power Research Institute, Taejon (Korea, Republic of); Jae, Moo Sung [Hanyang Univ., Seoul (Korea, Republic of)

    2004-02-01

    The purpose of this study is to develop a system dynamics model for the assessment of the organizational and human factors in a nuclear power plant which contribute to nuclear safety. Previous studies can be classified into two major approaches. One is the engineering approach using tools such as ergonomics and Probability Safety Assessment (PSA). The other is the socio-psychology approach. Both have contributed to find organizational and human factors and to present guidelines to lessen human error in plants. However, since these approaches assume that the relationship among factors is independent they do not explain the interactions among the factors or variables in nuclear power plants. To overcome these restrictions, a system dynamics model, which can show cause and effect relationships among factors and quantify the organizational and human factors, has been developed. Handling variables such as the degree of leadership, the number of employees, and workload in each department, users can simulate various situations in nuclear power plant organization. Through simulation, users can get insights to improve safety in plants and to find managerial tools in both organizational and human factors.

  1. A quantitative assessment of organizational factors affecting safety using system dynamics model

    International Nuclear Information System (INIS)

    Yu, Jae Kook; Ahn, Nam Sung; Jae, Moo Sung

    2004-01-01

    The purpose of this study is to develop a system dynamics model for the assessment of the organizational and human factors in a nuclear power plant which contribute to nuclear safety. Previous studies can be classified into two major approaches. One is the engineering approach using tools such as ergonomics and Probability Safety Assessment (PSA). The other is the socio-psychology approach. Both have contributed to find organizational and human factors and to present guidelines to lessen human error in plants. However, since these approaches assume that the relationship among factors is independent they do not explain the interactions among the factors or variables in nuclear power plants. To overcome these restrictions, a system dynamics model, which can show cause and effect relationships among factors and quantify the organizational and human factors, has been developed. Handling variables such as the degree of leadership, the number of employees, and workload in each department, users can simulate various situations in nuclear power plant organization. Through simulation, users can get insights to improve safety in plants and to find managerial tools in both organizational and human factors

  2. Factors Models of Scrum Adoption in the Software Development Process: A Systematic Literature Review

    Directory of Open Access Journals (Sweden)

    Marilyn Sihuay

    2018-05-01

    Full Text Available (Background The adoption of Agile Software Development (ASD, in particular Scrum, has grown significantly since its introduction in 2001. However, in Lima, many ASDs implementations have been not suitable (uncompleted or inconsistent, thus losing benefits obtainable by this approach and the critical success factors in this context are unknown. (Objective To analyze factors models used in the evaluation of the adoption of ASDs, as these factors models can contribute to explaining the success or failure of these adoptions. (Method In this study we used a systematic literature review. (Result Ten models have been identified; their similarities and differences are presented. (Conclusion Each model identified consider different factors, however some of them are shared by five of these models, such as team member attributes, engaging customer, customer collaboration, experience and work environment.

  3. Smoking Status and the Five-Factor Model of Personality: Results of a Cross-Sectional Study Conducted in Poland.

    Science.gov (United States)

    Buczkowski, Krzysztof; Basinska, Małgorzata A; Ratajska, Anna; Lewandowska, Katarzyna; Luszkiewicz, Dorota; Sieminska, Alicja

    2017-01-27

    Tobacco smoking is the single most important modifiable factor in increased morbidity and premature mortality. Numerous factors-including genetics, personality, and environment-affect the development and persistence of tobacco addiction, and knowledge regarding these factors could improve smoking cessation rates. This study compared personality traits between never, former, and current smokers, using the Five-Factor Model of Personality in a country with a turbulent smoking reduction process. : In this cross-sectional study, 909 Polish adults completed the Revised Neuroticism-Extraversion-Openness Personality Inventory. Our results showed that current smokers' scores for extraversion, one of the five global dimensions of personality, were higher relative to never smokers. Neuroticism, openness to experience, agreeableness, and conscientiousness did not differ significantly according to smoking status. Facet analysis, which described each dimension in detail, showed that current smokers' activity and excitement seeking (facets of extraversion) scores were higher relative to those of never and former smokers. In turn, current smokers' dutifulness and deliberation (facets of conscientiousness) scores were lower than those found in former and never smokers. Never smokers scored the highest in self-consciousness (a facet of neuroticism) and compliance (a component of agreeableness). The study conducted among Polish individuals showed variation in personality traits according to their smoking status; however, this variation differed from that reported in countries in which efforts to reduce smoking had begun earlier relative to Poland. Knowledge regarding personality traits could be useful in designing smoking prevention and cessation programs tailored to individuals' needs.

  4. A quantitative assessment of organizational factors affecting safety using a system dynamics model

    International Nuclear Information System (INIS)

    Yoo, J. K.; Yoon, T. S.

    2003-01-01

    The purpose of this study is to develop a system dynamics model for the assessment of organizational and human factors in the nuclear power plant safety. Previous studies are classified into two major approaches. One is the engineering approach such as ergonomics and Probabilistic Safety Assessment (PSA). The other is socio-psychology one. Both have contributed to find organizational and human factors and increased nuclear safety However, since these approaches assume that the relationship among factors is independent they do not explain the interactions between factors or variables in NPP's. To overcome these restrictions, a system dynamics model, which can show causal relations between factors and quantify organizational and human factors, has been developed. Operating variables such as degree of leadership, adjustment of number of employee, and workload in each department, users can simulate various situations in nuclear power plants in the organization side. Through simulation, user can get an insight to improve safety in plants and to find managerial tools in the organization and human side

  5. TEST OF THE FAMA-FRENCH THREE-FACTOR MODEL IN CROATIA

    Directory of Open Access Journals (Sweden)

    Denis Dolinar

    2013-06-01

    Full Text Available This paper empirically examines the Fama-French three-factor model of stock returns for Croatia. In contrast to the results of Fama and French (1993 for the U.S. stock market, their three-factor model did not show so successful when describing risk-return relation of Croatian stocks. This paper shows that the Fama-French three-factor model is a valid pricing model, since it explains cross-section of average returns on stocks in Croatia, and that has a greater explanatory power in comparison to the CAPM. In the case of Croatian stock market, size and B/M factors are not always significant, but on average they individually have certain marginal explanatory power. Namely, they capture small common variation in returns that is missed by the market factor. Moreover, B/M factor has shown as a stronger common risk proxy in relation to size factor. Finally, there is still a large portion of common variation in stock return that may be explained by other factors. Because emerging capital markets bear their own specificity, special care needs to be taken when applying existing or developing new pricing models.

  6. Modeling impact of environmental factors on photovoltaic array performance

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Jie; Sun, Yize; Xu, Yang [College of Mechanical Engineering, Donghua University NO.2999, North Renmin Road, Shanghai (China)

    2013-07-01

    It is represented in this paper that a methodology to model and quantify the impact of the three environmental factors, the ambient temperature, the incident irradiance and the wind speed, upon the performance of photovoltaic array operating under outdoor conditions. First, A simple correlation correlating operating temperature with the three environmental variables is validated for a range of wind speed studied, 2-8, and for irradiance values between 200 and 1000. Root mean square error (RMSE) between modeled operating temperature and measured values is 1.19% and the mean bias error (MBE) is -0.09%. The environmental factors studied influence I-V curves, P-V curves, and maximum-power outputs of photovoltaic array. The cell-to-module-to-array mathematical model for photovoltaic panels is established in this paper and the method defined as segmented iteration is adopted to solve the I-V curve expression to relate model I-V curves. The model I-V curves and P-V curves are concluded to coincide well with measured data points. The RMSE between numerically calculated maximum-power outputs and experimentally measured ones is 0.2307%, while the MBE is 0.0183%. In addition, a multivariable non-linear regression equation is proposed to eliminate the difference between numerically calculated values and measured ones of maximum power outputs over the range of high ambient temperature and irradiance at noon and in the early afternoon. In conclusion, the proposed method is reasonably simple and accurate.

  7. A study of factors enhancing smart grid consumer engagement

    International Nuclear Information System (INIS)

    Park, Chan-Kook; Kim, Hyun-Jae; Kim, Yang-Soo

    2014-01-01

    It is important to ensure consumer acceptance in a smart grid since the ultimate deployment of the smart grid depends on the end users' acceptance of smart grid products and services such as smart meters and advanced metering services. We examine how residential consumers perceive the smart grid and what factors influence their acceptance of the smart grid through a survey for electricity consumers in Korea. In this study, consumers' smart grid acceptance factors, including the perceived risk, were examined with the existing technology acceptance model suggested by Davis. This study has an implication that it has provided theoretical and empirical ground, based on which the policies to promote consumer participation in the deployment of the smart grid can be developed. Since there are few studies on the policies from the perspective of the smart grid users, this study will contribute directly to the development of the strategy to ensure the acceptance of the smart grid. - Highlights: • We examine what factors influence electricity consumers' smart grid acceptance. • We test the smart grid technology acceptance model including the perceived risk as a main factor. • The importance of consumer education and public relations of the smart grid has been confirmed. • Another shortcut to ensure the acceptance of the smart grid is to mitigate the anxiety about the risk in the use of the smart grid

  8. Factor copula models for data with spatio-temporal dependence

    KAUST Repository

    Krupskii, Pavel

    2017-10-13

    We propose a new copula model for spatial data that are observed repeatedly in time. The model is based on the assumption that there exists a common factor that affects the measurements of a process in space and in time. Unlike models based on multivariate normality, our model can handle data with tail dependence and asymmetry. The likelihood for the proposed model can be obtained in a simple form and therefore parameter estimation is quite fast. Simulation from this model is straightforward and data can be predicted at any spatial location and time point. We use simulation studies to show different types of dependencies, both in space and in time, that can be generated by this model. We apply the proposed copula model to hourly wind data and compare its performance with some classical models for spatio-temporal data.

  9. Factor copula models for data with spatio-temporal dependence

    KAUST Repository

    Krupskii, Pavel; Genton, Marc G.

    2017-01-01

    We propose a new copula model for spatial data that are observed repeatedly in time. The model is based on the assumption that there exists a common factor that affects the measurements of a process in space and in time. Unlike models based on multivariate normality, our model can handle data with tail dependence and asymmetry. The likelihood for the proposed model can be obtained in a simple form and therefore parameter estimation is quite fast. Simulation from this model is straightforward and data can be predicted at any spatial location and time point. We use simulation studies to show different types of dependencies, both in space and in time, that can be generated by this model. We apply the proposed copula model to hourly wind data and compare its performance with some classical models for spatio-temporal data.

  10. Model Fit and Item Factor Analysis: Overfactoring, Underfactoring, and a Program to Guide Interpretation.

    Science.gov (United States)

    Clark, D Angus; Bowles, Ryan P

    2018-04-23

    In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present study used Monte Carlo simulation methods to investigate the ability of popular model fit statistics (chi-square, root mean square error of approximation, the comparative fit index, and the Tucker-Lewis index) and their standard cutoff values to detect the optimal number of latent dimensions underlying sets of dichotomous items. Models were fit to data generated from three-factor population structures that varied in factor loading magnitude, factor intercorrelation magnitude, number of indicators, and whether cross loadings or minor factors were included. The effectiveness of the thresholds varied across fit statistics, and was conditional on many features of the underlying model. Together, results suggest that conventional fit thresholds offer questionable utility in the context of IFA.

  11. Verification of the model of predisposition in triathlon – structural model of confirmative factor analysis

    Directory of Open Access Journals (Sweden)

    Lenka Kovářová

    2012-09-01

    Full Text Available BACKGROUND: The triathlon is a combination of three different types of sport – swimming, cycling, and running. Each of these requires different top level predispositions and complex approach to talent selection is a rather difficult process. Attempts to identify assumptions in the triathlon have so far been specific and focused only on some groups of predispositions (physiology, motor tests, and psychology. The latest studies missed the structural approach and were based on determinants of sport performance, theory of sports training and expert assessment. OBJECTIVE: The aim of our study was to verify the model of predisposition in the short triathlon for talent assessment of young male athletes age 17–20 years. METHODS: The research sample consisted of 55 top level triathletes – men, who were included in the Government supported sports talent programme in the Czech Republic at the age of 17–20 years. We used a confirmative factor analysis (FA and Path diagram to verify the model, which allow us to explain mutual relationships among observed variables. For statistical data processing we used a structure equating modeling (SEM by software Lisrel L88. RESULTS: The study confirms best structural model for talent selection in triathlon at the age of 17–20 years old men, which composed seventeen indicators (tests and explained 91% of all cross-correlations (Goodness of Fit Index /GFI/ 0.91, Root Mean Square Residual /RMSR/ 0.13. Tests for predispositions in triathlons were grouped into five items, three motor predispositions (swimming, cycling and running skills, aerobic and psychological predispositions. Aerobic predispositions showed the highest importance to the assumptions to the general factor (1.00; 0. Running predispositions were measured as a very significant factor (–0.85; 0.28 which confirms importance of this critical stage of the race. Lower factor weight showed clusters of swimming (–0.61; 0.63 and cycling (0.53; 0

  12. A Multinomial Probit Model with Latent Factors

    DEFF Research Database (Denmark)

    Piatek, Rémi; Gensowski, Miriam

    2017-01-01

    be meaningfully linked to an economic model. We provide sufficient conditions that make this structure identified and interpretable. For inference, we design a Markov chain Monte Carlo sampler based on marginal data augmentation. A simulation exercise shows the good numerical performance of our sampler......We develop a parametrization of the multinomial probit model that yields greater insight into the underlying decision-making process, by decomposing the error terms of the utilities into latent factors and noise. The latent factors are identified without a measurement system, and they can...

  13. Forming Factors And Builder Indicators Of Brand Personality Models In Traditional Retail Traders

    Directory of Open Access Journals (Sweden)

    Yunelly Asra

    2017-12-01

    Full Text Available This study aims to find the factors forming and indicator builder model of brand personality of traditional retail traders through measuring the influence of retail mix and culture. The formation of brand personality uses Aaker brand personality dimension to 250 consumers in Bengkalis Regency. The type of research is causal research design. The research variables are brand personality Retail Mix and Brand Personality. Data collection is done by probability sampling with purposive method. Data analysis was done by perception analysis frequency distribution and multiple regression using SPSS version 21.0. The results of this study are The factor of retail mix partially has a positive and significant impact on the brand personality of traditional retail traders in Bengkalis Regency. Factor cultural partially does not affect the brand personality of traditional retail traders in Bengkalis Regency. Simultaneously retail mix and cultural have positive and significant influence on traditional brand traders brand personality in Bengkalis Regency. Initial forming factor of brand personality model of traditional retail traders in Bengkalis Regency is Retail Mix Factor. Indicator of the model of traditional traders brand personality builder in Bengkalis are sincerity excitement competence sophistication competence ruggedness.

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

    Science.gov (United States)

    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.

  15. Two-vehicle injury severity models based on integration of pavement management and traffic engineering factors.

    Science.gov (United States)

    Jiang, Ximiao; Huang, Baoshan; Yan, Xuedong; Zaretzki, Russell L; Richards, Stephen

    2013-01-01

    The severity of traffic-related injuries has been studied by many researchers in recent decades. However, the evaluation of many factors is still in dispute and, until this point, few studies have taken into account pavement management factors as points of interest. The objective of this article is to evaluate the combined influences of pavement management factors and traditional traffic engineering factors on the injury severity of 2-vehicle crashes. This study examines 2-vehicle rear-end, sideswipe, and angle collisions that occurred on Tennessee state routes from 2004 to 2008. Both the traditional ordered probit (OP) model and Bayesian ordered probit (BOP) model with weak informative prior were fitted for each collision type. The performances of these models were evaluated based on the parameter estimates and deviances. The results indicated that pavement management factors played identical roles in all 3 collision types. Pavement serviceability produces significant positive effects on the severity of injuries. The pavement distress index (PDI), rutting depth (RD), and rutting depth difference between right and left wheels (RD_df) were not significant in any of these 3 collision types. The effects of traffic engineering factors varied across collision types, except that a few were consistently significant in all 3 collision types, such as annual average daily traffic (AADT), rural-urban location, speed limit, peaking hour, and light condition. The findings of this study indicated that improved pavement quality does not necessarily lessen the severity of injuries when a 2-vehicle crash occurs. The effects of traffic engineering factors are not universal but vary by the type of crash. The study also found that the BOP model with a weak informative prior can be used as an alternative but was not superior to the traditional OP model in terms of overall performance.

  16. Example of emergency response model evaluation of studies using the Mathew/Adpic models

    International Nuclear Information System (INIS)

    Dickerson, M.H.; Lange, R.

    1986-04-01

    This report summarizes model evaluation studies conducted for the MATHEW/ADPIC transport and diffusion models during the past ten years. These models support the US Department of Energy Atmospheric Release Advisory Capability, an emergency response service for atmospheric releases of nuclear material. Field studies involving tracer releases used in these studies cover a broad range of meteorology, terrain and tracer release heights, the three most important aspects of estimating air concentration values resulting from airborne releases of toxic material. Results of these studies show that these models can estimate air concentration values within a factor of 2 20% to 50% of the time and a factor of 5 40% to 80% of the time. As the meterology and terrain become more complex and the release height of the tracer is increased, the accuracy of the model calculations degrades. This band of uncertainty appears to correctly represent the capability of these models at this time. A method for estimating angular uncertainty in the model calculations is described and used to suggest alternative methods for evaluating emergency response models

  17. Model-based identification and use of task complexity factors of human integrated systems

    International Nuclear Information System (INIS)

    Ham, Dong-Han; Park, Jinkyun; Jung, Wondea

    2012-01-01

    Task complexity is one of the conceptual constructs that are critical to explain and predict human performance in human integrated systems. A basic approach to evaluating the complexity of tasks is to identify task complexity factors and measure them. Although a great deal of task complexity factors have been studied, there is still a lack of conceptual frameworks for identifying and organizing them analytically, which can be generally used irrespective of the types of domains and tasks. This study proposes a model-based approach to identifying and using task complexity factors, which has two facets—the design aspects of a task and complexity dimensions. Three levels of design abstraction, which are functional, behavioral, and structural aspects of a task, characterize the design aspect of a task. The behavioral aspect is further classified into five cognitive processing activity types. The complexity dimensions explain a task complexity from different perspectives, which are size, variety, and order/organization. Twenty-one task complexity factors are identified by the combination of the attributes of each facet. Identification and evaluation of task complexity factors based on this model is believed to give insights for improving the design quality of tasks. This model for complexity factors can also be used as a referential framework for allocating tasks and designing information aids. The proposed approach is applied to procedure-based tasks of nuclear power plants (NPPs) as a case study to demonstrate its use. Last, we compare the proposed approach with other studies and then suggest some future research directions.

  18. The animal model determines the results of Aeromonas virulence factors

    Directory of Open Access Journals (Sweden)

    Alejandro Romero

    2016-10-01

    Full Text Available The selection of an experimental animal model is of great importance in the study of bacterial virulence factors. Here, a bath infection of zebrafish larvae is proposed as an alternative model to study the virulence factors of A. hydrophila. Intraperitoneal infections in mice and trout were compared with bath infections in zebrafish larvae using specific mutants. The great advantage of this model is that bath immersion mimics the natural route of infection, and injury to the tail also provides a natural portal of entry for the bacteria. The implication of T3SS in the virulence of A. hydrophila was analysed using the AH-1::aopB mutant. This mutant was less virulent than the wild-type strain when inoculated into zebrafish larvae, as described in other vertebrates. However, the zebrafish model exhibited slight differences in mortality kinetics only observed using invertebrate models. Infections using the mutant AH-1∆vapA lacking the gene coding for the surface S-layer suggested that this protein was not totally necessary to the bacteria once it was inside the host, but it contributed to the inflammatory response. Only when healthy zebrafish larvae were infected did the mutant produce less mortality than the wild type. Variations between models were evidenced using the AH-1∆rmlB, which lacks the O-antigen lipopolysaccharide (LPS, and the AH-1∆wahD, which lacks the O-antigen LPS and part of the LPS outer-core. Both mutants showed decreased mortality in all of the animal models, but the differences between them were only observed in injured zebrafish larvae, suggesting that residues from the LPS outer core must be important for virulence. The greatest differences were observed using the AH-1ΔFlaB-J (lacking polar flagella and unable to swim and the AH-1::motX (non-motile but producing flagella. They were as pathogenic as the wild-type strain when injected into mice and trout, but no mortalities were registered in zebrafish larvae. This study

  19. Matrix factorizations, minimal models and Massey products

    International Nuclear Information System (INIS)

    Knapp, Johanna; Omer, Harun

    2006-01-01

    We present a method to compute the full non-linear deformations of matrix factorizations for ADE minimal models. This method is based on the calculation of higher products in the cohomology, called Massey products. The algorithm yields a polynomial ring whose vanishing relations encode the obstructions of the deformations of the D-branes characterized by these matrix factorizations. This coincides with the critical locus of the effective superpotential which can be computed by integrating these relations. Our results for the effective superpotential are in agreement with those obtained from solving the A-infinity relations. We point out a relation to the superpotentials of Kazama-Suzuki models. We will illustrate our findings by various examples, putting emphasis on the E 6 minimal model

  20. Estimating Dynamic Connectivity States in fMRI Using Regime-Switching Factor Models

    KAUST Repository

    Ting, Chee-Ming

    2017-12-06

    We consider the challenges in estimating state-related changes in brain connectivity networks with a large number of nodes. Existing studies use sliding-window analysis or time-varying coefficient models which are unable to capture both smooth and abrupt changes simultaneously, and rely on ad-hoc approaches to the high-dimensional estimation. To overcome these limitations, we propose a Markov-switching dynamic factor model which allows the dynamic connectivity states in functional magnetic resonance imaging (fMRI) data to be driven by lower-dimensional latent factors. We specify a regime-switching vector autoregressive (SVAR) factor process to quantity the time-varying directed connectivity. The model enables a reliable, data-adaptive estimation of change-points of connectivity regimes and the massive dependencies associated with each regime. We develop a three-step estimation procedure: 1) extracting the factors using principal component analysis, 2) identifying connectivity regimes in a low-dimensional subspace based on the factor-based SVAR model, 3) constructing high-dimensional state connectivity metrics based on the subspace estimates. Simulation results show that our estimator outperforms K-means clustering of time-windowed coefficients, providing more accurate estimate of time-evolving connectivity. It achieves percentage of reduction in mean squared error by 60% when the network dimension is comparable to the sample size. When applied to resting-state fMRI data, our method successfully identifies modular organization in resting-state networks in consistency with other studies. It further reveals changes in brain states with variations across subjects and distinct large-scale directed connectivity patterns across states.

  1. A Bayesian Belief Network modelling of organisational factors in risk analysis: A case study in maritime transportation

    International Nuclear Information System (INIS)

    Trucco, P.; Cagno, E.; Ruggeri, F.; Grande, O.

    2008-01-01

    The paper presents an innovative approach to integrate Human and Organisational Factors (HOF) into risk analysis. The approach has been developed and applied to a case study in the maritime industry, but it can also be utilised in other sectors. A Bayesian Belief Network (BBN) has been developed to model the Maritime Transport System (MTS), by taking into account its different actors (i.e., ship-owner, shipyard, port and regulator) and their mutual influences. The latter have been modelled by means of a set of dependent variables whose combinations express the relevant functions performed by each actor. The BBN model of the MTS has been used in a case study for the quantification of HOF in the risk analysis carried out at the preliminary design stage of High Speed Craft (HSC). The study has focused on a collision in open sea hazard carried out by means of an original method of integration of a Fault Tree Analysis (FTA) of technical elements with a BBN model of the influences of organisational functions and regulations, as suggested by the International Maritime Organisation's (IMO) Guidelines for Formal Safety Assessment (FSA). The approach has allowed the identification of probabilistic correlations between the basic events of a collision accident and the BBN model of the operational and organisational conditions. The linkage can be exploited in different ways, especially to support identification and evaluation of risk control options also at the organisational level. Conditional probabilities for the BBN have been estimated by means of experts' judgments, collected from an international panel of different European countries. Finally, a sensitivity analysis has been carried out over the model to identify configurations of the MTS leading to a significant reduction of accident probability during the operation of the HSC

  2. Estimating safety effects of pavement management factors utilizing Bayesian random effect models.

    Science.gov (United States)

    Jiang, Ximiao; Huang, Baoshan; Zaretzki, Russell L; Richards, Stephen; Yan, Xuedong

    2013-01-01

    Previous studies of pavement management factors that relate to the occurrence of traffic-related crashes are rare. Traditional research has mostly employed summary statistics of bidirectional pavement quality measurements in extended longitudinal road segments over a long time period, which may cause a loss of important information and result in biased parameter estimates. The research presented in this article focuses on crash risk of roadways with overall fair to good pavement quality. Real-time and location-specific data were employed to estimate the effects of pavement management factors on the occurrence of crashes. This research is based on the crash data and corresponding pavement quality data for the Tennessee state route highways from 2004 to 2009. The potential temporal and spatial correlations among observations caused by unobserved factors were considered. Overall 6 models were built accounting for no correlation, temporal correlation only, and both the temporal and spatial correlations. These models included Poisson, negative binomial (NB), one random effect Poisson and negative binomial (OREP, ORENB), and two random effect Poisson and negative binomial (TREP, TRENB) models. The Bayesian method was employed to construct these models. The inference is based on the posterior distribution from the Markov chain Monte Carlo (MCMC) simulation. These models were compared using the deviance information criterion. Analysis of the posterior distribution of parameter coefficients indicates that the pavement management factors indexed by Present Serviceability Index (PSI) and Pavement Distress Index (PDI) had significant impacts on the occurrence of crashes, whereas the variable rutting depth was not significant. Among other factors, lane width, median width, type of terrain, and posted speed limit were significant in affecting crash frequency. The findings of this study indicate that a reduction in pavement roughness would reduce the likelihood of traffic

  3. A hierarchical model for ordinal matrix factorization

    DEFF Research Database (Denmark)

    Paquet, Ulrich; Thomson, Blaise; Winther, Ole

    2012-01-01

    This paper proposes a hierarchical probabilistic model for ordinal matrix factorization. Unlike previous approaches, we model the ordinal nature of the data and take a principled approach to incorporating priors for the hidden variables. Two algorithms are presented for inference, one based...

  4. Cloud Computing Adoption Business Model Factors: Does Enterprise Size Matter?

    OpenAIRE

    Bogataj Habjan, Kristina; Pucihar, Andreja

    2017-01-01

    This paper presents the results of research investigating the impact of business model factors on cloud computing adoption. The introduced research model consists of 40 cloud computing business model factors, grouped into eight factor groups. Their impact and importance for cloud computing adoption were investigated among enterpirses in Slovenia. Furthermore, differences in opinion according to enterprise size were investigated. Research results show no statistically significant impacts of in...

  5. Positive Orientation and the Five-Factor Model

    Directory of Open Access Journals (Sweden)

    Miciuk Łukasz Roland

    2016-04-01

    Full Text Available The aim of the present study was to investigate the relationship between positive orientation (PO defined as a basic predisposition to perceive and evaluate positive aspects of life, the future and oneself and the Five-Factor Model of personality (FFM. Hypotheses postulated positive correlations between PO and extraversion, conscientiousness, agreeableness and openness; a negative correlation was predicted between PO and neuroticism. Two hundred Polish students completed the following measures: SES (Self-Esteem Scale, Rosenberg, SWLS (The Satisfaction with Life Scale; Diener, Emmons, Larson & Griffin, LOT-R (The Life Orientation Test - Revised; Scheier, Carver & Bridges and NEOFFI (NEO Five Factor Inventory, Costa & McCrae. The results confirmed correlations between PO and extraversion, conscientiousness, and neuroticism; correlations with openness and agreeableness were not supported. According to canonical correlations, PO shows a clear affinity to the FFM.

  6. A quantitative assessment of organizational factors affecting safety using a system dynamics model

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, J. K. [Systemix Company, Seoul (Korea, Republic of); Yoon, T. S. [Korea Electric Power Research Institute (Korea, Republic of)

    2003-07-01

    The purpose of this study is to develop a system dynamics model for the assessment of organizational and human factors in the nuclear power plant safety. Previous studies are classified into two major approaches. One is the engineering approach such as ergonomics and Probabilistic Safety Assessment (PSA). The other is socio-psychology one. Both have contributed to find organizational and human factors and increased nuclear safety However, since these approaches assume that the relationship among factors is independent they do not explain the interactions between factors or variables in NPP's. To overcome these restrictions, a system dynamics model, which can show causal relations between factors and quantify organizational and human factors, has been developed. Operating variables such as degree of leadership, adjustment of number of employee, and workload in each department, users can simulate various situations in nuclear power plants in the organization side. Through simulation, user can get an insight to improve safety in plants and to find managerial tools in the organization and human side.

  7. The Critical Factors of Scrum Implementation in IT Project - the Case Study

    Directory of Open Access Journals (Sweden)

    Aneta Ozierańska

    2016-07-01

    Full Text Available The paper first presents basic information about the Scrum method. Then it summarizes the state of art in the domain of Scrum implementation, especially as far as the critical factors of its success are concerned. On the basis of literature survey a new model classifying Scrum implementation critical factors is proposed. The model divides Scrum implementation critical factors into five categories: Project Team factors, Psychological and cultural factors, Process and Method, Environment and Technology. The model is then developed and verified using the case study method. The research was carried out in a French IT company by means of a participating observation. The company was implementing Scrum, which ended up as a success. A journal of the Scrum implementation was conducted, presenting the experiences of the Scrum Team, their opinions and changes in the Scrum method which were introduced. On its basis critical factors, crucial for the success of Scrum implementation, classified according to the above mentioned model, were identified, completing those which had been found in the literaturę.

  8. Critical Success Factors of Mobile Application Development Projects: A Qualitative Study

    Directory of Open Access Journals (Sweden)

    Hamza Khastar

    2016-07-01

    Full Text Available This study seeks to identify the critical success factors of teams in the application-development project. To achieve this goal, a qualitative approach and content analysis was utilized. Semi-structured interviews with 14 developers and experts was performed for data collection. A systematic review of previous research shows that after 9 critical success factors. With the analysis interviews, the CSf's raised to 12; including user experience, strategy and project management, support and promotion, business models, planning and goal setting, financial and budgeting, marketing and customer needs, infrastructure, technical issues and design, contextual factors, teamwork and staffing. The results show that the customer experience, teamwork and contextual factors are core categories in the research paradigm model.

  9. Rough electricity: a new fractal multi-factor model of electricity spot prices

    DEFF Research Database (Denmark)

    Bennedsen, Mikkel

    We introduce a new mathematical model of electricity spot prices which accounts for the most important stylized facts of these time series: seasonality, spikes, stochastic volatility and mean reversion. Empirical studies have found a possible fifth stylized fact, fractality, and our approach...... explicitly incorporates this into the model of the prices. Our setup generalizes the popular Ornstein Uhlenbeck-based multi-factor framework of Benth et al. (2007) and allows us to perform statistical tests to distinguish between an Ornstein Uhlenbeck-based model and a fractal model. Further, through...... the multi-factor approach we account for seasonality and spikes before estimating - and making inference on - the degree of fractality. This is novel in the literature and we present simulation evidence showing that these precautions are crucial to accurate estimation. Lastly, we estimate our model...

  10. Skyrme-model πNN form factor and nucleon-nucleon interaction

    International Nuclear Information System (INIS)

    Holzwarth, G.; Machleidt, R.

    1997-01-01

    We apply the strong πNN form factor, which emerges from the Skyrme model, in the two-nucleon system using a one-boson-exchange (OBE) model for the nucleon-nucleon (NN) interaction. Deuteron properties and phase parameters of NN scattering are reproduced well. In contrast to the form factor of monopole shape that is traditionally used in OBE models, the Skyrme form factor leaves low-momentum transfers essentially unaffected while it suppresses the high-momentum region strongly. It turns out that this behavior is very appropriate for models of the NN interaction and makes it possible to use a soft pion form factor in the NN system. As a consequence, the πN and the NN systems can be described using the same πNN form factor, which is impossible with the monopole. copyright 1997 The American Physical Society

  11. Reproductive Behavior and Personality Traits of the Five Factor Model

    NARCIS (Netherlands)

    Jokela, Markus; Alvergne, Alexandra; Pollet, Thomas V.; Lummaa, Virpi

    2011-01-01

    We examined associations between Five Factor Model personality traits and various outcomes of reproductive behavior in a sample of 15 729 women and men from the Wisconsin Longitudinal Study (WLS) and Midlife Development in the United States (MIDUS) survey. Personality and reproductive history was

  12. Risk Factors for Stroke-associated Pneumonia: A Prospective Cohort Study

    Directory of Open Access Journals (Sweden)

    Alexis Suárez Quesada

    2015-12-01

    Full Text Available Background: stroke-associated pneumonia prolongs hospital stay and is an important risk factor for morbidity and mortality. Objective: to determine risk factors for stroke-associated pneumonia. Methods: a prospective single-cohort study was conducted involving 390 patients aged 16-93 years who met clinical and neuroimaging criteria for acute stroke treated at the Carlos Manuel de Céspedes Hospital from January 2012 through March 2015. Univariate comparison of qualitative variables was performed by using the Kaplan-Meier method. The Cox regression model was applied for multivariate analysis of risk factors for pneumonia. The area under the ROC curve was used to determine the discriminatory power of the model. Results: two hundred thirteen patients (54.6 % with ischemic stroke and 177 (45.4 % with hemorrhagic stroke were studied. Cases of nosocomial pneumonia after acute stroke accounted for 25.4 %. Subjects who developed pneumonia had lower scores on the Glasgow scale and higher scores on the modified Rankin scale. The following risk factors were identified using the Cox regression model: Glasgow coma score (Exp (B: 0.687; 95 % CI 0.630 to 0.750 and stroke subtype (Exp (B: 1.723; 95 % CI 1.137 to 2.610. The area under the ROC curve was 0.88. Conclusions: the risk factors for the development of nosocomial pneumonia after acute stroke found were the level of consciousness and suffering a hemorrhagic stroke. Other influencing variables are chronic obstructive pulmonary disease and heart disease as a comorbid condition.

  13. Technical Note: Assessing predictive capacity and conditional independence of landslide predisposing factors for shallow landslide susceptibility models

    Directory of Open Access Journals (Sweden)

    S. Pereira

    2012-04-01

    Full Text Available The aim of this study is to identify the landslide predisposing factors' combination using a bivariate statistical model that best predicts landslide susceptibility. The best model is one that has simultaneously good performance in terms of suitability and predictive power and has been developed using variables that are conditionally independent. The study area is the Santa Marta de Penaguião council (70 km2 located in the Northern Portugal.

    In order to identify the best combination of landslide predisposing factors, all possible combinations using up to seven predisposing factors were performed, which resulted in 120 predictions that were assessed with a landside inventory containing 767 shallow translational slides. The best landslide susceptibility model was selected according to the model degree of fitness and on the basis of a conditional independence criterion. The best model was developed with only three landslide predisposing factors (slope angle, inverse wetness index, and land use and was compared with a model developed using all seven landslide predisposing factors.

    Results showed that it is possible to produce a reliable landslide susceptibility model using fewer landslide predisposing factors, which contributes towards higher conditional independence.

  14. Effective factors in providing holistic care: a qualitative study.

    Science.gov (United States)

    Zamanzadeh, Vahid; Jasemi, Madineh; Valizadeh, Leila; Keogh, Brian; Taleghani, Fariba

    2015-01-01

    Holistic care is a comprehensive model of caring. Previous studies have shown that most nurses do not apply this method. Examining the effective factors in nurses' provision of holistic care can help with enhancing it. Studying these factors from the point of view of nurses will generate real and meaningful concepts and can help to extend this method of caring. A qualitative study was used to identify effective factors in holistic care provision. Data gathered by interviewing 14 nurses from university hospitals in Iran were analyzed with a conventional qualitative content analysis method and by using MAXQDA (professional software for qualitative and mixed methods data analysis) software. Analysis of data revealed three main themes as effective factors in providing holistic care: The structure of educational system, professional environment, and personality traits. Establishing appropriate educational, management systems, and promoting religiousness and encouragement will induce nurses to provide holistic care and ultimately improve the quality of their caring.

  15. Effective factors in providing holistic care: A qualitative study

    Directory of Open Access Journals (Sweden)

    Vahid Zamanzadeh

    2015-01-01

    Full Text Available Background: Holistic care is a comprehensive model of caring. Previous studies have shown that most nurses do not apply this method. Examining the effective factors in nurses′ provision of holistic care can help with enhancing it. Studying these factors from the point of view of nurses will generate real and meaningful concepts and can help to extend this method of caring. Materials and Methods: A qualitative study was used to identify effective factors in holistic care provision. Data gathered by interviewing 14 nurses from university hospitals in Iran were analyzed with a conventional qualitative content analysis method and by using MAXQDA (professional software for qualitative and mixed methods data analysis software. Results: Analysis of data revealed three main themes as effective factors in providing holistic care: The structure of educational system, professional environment, and personality traits. Conclusion: Establishing appropriate educational, management systems, and promoting religiousness and encouragement will induce nurses to provide holistic care and ultimately improve the quality of their caring.

  16. Form factors in quantum integrable models with GL(3)-invariant R-matrix

    Energy Technology Data Exchange (ETDEWEB)

    Pakuliak, S., E-mail: pakuliak@theor.jinr.ru [Laboratory of Theoretical Physics, JINR, 141980 Dubna, Moscow Reg. (Russian Federation); Moscow Institute of Physics and Technology, 141700 Dolgoprudny, Moscow Reg. (Russian Federation); Institute of Theoretical and Experimental Physics, 117259 Moscow (Russian Federation); Ragoucy, E., E-mail: eric.ragoucy@lapth.cnrs.fr [Laboratoire de Physique Théorique LAPTH, CNRS and Université de Savoie, BP 110, 74941 Annecy-le-Vieux Cedex (France); Slavnov, N.A., E-mail: nslavnov@mi.ras.ru [Steklov Mathematical Institute, Moscow (Russian Federation)

    2014-04-15

    We study integrable models solvable by the nested algebraic Bethe ansatz and possessing GL(3)-invariant R-matrix. We obtain determinant representations for form factors of off-diagonal entries of the monodromy matrix. These representations can be used for the calculation of form factors and correlation functions of the XXX SU(3)-invariant Heisenberg chain.

  17. A factor analytic investigation of the Tripartite model of affect in a clinical sample of young Australians

    Directory of Open Access Journals (Sweden)

    Cosgrave Elizabeth M

    2008-09-01

    Full Text Available Abstract Background The Mood and Anxiety Symptom Questionnaire (MASQ was designed to specifically measure the Tripartite model of affect and is proposed to offer a delineation between the core components of anxiety and depression. Factor analytic data from adult clinical samples has shown mixed results; however no studies employing confirmatory factor analysis (CFA have supported the predicted structure of distinct Depression, Anxiety and General Distress factors. The Tripartite model has not been validated in a clinical sample of older adolescents and young adults. The aim of the present study was to examine the validity of the Tripartite model using scale-level data from the MASQ and correlational and confirmatory factor analysis techniques. Methods 137 young people (M = 17.78, SD = 2.63 referred to a specialist mental health service for adolescents and young adults completed the MASQ and diagnostic interview. Results All MASQ scales were highly inter-correlated, with the lowest correlation between the depression- and anxiety-specific scales (r = .59. This pattern of correlations was observed for all participants rating for an Axis-I disorder but not for participants without a current disorder (r = .18. Confirmatory factor analyses were conducted to evaluate the model fit of a number of solutions. The predicted Tripartite structure was not supported. A 2-factor model demonstrated superior model fit and parsimony compared to 1- or 3-factor models. These broad factors represented Depression and Anxiety and were highly correlated (r = .88. Conclusion The present data lend support to the notion that the Tripartite model does not adequately explain the relationship between anxiety and depression in all clinical populations. Indeed, in the present study this model was found to be inappropriate for a help-seeking community sample of older adolescents and young adults.

  18. Remarks on electromagnetic form factors of hadrons in the quark model

    International Nuclear Information System (INIS)

    Vainshtein, A.I.; Zakharov, V.I.

    1977-01-01

    Relations between the transversal and longitudinal parts of elastic and quasielastic form factors are studied within the quark model. It is shown that for an even number of the constituent quarks the longitudinal part dominates while for an odd number the transversal part is the largest one. Consequences form this result are considered for deuteron form factor and for matrix elements of the electromagnetic transitions between π, rho, A 1 mesons

  19. Risk factors and prognostic models for perinatal asphyxia at term

    NARCIS (Netherlands)

    Ensing, S.

    2015-01-01

    This thesis will focus on the risk factors and prognostic models for adverse perinatal outcome at term, with a special focus on perinatal asphyxia and obstetric interventions during labor to reduce adverse pregnancy outcomes. For the majority of the studies in this thesis we were allowed to use data

  20. Studying psychosocial adaptation to end-stage renal disease: the proximal-distal model of health-related outcomes as a base model.

    Science.gov (United States)

    Chan, Ramony; Brooks, Robert; Erlich, Jonathan; Gallagher, Martin; Snelling, Paul; Chow, Josephine; Suranyi, Michael

    2011-05-01

    Studying psychosocial adaptation in end-stage renal disease (ESRD) is increasingly important, as it may explain the variability in health outcomes unaccounted for by clinical factors. The Brenner et al. proximal-distal model of health-related outcomes provides a theoretical foundation for understanding psychosocial adaptation and integrating health outcomes, clinical, and psychosocial factors (Brenner MH, Curbow B, Legro MW. The proximal-distal continuum of multiple health outcome measures: the case of cataract surgery. Med Care. 1995;33(4 Suppl):AS236-44). This study aims to empirically validate the proximal-distal model in the dialysis population and examine the impact of psychosocial factors on the model. A cross-sectional observational study was conducted with a sample of long-term dialysis patients (n=201). Eleven factors: quality of life (QoL), depression, positive affect, comorbidity, symptoms, physical functioning, disease accommodation, loss, self-efficacy, illness acceptance, and social support were measured by standardized psychometric scales. A three-month average of hemoglobin was used. Latent composite structural equation modeling was used to examine the models. The proximal-distal model with slight modification was supported by fit statistics [χ(2)=16.04, df=13, P=.25, root mean square error of approximation (RMSEA)=0.024], indicating that the impact of clinical factors on QoL is mediated through a range of functional and psychological factors, except for hemoglobin which impacts directly on QoL. The model with additional psychosocial factors was also supported by fit statistics (χ(2)=43.59, df=41, P=.36, RMSEA=0.018). These additional factors mainly impact on symptom status, psychological states, and QoL components of the model. The present study supported the proximal-distal model in the dialysis population and demonstrated the considerable impact of psychosocial factors on the model. The proximal-distal model plus psychosocial factors as a

  1. Generalized Efficient Inference on Factor Models with Long-Range Dependence

    DEFF Research Database (Denmark)

    Ergemen, Yunus Emre

    . Short-memory dynamics are allowed in the common factor structure and possibly heteroskedastic error term. In the estimation, a generalized version of the principal components (PC) approach is proposed to achieve efficiency. Asymptotics for efficient common factor and factor loading as well as long......A dynamic factor model is considered that contains stochastic time trends allowing for stationary and nonstationary long-range dependence. The model nests standard I(0) and I(1) behaviour smoothly in common factors and residuals, removing the necessity of a priori unit-root and stationarity testing...

  2. Parallelized preconditioned model building algorithm for matrix factorization

    OpenAIRE

    Kaya, Kamer; Birbil, İlker; Birbil, Ilker; Öztürk, Mehmet Kaan; Ozturk, Mehmet Kaan; Gohari, Amir

    2017-01-01

    Matrix factorization is a common task underlying several machine learning applications such as recommender systems, topic modeling, or compressed sensing. Given a large and possibly sparse matrix A, we seek two smaller matrices W and H such that their product is as close to A as possible. The objective is minimizing the sum of square errors in the approximation. Typically such problems involve hundreds of thousands of unknowns, so an optimizer must be exceptionally efficient. In this study, a...

  3. Factors affecting strategic plan implementation using interpretive structural modeling (ISM).

    Science.gov (United States)

    Bahadori, Mohammadkarim; Teymourzadeh, Ehsan; Tajik, Hamidreza; Ravangard, Ramin; Raadabadi, Mehdi; Hosseini, Seyed Mojtaba

    2018-06-11

    Purpose Strategic planning is the best tool for managers seeking an informed presence and participation in the market without surrendering to changes. Strategic planning enables managers to achieve their organizational goals and objectives. Hospital goals, such as improving service quality and increasing patient satisfaction cannot be achieved if agreed strategies are not implemented. The purpose of this paper is to investigate the factors affecting strategic plan implementation in one teaching hospital using interpretive structural modeling (ISM). Design/methodology/approach The authors used a descriptive study involving experts and senior managers; 16 were selected as the study sample using a purposive sampling method. Data were collected using a questionnaire designed and prepared based on previous studies. Data were analyzed using ISM. Findings Five main factors affected strategic plan implementation. Although all five variables and factors are top level, "senior manager awareness and participation in the strategic planning process" and "creating and maintaining team participation in the strategic planning process" had maximum drive power. "Organizational structure effects on the strategic planning process" and "Organizational culture effects on the strategic planning process" had maximum dependence power. Practical implications Identifying factors affecting strategic plan implementation is a basis for healthcare quality improvement by analyzing the relationship among factors and overcoming the barriers. Originality/value The authors used ISM to analyze the relationship between factors affecting strategic plan implementation.

  4. Innovative supply chain optimization models with multiple uncertainty factors

    DEFF Research Database (Denmark)

    Choi, Tsan Ming; Govindan, Kannan; Li, Xiang

    2017-01-01

    Uncertainty is an inherent factor that affects all dimensions of supply chain activities. In today’s business environment, initiatives to deal with one specific type of uncertainty might not be effective since other types of uncertainty factors and disruptions may be present. These factors relate...... to supply chain competition and coordination. Thus, to achieve a more efficient and effective supply chain requires the deployment of innovative optimization models and novel methods. This preface provides a concise review of critical research issues regarding innovative supply chain optimization models...

  5. The Earnings/Price Risk Factor in Capital Asset Pricing Models

    Directory of Open Access Journals (Sweden)

    Rafael Falcão Noda

    2015-01-01

    Full Text Available This article integrates the ideas from two major lines of research on cost of equity and asset pricing: multi-factor models and ex ante accounting models. The earnings/price ratio is used as a proxy for the ex ante cost of equity, in order to explain realized returns of Brazilian companies within the period from 1995 to 2013. The initial finding was that stocks with high (low earnings/price ratios have higher (lower risk-adjusted realized returns, already controlled by the capital asset pricing model's beta. The results show that selecting stocks based on high earnings/price ratios has led to significantly higher risk-adjusted returns in the Brazilian market, with average abnormal returns close to 1.3% per month. We design asset pricing models including an earnings/price risk factor, i.e. high earnings minus low earnings, based on the Fama and French three-factor model. We conclude that such a risk factor is significant to explain returns on portfolios, even when controlled by size and market/book ratios. Models including the high earnings minus low earnings risk factor were better to explain stock returns in Brazil when compared to the capital asset pricing model and to the Fama and French three-factor model, having the lowest number of significant intercepts. These findings may be due to the impact of historically high inflation rates, which reduce the information content of book values, thus making the models based on earnings/price ratios better than those based on market/book ratios. Such results are different from those obtained in more developed markets and the superiority of the earnings/price ratio for asset pricing may also exist in other emerging markets.

  6. Study of Influencing Factors on ConsumerOnline Impulse Buying

    Institute of Scientific and Technical Information of China (English)

    2015-01-01

    The convenience and anonymity of online shopping have stimulated people's impulse buying tendency. Impulse buying is notonly a competitive method for businesses, but also a crucial factor influencing sales of e-commerce. Based on a systematic reviewof literatures, this paper explores factors affecting the online impulse buying. Moreover, by using the S-O-R model, this paperdescribes the formation mechanism of the online impulse buying behavior. At Last, it points out issues worthy of future studies.For example, this paper suggests to take into consideration of sociocultural impact and to put more emphasis on empirical studies.

  7. A six-factor model of brand personality and its predictive validity

    Directory of Open Access Journals (Sweden)

    Živanović Marko

    2017-01-01

    Full Text Available The study examines applicability and usefulness of HEXACO-based model in the description of brand personality. Following contemporary theoretical developments in human personality research, Study 1 explored the latent personality structure of 120 brands using descriptors of six personality traits as defined in HEXACO model: Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, and Openness. The results of exploratory factor analyses have supported HEXACO personality six-factor structure to a large extent. In Study 2 we addressed the question of predictive validity of HEXACO-based brand personality. Brand personality traits, but predominantly Honesty-Humility, accounted for substantial amount of variance in prediction of important aspects of consumer-brand relationship: attitude toward brand, perceived quality of a brand, and brand loyalty. The implications of applying HEXACO-based brand personality in marketing research are discussed. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. 179018 and Grant no. 175012

  8. Factors Affecting Acceptance of Hospital Information Systems Based on Extended Technology Acceptance Model: A Case Study in Three Paraclinical Departments.

    Science.gov (United States)

    Nadri, Hamed; Rahimi, Bahlol; Lotfnezhad Afshar, Hadi; Samadbeik, Mahnaz; Garavand, Ali

    2018-04-01

     Regardless of the acceptance of users, information and communication systems can be considered as a health intervention designed to improve the care delivered to patients. This study aimed to determine the adoption and use of the extended Technology Acceptance Model (TAM2) by the users of hospital information system (HIS) in paraclinical departments including laboratory, radiology, and nutrition and to investigate the key factors of adoption and use of these systems.  A standard questionnaire was used to collect the data from nearly 253 users of these systems in paraclinical departments of eight university hospitals in two different cities of Iran. A total of 202 questionnaires including valid responses were used in this study (105 in Urmia and 97 in Khorramabad). The data were processed using LISREL and SPSS software and statistical analysis technique was based on the structural equation modeling (SEM).  It was found that the original TAM constructs had a significant impact on the staffs' behavioral intention to adopt HIS in paraclinical departments. The results of this study indicated that cognitive instrumental processes (job relevance, output quality, result demonstrability, and perceived ease of use), except for result demonstrability, were significant predictors of intention to use, whereas the result revealed no significant relationship between social influence processes (subjective norm, voluntariness, and image) and the users' behavioral intention to use the system.  The results confirmed that several factors in the TAM2 that were important in previous studies were not significant in paraclinical departments and in government-owned hospitals. The users' behavior factors are essential for successful usage of the system and should be considered. It provides valuable information for hospital system providers and policy makers in understanding the adoption challenges as well as practical guidance for the successful implementation of information

  9. Mathematical models for prediction of safety factors for a simply ...

    African Journals Online (AJOL)

    From the results obtained, mathematical prediction models were developed using a least square regression analysis for bending, shear and deflection modes of failure considered in the study. The results showed that the safety factors for material, dead and live load are not unique, but they are influenced by safety index ...

  10. The Predictive Effect of Big Five Factor Model on Social Reactivity ...

    African Journals Online (AJOL)

    The study tested a model of providing a predictive explanation of Big Five Factor on social reactivity among secondary school adolescents of Cross River State, Nigeria. A sample of 200 students randomly selected across 12 public secondary schools in the State participated in the study (120 male and 80 female). Data ...

  11. Factor structure and internal reliability of an exercise health belief model scale in a Mexican population

    Directory of Open Access Journals (Sweden)

    Oscar Armando Esparza-Del Villar

    2017-03-01

    Full Text Available Abstract Background Mexico is one of the countries with the highest rates of overweight and obesity around the world, with 68.8% of men and 73% of women reporting both. This is a public health problem since there are several health related consequences of not exercising, like having cardiovascular diseases or some types of cancers. All of these problems can be prevented by promoting exercise, so it is important to evaluate models of health behaviors to achieve this goal. Among several models the Health Belief Model is one of the most studied models to promote health related behaviors. This study validates the first exercise scale based on the Health Belief Model (HBM in Mexicans with the objective of studying and analyzing this model in Mexico. Methods Items for the scale called the Exercise Health Belief Model Scale (EHBMS were developed by a health research team, then the items were applied to a sample of 746 participants, male and female, from five cities in Mexico. The factor structure of the items was analyzed with an exploratory factor analysis and the internal reliability with Cronbach’s alpha. Results The exploratory factor analysis reported the expected factor structure based in the HBM. The KMO index (0.92 and the Barlett’s sphericity test (p < 0.01 indicated an adequate and normally distributed sample. Items had adequate factor loadings, ranging from 0.31 to 0.92, and the internal consistencies of the factors were also acceptable, with alpha values ranging from 0.67 to 0.91. Conclusions The EHBMS is a validated scale that can be used to measure exercise based on the HBM in Mexican populations.

  12. The multi-factor energy input–output model

    International Nuclear Information System (INIS)

    Guevara, Zeus; Domingos, Tiago

    2017-01-01

    Energy input–output analysis (EIO analysis) is a noteworthy tool for the analysis of the role of energy in the economy. However, it has relied on models that provide a limited description of energy flows in the economic system and do not allow an adequate analysis of energy efficiency. This paper introduces a novel energy input–output model, the multi-factor energy input–output model (MF-EIO model), which is obtained from a partitioning of a hybrid-unit input–output system of the economy. This model improves on current models by describing the energy flows according to the processes of energy conversion and the levels of energy use in the economy. It characterizes the vector of total energy output as a function of seven factors: two energy efficiency indicators; two characteristics of end-use energy consumption; and three economic features of the rest of the economy. Moreover, it is consistent with the standard model for EIO analysis, i.e., the hybrid-unit model. This paper also introduces an approximate version of the MF-EIO model, which is equivalent to the former under equal energy prices for industries and final consumers, but requires less data processing. The latter is composed by two linked models: a model of the energy sector in physical units, and a model of the rest of the economy in monetary units. In conclusion, the proposed modelling framework improves EIO analysis and extends EIO applications to the accounting for energy efficiency of the economy. - Highlights: • A novel energy input–output model is introduced. • It allows a more adequate analysis of energy flows than current models. • It describes energy flows according to processes of energy conversion and use. • It can be used for other environmental applications (material use and emissions). • An approximate version of the model is introduced, simpler and less data intensive.

  13. Situational Factors in Focus Group Studies: A Systematic Review

    Directory of Open Access Journals (Sweden)

    Arne Orvik MPolSc

    2013-02-01

    Full Text Available The aim of this study was to see how contextual factors are expressed, used, and analyzed in data collected in focus group discussions (FGDs. The study includes an assessment of how the methodological reporting of contextual factors might influence and improve the trustworthiness of articles. Articles reporting workplace health, stress, and coping among health professionals were identified in a systematic review and used in the analysis. By using Vicsek's framework of situational factors for analysis of focus group results as a starting point, we found that contextual factors were most frequently described in the method sections and less frequently in the results and discussion sections. Vicsek's framework for the analysis of focus group results covers six contextual and methodological dimensions: interactional factors, personal characteristics of the participants, the moderator, the environment, time factors, and the content of FGDs. We found that the framework does not include a consideration of psychological safety, ethical issues, or organizational information. To deepen the analysis of focus group results, we argue that contextual factors should be analyzed as methodological dimensions and be considered as a sensitizing concept. Credibility, confirmability, dependability, and transferability can be strengthened by using, reporting, and discussing contextual factors in detail. The study contributes to elucidating how reporting of contextual data may enrich the analysis of focus group results and strengthen the trustworthiness. Future research should focus on clear reporting of contextual factors as well as further develop Vicsek's model to enhance reporting accuracy and transferability.

  14. Risk modelling study for carotid endarterectomy.

    Science.gov (United States)

    Kuhan, G; Gardiner, E D; Abidia, A F; Chetter, I C; Renwick, P M; Johnson, B F; Wilkinson, A R; McCollum, P T

    2001-12-01

    The aims of this study were to identify factors that influence the risk of stroke or death following carotid endarterectomy (CEA) and to develop a model to aid in comparative audit of vascular surgeons and units. A series of 839 CEAs performed by four vascular surgeons between 1992 and 1999 was analysed. Multiple logistic regression analysis was used to model the effect of 15 possible risk factors on the 30-day risk of stroke or death. Outcome was compared for four surgeons and two units after adjustment for the significant risk factors. The overall 30-day stroke or death rate was 3.9 per cent (29 of 741). Heart disease, diabetes and stroke were significant risk factors. The 30-day predicted stroke or death rates increased with increasing risk scores. The observed 30-day stroke or death rate was 3.9 per cent for both vascular units and varied from 3.0 to 4.2 per cent for the four vascular surgeons. Differences in the outcomes between the surgeons and vascular units did not reach statistical significance after risk adjustment. Diabetes, heart disease and stroke are significant risk factors for stroke or death following CEA. The risk score model identified patients at higher risk and aided in comparative audit.

  15. John Carroll’s Views on Intelligence: Bi-Factor vs. Higher-Order Models

    Directory of Open Access Journals (Sweden)

    A. Alexander Beaujean

    2015-10-01

    Full Text Available The development of factor models is inextricably tied to the history of intelligence research. One of the most commonly-cited scholars in the field is John Carroll, whose three-stratum theory of cognitive ability has been one of the most influential models of cognitive ability in the past 20 years. Nonetheless, there is disagreement about how Carroll conceptualized the factors in his model. Some argue that his model is best represented through a higher-order model, while others argue that a bi-factor model is a better representation. Carroll was explicit about what he perceived the best way to represent his model, but his writings are not always easy to understand. In this article, I clarify his position by first describing the details and implications of bi-factor and higher-order models then show that Carroll’s published views are better represented by a bi-factor model.

  16. An Explanatory Model of Dating Violence Risk Factors in Spanish Adolescents.

    Science.gov (United States)

    Aizpitarte, Alazne; Alonso-Arbiol, Itziar; Van de Vijver, Fons J R

    2017-12-01

    Dating violence is a serious public health issue that needs further understanding in terms of risk factors that may be involved in it. The main goal of this study was to test a mediational model of dating violence risk factors. The sample was composed of 477 secondary and college students from Spain (59% females). A dynamic developmental explanatory model considering aggressiveness, insecure attachment, interparental conflict, and peer dating violence was tested using a multigroup structural equation model. Aggressiveness partially mediated the relation between anxious attachment and dating violence and fully mediated the association between interparental conflict resolution and dating violence. Furthermore, perceived peer dating violence was a direct predictor of dating violence. Implications for prevention and intervention plans are discussed. © 2017 The Authors. Journal of Research on Adolescence © 2017 Society for Research on Adolescence.

  17. Workforce scheduling: A new model incorporating human factors

    Directory of Open Access Journals (Sweden)

    Mohammed Othman

    2012-12-01

    Full Text Available Purpose: The majority of a company’s improvement comes when the right workers with the right skills, behaviors and capacities are deployed appropriately throughout a company. This paper considers a workforce scheduling model including human aspects such as skills, training, workers’ personalities, workers’ breaks and workers’ fatigue and recovery levels. This model helps to minimize the hiring, firing, training and overtime costs, minimize the number of fired workers with high performance, minimize the break time and minimize the average worker’s fatigue level.Design/methodology/approach: To achieve this objective, a multi objective mixed integer programming model is developed to determine the amount of hiring, firing, training and overtime for each worker type.Findings: The results indicate that the worker differences should be considered in workforce scheduling to generate realistic plans with minimum costs. This paper also investigates the effects of human fatigue and recovery on the performance of the production systems.Research limitations/implications: In this research, there are some assumptions that might affect the accuracy of the model such as the assumption of certainty of the demand in each period, and the linearity function of Fatigue accumulation and recovery curves. These assumptions can be relaxed in future work.Originality/value: In this research, a new model for integrating workers’ differences with workforce scheduling is proposed. To the authors' knowledge, it is the first time to study the effects of different important human factors such as human personality, skills and fatigue and recovery in the workforce scheduling process. This research shows that considering both technical and human factors together can reduce the costs in manufacturing systems and ensure the safety of the workers.

  18. Analyzing Factors Influencing Teaching as a Career Choice Using Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Budhinath Padhy

    2015-02-01

    Full Text Available The purpose of the study is to analyze factors influencing students’ perceptions of teaching as a career choice using structural equation modeling with the goal of shaping a teacher education recruitment program. In this study, 458 students from a Midwestern university in the United States responded to an online survey about career-related factors they value, their expectation that teaching would offer those factors, and any social-influence factors that might encourage them to choose a teaching career. The effect of 10 exogenous motivation variables (value-environment, value-intrinsic, value-extrinsic, value-altruistic, expectancy-environment, expectancy-intrinsic, expectancy-extrinsic, social-media-education, social-prior-experience, and social-suggestions on choosing a teaching career was examined. Results of our analysis showed that the factors related to expectancy-environment, expectancy-intrinsic, social-media-education, social-prior-experience, and social-suggestions were found to be significant, whereas value-related factors and expectancy-extrinsic factors were found to be insignificant.

  19. System dynamics modeling of social/political factors in nuclear power plant operations

    International Nuclear Information System (INIS)

    Hansen, K.F.; Turek, M.G.; Eubanks, C.K.

    1995-01-01

    The safety and performance of nuclear power plants are a function of many technical factors such as initial design, service and maintenance programs, and utility investment in improvements. Safety and performance are also a function of the social/political influences that affect requirements on personnel, practices and procedures, and resource availability. This paper describes a process for constructing models of the social/political influences on plant operations using the system dynamics technique. The model incorporates representation of internal utility actions and decisions as affected by external factors such as public opinion, intervenor actions, safety and economic regulation, and the financial community. The feedback between external agents and plant performance is explicitly modeled. The resulting model can be used to simulate performance under a variety of different external and internal policy choices. In particular, the model can be used to study means of improving performance in response to externally imposed regulations

  20. [Success factors in public healthy eating campaigns: a case study].

    Science.gov (United States)

    Aschemann-Witzel, J; Pérez-Cueto, F J A; Strand, M; Verbeke, W; Bech-Larsen, T

    2012-01-01

    Public campaigns and interventions are rarely fully evaluated regarding their effectiveness. The analysis of past, successful activities can contribute to the future development of public campaigns and interventions for healthier eating. The study of public campaigns and interventions for healthier eating aimed at identifying the underlying success factors and describing their relation. Interviews were conducted with representatives of 11 cases that had been identified as especially successful in an earlier research step. The interviews were analysed with regard to possible success factors and the latter used to develop a model of success factor interrelation. It was found that success of the cases was first, attributed to characteristics of the macro environment or to public private partnerships in the initiation of campaigns, second, to the engagement of social communities, elements of empowerment of the target group and the implementation of social marketing measures, and thirdly, in citizens adoption of the campaign and in accompanying structural changes. The model and identified success factors underline that success can stem from three crucial phases: the set up of a campaign, the conduction and finally, the interrelation with the citizen. The model can serve as a guide in the future development of campaigns.

  1. Factors influencing the renal arterial Doppler waveform: a simulation study using an electrical circuit model (secondary publication)

    Energy Technology Data Exchange (ETDEWEB)

    Sung, Chang Kyu [Dept. of Radiology, SMG-SNU Boramae Medical Center, Seoul National University College of Medicine, Seoul (Korea, Republic of); Han, Bong Soo [Dept. of Radiological Science, College of Health Science, Yonsei University, Wonju (Korea, Republic of); Kim, Seung Hyup [Dept. of Radiology, Institute of Radiation Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul (Korea, Republic of)

    2016-01-15

    The goal of this study was to evaluate the effect of vascular compliance, resistance, and pulse rate on the resistive index (RI) by using an electrical circuit model to simulate renal blood flow. In order to analyze the renal arterial Doppler waveform, we modeled the renal blood-flow circuit with an equivalent simple electrical circuit containing resistance, inductance, and capacitance. The relationships among the impedance, resistance, and compliance of the circuit were derived from well-known equations, including Kirchhoff’s current law for alternating current circuits. Simulated velocity-time profiles for pulsatile flow were generated using Mathematica (Wolfram Research) and the influence of resistance, compliance, and pulse rate on waveforms and the RI was evaluated. Resistance and compliance were found to alter the waveforms independently. The impedance of the circuit increased with increasing proximal compliance, proximal resistance, and distal resistance. The impedance decreased with increasing distal compliance. The RI of the circuit decreased with increasing proximal compliance and resistance. The RI increased with increasing distal compliance and resistance. No positive correlation between impedance and the RI was found. Pulse rate was found to be an extrinsic factor that also influenced the RI. This simulation study using an electrical circuit model led to a better understanding of the renal arterial Doppler waveform and the RI, which may be useful for interpreting Doppler findings in various clinical settings.

  2. Factors influencing the renal arterial Doppler waveform: a simulation study using an electrical circuit model (secondary publication)

    International Nuclear Information System (INIS)

    Sung, Chang Kyu; Han, Bong Soo; Kim, Seung Hyup

    2016-01-01

    The goal of this study was to evaluate the effect of vascular compliance, resistance, and pulse rate on the resistive index (RI) by using an electrical circuit model to simulate renal blood flow. In order to analyze the renal arterial Doppler waveform, we modeled the renal blood-flow circuit with an equivalent simple electrical circuit containing resistance, inductance, and capacitance. The relationships among the impedance, resistance, and compliance of the circuit were derived from well-known equations, including Kirchhoff’s current law for alternating current circuits. Simulated velocity-time profiles for pulsatile flow were generated using Mathematica (Wolfram Research) and the influence of resistance, compliance, and pulse rate on waveforms and the RI was evaluated. Resistance and compliance were found to alter the waveforms independently. The impedance of the circuit increased with increasing proximal compliance, proximal resistance, and distal resistance. The impedance decreased with increasing distal compliance. The RI of the circuit decreased with increasing proximal compliance and resistance. The RI increased with increasing distal compliance and resistance. No positive correlation between impedance and the RI was found. Pulse rate was found to be an extrinsic factor that also influenced the RI. This simulation study using an electrical circuit model led to a better understanding of the renal arterial Doppler waveform and the RI, which may be useful for interpreting Doppler findings in various clinical settings

  3. Factor structure of a conceptual model of oral health tested among 65-year olds in Norway and Sweden.

    Science.gov (United States)

    Astrøm, Anne Nordrehaug; Ekbäck, Gunnar; Ordell, Sven

    2010-04-01

    No studies have tested oral health-related quality of life models in dentate older adults across different populations. To test the factor structure of oral health outcomes within Gilbert's conceptual model among 65-year olds in Sweden and Norway. It was hypothesized that responses to 14 observed indicators could be explained by three correlated factors, symptom status, functional limitations and oral disadvantages, that each observed oral health indicator would associate more strongly with the factor it is supposed to measure than with competing factors and that the proposed 3-factor structure would possess satisfactory cross-national stability with 65-year olds in Norway and Sweden. In 2007, 6078 Swedish- and 4062 Norwegian adults borne in 1942 completed mailed questionnaires including oral symptoms, functional limitations and the eight item Oral Impacts on Daily Performances inventory. Model generation analysis was restricted to the Norwegian study group and the model achieved was tested without modifications in Swedish 65-year olds. A modified 3-factor solution with cross-loadings, improved the fit to the data compared with a 2-factor- and the initially proposed 3-factor model among the Norwegian [comparative fit index (CFI) = 0.97] and Swedish (CFI = 0.98) participants. All factor loadings for the modified 3-factor model were in the expected direction and were statistically significant at CR > 1. Multiple group confirmatory factor analyses, with Norwegian and Swedish data simultaneously revealed acceptable fit for the unconstrained model (CFI = 0.97), whereas unconstrained and constrained models were statistically significant different in nested model comparison. Within construct validity of Gilbert's model was supported with Norwegian and Swedish 65-year olds, indicating that the 14-item questionnaire reflected three constructs; symptom status, functional limitation and oral disadvantage. Measurement invariance was confirmed at the level of factor structure

  4. Quantifying credit portfolio losses under multi-factor models

    NARCIS (Netherlands)

    G. Colldeforns-Papiol (Gemma); L. Ortiz Gracia (Luis); C.W. Oosterlee (Kees)

    2018-01-01

    textabstractIn this work, we investigate the challenging problem of estimating credit risk measures of portfolios with exposure concentration under the multi-factor Gaussian and multi-factor t-copula models. It is well-known that Monte Carlo (MC) methods are highly demanding from the computational

  5. An updated summary of MATHEW/ADPIC model evaluation studies

    International Nuclear Information System (INIS)

    Foster, K.T.; Dickerson, M.H.

    1990-05-01

    This paper summarizes the major model evaluation studies conducted for the MATHEW/ADPIC atmospheric transport and diffusion models used by the US Department of Energy's Atmospheric Release Advisory Capability. These studies have taken place over the last 15 years and involve field tracer releases influenced by a variety of meteorological and topographical conditions. Neutrally buoyant tracers released both as surface and elevated point sources, as well as material dispersed by explosive, thermally bouyant release mechanisms have been studied. Results from these studies show that the MATHEW/ADPIC models estimate the tracer air concentrations to within a factor of two of the measured values 20% to 50% of the time, and within a factor of five of the measurements 35% to 85% of the time depending on the complexity of the meteorology and terrain, and the release height of the tracer. Comparisons of model estimates to peak downwind deposition and air concentration measurements from explosive releases are shown to be generally within a factor of two to three. 24 refs., 14 figs., 3 tabs

  6. SEARCHING THE FACTORS HAVING CREDIT CARD: A SURVEY STUDY IN ERZURUM

    Directory of Open Access Journals (Sweden)

    ERKAN OKTAY

    2013-06-01

    Full Text Available In this study, the factors related with having credit card in Erzurum have been searched by a logit model. There are demographic, social, cultural, and economic variables in the model. The final model is statistically significant. According to the model, job, average household income per month, payment method at shopping, usefulness of credit card and increasing the shopping tendency are statistically significant on having credit card.

  7. The Barrett–Crane model: asymptotic measure factor

    International Nuclear Information System (INIS)

    Kamiński, Wojciech; Steinhaus, Sebastian

    2014-01-01

    The original spin foam model construction for 4D gravity by Barrett and Crane suffers from a few troubling issues. In the simple examples of the vertex amplitude they can be summarized as the existence of contributions to the asymptotics from non-geometric configurations. Even restricted to geometric contributions the amplitude is not completely worked out. While the phase is known to be the Regge action, the so-called measure factor has remained mysterious for a decade. In the toy model case of the 6j symbol this measure factor has a nice geometric interpretation of V −1/2 leading to speculations that a similar interpretation should be possible also in the 4D case. In this paper we provide the first geometric interpretation of the geometric part of the asymptotic for the spin foam consisting of two glued 4-simplices (decomposition of the 4-sphere) in the Barrett–Crane model in the large internal spin regime. (paper)

  8. The Barrett-Crane model: asymptotic measure factor

    Science.gov (United States)

    Kamiński, Wojciech; Steinhaus, Sebastian

    2014-04-01

    The original spin foam model construction for 4D gravity by Barrett and Crane suffers from a few troubling issues. In the simple examples of the vertex amplitude they can be summarized as the existence of contributions to the asymptotics from non-geometric configurations. Even restricted to geometric contributions the amplitude is not completely worked out. While the phase is known to be the Regge action, the so-called measure factor has remained mysterious for a decade. In the toy model case of the 6j symbol this measure factor has a nice geometric interpretation of V-1/2 leading to speculations that a similar interpretation should be possible also in the 4D case. In this paper we provide the first geometric interpretation of the geometric part of the asymptotic for the spin foam consisting of two glued 4-simplices (decomposition of the 4-sphere) in the Barrett-Crane model in the large internal spin regime.

  9. Consumer's Online Shopping Influence Factors and Decision-Making Model

    Science.gov (United States)

    Yan, Xiangbin; Dai, Shiliang

    Previous research on online consumer behavior has mostly been confined to the perceived risk which is used to explain those barriers for purchasing online. However, perceived benefit is another important factor which influences consumers’ decision when shopping online. As a result, an integrated consumer online shopping decision-making model is developed which contains three elements—Consumer, Product, and Web Site. This model proposed relative factors which influence the consumers’ intention during the online shopping progress, and divided them into two different dimensions—mentally level and material level. We tested those factors with surveys, from both online volunteers and offline paper surveys with more than 200 samples. With the help of SEM, the experimental results show that the proposed model and method can be used to analyze consumer’s online shopping decision-making process effectively.

  10. Effects of source shape on the numerical aperture factor with a geometrical-optics model.

    Science.gov (United States)

    Wan, Der-Shen; Schmit, Joanna; Novak, Erik

    2004-04-01

    We study the effects of an extended light source on the calibration of an interference microscope, also referred to as an optical profiler. Theoretical and experimental numerical aperture (NA) factors for circular and linear light sources along with collimated laser illumination demonstrate that the shape of the light source or effective aperture cone is critical for a correct NA factor calculation. In practice, more-accurate results for the NA factor are obtained when a linear approximation to the filament light source shape is used in a geometric model. We show that previously measured and derived NA factors show some discrepancies because a circular rather than linear approximation to the filament source was used in the modeling.

  11. The risk factors of laryngeal pathology in Korean adults using a decision tree model.

    Science.gov (United States)

    Byeon, Haewon

    2015-01-01

    The purpose of this study was to identify risk factors affecting laryngeal pathology in the Korean population and to evaluate the derived prediction model. Cross-sectional study. Data were drawn from the 2008 Korea National Health and Nutritional Examination Survey. The subjects were 3135 persons (1508 male and 2114 female) aged 19 years and older living in the community. The independent variables were age, sex, occupation, smoking, alcohol drinking, and self-reported voice problems. A decision tree analysis was done to identify risk factors for predicting a model of laryngeal pathology. The significant risk factors of laryngeal pathology were age, gender, occupation, smoking, and self-reported voice problem in decision tree model. Four significant paths were identified in the decision tree model for the prediction of laryngeal pathology. Those identified as high risk groups for laryngeal pathology included those who self-reported a voice problem, those who were males in their 50s who did not recognize a voice problem, those who were not economically active males in their 40s, and male workers aged 19 and over and under 50 or 60 and over who currently smoked. The results of this study suggest that individual risk factors, such as age, sex, occupation, health behavior, and self-reported voice problem, affect the onset of laryngeal pathology in a complex manner. Based on the results of this study, early management of the high-risk groups is needed for the prevention of laryngeal pathology. Copyright © 2015 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  12. Factors Predicting Sustainability of the Schoolwide Positive Behavior Intervention Support Model

    Science.gov (United States)

    Chitiyo, Jonathan; May, Michael E.

    2018-01-01

    The Schoolwide Positive Behavior Intervention Support model (SWPBIS) continues to gain widespread use across schools in the United States and abroad. Despite its widespread implementation, little research has examined factors that influence its sustainability. Informed by Rogers's diffusion theory, this study examined school personnel's…

  13. A study to detect important factors influencing purchasing product: A case study of home appliances

    Directory of Open Access Journals (Sweden)

    Amir Ghafurian Shagerdi

    2013-07-01

    Full Text Available Home appliances are among basic requirements of anyone in the world and it is always important to find out about factors influencing this industry. Therefore, the purpose of this study is to provide a comprehensive model to detect major factors influencing on consumer purchasing intention. For this purpose, the proposed study designs a questionnaire and distributes it among 400 customers who have some experiences on purchasing home appliances in city of Tehran, Iran, recently. Cronbach alpha was calculated for all components of the survey and they were all well above the minimum acceptable level. We analyzed the data using structural equation modeling via LISREL and the results of this survey show that brand familiarity, brand trust, and perceived value have significant positive effects on consumers purchase intention.

  14. Functional significance of a novel 7-factor model of DSM-5 PTSD symptoms: results from the National Health and Resilience in Veterans study.

    Science.gov (United States)

    Pietrzak, Robert H; Tsai, Jack; Armour, Cherie; Mota, Natalie; Harpaz-Rotem, Ilan; Southwick, Steven M

    2015-03-15

    While posttraumatic stress disorder (PTSD) symptoms in the recently published Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) are clustered into four factors, emerging confirmatory factor analytic studies suggest that this disorder is best characterized by seven symptom clusters, including re-experiencing, avoidance, negative affect, anhedonia, externalizing behaviors, and anxious and dysphoric arousal symptoms. To date, however, data are lacking regarding the relation between this novel model of DSM-5 PTSD symptoms and measures of clinical significance in this population (e.g., functioning). Using data from the National Health and Resilience in Veterans Study (NHRVS), a contemporary, nationally representative sample of 1484 U.S. veterans, we evaluated clinical and functional correlates of a novel 7-factor model of DSM-5 PTSD symptoms. Differential patterns of associations were observed between DSM-5 PTSD symptom clusters, and psychiatric comorbidities, suicidal ideation, hostility, and functioning and quality of life. Anhedonia symptoms, in particular, were strongly related to current depression, as well as reduced mental functioning and quality of life. Externalizing behaviors were most strongly related to hostility, supporting the convergent validity of this construct. Cross-sectional design and employment of self-report measures. These results suggest that a more refined 7-factor model of DSM-5 PTSD symptoms may provide greater specificity in understanding associations with comorbid psychopathology, suicidal ideation, and functioning and quality of life in U.S. veterans. They further suggest that prevention and treatment efforts that target distinct aspects of the PTSD phenotype may be more effective in mitigating key clinical and functional outcomes in this population. Published by Elsevier B.V.

  15. The HEXACO and Five-Factor Models of Personality in Relation to RIASEC Vocational Interests

    Science.gov (United States)

    McKay, Derek A.; Tokar, David M.

    2012-01-01

    The current study extended the empirical research on the overlap of vocational interests and personality by (a) testing hypothesized relations between RIASEC interests and the personality dimensions of the HEXACO model, and (b) exploring the HEXACO personality model's predictive advantage over the five-factor model (FFM) in capturing RIASEC…

  16. Factors associated with leisure time physical inactivity in black individuals: hierarchical model

    Directory of Open Access Journals (Sweden)

    Francisco José Gondim Pitanga

    2014-09-01

    Full Text Available Background. A number of studies have shown that the black population exhibits higher levels of leisure-time physical inactivity (LTPI, but few have investigated the factors associated with this behavior.Objective. The aim of this study was to analyze associated factors and the explanatory model proposed for LTPI in black adults.Methods. The design was cross-sectional with a sample of 2,305 adults from 20–96 years of age, 902 (39.1% men, living in the city of Salvador, Brazil. LTPI was analyzed using the International Physical Activity Questionnaire (IPAQ. A hierarchical model was built with the possible factors associated with LTPI, distributed in distal (age and sex, intermediate 1 (socioeconomic status, educational level and marital status, intermediate 2 (perception of safety/violence in the neighborhood, racial discrimination in private settings and physical activity at work and proximal blocks (smoking and participation in Carnival block rehearsals. We estimated crude and adjusted odds ratio (OR using logistic regression.Results. The variables inversely associated with LTPI were male gender, socioeconomic status and secondary/university education, although the proposed model explains only 4.2% of LTPI.Conclusions. We conclude that male gender, higher education and socioeconomic status can reduce LTPI in black adults.

  17. An extended technology acceptance model for detecting influencing factors: An empirical investigation

    Directory of Open Access Journals (Sweden)

    Mohamd Hakkak

    2013-11-01

    Full Text Available The rapid diffusion of the Internet has radically changed the delivery channels applied by the financial services industry. The aim of this study is to identify the influencing factors that encourage customers to adopt online banking in Khorramabad. The research constructs are developed based on the technology acceptance model (TAM and incorporates some extra important control variables. The model is empirically verified to study the factors influencing the online banking adoption behavior of 210 customers of Tejarat Banks in Khorramabad. The findings of the study suggest that the quality of the internet connection, the awareness of online banking and its benefits, the social influence and computer self-efficacy have significant impacts on the perceived usefulness (PU and perceived ease of use (PEOU of online banking acceptance. Trust and resistance to change also have significant impact on the attitude towards the likelihood of adopting online banking.

  18. The structure of PTSD symptoms: a test of alternative models using confirmatory factor analysis.

    Science.gov (United States)

    Elklit, Ask; Shevlin, Mark

    2007-09-01

    This study aimed to examine the structure of self-reported post-traumatic stress disorder (PTSD) symptoms. Based on previous factor analytic findings and the DSM-IV formulation, six confirmatory factor models were specified and estimated that reflected different symptom clusters. The analyses were based on responses from 1116 participants who had suffered whiplash injuries and screened for full or subclinical PTSD using the Harvard Trauma Questionnaire. A correlated four-factor model with re-experiencing, avoidance, dysphoria and arousal factors fitted the data very well. Correlations with criteria measures showed that these factors were associated with other trauma related variables in a theoretically predictable way and showed evidence of unique predictive utility. These results concur with previous research findings using different trauma populations but do not reflect the current DSM-IV symptom groupings.

  19. Human Factor Modelling in the Risk Assessment of Port Manoeuvers

    Directory of Open Access Journals (Sweden)

    Teresa Abramowicz-Gerigk

    2015-09-01

    Full Text Available The documentation of human factor influence on the scenario development in maritime accidents compared with expert methods is commonly used as a basis in the process of setting up safety regulations and instructions. The new accidents and near misses show the necessity for further studies in determining the human factor influence on both risk acceptance criteria and development of risk control options for the manoeuvers in restricted waters. The paper presents the model of human error probability proposed for the assessment of ship masters and marine pilots' error decision and its influence on the risk of port manoeuvres.

  20. The relationship between the Five-Factor Model and latent DSM-IV personality disorder dimensions

    OpenAIRE

    Nestadt, Gerald; Costa, Paul T.; Hsu, Fang-Chi; Samuels, Jack; Bienvenu, O. Joseph; Eaton, William W.

    2007-01-01

    This study compared the latent structure of the DSM-IV personality disorders to the Five-Factor Model (FFM) of general personality dimensions. The subjects in the study were 742 community-residing individuals who participated in the Hopkins Epidemiology of Personality Disorder Study. DSM-IV personality disorder traits were assessed by psychologists using the International Personality Disorder Examination, and personality disorder dimensions were derived previously using dichotomous factor ana...

  1. Testing for time-varying loadings in dynamic factor models

    DEFF Research Database (Denmark)

    Mikkelsen, Jakob Guldbæk

    Abstract: In this paper we develop a test for time-varying factor loadings in factor models. The test is simple to compute and is constructed from estimated factors and residuals using the principal components estimator. The hypothesis is tested by regressing the squared residuals on the squared...... there is evidence of time-varying loadings on the risk factors underlying portfolio returns for around 80% of the portfolios....

  2. Factors associated with therapeutic inertia in hypertension: validation of a predictive model.

    Science.gov (United States)

    Redón, Josep; Coca, Antonio; Lázaro, Pablo; Aguilar, Ma Dolores; Cabañas, Mercedes; Gil, Natividad; Sánchez-Zamorano, Miguel Angel; Aranda, Pedro

    2010-08-01

    To study factors associated with therapeutic inertia in treating hypertension and to develop a predictive model to estimate the probability of therapeutic inertia in a given medical consultation, based on variables related to the consultation, patient, physician, clinical characteristics, and level of care. National, multicentre, observational, cross-sectional study in primary care and specialist (hospital) physicians who each completed a questionnaire on therapeutic inertia, provided professional data and collected clinical data on four patients. Therapeutic inertia was defined as a consultation in which treatment change was indicated (i.e., SBP >or= 140 or DBP >or= 90 mmHg in all patients; SBP >or= 130 or DBP >or= 80 in patients with diabetes or stroke), but did not occur. A predictive model was constructed and validated according to the factors associated with therapeutic inertia. Data were collected on 2595 patients and 13,792 visits. Therapeutic inertia occurred in 7546 (75%) of the 10,041 consultations in which treatment change was indicated. Factors associated with therapeutic inertia were primary care setting, male sex, older age, SPB and/or DBP values close to normal, treatment with more than one antihypertensive drug, treatment with an ARB II, and more than six visits/year. Physician characteristics did not weigh heavily in the association. The predictive model was valid internally and externally, with acceptable calibration, discrimination and reproducibility, and explained one-third of the variability in therapeutic inertia. Although therapeutic inertia is frequent in the management of hypertension, the factors explaining it are not completely clear. Whereas some aspects of the consultations were associated with therapeutic inertia, physician characteristics were not a decisive factor.

  3. Is There Really a Global Business Cycle? : A Dynamic Factor Model with Stochastic Factor Selection

    NARCIS (Netherlands)

    T. Berger (Tino); L.C.G. Pozzi (Lorenzo)

    2016-01-01

    textabstractWe investigate the presence of international business cycles in macroeconomic aggregates (output, consumption, investment) using a panel of 60 countries over the period 1961-2014. The paper presents a Bayesian stochastic factor selection approach for dynamic factor models with

  4. INNOVATIVE PRACTICES IN TOURISM. APOSSIBLE MODEL BY FOSTERING SHADOW FACTORS

    Directory of Open Access Journals (Sweden)

    Ada Mirela TOMESCU

    2015-08-01

    Full Text Available The paper is the result of an empirical research, a study that includes a theoretical framework. The data used to test our hypotheses come from 60 small tourism firms from Bihor County, Romania. The research conducted has revealed that actions focusing on innovation must be based on a solid analysis, supported by the knowledge and the understanding of the contextual factors (environment, culture as a mental programming, values also based on the organizational factors (the management commitment, systemic perspective, learning and practice of experimentation, rapid transfer of knowledge within the organization. For the purpose of this work, the contextual factors that are exogenous represent the shadow factors. The studies performed in three European projects implemented in tourism SMEs of Bihor County have allowed us to advance the idea that contextual and organizational factors, that are identified as the source of innovation are based on rationality, which is enlarged by affectivity and imagination. The identified correlations may be considered, in our opinion an element of novelty and originality. Finally, the purpose of this paper is to provide a possible model, based on the idea of building an innovative firm, the one that has learned how to determine their own employees to be innovative. O03, L2, L26

  5. Comparison of Acceleration and Impact Stress as Possible Loading Factors in Phonation: A Computer Modeling Study

    Czech Academy of Sciences Publication Activity Database

    Horáček, Jaromír; Laukkanen, A. M.; Šidlof, Petr; Murphy, P.; Švec, J. G.

    2009-01-01

    Roč. 61, č. 3 (2009), s. 137-145 ISSN 1021-7762 R&D Projects: GA ČR(CZ) GA101/08/1155 Institutional research plan: CEZ:AV0Z20760514 Keywords : biomechanics of voice modeling * fundamental frequency * phoniation type * gender differences in voice Subject RIV: BI - Acoustics Impact factor: 1.439, year: 2007

  6. Factors associated with suicide: Case-control study in South Tyrol.

    Science.gov (United States)

    Giupponi, Giancarlo; Innamorati, Marco; Baldessarini, Ross J; De Leo, Diego; de Giovannelli, Francesca; Pycha, Roger; Conca, Andreas; Girardi, Paolo; Pompili, Maurizio

    2018-01-01

    As suicide is related to many factors in addition to psychiatric illness, broad and comprehensive risk-assessment for risk of suicide is required. This study aimed to differentiate nondiagnostic risk factors among suicides versus comparable psychiatric patients without suicidal behavior. We carried out a pilot, case-control comparison of 131 cases of suicide in South Tyrol matched for age and sex with 131 psychiatric controls, using psychological autopsy methods to evaluate differences in clinically assessed demographic, social, and clinical factors, using bivariate conditional Odds Risk comparisons followed by conditional regression modeling controlled for ethnicity. Based on multivariable conditional regression modeling, suicides were significantly more likely to have experienced risk factors, ranking as: [a] family history of suicide or attempt≥[b] recent interpersonal stressors≥[c] childhood traumatic events≥[d] lack of recent clinician contacts≥[e] previous suicide attempt≥[f] non-Italian ethnicity, but did not differ in education, marital status, living situation, or employment, nor by psychiatric or substance-abuse diagnoses. Both recent and early factors were associated with suicide, including lack of recent clinical care, non-Italian cultural subgroup-membership, familial suicidal behavior, and recent interpersonal distress. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Psychosocial work factors and social inequalities in psychological distress: a population-based study

    Directory of Open Access Journals (Sweden)

    Caroline S. Duchaine

    2017-01-01

    Full Text Available Abstract Background Mental health problems (MHP are the leading cause of disability worldwide. The inverse association between socioeconomic position (SEP and MHP has been well documented. There is prospective evidence that factors from the work environment, including adverse psychosocial work factors, could contribute to the development of MHP including psychological distress. However, the contribution of psychosocial work factors to social inequalities in MHP remains unclear. This study evaluates the contribution of psychosocial work factors from two highly supported models, the Demand-Control-Support (DCS and the Effort-Reward Imbalance (ERI models to SEP inequalities of psychological distress in men and women from a population-based sample of Quebec workers. Methods Data were collected during a survey on working conditions, health and safety at work. SEP was evaluated using education, occupation and household income. Psychosocial work factors and psychological distress were assessed using validated instruments. Mean differences (MD in the score of psychological distress were estimated separately for men and women. Results Low education level and low household income were associated with psychological distress among men (MD, 0.56 (95% CI 0.06; 1.05 and 1.26 (95% CI 0.79; 1.73 respectively. In men, the contribution of psychosocial work factors from the DCS and the ERI models to the association between household income and psychological distress ranged from 9% to 24%. No clear inequalities were observed among women. Conclusions These results suggest that psychosocial work factors from the DCS and the ERI models contribute to explain a part of social inequalities in psychological distress among men. Psychosocial factors at work are frequent and modifiable. The present study supports the relevance of targeting these factors for the primary prevention of MHP and for health policies aiming to reduce social inequalities in mental health.

  8. Psychosocial work factors and social inequalities in psychological distress: a population-based study.

    Science.gov (United States)

    Duchaine, Caroline S; Ndjaboué, Ruth; Levesque, Manon; Vézina, Michel; Trudel, Xavier; Gilbert-Ouimet, Mahée; Dionne, Clermont E; Mâsse, Benoît; Pearce, Neil; Brisson, Chantal

    2017-01-18

    Mental health problems (MHP) are the leading cause of disability worldwide. The inverse association between socioeconomic position (SEP) and MHP has been well documented. There is prospective evidence that factors from the work environment, including adverse psychosocial work factors, could contribute to the development of MHP including psychological distress. However, the contribution of psychosocial work factors to social inequalities in MHP remains unclear. This study evaluates the contribution of psychosocial work factors from two highly supported models, the Demand-Control-Support (DCS) and the Effort-Reward Imbalance (ERI) models to SEP inequalities of psychological distress in men and women from a population-based sample of Quebec workers. Data were collected during a survey on working conditions, health and safety at work. SEP was evaluated using education, occupation and household income. Psychosocial work factors and psychological distress were assessed using validated instruments. Mean differences (MD) in the score of psychological distress were estimated separately for men and women. Low education level and low household income were associated with psychological distress among men (MD, 0.56 (95% CI 0.06; 1.05) and 1.26 (95% CI 0.79; 1.73) respectively). In men, the contribution of psychosocial work factors from the DCS and the ERI models to the association between household income and psychological distress ranged from 9% to 24%. No clear inequalities were observed among women. These results suggest that psychosocial work factors from the DCS and the ERI models contribute to explain a part of social inequalities in psychological distress among men. Psychosocial factors at work are frequent and modifiable. The present study supports the relevance of targeting these factors for the primary prevention of MHP and for health policies aiming to reduce social inequalities in mental health.

  9. A survey of the influencing factors and models for resident's household waste management behavior

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The problem of household solid waste has been concerned and researched on by municipalities and researchers.At present, household solid waste has been changed to management problem from technical one. From the point view of management, the research on household solid waste is to study the factors which influence resident's behavior of managtng their waste. Based on the literature review, firstly, this paper summarizes those factors which have already been identified to have impact on resident's behavior of managing their waste. They are social-demographic variables,knowledge, environmental values, psychological factors, publicity and system design. Secondly, three typical models of the relationship between factors and behavior, which are factors determining task performance in waste management,conceptualization of waste management behavior and the theoretical model of repeated behavior on household waste management, are analyzed and the deficiencies of these models are also analyzed. Finally, according to the current situation in household waste management and the culture and resident's habits in China, this paper puts forward a research focus and suggestions about resident 's behavior of household solid waste management.

  10. A study of the dengue epidemic and meteorological factors in Guangzhou, China, by using a zero-inflated Poisson regression model.

    Science.gov (United States)

    Wang, Chenggang; Jiang, Baofa; Fan, Jingchun; Wang, Furong; Liu, Qiyong

    2014-01-01

    The aim of this study is to develop a model that correctly identifies and quantifies the relationship between dengue and meteorological factors in Guangzhou, China. By cross-correlation analysis, meteorological variables and their lag effects were determined. According to the epidemic characteristics of dengue in Guangzhou, those statistically significant variables were modeled by a zero-inflated Poisson regression model. The number of dengue cases and minimum temperature at 1-month lag, along with average relative humidity at 0- to 1-month lag were all positively correlated with the prevalence of dengue fever, whereas wind velocity and temperature in the same month along with rainfall at 2 months' lag showed negative association with dengue incidence. Minimum temperature at 1-month lag and wind velocity in the same month had a greater impact on the dengue epidemic than other variables in Guangzhou.

  11. Drug development costs when financial risk is measured using the Fama-French three-factor model.

    Science.gov (United States)

    Vernon, John A; Golec, Joseph H; Dimasi, Joseph A

    2010-08-01

    In a widely cited article, DiMasi, Hansen, and Grabowski (2003) estimate the average pre-tax cost of bringing a new molecular entity to market. Their base case estimate, excluding post-marketing studies, was $802 million (in $US 2000). Strikingly, almost half of this cost (or $399 million) is the cost of capital (COC) used to fund clinical development expenses to the point of FDA marketing approval. The authors used an 11% real COC computed using the capital asset pricing model (CAPM). But the CAPM is a single factor risk model, and multi-factor risk models are the current state of the art in finance. Using the Fama-French three factor model we find that the cost of drug development to be higher than the earlier estimate. Copyright (c) 2009 John Wiley & Sons, Ltd.

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

    Science.gov (United States)

    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.

  13. Modeling the factors associating with health-related habits among Japanese students.

    Science.gov (United States)

    Mato, Mie; Tsukasaki, Keiko

    2017-11-23

    The aim of the present study was to clarify the structural relationship between health-related habits and psychosocial factors during adolescence/early adulthood. An anonymous, self-administered questionnaire was provided to 1141 third- and fourth-year students at eight academic departments from six universities in regional Japanese cities. Surveys included items addressing participants' demographic characteristics, psychosocial factors (individual-level social capital, self-efficacy, mental health (from health-related quality of life SF-36v2), and sense of coherence (SOC)), and health-related habits. A multiple indicator analysis based on structural equation modeling was conducted to examine the structural relationship between health-related habits and these factors. Valid responses were obtained from 952 participants. The final model demonstrated a high level of goodness of fit. While the path from SOC to health-related habits was significant, those from self-efficacy to health-related habits and from mental health to health-related habits were not significant. The path coefficient from SOC to health-related habits was greater than the path coefficient from background characteristics. In the multiple population comparison that considered gender, a nearly identical model was supported for men and women. Psychosocial factors related to health-related habits were social capital, self-efficacy, mental health, and SOC. Furthermore, it was suggested that SOC functions as an intervening factor for maintaining a healthy lifestyle. It was observed that individual psychosocial factors influence health-related habits more than their background characteristics. Findings highlight that supporting the building of social relationships and social environments is essential to promote a healthy lifestyle among university students. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  14. Risk factors of chronic periodontitis on healing response: a multilevel modelling analysis.

    Science.gov (United States)

    Song, J; Zhao, H; Pan, C; Li, C; Liu, J; Pan, Y

    2017-09-15

    Chronic periodontitis is a multifactorial polygenetic disease with an increasing number of associated factors that have been identified over recent decades. Longitudinal epidemiologic studies have demonstrated that the risk factors were related to the progression of the disease. A traditional multivariate regression model was used to find risk factors associated with chronic periodontitis. However, the approach requirement of standard statistical procedures demands individual independence. Multilevel modelling (MLM) data analysis has widely been used in recent years, regarding thorough hierarchical structuring of the data, decomposing the error terms into different levels, and providing a new analytic method and framework for solving this problem. The purpose of our study is to investigate the relationship of clinical periodontal index and the risk factors in chronic periodontitis through MLM analysis and to identify high-risk individuals in the clinical setting. Fifty-four patients with moderate to severe periodontitis were included. They were treated by means of non-surgical periodontal therapy, and then made follow-up visits regularly at 3, 6, and 12 months after therapy. Each patient answered a questionnaire survey and underwent measurement of clinical periodontal parameters. Compared with baseline, probing depth (PD) and clinical attachment loss (CAL) improved significantly after non-surgical periodontal therapy with regular follow-up visits at 3, 6, and 12 months after therapy. The null model and variance component models with no independent variables included were initially obtained to investigate the variance of the PD and CAL reductions across all three levels, and they showed a statistically significant difference (P periodontal therapy with regular follow-up visits had a remarkable curative effect. All three levels had a substantial influence on the reduction of PD and CAL. Site-level had the largest effect on PD and CAL reductions.

  15. [Psychosocial factors as predictors of atherosclerosis and cardiovascular events: contribution from animal models].

    Science.gov (United States)

    Alboni, Paolo; Alboni, Marco

    2006-11-01

    Conventional risk factors (abnormal lipids, hypertension, etc.) are independent predictors of atherosclerosis and cardiovascular events; however, these factors are not specific since about half patients with acute myocardial infarction paradoxically result at low cardiovascular risk. Recent prospective studies provide convincing evidence that some psychosocial factors are independent predictors of atherosclerosis and cardiovascular events, as well. Psychosocial factors that promote atherosclerosis can be divided into two general categories: chronic stressors, including social isolation/low social support and work stress (subordination without job control) and emotional factors, including affective disorders such as depression, severe anxiety and hostility/anger. The emotional factors, such as the chronic stressors, activate the biological mechanisms of chronic stress: increased activity of the hypothalamic-pituitary-adrenal axis, sympathetic system and inflammation processes, which have atherogenic effects, and an increase in blood coagulation. In spite of the amount of published data, psychosocial factors receive little attention in the medical setting. About 30 years ago, Kuller defined the criteria for a causal relation between a risk factor and atherosclerosis and cardiac events. The first of these criteria states that experimental research should demonstrate that any new factor would increase the extent of atherosclerosis or its complications in suitable animal models. We carried out a bibliographic research in order to investigate whether the results of the studies dealing with animal examination and experimentation support the psychosocial factors as predictors of atherosclerosis. Contributions related to some of the psychosocial factors such as social isolation, subordination and hostility/anger have been found. In these studies atherosclerotic extension has been evaluated at necroscopy; however, the incidence of cardiovascular events has not been

  16. Improved SVR Model for Multi-Layer Buildup Factor Calculation

    International Nuclear Information System (INIS)

    Trontl, K.; Pevec, D.; Smuc, T.

    2006-01-01

    The accuracy of point kernel method applied in gamma ray dose rate calculations in shielding design and radiation safety analysis is limited by the accuracy of buildup factors used in calculations. Although buildup factors for single-layer shields are well defined and understood, buildup factors for stratified shields represent a complex physical problem that is hard to express in mathematical terms. The traditional approach for expressing buildup factors of multi-layer shields is through semi-empirical formulas obtained by fitting the results of transport theory or Monte Carlo calculations. Such an approach requires an ad-hoc definition of the fitting function and often results with numerous and usually inadequately explained and defined correction factors added to the final empirical formula. Even more, finally obtained formulas are generally limited to a small number of predefined combinations of materials within relatively small range of gamma ray energies and shield thicknesses. Recently, a new approach has been suggested by the authors involving one of machine learning techniques called Support Vector Machines, i.e., Support Vector Regression (SVR). Preliminary investigations performed for double-layer shields revealed great potential of the method, but also pointed out some drawbacks of the developed model, mostly related to the selection of one of the parameters describing the problem (material atomic number), and the method in which the model was designed to evolve during the learning process. It is the aim of this paper to introduce a new parameter (single material buildup factor) that is to replace the existing material atomic number as an input parameter. The comparison of two models generated by different input parameters has been performed. The second goal is to improve the evolution process of learning, i.e., the experimental computational procedure that provides a framework for automated construction of complex regression models of predefined

  17. Testing multi-factor asset pricing models in the Visegrad countries

    Czech Academy of Sciences Publication Activity Database

    Morgese Borys, Magdalena

    2011-01-01

    Roč. 61, č. 2 (2011), s. 118-139 ISSN 0015-1920 R&D Projects: GA MŠk LC542 Institutional research plan: CEZ:AV0Z70850503 Keywords : capital asset pricing model * macroeconomic factor models * asset pricing Subject RIV: AH - Economics Impact factor: 0.346, year: 2011 http://journal.fsv.cuni.cz/mag/article/show/id/1208

  18. The Factors That Influence Bureaucracy and Professionalism in Schools: A Grounded Theory Study

    Science.gov (United States)

    Koybasi, Fatma; Ugurlu, Celal Teyyar

    2017-01-01

    The aim of this study is to identify the factors that influence the interaction between bureaucracy and professionalism in schools and to develop a model of bureaucracy-professionalism interaction. This is a qualitative study carried out in grounded theory model. The study group consisted of 10 male and 10 female teachers who were working in Sivas…

  19. [Factor structure validity of the social capital scale used at baseline in the ELSA-Brasil study].

    Science.gov (United States)

    Souto, Ester Paiva; Vasconcelos, Ana Glória Godoi; Chor, Dora; Reichenheim, Michael E; Griep, Rosane Härter

    2016-07-21

    This study aims to analyze the factor structure of the Brazilian version of the Resource Generator (RG) scale, using baseline data from the Brazilian Longitudinal Health Study in Adults (ELSA-Brasil). Cross-validation was performed in three random subsamples. Exploratory factor analysis using exploratory structural equation models was conducted in the first two subsamples to diagnose the factor structure, and confirmatory factor analysis was used in the third to corroborate the model defined by the exploratory analyses. Based on the 31 initial items, the model with the best fit included 25 items distributed across three dimensions. They all presented satisfactory convergent validity (values greater than 0.50 for the extracted variance) and precision (values greater than 0.70 for compound reliability). All factor correlations were below 0.85, indicating full discriminative factor validity. The RG scale presents acceptable psychometric properties and can be used in populations with similar characteristics.

  20. Functional dynamic factor models with application to yield curve forecasting

    KAUST Repository

    Hays, Spencer

    2012-09-01

    Accurate forecasting of zero coupon bond yields for a continuum of maturities is paramount to bond portfolio management and derivative security pricing. Yet a universal model for yield curve forecasting has been elusive, and prior attempts often resulted in a trade-off between goodness of fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM with functional factor loading curves. This results in a model capable of forecasting functional time series. Further, in the yield curve context we show that the model retains economic interpretation. Model estimation is achieved through an expectation- maximization algorithm, where the time series parameters and factor loading curves are simultaneously estimated in a single step. Efficient computing is implemented and a data-driven smoothing parameter is nicely incorporated. We show that our model performs very well on forecasting actual yield data compared with existing approaches, especially in regard to profit-based assessment for an innovative trading exercise. We further illustrate the viability of our model to applications outside of yield forecasting.

  1. CUSTOMER RELATIONSHIP MANAGEMENT (CRM SUCCESS FACTORS: AN EXPLORATORY STUDY

    Directory of Open Access Journals (Sweden)

    Mohammed ALAMGIR

    2015-02-01

    Full Text Available Customer relationship management (CRM can improve organization’s performance through applying customer knowledge and maintaining relationships with customers. Literature on CRM in an integrative fashion is sparse, rather issues are presented in isolation mostly focusing on technology ignoring other extra-organizational issues like social rapport and customer knowledge. Likewise, CRM success is poorly sketched and social rapport as a facilitator of knowledge generation has received little attention in the previous literature. Therefore, the main purpose of this research is to investigate the role of CRM, customer knowledge and social rapport on CRM success. The present study considers the Resource-based view in developing CRM success framework. A Qualitative research approach has been taken in this study where ten customer-service managers of different telecom operators of Bangladesh have been interviewed. To identify the factors along with their associated variables and also to further develop a research model a content analysis technique has been utilized. The results of the interviews identified three factors affecting CRM success. This paper also highlights the research and managerial implications of the model.  

  2. A Two-Factor Model Better Explains Heterogeneity in Negative Symptoms: Evidence from the Positive and Negative Syndrome Scale.

    Science.gov (United States)

    Jang, Seon-Kyeong; Choi, Hye-Im; Park, Soohyun; Jaekal, Eunju; Lee, Ga-Young; Cho, Young Il; Choi, Kee-Hong

    2016-01-01

    Acknowledging separable factors underlying negative symptoms may lead to better understanding and treatment of negative symptoms in individuals with schizophrenia. The current study aimed to test whether the negative symptoms factor (NSF) of the Positive and Negative Syndrome Scale (PANSS) would be better represented by expressive and experiential deficit factors, rather than by a single factor model, using confirmatory factor analysis (CFA). Two hundred and twenty individuals with schizophrenia spectrum disorders completed the PANSS; subsamples additionally completed the Brief Negative Symptom Scale (BNSS) and the Motivation and Pleasure Scale-Self-Report (MAP-SR). CFA results indicated that the two-factor model fit the data better than the one-factor model; however, latent variables were closely correlated. The two-factor model's fit was significantly improved by accounting for correlated residuals between N2 (emotional withdrawal) and N6 (lack of spontaneity and flow of conversation), and between N4 (passive social withdrawal) and G16 (active social avoidance), possibly reflecting common method variance. The two NSF factors exhibited differential patterns of correlation with subdomains of the BNSS and MAP-SR. These results suggest that the PANSS NSF would be better represented by a two-factor model than by a single-factor one, and support the two-factor model's adequate criterion-related validity. Common method variance among several items may be a potential source of measurement error under a two-factor model of the PANSS NSF.

  3. The Meaning of Higher-Order Factors in Reflective-Measurement Models

    Science.gov (United States)

    Eid, Michael; Koch, Tobias

    2014-01-01

    Higher-order factor analysis is a widely used approach for analyzing the structure of a multidimensional test. Whenever first-order factors are correlated researchers are tempted to apply a higher-order factor model. But is this reasonable? What do the higher-order factors measure? What is their meaning? Willoughby, Holochwost, Blanton, and Blair…

  4. The Factors of Forming the National HR-Management Model

    Directory of Open Access Journals (Sweden)

    Elena P. Kostenko

    2017-12-01

    Full Text Available There are some factors considered in this article, which influence the forming of national HR-management model. The group-forming criterion is the nature of factors, that determine the system of HR-management as a system of corporate culture values, norms and rules of organizational behavior, ways of realization some important managing functions and dominating approaches to make decisions. This article shows that the plurality of combinations in different factors leads to forming the unique HR-management model. The geoclimatic factor influences the principles of the labor organization (orientation primarily on individual or collective forms of labor, attitude to the management experience of other countries, attitude to resources, etc., the distribution of labor resources, the level of labor mobility, and the psychosocial type of employee. Models of man's labor behavior are constituted In the process of historical development. Attention is focused on the formation of a national HR-model, such as the conducted socio-economic policy, the characteristics of the institutional environment, economic goals and priorities of the country's development, the level of development and the nature of the national productive forces and economic structures. Much attention was paid to the analysis of the historically formed value system and labor traditions, which influence the approaches to HR-management. As far as religion influences the model of person’s inclusion in labor, motives of labor behavior, management culture of a certain employee, preferred payment etc., we examined how the main traditional religions (Christianity, Islam, Judaism, Buddhism, Confucianism, Hinduism influence the HR-management system in different countries.

  5. Choice Model and Influencing Factor Analysis of Travel Mode for Migrant Workers: Case Study in Xi’an, China

    OpenAIRE

    Hong Chen; Zuo-xian Gan; Yu-ting He

    2015-01-01

    Based on the basic theory and methods of disaggregate choice model, the influencing factors in travel mode choice for migrant workers are analyzed, according to 1366 data samples of Xi’an migrant workers. Walking, bus, subway, and taxi are taken as the alternative parts of travel modes for migrant workers, and a multinomial logit (MNL) model of travel mode for migrant workers is set up. The validity of the model is verified by the hit rate, and the hit rates of four travel modes are all great...

  6. Hadron form factors in the constituent quark model

    International Nuclear Information System (INIS)

    Cardarelli, F.; Salme', G.; Simula, S.; Pace, E.

    1998-01-01

    Hadron electromagnetic form factors are evaluated in a light-front constituent quark model based on the eigenfunctions of a mass operator, including in the q-q interaction a confining term and a one-gluon-exchange term (OGE). The spin-dependent part of the interaction plays an essential role for obtaining both a proper fit of the experimental nucleon electromagnetic form factors and the faster than dipole decrease of the magnetic N-P 33 (1232) transition form factor. The effects of the D wave, produced by the tensor part of the OGE interaction, on the quadrupole and Coulomb N-P 33 (1232) transition form factors have been found to be negligible. (author)

  7. Dimensional models of personality: the five-factor model and the DSM-5

    Science.gov (United States)

    Trull, Timothy J.; Widiger, Thomas A.

    2013-01-01

    It is evident that the classification of personality disorder is shifting toward a dimensional trait model and, more specifically, the five-factor model (FFM). The purpose of this paper is to provide an overview of the FFM of personality disorder. It will begin with a description of this dimensional model of normal and abnormal personality functioning, followed by a comparison with a proposal for future revisions to DSM-5 and a discussion of its potential advantages as an integrative hierarchical model of normal and abnormal personality structure. PMID:24174888

  8. A Two-Factor Autoregressive Moving Average Model Based on Fuzzy Fluctuation Logical Relationships

    Directory of Open Access Journals (Sweden)

    Shuang Guan

    2017-10-01

    Full Text Available Many of the existing autoregressive moving average (ARMA forecast models are based on one main factor. In this paper, we proposed a new two-factor first-order ARMA forecast model based on fuzzy fluctuation logical relationships of both a main factor and a secondary factor of a historical training time series. Firstly, we generated a fluctuation time series (FTS for two factors by calculating the difference of each data point with its previous day, then finding the absolute means of the two FTSs. We then constructed a fuzzy fluctuation time series (FFTS according to the defined linguistic sets. The next step was establishing fuzzy fluctuation logical relation groups (FFLRGs for a two-factor first-order autoregressive (AR(1 model and forecasting the training data with the AR(1 model. Then we built FFLRGs for a two-factor first-order autoregressive moving average (ARMA(1,m model. Lastly, we forecasted test data with the ARMA(1,m model. To illustrate the performance of our model, we used real Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX and Dow Jones datasets as a secondary factor to forecast TAIEX. The experiment results indicate that the proposed two-factor fluctuation ARMA method outperformed the one-factor method based on real historic data. The secondary factor may have some effects on the main factor and thereby impact the forecasting results. Using fuzzified fluctuations rather than fuzzified real data could avoid the influence of extreme values in historic data, which performs negatively while forecasting. To verify the accuracy and effectiveness of the model, we also employed our method to forecast the Shanghai Stock Exchange Composite Index (SHSECI from 2001 to 2015 and the international gold price from 2000 to 2010.

  9. Study on Influencing Factor Analysis and Application of Consumer Mobile Commerce Acceptance

    Science.gov (United States)

    Li, Gaoguang; Lv, Tingjie

    Mobile commerce (MC) refers to e-commerce activities carried out using a mobile device such as a phone or PDA. With new technology, MC will be rapidly growing in the near future. At the present time, what factors making consumer accept MC and what MC applications are acceptable by consumers are two of hot issues both for MC providers and f or MC researchers. This study presents a proposed MC acceptance model that integrates perceived playfulness, perceived risk and cost into the TAM to study which factors affect consumer MC acceptance. The proposed model includes five variables, namely perceived risk, cost, perceived usefulness, perceived playfulness, perceived ease of use, perceived playfulness. Then, using analytic hierarchy process (AHP) to calculate weight of criteria involved in proposed model. Finally, the study utilizes fuzzy comprehensive evaluation method to evaluate MC applications accepted possibility, and then a MC application is empirically tested using data collected from a survey of MC consumers.

  10. Uncovering Transcriptional Regulatory Networks by Sparse Bayesian Factor Model

    Directory of Open Access Journals (Sweden)

    Qi Yuan(Alan

    2010-01-01

    Full Text Available Abstract The problem of uncovering transcriptional regulation by transcription factors (TFs based on microarray data is considered. A novel Bayesian sparse correlated rectified factor model (BSCRFM is proposed that models the unknown TF protein level activity, the correlated regulations between TFs, and the sparse nature of TF-regulated genes. The model admits prior knowledge from existing database regarding TF-regulated target genes based on a sparse prior and through a developed Gibbs sampling algorithm, a context-specific transcriptional regulatory network specific to the experimental condition of the microarray data can be obtained. The proposed model and the Gibbs sampling algorithm were evaluated on the simulated systems, and results demonstrated the validity and effectiveness of the proposed approach. The proposed model was then applied to the breast cancer microarray data of patients with Estrogen Receptor positive ( status and Estrogen Receptor negative ( status, respectively.

  11. Assessing Posttraumatic Stress Disorder's Latent Structure in Elderly Bereaved European Trauma Victims: Evidence for a Five Factor Dysphoric and Anxious Arousal Model

    DEFF Research Database (Denmark)

    Armour, Cherie; O'Connor, Maja; Elklit, Ask

    2013-01-01

    to provide superior fit over the existing four-factor models. The present study investigated the fit of the five-factor model against the existing four-factor models and assessed the resultant factors association with depression in a bereaved European trauma sample (N=325). Participants were assessed...... for PTSD via the Harvard Trauma Questionnaire and depression via the Beck Depression Inventory. The five-factor model provided superior fit to the data compared to the existing four-factor models. In the Dysphoric Arousal model depression was equally related to both Dysphoric Arousal and Emotional Numbing...

  12. Prognostic Factors of Uterine Serous Carcinoma-A Multicenter Study.

    Science.gov (United States)

    Zhong, Xiaozhu; Wang, Jianliu; Kaku, Tengen; Wang, Zhiqi; Li, Xiaoping; Wei, Lihui

    2018-04-04

    The prognostic factors of uterine serous carcinoma (USC) vary among studies, and there is no report of Chinese USC patients. The aim of this study was to investigate the clinicopathological characteristics and prognostic factors in Chinese patients with USC. Patients with USC from 13 authoritative university hospitals in China and treated between 2004 and 2014 were retrospectively reviewed. Three-year disease-free survival rate (DFSR), cumulative recurrence, and cumulative mortality were estimated by Kaplan-Meier analyses and log-rank tests. Multivariate Cox regression analysis was used to model the association of potential prognostic factors with clinical outcomes. Data of a total of 241 patients were reviewed. The median follow-up was 26 months (range, 1-128 months). Median age was 60 years (range, 39-84 years), and 58.0% had stages I-II disease. The 3-year DFSR and cumulative recurrence were 46.8% and 27.7%. Advanced stage (III and IV) (P = 0.004), myometrial invasion (P = 0.001), adnexal involvement (P USC. Prospective studies are needed to confirm these results.

  13. Followee recommendation in microblog using matrix factorization model with structural regularization.

    Science.gov (United States)

    Yu, Yan; Qiu, Robin G

    2014-01-01

    Microblog that provides us a new communication and information sharing platform has been growing exponentially since it emerged just a few years ago. To microblog users, recommending followees who can serve as high quality information sources is a competitive service. To address this problem, in this paper we propose a matrix factorization model with structural regularization to improve the accuracy of followee recommendation in microblog. More specifically, we adapt the matrix factorization model in traditional item recommender systems to followee recommendation in microblog and use structural regularization to exploit structure information of social network to constrain matrix factorization model. The experimental analysis on a real-world dataset shows that our proposed model is promising.

  14. Evaluation of the Thermodynamic Models for the Thermal Diffusion Factor

    DEFF Research Database (Denmark)

    Gonzalez-Bagnoli, Mariana G.; Shapiro, Alexander; Stenby, Erling Halfdan

    2003-01-01

    Over the years, several thermodynamic models for the thermal diffusion factors for binary mixtures have been proposed. The goal of this paper is to test some of these models in combination with different equations of state. We tested the following models: those proposed by Rutherford and Drickamer...... we applied different thermodynamic models, such as the Soave-Redlich-Kwong and the Peng-Robinson equations of state. The necessity to try different thermo-dynamic models is caused by the high sensitivity of the thermal diffusion factors to the values of the partial molar properties. Two different...... corrections for the determination of the partial molar volumes have been implemented; the Peneloux correction and the correction based on the principle of corresponding states....

  15. Study of Psycho-Social Factors Affecting Traffic Accidents Among Young Boys in Tehran.

    Science.gov (United States)

    Javadi, Seyyed Mohammad Hossein; Fekr Azad, Hossein; Tahmasebi, Siyamak; Rafiei, Hassan; Rahgozar, Mehdi; Tajlili, Alireza

    2015-07-01

    Unprecedented growth of fatalities due to traffic accidents in the recent years has raised great concerns and efforts of authorities in order to identify and control the causes of these accidents. In the present study, the contribution of psychological, social, demographic, environmental and behavioral factors on traffic accidents was studied for young boys in Tehran, emphasizing the importance of psychosocial factors. The design of the present study was quantitative (correlational) in which a sample population including 253 boys from Tehran (Iran) with an age range of 18 to 24 who had been referred to insurance institutions, hospitals, correctional facilities as well as prisons, were selected using stratified cluster sampling during the year 2013.The subjects completed the following questionnaires: demographic, general health, lifestyle, Manchester Driving Behavior Questionnaire (MDBQ), young parenting, and NEO-Five Factor Inventory (NEO-FFI). For data analysis, descriptive statistics, correlation coefficient, and inferential statistics including simultaneous regression, stepwise regression, and structural equations modeling were used. The findings indicated that in the psychosocial model of driving behavior (including lapses, mistakes, and intentional violations) and accidents, psychological factors, depression (P scope of these factors links accidents to other social issues and damages.

  16. External factors in hospital information system (HIS) adoption model: a case on Malaysia.

    Science.gov (United States)

    Lee, Heng Wei; Ramayah, Thurasamy; Zakaria, Nasriah

    2012-08-01

    Studies related to healthcare ICT integration in Malaysia are relatively little, thus this paper provide a literature review of the integration of information and communication technologies (ICT) in the healthcare sector in Malaysia through the hospital information system (HIS). Our study emphasized on secondary data to investigate the factors related to ICT integration in healthcare through HIS. Therefore this paper aimed to gather an in depth understanding of issues related to HIS adoption, and contributing in fostering HIS adoption in Malaysia and other countries. This paper provides a direction for future research to study the correlation of factors affecting HIS adoption. Finally a research model is proposed using current adoption theories and external factors from human, technology, and organization perspectives.

  17. SHMF: Interest Prediction Model with Social Hub Matrix Factorization

    Directory of Open Access Journals (Sweden)

    Chaoyuan Cui

    2017-01-01

    Full Text Available With the development of social networks, microblog has become the major social communication tool. There is a lot of valuable information such as personal preference, public opinion, and marketing in microblog. Consequently, research on user interest prediction in microblog has a positive practical significance. In fact, how to extract information associated with user interest orientation from the constantly updated blog posts is not so easy. Existing prediction approaches based on probabilistic factor analysis use blog posts published by user to predict user interest. However, these methods are not very effective for the users who post less but browse more. In this paper, we propose a new prediction model, which is called SHMF, using social hub matrix factorization. SHMF constructs the interest prediction model by combining the information of blogs posts published by both user and direct neighbors in user’s social hub. Our proposed model predicts user interest by integrating user’s historical behavior and temporal factor as well as user’s friendships, thus achieving accurate forecasts of user’s future interests. The experimental results on Sina Weibo show the efficiency and effectiveness of our proposed model.

  18. Theoretical Assessment of the Impact of Climatic Factors in a Vibrio Cholerae Model.

    Science.gov (United States)

    Kolaye, G; Damakoa, I; Bowong, S; Houe, R; Békollè, D

    2018-05-04

    A mathematical model for Vibrio Cholerae (V. Cholerae) in a closed environment is considered, with the aim of investigating the impact of climatic factors which exerts a direct influence on the bacterial metabolism and on the bacterial reservoir capacity. We first propose a V. Cholerae mathematical model in a closed environment. A sensitivity analysis using the eFast method was performed to show the most important parameters of the model. After, we extend this V. cholerae model by taking account climatic factors that influence the bacterial reservoir capacity. We present the theoretical analysis of the model. More precisely, we compute equilibria and study their stabilities. The stability of equilibria was investigated using the theory of periodic cooperative systems with a concave nonlinearity. Theoretical results are supported by numerical simulations which further suggest the necessity to implement sanitation campaigns of aquatic environments by using suitable products against the bacteria during the periods of growth of aquatic reservoirs.

  19. Physiologically-based toxicokinetic models help identifying the key factors affecting contaminant uptake during flood events

    International Nuclear Information System (INIS)

    Brinkmann, Markus; Eichbaum, Kathrin; Kammann, Ulrike; Hudjetz, Sebastian; Cofalla, Catrina; Buchinger, Sebastian; Reifferscheid, Georg; Schüttrumpf, Holger; Preuss, Thomas

    2014-01-01

    Highlights: • A PBTK model for trout was coupled with a sediment equilibrium partitioning model. • The influence of physical exercise on pollutant uptake was studies using the model. • Physical exercise during flood events can increase the level of biliary metabolites. • Cardiac output and effective respiratory volume were identified as relevant factors. • These confounding factors need to be considered also for bioconcentration studies. - Abstract: As a consequence of global climate change, we will be likely facing an increasing frequency and intensity of flood events. Thus, the ecotoxicological relevance of sediment re-suspension is of growing concern. It is vital to understand contaminant uptake from suspended sediments and relate it to effects in aquatic biota. Here we report on a computational study that utilizes a physiologically based toxicokinetic model to predict uptake, metabolism and excretion of sediment-borne pyrene in rainbow trout (Oncorhynchus mykiss). To this end, data from two experimental studies were compared with the model predictions: (a) batch re-suspension experiments with constant concentration of suspended particulate matter at two different temperatures (12 and 24 °C), and (b) simulated flood events in an annular flume. The model predicted both the final concentrations and the kinetics of 1-hydroxypyrene secretion into the gall bladder of exposed rainbow trout well. We were able to show that exhaustive exercise during exposure in simulated flood events can lead to increased levels of biliary metabolites and identified cardiac output and effective respiratory volume as the two most important factors for contaminant uptake. The results of our study clearly demonstrate the relevance and the necessity to investigate uptake of contaminants from suspended sediments under realistic exposure scenarios

  20. Physiologically-based toxicokinetic models help identifying the key factors affecting contaminant uptake during flood events

    Energy Technology Data Exchange (ETDEWEB)

    Brinkmann, Markus; Eichbaum, Kathrin [Department of Ecosystem Analysis, Institute for Environmental Research,ABBt – Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); Kammann, Ulrike [Thünen-Institute of Fisheries Ecology, Palmaille 9, 22767 Hamburg (Germany); Hudjetz, Sebastian [Department of Ecosystem Analysis, Institute for Environmental Research,ABBt – Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Cofalla, Catrina [Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Buchinger, Sebastian; Reifferscheid, Georg [Federal Institute of Hydrology (BFG), Department G3: Biochemistry, Ecotoxicology, Am Mainzer Tor 1, 56068 Koblenz (Germany); Schüttrumpf, Holger [Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Preuss, Thomas [Department of Environmental Biology and Chemodynamics, Institute for Environmental Research,ABBt- Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); and others

    2014-07-01

    Highlights: • A PBTK model for trout was coupled with a sediment equilibrium partitioning model. • The influence of physical exercise on pollutant uptake was studies using the model. • Physical exercise during flood events can increase the level of biliary metabolites. • Cardiac output and effective respiratory volume were identified as relevant factors. • These confounding factors need to be considered also for bioconcentration studies. - Abstract: As a consequence of global climate change, we will be likely facing an increasing frequency and intensity of flood events. Thus, the ecotoxicological relevance of sediment re-suspension is of growing concern. It is vital to understand contaminant uptake from suspended sediments and relate it to effects in aquatic biota. Here we report on a computational study that utilizes a physiologically based toxicokinetic model to predict uptake, metabolism and excretion of sediment-borne pyrene in rainbow trout (Oncorhynchus mykiss). To this end, data from two experimental studies were compared with the model predictions: (a) batch re-suspension experiments with constant concentration of suspended particulate matter at two different temperatures (12 and 24 °C), and (b) simulated flood events in an annular flume. The model predicted both the final concentrations and the kinetics of 1-hydroxypyrene secretion into the gall bladder of exposed rainbow trout well. We were able to show that exhaustive exercise during exposure in simulated flood events can lead to increased levels of biliary metabolites and identified cardiac output and effective respiratory volume as the two most important factors for contaminant uptake. The results of our study clearly demonstrate the relevance and the necessity to investigate uptake of contaminants from suspended sediments under realistic exposure scenarios.

  1. Modelling the effect of support practices (P-factor) on the reduction of soil erosion by water at European Scale

    NARCIS (Netherlands)

    Panagos, P.; Borrelli, P.; Meusburger, K.; van der Zanden, E.H.; Poesen, J.; Alewell, C.

    2015-01-01

    The USLE/RUSLE support practice factor (P-factor) is rarely taken into account in soil erosion risk modelling at sub-continental scale, as it is difficult to estimate for large areas. This study attempts to model the P-factor in the European Union. For this, it considers the latest policy

  2. The role of outside-school factors in science education: a two-stage theoretical model linking Bourdieu and Sen, with a case study

    Science.gov (United States)

    Gokpinar, Tuba; Reiss, Michael

    2016-05-01

    The literature in science education highlights the potentially significant role of outside-school factors such as parents, cultural contexts and role models in students' formation of science attitudes and aspirations, and their attainment in science classes. In this paper, building on and linking Bourdieu's key concepts of habitus, cultural and social capital, and field with Sen's capability approach, we develop a model of students' science-related capability development. Our model proposes that the role of outside-school factors is twofold, first, in providing an initial set of science-related resources (i.e. habitus, cultural and social capital), and then in conversion of these resources to science-related capabilities. The model also highlights the distinction between science-related functionings (outcomes achieved by individuals) and science-related capabilities (ability to achieve desired functionings), and argues that it is necessary to consider science-related capability development in evaluating the effectiveness of science education. We then test our theoretical model with an account of three Turkish immigrant students' science-related capabilities and the role of outside-school factors in forming and extending these capabilities. We use student and parent interviews, student questionnaires and in-class observations to provide an analysis of how outside-school factors influence these students' attitudes, aspirations and attainment in science.

  3. The relationships between behavioral addictions and the five-factor model of personality.

    Science.gov (United States)

    Andreassen, Cecilie Schou; Griffiths, Mark D; Gjertsen, Siri Renate; Krossbakken, Elfrid; Kvam, Siri; Pallesen, Ståle

    2013-06-01

    Aims Although relationships between addiction and personality have previously been explored, no study has ever simultaneously investigated the interrelationships between several behavioral addictions, and related these to the main dimensions of the five-factor model of personality. Methods In this study, 218 university students completed questionnaires assessing seven different behavioral addictions (i.e., Facebook addiction, video game addiction, Internet addiction, exercise addiction, mobile phone addiction, compulsive buying, and study addiction) as well as an instrument assessing the main dimensions of the five-factor model of personality. Results Of the 21 bivariate intercorrelations between the seven behavioral addictions, all were positive (and nine significantly). The results also showed that (i) Neuroticism was positively associated with Internet addiction, exercise addiction, compulsive buying, and study addiction, (ii) Extroversion was positively associated with Facebook addiction, exercise addiction, mobile phone addiction, and compulsive buying, (iii) Openness to experience was negatively associated with Facebook addiction and mobile phone addiction, (iv) Agreeableness was negatively associated with Internet addiction, exercise addiction, mobile phone addiction, and compulsive buying, and (v) Conscientiousness was negatively associated with Facebook addiction, video game addiction, Internet addiction, and compulsive buying and positively associated with exercise addiction and study addiction. Conclusions The positive associations between the seven behavioral addictions suggest one or several underlying pathological factors. Hierarchical multiple regressions showed that personality traits explained between 6% and 17% of the variance in the seven behavioral addictions, suggesting that personality to a varying degree explains scores on measures of addictive behaviors.

  4. Modelling of Safety Factors in the Design of GRP Composite Products

    DEFF Research Database (Denmark)

    Babu, B.J.C.; Prabhakaran, R.T. Durai; Lystrup, Aage

    2010-01-01

    as independent, while in real applications these factors may interact/influence each other. Following the concept developed by the authors, a simple graph theoretic model has been used to determine overall factor of safety. This is described with the help of an example and it has been demonstrated......An attempt has been made in this paper to arrive at the safety factor design of glass fibre reinforced polymer (GRP) composite products using graph theoretic model. In the conventional design and recommendations of the standards, these design factors affecting properties have been considered...

  5. Studying the effect of meteorological factors on the SO2 and PM10 pollution levels with refined versions of the SARIMA model

    Energy Technology Data Exchange (ETDEWEB)

    Voynikova, D. S., E-mail: desi-sl2000@yahoo.com; Gocheva-Ilieva, S. G., E-mail: snegocheva@yahoo.com; Ivanov, A. V., E-mail: aivanov-99@yahoo.com [Department of Applied Mathematics and Modeling, Faculty of Mathematics and Informatics, Paisii Hilendarski University of Plovdiv, 24 Tzar Assen str., 4000 Plovdiv (Bulgaria); Iliev, I. P., E-mail: iliev55@abv.bg [Department of Physics, Technical University – Plovdiv, 25 Tzanko Djusstabanov str., 4000 Plovdiv (Bulgaria)

    2015-10-28

    Numerous time series methods are used in environmental sciences allowing the detailed investigation of air pollution processes. The goal of this study is to present the empirical analysis of various aspects of stochastic modeling and in particular the ARIMA/SARIMA methods. The subject of investigation is air pollution in the town of Kardzhali, Bulgaria with 2 problematic pollutants – sulfur dioxide (SO2) and particulate matter (PM10). Various SARIMA Transfer Function models are built taking into account meteorological factors, data transformations and the use of different horizons selected to predict future levels of concentrations of the pollutants.

  6. Factors influencing creep model equation selection

    International Nuclear Information System (INIS)

    Holdsworth, S.R.; Askins, M.; Baker, A.; Gariboldi, E.; Holmstroem, S.; Klenk, A.; Ringel, M.; Merckling, G.; Sandstrom, R.; Schwienheer, M.; Spigarelli, S.

    2008-01-01

    During the course of the EU-funded Advanced-Creep Thematic Network, ECCC-WG1 reviewed the applicability and effectiveness of a range of model equations to represent the accumulation of creep strain in various engineering alloys. In addition to considering the experience of network members, the ability of several models to describe the deformation characteristics of large single and multi-cast collations of ε(t,T,σ) creep curves have been evaluated in an intensive assessment inter-comparison activity involving three steels, 21/4 CrMo (P22), 9CrMoVNb (Steel-91) and 18Cr13NiMo (Type-316). The choice of the most appropriate creep model equation for a given application depends not only on the high-temperature deformation characteristics of the material under consideration, but also on the characteristics of the dataset, the number of casts for which creep curves are available and on the strain regime for which an analytical representation is required. The paper focuses on the factors which can influence creep model selection and model-fitting approach for multi-source, multi-cast datasets

  7. Zero-Inflated Poisson Modeling of Fall Risk Factors in Community-Dwelling Older Adults.

    Science.gov (United States)

    Jung, Dukyoo; Kang, Younhee; Kim, Mi Young; Ma, Rye-Won; Bhandari, Pratibha

    2016-02-01

    The aim of this study was to identify risk factors for falls among community-dwelling older adults. The study used a cross-sectional descriptive design. Self-report questionnaires were used to collect data from 658 community-dwelling older adults and were analyzed using logistic and zero-inflated Poisson (ZIP) regression. Perceived health status was a significant factor in the count model, and fall efficacy emerged as a significant predictor in the logistic models. The findings suggest that fall efficacy is important for predicting not only faller and nonfaller status but also fall counts in older adults who may or may not have experienced a previous fall. The fall predictors identified in this study--perceived health status and fall efficacy--indicate the need for fall-prevention programs tailored to address both the physical and psychological issues unique to older adults. © The Author(s) 2014.

  8. Recent Studies of Nucleon Electromagnetic Form Factors

    International Nuclear Information System (INIS)

    Gilad, Shalev

    2010-01-01

    The electromagnetic form factors of nucleons are fundamental quantities in nucleon structure. As such, they have been studied extensively both theoretically and experimentally. Significant progress has been made with new measurements at Jlab, MAMI and MIT-Bates, with emphases on expanding the momentum-transfer range and on higher precision. In this paper, we describe the status of this field and present new results from measurements at both low and high momentum transfers. We also compare the experimental data to model predictions, and mention possible implications of the new results to other fields.

  9. [Risk factors of eating disorders in the narratives of fashion models].

    Science.gov (United States)

    Bogár, Nikolett; Túry, Ferenc

    2017-01-01

    The risk of eating disorders is high in populations who are exposed to slimness ideal, so among fashion models. The present qualitative study evaluates the risk factors of eating disorders in a group of fashion models with semistructured interview. Moreover, the aim of the study was to examine the impact of professional requirements on the health of models. The study group was internationally heterogeneous. The models were involved by personal professional relationship. A semistructured questionnaire was used by e-mail containing anthropometric data and different aspects of the model profession. 29 female and three male models, three agents, two designers, three fotographers, one personal trainer and one stylist answered the questionnaire. Transient bulimic symptoms were reported by six female models (21%). Moreover, five female models fulfilled the DSM-5 criteria of anorexia nervosa or bulimia nervosa. Four of them were anorexic (body mass index: 13.9-15.3), one was bulimic. The symptoms of three persons began before the model career, those of two models after it. 17 models reported that the model profession intensively increased the bodily preoccupations. The study corroborates the effect of the model profession on the increase of the risk for eating disorders. In the case of the models, whose eating disorder began after stepping into the model profession, the role of the representants of the fashion industry can be suggested as a form of psychological abuse. As the models or in the case of underages their parents accepted the strong requirement of slimness, an unconscious collusion is probable. Our date highlight the health impact of cultural ideals, and call the attention to prevention strategies.

  10. Modeling the thermal absorption factor of photovoltaic/thermal combi-panels

    International Nuclear Information System (INIS)

    Santbergen, R.; Zolingen, R.J.Ch. van

    2006-01-01

    In a photovoltaic/thermal combi-panel solar cells generate electricity while residual heat is extracted to be used for tap water heating or room heating. In such a panel the entire solar spectrum can be used in principle. Unfortunately long wavelength solar irradiance is poorly absorbed by the semiconductor material in standard solar cells. A computer model was developed to determine the thermal absorption factor of crystalline silicon solar cells. It was found that for a standard untextured solar cell with a silver back contact a relatively large amount of long wavelength irradiance is lost by reflection resulting in an absorption factor of only 74%. The model was then used to investigate ways to increase this absorption factor. One way is absorbing long wavelength irradiance in a second absorber behind a semi-transparent solar cell. According to the model this will increase the total absorption factor to 87%. The second way is to absorb irradiance in the back contact of the solar cell by using rough interfaces in combination with a non-standard metal as back contact. Theoretically the absorption factor can then be increased to 85%

  11. Cross-Cultural Validation of the Modified Practice Attitudes Scale: Initial Factor Analysis and a New Factor Model.

    Science.gov (United States)

    Park, Heehoon; Ebesutani, Chad K; Chung, Kyong-Mee; Stanick, Cameo

    2018-01-01

    The objective of this study was to create the Korean version of the Modified Practice Attitudes Scale (K-MPAS) to measure clinicians' attitudes toward evidence-based treatments (EBTs) in the Korean mental health system. Using 189 U.S. therapists and 283 members from the Korean mental health system, we examined the reliability and validity of the MPAS scores. We also conducted the first exploratory and confirmatory factor analysis on the MPAS and compared EBT attitudes across U.S. and Korean therapists. Results revealed that the inclusion of both "reversed-worded" and "non-reversed-worded" items introduced significant method effects that compromised the integrity of the one-factor MPAS model. Problems with the one-factor structure were resolved by eliminating the "non-reversed-worded" items. Reliability and validity were adequate among both Korean and U.S. therapists. Korean therapists also reported significantly more negative attitudes toward EBTs on the MPAS than U.S. therapists. The K-MPAS is the first questionnaire designed to measure Korean service providers' attitudes toward EBTs to help advance the dissemination of EBTs in Korea. The current study also demonstrated the negative impacts that can be introduced by incorporating oppositely worded items into a scale, particularly with respect to factor structure and detecting significant group differences.

  12. Effect of Necessary Factors for Deploying E-Business Models on Business Performance in Automotive Industry

    OpenAIRE

    Mohsen Shafiei Nikabadi; Laya Olfat; Ahmad Jafarian; Hassan Alibabaei Khamene

    2013-01-01

    The main goal of this article is to survey effects of necessary factors for deploying e-business models on business performance in automotive industry. Today, application of information technology and internet in business is turned to a critical tool to gain competitive advantages in business. The impact of e-businesses is so that changed competitive approach between companies from traditional to modern models. In this study, first, necessary key factors of implementing e-business in automoti...

  13. Confirmatory Factor Analysis of the Structure of Statistics Anxiety Measure: An Examination of Four Alternative Models

    Directory of Open Access Journals (Sweden)

    Hossein Bevrani, PhD

    2011-09-01

    Full Text Available Objective: The aim of this study is to explore the confirmatory factor analysis results of the Persian adaptation of Statistics Anxiety Measure (SAM, proposed by Earp.Method: The validity and reliability assessments of the scale were performed on 298 college students chosen randomly from Tabriz University in Iran. Confirmatory factor analysis (CFA was carried out to determine the factor structures of the Persian adaptation of SAM.Results: As expected, the second order model provided a better fit to the data than the three alternative models. Conclusions: Hence, SAM provides an equally valid measure for use among college students. The study both expands and adds support to the existing body of math anxiety literature.

  14. Modeling Child Development Factors for the Early Introduction of ICTs in Schools

    OpenAIRE

    K. E. Oyetade; S. D. Eyono Obono

    2015-01-01

    One of the fundamental characteristics of Information and Communication Technology (ICT) has been the ever-changing nature of continuous release and models of ICTs with its impact on the academic, social, and psychological benefits of its introduction in schools. However, there seems to be a growing concern about its negative impact on students when introduced early in schools for teaching and learning. This study aims to design a model of child development factors affect...

  15. Modeling wind adjustment factor and midflame wind speed for Rothermel's surface fire spread model

    Science.gov (United States)

    Patricia L. Andrews

    2012-01-01

    Rothermel's surface fire spread model was developed to use a value for the wind speed that affects surface fire, called midflame wind speed. Models have been developed to adjust 20-ft wind speed to midflame wind speed for sheltered and unsheltered surface fuel. In this report, Wind Adjustment Factor (WAF) model equations are given, and the BehavePlus fire modeling...

  16. A New European Slope Length and Steepness Factor (LS-Factor for Modeling Soil Erosion by Water

    Directory of Open Access Journals (Sweden)

    Panos Panagos

    2015-04-01

    Full Text Available The Universal Soil Loss Equation (USLE model is the most frequently used model for soil erosion risk estimation. Among the six input layers, the combined slope length and slope angle (LS-factor has the greatest influence on soil loss at the European scale. The S-factor measures the effect of slope steepness, and the L-factor defines the impact of slope length. The combined LS-factor describes the effect of topography on soil erosion. The European Soil Data Centre (ESDAC developed a new pan-European high-resolution soil erosion assessment to achieve a better understanding of the spatial and temporal patterns of soil erosion in Europe. The LS-calculation was performed using the original equation proposed by Desmet and Govers (1996 and implemented using the System for Automated Geoscientific Analyses (SAGA, which incorporates a multiple flow algorithm and contributes to a precise estimation of flow accumulation. The LS-factor dataset was calculated using a high-resolution (25 m Digital Elevation Model (DEM for the whole European Union, resulting in an improved delineation of areas at risk of soil erosion as compared to lower-resolution datasets. This combined approach of using GIS software tools with high-resolution DEMs has been successfully applied in regional assessments in the past, and is now being applied for first time at the European scale.

  17. Form factors of ηc in light-front quark model

    International Nuclear Information System (INIS)

    Geng, Chao-Qiang; Lih, Chong-Chung

    2013-01-01

    We study the form factors of the η c meson in the light-front quark model. We explicitly show that the transition form factor of η c → γ * γ as a function of the momentum transfer is consistent with the experimental data by the BaBar collaboration, while the decay constant of η c is found to be f η c = 230.5 +52.2 -61.0 and 303.6 +115.2 -116.4 MeV for η c ∝ c anti c by using two η c → γγ decay widths of 5.3 ± 0.5 and 7.2 ± 2.1 keV, given by Particle Data Group and Lattice QCD calculation, respectively. (orig.)

  18. Factors associated with adoption of health information technology: a conceptual model based on a systematic review.

    Science.gov (United States)

    Kruse, Clemens Scott; DeShazo, Jonathan; Kim, Forest; Fulton, Lawrence

    2014-05-23

    The Health Information Technology for Economic and Clinical Health Act (HITECH) allocated $19.2 billion to incentivize adoption of the electronic health record (EHR). Since 2009, Meaningful Use Criteria have dominated information technology (IT) strategy. Health care organizations have struggled to meet expectations and avoid penalties to reimbursements from the Center for Medicare and Medicaid Services (CMS). Organizational theories attempt to explain factors that influence organizational change, and many theories address changes in organizational strategy. However, due to the complexities of the health care industry, existing organizational theories fall short of demonstrating association with significant health care IT implementations. There is no organizational theory for health care that identifies, groups, and analyzes both internal and external factors of influence for large health care IT implementations like adoption of the EHR. The purpose of this systematic review is to identify a full-spectrum of both internal organizational and external environmental factors associated with the adoption of health information technology (HIT), specifically the EHR. The result is a conceptual model that is commensurate with the complexity of with the health care sector. We performed a systematic literature search in PubMed (restricted to English), EBSCO Host, and Google Scholar for both empirical studies and theory-based writing from 1993-2013 that demonstrated association between influential factors and three modes of HIT: EHR, electronic medical record (EMR), and computerized provider order entry (CPOE). We also looked at published books on organizational theories. We made notes and noted trends on adoption factors. These factors were grouped as adoption factors associated with various versions of EHR adoption. The resulting conceptual model summarizes the diversity of independent variables (IVs) and dependent variables (DVs) used in articles, editorials, books, as

  19. Report: Optimization study of the preparation factors for argan oil microcapsule based on hybrid-level orthogonal array design via SPSS modeling.

    Science.gov (United States)

    Zhao, Xi; Wu, Xiaoli; Zhou, Hui; Jiang, Tao; Chen, Chun; Liu, Mingshi; Jin, Yuanbao; Yang, Dongsheng

    2014-11-01

    To optimize the preparation factors for argan oil microcapsule using complex coacervation of chitosan cross-linked with gelatin based on hybrid-level orthogonal array design via SPSS modeling. Eight relatively significant factors were firstly investigated and selected as calculative factors for the orthogonal array design from the total of ten factors effecting the preparation of argan oil microcapsule by utilizing the single factor variable method. The modeling of hybrid-level orthogonal array design was built in these eight factors with the relevant levels (9, 9, 9, 9, 7, 6, 2 and 2 respectively). The preparation factors for argan oil microcapsule were investigated and optimized according to the results of hybrid-level orthogonal array design. The priorities order and relevant optimum levels of preparation factors standard to base on the percentage of microcapsule with the diameter of 30~40 μm via SPSS. Experimental data showed that the optimum factors were controlling the chitosan/gelatin ratio, the systemic concentration and the core/shell ratio at 1:2, 1.5% and 1:7 respectively, presetting complex coacervation pH at 6.4, setting cross-linking time and complex coacervation at 75 min and 30 min, using the glucose-delta lactone as the type of cross-linking agent, and selecting chitosan with the molecular weight of 2000~3000.

  20. A protective factors model for alcohol abuse and suicide prevention among Alaska Native youth.

    Science.gov (United States)

    Allen, James; Mohatt, Gerald V; Fok, Carlotta Ching Ting; Henry, David; Burkett, Rebekah

    2014-09-01

    This study provides an empirical test of a culturally grounded theoretical model for prevention of alcohol abuse and suicide risk with Alaska Native youth, using a promising set of culturally appropriate measures for the study of the process of change and outcome. This model is derived from qualitative work that generated an heuristic model of protective factors from alcohol (Allen et al. in J Prev Interv Commun 32:41-59, 2006; Mohatt et al. in Am J Commun Psychol 33:263-273, 2004a; Harm Reduct 1, 2004b). Participants included 413 rural Alaska Native youth ages 12-18 who assisted in testing a predictive model of Reasons for Life and Reflective Processes about alcohol abuse consequences as co-occurring outcomes. Specific individual, family, peer, and community level protective factor variables predicted these outcomes. Results suggest prominent roles for these predictor variables as intermediate prevention strategy target variables in a theoretical model for a multilevel intervention. The model guides understanding of underlying change processes in an intervention to increase the ultimate outcome variables of Reasons for Life and Reflective Processes regarding the consequences of alcohol abuse.

  1. Person-fit to the Five Factor Model of personality

    Czech Academy of Sciences Publication Activity Database

    Allik, J.; Realo, A.; Mõttus, R.; Borkenau, P.; Kuppens, P.; Hřebíčková, Martina

    2012-01-01

    Roč. 71, č. 1 (2012), s. 35-45 ISSN 1421-0185 R&D Projects: GA ČR GAP407/10/2394 Institutional research plan: CEZ:AV0Z70250504 Keywords : Five Factor Model * cross - cultural comparison * person-fit Subject RIV: AN - Psychology Impact factor: 0.638, year: 2012

  2. A Solution to Modeling Multilevel Confirmatory Factor Analysis with Data Obtained from Complex Survey Sampling to Avoid Conflated Parameter Estimates

    Directory of Open Access Journals (Sweden)

    Jiun-Yu Wu

    2017-09-01

    Full Text Available The issue of equality in the between-and within-level structures in Multilevel Confirmatory Factor Analysis (MCFA models has been influential for obtaining unbiased parameter estimates and statistical inferences. A commonly seen condition is the inequality of factor loadings under equal level-varying structures. With mathematical investigation and Monte Carlo simulation, this study compared the robustness of five statistical models including two model-based (a true and a mis-specified models, one design-based, and two maximum models (two models where the full rank of variance-covariance matrix is estimated in between level and within level, respectively in analyzing complex survey measurement data with level-varying factor loadings. The empirical data of 120 3rd graders' (from 40 classrooms perceived Harter competence scale were modeled using MCFA and the parameter estimates were used as true parameters to perform the Monte Carlo simulation study. Results showed maximum models was robust to unequal factor loadings while the design-based and the miss-specified model-based approaches produced conflated results and spurious statistical inferences. We recommend the use of maximum models if researchers have limited information about the pattern of factor loadings and measurement structures. Measurement models are key components of Structural Equation Modeling (SEM; therefore, the findings can be generalized to multilevel SEM and CFA models. Mplus codes are provided for maximum models and other analytical models.

  3. Efficient fully 3D list-mode TOF PET image reconstruction using a factorized system matrix with an image domain resolution model

    International Nuclear Information System (INIS)

    Zhou, Jian; Qi, Jinyi

    2014-01-01

    A factorized system matrix utilizing an image domain resolution model is attractive in fully 3D time-of-flight PET image reconstruction using list-mode data. In this paper, we study a factored model based on sparse matrix factorization that is comprised primarily of a simplified geometrical projection matrix and an image blurring matrix. Beside the commonly-used Siddon’s ray-tracer, we propose another more simplified geometrical projector based on the Bresenham’s ray-tracer which further reduces the computational cost. We discuss in general how to obtain an image blurring matrix associated with a geometrical projector, and provide theoretical analysis that can be used to inspect the efficiency in model factorization. In simulation studies, we investigate the performance of the proposed sparse factorization model in terms of spatial resolution, noise properties and computational cost. The quantitative results reveal that the factorization model can be as efficient as a non-factored model, while its computational cost can be much lower. In addition we conduct Monte Carlo simulations to identify the conditions under which the image resolution model can become more efficient in terms of image contrast recovery. We verify our observations using the provided theoretical analysis. The result offers a general guide to achieve the optimal reconstruction performance based on a sparse factorization model with an image domain resolution model. (paper)

  4. Baryon octet electromagnetic form factors in a confining NJL model

    Directory of Open Access Journals (Sweden)

    Manuel E. Carrillo-Serrano

    2016-08-01

    Full Text Available Electromagnetic form factors of the baryon octet are studied using a Nambu–Jona-Lasinio model which utilizes the proper-time regularization scheme to simulate aspects of colour confinement. In addition, the model also incorporates corrections to the dressed quarks from vector meson correlations in the t-channel and the pion cloud. Comparison with recent chiral extrapolations of lattice QCD results shows a remarkable level of consistency. For the charge radii we find the surprising result that rEp

  5. A mathematical model for process cycle time - theory and case study

    Directory of Open Access Journals (Sweden)

    Filip Tošenovský

    2011-04-01

    Full Text Available The article focuses on derivation of a regression model which describes dependence of process cycle time on relevant factors entering the process. The analyzed processes are typical in that the coefficient of variation of times corresponding to a given level of influential factors remains stable if the level of the factors change. The derived model is subsequently applied to real industrial data which show that such a model is suitable for the description of relations. The paper has been published with support of Slovak Ministry of Education project KEGA 3/6411/08 „Transformation of the already existing study programme Management of production quality to an university-wide bilingual study programme“.

  6. A MATHEMATICAL MODEL FOR PROCESS CYCLE TIME - THEORY AND CASE STUDY

    Directory of Open Access Journals (Sweden)

    FILIP TOŠENOVSKÝ

    2010-12-01

    Full Text Available The article focuses on derivation of a regression model which describes dependence of process cycle time on relevant factors entering the process. The analyzed processes are typical in that the coefficient of variation of times corresponding to a given level of influential factors remains stable if the level of the factors change. The derived model is subsequently applied to real industrial data which show that such a model is suitable for the description of relations. The paper has been published with support of Slovak Ministry of Education project KEGA 3/6411/08 „Transformation of the already existing study programme Management of production quality to an university-wide bilingual study programme“.

  7. Application of the CIPP model in the study of factors that promote intercultural sensitivity

    Directory of Open Access Journals (Sweden)

    Ruiz-Bernardo, Paola

    2012-10-01

    Full Text Available The present study proposes a group of factors (related to self, context and process favouring the development of intercultural sensitivity. A social diagnosis was performed in the Spanish province of Castellón in order to identify these factors by means of a correlational study. A non-probabilistic but representative sample consisting of 995 people from 37 different countries living in this province was used. Data were collected by means of an adaptation of the scale proposed by Chen and Starosta (2000 for the assessment of intercultural sensitivity. Results showed four profiles, and their main characteristics were studied. Variables such as country of origin, gender, academic background, number of languages spoken, or the experience of living in a foreign country revealed to have a positive influence on the development of this attitude. El presente artículo propone un conjunto de los factores (personales, contextuales y de proceso que favorecen el desarrollo de la sensibilidad intercultural. Para identificar dichos factores se ha realizado un diagnóstico social en la provincia de Castellón (España. Este estudio de tipo descriptivo de carácter correlacional se ha concretado con una muestra de 995 personas de 37 nacionalidades diferentes, constituyendo una muestra representativa, caracterizada por ser de tipo fortuito o accidental. Para recoger la información se ha utilizado una adaptación de la escala de sensibilidad intercultural de Chen y Starosta (2000. El análisis de datos ha permitido identificar cuatro perfiles, de los cuales se han estudiado sus principales características y se ha podido concluir que variables tales como la condición de origen, el sexo, la formación, la cantidad de lenguas que habla o el haber vivido en otro país influyen positivamente para el desarrollo de esta actitud.

  8. Rethinking "Harmonious Parenting" Using a Three-Factor Discipline Model

    Science.gov (United States)

    Greenspan, Stephen

    2006-01-01

    Diana Baumrind's typology of parenting is based on a two-factor model of "control" and "warmth". Her recommended discipline style, labeled "authoritative parenting", was constructed by taking high scores on these two factors. A problem with authoritative parenting is that it does not allow for flexible and differentiated responses to discipline…

  9. Human Modeling for Ground Processing Human Factors Engineering Analysis

    Science.gov (United States)

    Stambolian, Damon B.; Lawrence, Brad A.; Stelges, Katrine S.; Steady, Marie-Jeanne O.; Ridgwell, Lora C.; Mills, Robert E.; Henderson, Gena; Tran, Donald; Barth, Tim

    2011-01-01

    There have been many advancements and accomplishments over the last few years using human modeling for human factors engineering analysis for design of spacecraft. The key methods used for this are motion capture and computer generated human models. The focus of this paper is to explain the human modeling currently used at Kennedy Space Center (KSC), and to explain the future plans for human modeling for future spacecraft designs

  10. Effects of leukemia inhibitory factor and basic fibroblast growth factor on free radicals and endogenous stem cell proliferation in a mouse model of cerebral infarction.

    Science.gov (United States)

    Huang, Weihui; Li, Yadan; Lin, Yufeng; Ye, Xue; Zang, Dawei

    2012-07-05

    The present study established a mouse model of cerebral infarction by middle cerebral artery occlusion, and monitored the effect of 25 μg/kg leukemia inhibitory factor and (or) basic fibroblast growth factor administration 2 hours after model establishment. Results showed that following administration, the number of endogenous neural stem cells in the infarct area significantly increased, malondialdehyde content in brain tissue homogenates significantly decreased, nitric oxide content, glutathione peroxidase and superoxide dismutase activity significantly elevated, and mouse motor function significantly improved as confirmed by the rotarod and bar grab tests. In particular, the effect of leukemia inhibitory factor in combination with basic fibroblast growth factor was the most significant. Results indicate that leukemia inhibitory factor and basic fibroblast growth factor can improve the microenvironment after cerebral infarction by altering free radical levels, improving the quantity of endogenous neural stem cells, and promoting neurological function of mice with cerebral infarction.

  11. Role of intrinsic factors in impulsive buying decision: An empirical study of young consumers

    Directory of Open Access Journals (Sweden)

    Shakeel Ahmad Sofi

    2017-06-01

    Full Text Available The primary aim of the current research was to study the effect of various intrinsic factors on consumer decision making vis-à-vis impulsive buying tendencies. After employing EFA and CFA on 630 consumers in the different parts of Jammu and Kashmir, results showed that intrinsic factors significantly influence the Impulsive Buying Decision. The application of Structural Equation Modeling disintegrated intrinsic factors into positive and negative influencers of impulsive buying behaviour. The present study has significant bearing in consumer world as it has highlighted through a model for how intrinsic factors shape the buying tendencies of a young consumer. Through the application of Multi Group Analysis, a comparison has been drawn between impulsive buying behaviour and various intrinsic factors across males and females taken as two different consumer groups. Overall results have been found significant and could well be adopted for strategy making by various stake holders in the field of consumer psychology and consumer behaviour to figure out the effects of intrinsic factors on buying behaviour.

  12. Volatile particles formation during PartEmis: a modelling study

    Directory of Open Access Journals (Sweden)

    X. Vancassel

    2004-01-01

    Full Text Available A modelling study of the formation of volatile particles in a combustor exhaust has been carried out in the frame of the PartEmis European project. A kinetic model has been used in order to investigate nucleation efficiency of the H2O-H2SO4 binary mixture in the sampling system. A value for the fraction of the fuel sulphur S(IV converted into S(VI has been indirectly deduced from comparisons between model results and measurements. In the present study, ranges between roughly 2.5% and 6%, depending on the combustor settings and on the value assumed for the parameter describing sulphuric acid wall losses. Soot particles hygroscopicity has also been investigated as their activation is a key parameter for contrail formation. Growth factors of monodisperse particles exposed to high relative humidity (95% have been calculated and compared with experimental results. The modelling study confirms that the growth factor increases as the soot particle size decreases.

  13. Aspect-Aware Latent Factor Model: Rating Prediction with Ratings and Reviews

    OpenAIRE

    Cheng, Zhiyong; Ding, Ying; Zhu, Lei; Kankanhalli, Mohan

    2018-01-01

    Although latent factor models (e.g., matrix factorization) achieve good accuracy in rating prediction, they suffer from several problems including cold-start, non-transparency, and suboptimal recommendation for local users or items. In this paper, we employ textual review information with ratings to tackle these limitations. Firstly, we apply a proposed aspect-aware topic model (ATM) on the review text to model user preferences and item features from different aspects, and estimate the aspect...

  14. A test of resuspension factor models against Chernobyl data

    International Nuclear Information System (INIS)

    Garger, E.K.; Hoffman, F.O.

    1995-04-01

    After the accident at Unit 4 of the Chernobyl nuclear power plant (NPP), stationary air samplers were operated at Chernobyl and Baryshevka, cities which are 16 km and 150 km, respectively, from the NPP. Other air samplers were operated simultaneously, but intermittently, at locations within the 30 km zone at distances of 4-25 km from the NPP. These data were used to check the validity of time dependent models of the resuspension factor K (m -1 ). Seven different models were examined, three of which are discussed in the paper. Data from the stationary air samplers were averaged over one day or one month; dam from the intermittent air samplers were averaged over three days in 1986 and over four hours in 1991. The concentrations of eight radionuclides were measured at ten points during the same time period (14-17 September 1986). The calculated resuspension factors range from 6 x 10 -9 m -1 to 3 x 10 -6 m -1 . Data for the spatial means of K are given for certain time periods in 1986 and 1991; also presented are the calculated values according to the models. The experimental data and the calculated values differ by up to more than one order of magnitude. Also analysed was the temporal change in experimental values of K and these values were compared with model predictions. The annual means of the resuspension factor as determined experimentally and as calculated with the models are presented. The model derived from empirical data measured in Neuherberg after the Chernobyl accident agrees best with the data. The Garland model systematically gives results lower than the experimental values, and the calculated values of K from the Linsley model are consistently conservative. Also considered were the uncertainty of K due to fluctuations in air concentrations and possible biological effects of episodic exposures

  15. A test of resuspension factor models against Chernobyl data

    Energy Technology Data Exchange (ETDEWEB)

    Garger, E.K. [Ukrainian Academy of Agricultural Sciences, Kiev (Ukraine). Inst. of Radioecology; Anspaugh, L.R.; Shinn, J.H. [Lawrence Livermore National Lab., CA (United States); Hoffman, F.O. [Senes Oak Ridge, Inc., TN (United States)

    1995-04-01

    After the accident at Unit 4 of the Chernobyl nuclear power plant (NPP), stationary air samplers were operated at Chernobyl and Baryshevka, cities which are 16 km and 150 km, respectively, from the NPP. Other air samplers were operated simultaneously, but intermittently, at locations within the 30 km zone at distances of 4-25 km from the NPP. These data were used to check the validity of time dependent models of the resuspension factor K (m{sup -1}). Seven different models were examined, three of which are discussed in the paper. Data from the stationary air samplers were averaged over one day or one month; dam from the intermittent air samplers were averaged over three days in 1986 and over four hours in 1991. The concentrations of eight radionuclides were measured at ten points during the same time period (14-17 September 1986). The calculated resuspension factors range from 6 x 10{sup -9} m{sup -1} to 3 x 10{sup -6} m{sup -1}. Data for the spatial means of K are given for certain time periods in 1986 and 1991; also presented are the calculated values according to the models. The experimental data and the calculated values differ by up to more than one order of magnitude. Also analysed was the temporal change in experimental values of K and these values were compared with model predictions. The annual means of the resuspension factor as determined experimentally and as calculated with the models are presented. The model derived from empirical data measured in Neuherberg after the Chernobyl accident agrees best with the data. The Garland model systematically gives results lower than the experimental values, and the calculated values of K from the Linsley model are consistently conservative. Also considered were the uncertainty of K due to fluctuations in air concentrations and possible biological effects of episodic exposures.

  16. Model endophenotype for bipolar disorder: Qualitative Analysis, etiological factors, and research areas

    Directory of Open Access Journals (Sweden)

    Naraiana de Oliveira Tavares

    2014-12-01

    Full Text Available The aim of this study is to present an updated view of the writings on the endophenotype model for bipolar disorder using analytical methodologies. A review and analysis of networks was performed through descriptors and keywords that characterize the composition of the endophenotype model as a model of health. Information was collected from between 1992 and 2014, and the main thematic areas covered in the articles were identified. We discuss the results and question their cohesion, emphasizing the need to strengthen and identify the points of connection between etiological factors and characteristics that make up the model of endophenotypes for bipolar disorder.

  17. Model calculation of the scanned field enhancement factor of CNTs

    International Nuclear Information System (INIS)

    Ahmad, Amir; Tripathi, V K

    2006-01-01

    The field enhancement factor of a carbon nanotube (CNT) placed in a cluster of CNTs is smaller than an isolated CNT because the electric field on one tube is screened by neighbouring tubes. This screening depends on the length of the CNTs and the spacing between them. We have derived an expression to compute the field enhancement factor of CNTs under any positional distribution of CNTs using a model of a floating sphere between parallel anode and cathode plates. Using this expression we can compute the field enhancement factor of a CNT in a cluster (non-uniformly distributed CNTs). This expression is used to compute the field enhancement factor of a CNT in an array (uniformly distributed CNTs). Comparison has been shown with experimental results and existing models

  18. Container Throughput Forecasting Using Dynamic Factor Analysis and ARIMAX Model

    Directory of Open Access Journals (Sweden)

    Marko Intihar

    2017-11-01

    Full Text Available The paper examines the impact of integration of macroeconomic indicators on the accuracy of container throughput time series forecasting model. For this purpose, a Dynamic factor analysis and AutoRegressive Integrated Moving-Average model with eXogenous inputs (ARIMAX are used. Both methodologies are integrated into a novel four-stage heuristic procedure. Firstly, dynamic factors are extracted from external macroeconomic indicators influencing the observed throughput. Secondly, the family of ARIMAX models of different orders is generated based on the derived factors. In the third stage, the diagnostic and goodness-of-fit testing is applied, which includes statistical criteria such as fit performance, information criteria, and parsimony. Finally, the best model is heuristically selected and tested on the real data of the Port of Koper. The results show that by applying macroeconomic indicators into the forecasting model, more accurate future throughput forecasts can be achieved. The model is also used to produce future forecasts for the next four years indicating a more oscillatory behaviour in (2018-2020. Hence, care must be taken concerning any bigger investment decisions initiated from the management side. It is believed that the proposed model might be a useful reinforcement of the existing forecasting module in the observed port.

  19. Factors influencing antibiotic prescribing in long-term care facilities: a qualitative in-depth study.

    Science.gov (United States)

    van Buul, Laura W; van der Steen, Jenny T; Doncker, Sarah M M M; Achterberg, Wilco P; Schellevis, François G; Veenhuizen, Ruth B; Hertogh, Cees M P M

    2014-12-16

    Insight into factors that influence antibiotic prescribing is crucial when developing interventions aimed at a more rational use of antibiotics. We examined factors that influence antibiotic prescribing in long-term care facilities, and present a conceptual model that integrates these factors. Semi-structured qualitative interviews were conducted with physicians (n = 13) and nursing staff (n = 13) in five nursing homes and two residential care homes in the central-west region of the Netherlands. An iterative analysis was applied to interviews with physicians to identify and categorize factors that influence antibiotic prescribing, and to integrate these into a conceptual model. This conceptual model was triangulated with the perspectives of nursing staff. The analysis resulted in the identification of six categories of factors that can influence the antibiotic prescribing decision: the clinical situation, advance care plans, utilization of diagnostic resources, physicians' perceived risks, influence of others, and influence of the environment. Each category comprises several factors that may influence the decision to prescribe or not prescribe antibiotics directly (e.g. pressure of patients' family leading to antibiotic prescribing) or indirectly via influence on other factors (e.g. unfamiliarity with patients resulting in a higher physician perceived risk of non-treatment, in turn resulting in a higher tendency to prescribe antibiotics). Our interview study shows that several non-rational factors may affect antibiotic prescribing decision making in long-term care facilities, suggesting opportunities to reduce inappropriate antibiotic use. We developed a conceptual model that integrates the identified categories of influencing factors and shows the relationships between those categories. This model may be used as a practical tool in long-term care facilities to identify local factors potentially leading to inappropriate prescribing, and to subsequently

  20. The Benefits of Including Clinical Factors in Rectal Normal Tissue Complication Probability Modeling After Radiotherapy for Prostate Cancer

    International Nuclear Information System (INIS)

    Defraene, Gilles; Van den Bergh, Laura; Al-Mamgani, Abrahim; Haustermans, Karin; Heemsbergen, Wilma; Van den Heuvel, Frank; Lebesque, Joos V.

    2012-01-01

    Purpose: To study the impact of clinical predisposing factors on rectal normal tissue complication probability modeling using the updated results of the Dutch prostate dose-escalation trial. Methods and Materials: Toxicity data of 512 patients (conformally treated to 68 Gy [n = 284] and 78 Gy [n = 228]) with complete follow-up at 3 years after radiotherapy were studied. Scored end points were rectal bleeding, high stool frequency, and fecal incontinence. Two traditional dose-based models (Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) and a logistic model were fitted using a maximum likelihood approach. Furthermore, these model fits were improved by including the most significant clinical factors. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminating ability of all fits. Results: Including clinical factors significantly increased the predictive power of the models for all end points. In the optimal LKB, RS, and logistic models for rectal bleeding and fecal incontinence, the first significant (p = 0.011–0.013) clinical factor was “previous abdominal surgery.” As second significant (p = 0.012–0.016) factor, “cardiac history” was included in all three rectal bleeding fits, whereas including “diabetes” was significant (p = 0.039–0.048) in fecal incontinence modeling but only in the LKB and logistic models. High stool frequency fits only benefitted significantly (p = 0.003–0.006) from the inclusion of the baseline toxicity score. For all models rectal bleeding fits had the highest AUC (0.77) where it was 0.63 and 0.68 for high stool frequency and fecal incontinence, respectively. LKB and logistic model fits resulted in similar values for the volume parameter. The steepness parameter was somewhat higher in the logistic model, also resulting in a slightly lower D 50 . Anal wall DVHs were used for fecal incontinence, whereas anorectal wall dose best described the other two endpoints. Conclusions

  1. The Benefits of Including Clinical Factors in Rectal Normal Tissue Complication Probability Modeling After Radiotherapy for Prostate Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Defraene, Gilles, E-mail: gilles.defraene@uzleuven.be [Radiation Oncology Department, University Hospitals Leuven, Leuven (Belgium); Van den Bergh, Laura [Radiation Oncology Department, University Hospitals Leuven, Leuven (Belgium); Al-Mamgani, Abrahim [Department of Radiation Oncology, Erasmus Medical Center - Daniel den Hoed Cancer Center, Rotterdam (Netherlands); Haustermans, Karin [Radiation Oncology Department, University Hospitals Leuven, Leuven (Belgium); Heemsbergen, Wilma [Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam (Netherlands); Van den Heuvel, Frank [Radiation Oncology Department, University Hospitals Leuven, Leuven (Belgium); Lebesque, Joos V. [Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam (Netherlands)

    2012-03-01

    Purpose: To study the impact of clinical predisposing factors on rectal normal tissue complication probability modeling using the updated results of the Dutch prostate dose-escalation trial. Methods and Materials: Toxicity data of 512 patients (conformally treated to 68 Gy [n = 284] and 78 Gy [n = 228]) with complete follow-up at 3 years after radiotherapy were studied. Scored end points were rectal bleeding, high stool frequency, and fecal incontinence. Two traditional dose-based models (Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) and a logistic model were fitted using a maximum likelihood approach. Furthermore, these model fits were improved by including the most significant clinical factors. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminating ability of all fits. Results: Including clinical factors significantly increased the predictive power of the models for all end points. In the optimal LKB, RS, and logistic models for rectal bleeding and fecal incontinence, the first significant (p = 0.011-0.013) clinical factor was 'previous abdominal surgery.' As second significant (p = 0.012-0.016) factor, 'cardiac history' was included in all three rectal bleeding fits, whereas including 'diabetes' was significant (p = 0.039-0.048) in fecal incontinence modeling but only in the LKB and logistic models. High stool frequency fits only benefitted significantly (p = 0.003-0.006) from the inclusion of the baseline toxicity score. For all models rectal bleeding fits had the highest AUC (0.77) where it was 0.63 and 0.68 for high stool frequency and fecal incontinence, respectively. LKB and logistic model fits resulted in similar values for the volume parameter. The steepness parameter was somewhat higher in the logistic model, also resulting in a slightly lower D{sub 50}. Anal wall DVHs were used for fecal incontinence, whereas anorectal wall dose best described the other two endpoints

  2. Health-related quality of life in patients with polycystic ovary syndrome (PCOS): a model-based study of predictive factors.

    Science.gov (United States)

    Bazarganipour, Fatemeh; Ziaei, Saeide; Montazeri, Ali; Foroozanfard, Fatemeh; Kazemnejad, Anoshirvan; Faghihzadeh, Soghrat

    2014-04-01

    Understanding the factors that contribute to health-related quality of life (HRQOL) is critical for developing the most appropriate interventions for improving or maintaining the HRQOL in polycystic ovary syndrome (PCOS) patients. This study sought to determine the most significant predictors of the HRQOL in patients with PCOS. This was a cross-sectional study of 300 women with PCOS that was carried out in Kashan, Iran. A sample of women with PCOS was entered into the study and completed the following questionnaires: the Hospital Anxiety and Depression Scale, the Body Image Concern Inventory (BICI), the Rosenberg's Self-Esteem Scale score, the modified polycystic ovary syndrome health-related quality of life questionnaire, the Female Sexual Function Index. Both direct and indirect relationships among clinical severity, psychological status, self-esteem, body image, and sexual function as independent predictors of HRQOL were examined using structural equation modeling (SEM) analysis. By using the SEM, we simultaneously test a number of possible hypotheses concerning the interrelations among the predictors of HRQOL in PCOS patients. In relation with severity of PCOS, reproductive history and menstrual status explained a high proportion of the variance of clinical variables (factor loading 0.37 and 0.34, respectively). The highest effect on HRQL was exerted by indirect effect of clinical factor (β = 0.90), self-esteem (β = 1.12), body image (β = 1.06), and sexual function (β = 0.26) that influenced negatively HRQOL. The infertility and menstrual domains were the most affected areas of HRQOL. In relation with sexual dysfunction, the most affected domains were desire and arousal. The highest effect of PCOS symptoms on HRQOL impairment among patients was exerted by self-esteem, body image, and sexual dysfunction. With regard to HRQOL in clinical routine, we conclude these mediating factors should be taken into consideration and adequately treated if

  3. Maximum Likelihood Dynamic Factor Modeling for Arbitrary "N" and "T" Using SEM

    Science.gov (United States)

    Voelkle, Manuel C.; Oud, Johan H. L.; von Oertzen, Timo; Lindenberger, Ulman

    2012-01-01

    This article has 3 objectives that build on each other. First, we demonstrate how to obtain maximum likelihood estimates for dynamic factor models (the direct autoregressive factor score model) with arbitrary "T" and "N" by means of structural equation modeling (SEM) and compare the approach to existing methods. Second, we go beyond standard time…

  4. Modeling redistribution of α-HCH in Chinese soil induced by environment factors

    International Nuclear Information System (INIS)

    Tian, Chongguo; Liu Liyan; Ma Jianmin; Tang Jianhui; Li Yifan

    2011-01-01

    This study explores long-term environmental fate of α-HCH in China from 1952 to 2007 using ChnGPERM (Chinese Gridded Pesticide Emission and Residue Model). The model captures well the temporal and spatial variations of α-HCH concentration in Chinese soils by comparing with a number of measured data across China in different periods. The results demonstrate α-HCH grasshopping effect in Eastern China and reveal several important features of the chemical in Northeast and Southeast China. It is found that Northeast China is a prominent sink region of α-HCH emitted from Chinese sources and α-HCH contamination in Southwest China is largely attributed to foreign sources. Southeast China is shown to be a major source contributing to α-HCH contamination in Northeast China, incurred by several environmental factors including temperature, soil organic carbon content, wind field and precipitation. - Highlights: → Grasshopping effect is found in Eastern China. → Northeast China is a prominent sink region of α-HCH emitted from Chinese sources. → Southeast China is a major source region to α-HCH contamination in Northeast China. → The source-sink relationship is incurred by several environmental factors. - This study provides the first comprehensive overview to redistribution of a toxic chemical incurred by long-term variation of environmental factors across China.

  5. Modeling soft factors in computer-based wargames

    Science.gov (United States)

    Alexander, Steven M.; Ross, David O.; Vinarskai, Jonathan S.; Farr, Steven D.

    2002-07-01

    Computer-based wargames have seen much improvement in recent years due to rapid increases in computing power. Because these games have been developed for the entertainment industry, most of these advances have centered on the graphics, sound, and user interfaces integrated into these wargames with less attention paid to the game's fidelity. However, for a wargame to be useful to the military, it must closely approximate as many of the elements of war as possible. Among the elements that are typically not modeled or are poorly modeled in nearly all military computer-based wargames are systematic effects, command and control, intelligence, morale, training, and other human and political factors. These aspects of war, with the possible exception of systematic effects, are individually modeled quite well in many board-based commercial wargames. The work described in this paper focuses on incorporating these elements from the board-based games into a computer-based wargame. This paper will also address the modeling and simulation of the systemic paralysis of an adversary that is implied by the concept of Effects Based Operations (EBO). Combining the fidelity of current commercial board wargames with the speed, ease of use, and advanced visualization of the computer can significantly improve the effectiveness of military decision making and education. Once in place, the process of converting board wargames concepts to computer wargames will allow the infusion of soft factors into military training and planning.

  6. The effects of motivational factors on car use: a multidisciplinary modelling approach

    Energy Technology Data Exchange (ETDEWEB)

    Steg, L.; Ras, M. [University of Groningen (Netherlands). Centre for Environmental and Traffic Psychology; Geurs, K. [National Institute of Public Health and Environment, Bilthoven (Netherlands)

    2001-11-01

    Current transport models usually do not take motivational factors into account, and if they do, it is only implicitly. This paper presents a modelling approach aimed at explicitly examining the effects of motivational factors on present and future car use in the Netherlands. A car-use forecasting model for the years 2010 and 2020 was constructed on the basis of (i) a multinominal regression analysis, which revealed the importance of a motivational variable (viz., problem awareness) in explaining current car-use behavior separate from socio-demographic and socio-economic variables, and (ii) a population model constructed to forecast the size and composition of the Dutch population. The results show that car use could be better explained by taking motivational factors explicitly into account, and that the level of car use forecast might change significantly if changes in motivations are assumed. The question on how motivational factors could be incorporated into current (Dutch) national transport models was also addressed. (author)

  7. A model of real estate and psychological factors in decision-making to buy real estate

    Directory of Open Access Journals (Sweden)

    Bojan Grum

    2015-06-01

    Full Text Available This article explores the psychological characteristics of potential real estate buyers connected with their decision to buy. Through a review of research, it reveals that most studies of psychological factors in the decision to buy real estate have a partial and dispersed orientation, and examine individual factors independently. It appears that the research area is lacking clearly defined models of psychological factors in the decision to buy real estate that would integrally and relationally explain the role of psychological characteristics of real estate buyers and their expectations in relation to a decision to buy. The article identifies two sets of psychological factors, motivational and emotional, determines their interaction with potential buyers’ expectations when deciding to purchase real estate and offers starting points for forming a model.

  8. Clinical application of the five-factor model.

    Science.gov (United States)

    Widiger, Thomas A; Presnall, Jennifer Ruth

    2013-12-01

    The Five-Factor Model (FFM) has become the predominant dimensional model of general personality structure. The purpose of this paper is to suggest a clinical application. A substantial body of research indicates that the personality disorders included within the American Psychiatric Association's (APA) Diagnostic and Statistical Manual of Mental Disorders (DSM) can be understood as extreme and/or maladaptive variants of the FFM (the acronym "DSM" refers to any particular edition of the APA DSM). In addition, the current proposal for the forthcoming fifth edition of the DSM (i.e., DSM-5) is shifting closely toward an FFM dimensional trait model of personality disorder. Advantages of this shifting conceptualization are discussed, including treatment planning. © 2012 Wiley Periodicals, Inc.

  9. Assessing factors related to waist circumference and obesity: application of a latent variable model.

    Science.gov (United States)

    Dalvand, Sahar; Koohpayehzadeh, Jalil; Karimlou, Masoud; Asgari, Fereshteh; Rafei, Ali; Seifi, Behjat; Niksima, Seyed Hassan; Bakhshi, Enayatollah

    2015-01-01

    Because the use of BMI (Body Mass Index) alone as a measure of adiposity has been criticized, in the present study our aim was to fit a latent variable model to simultaneously examine the factors that affect waist circumference (continuous outcome) and obesity (binary outcome) among Iranian adults. Data included 18,990 Iranian individuals aged 20-65 years that are derived from the third National Survey of Noncommunicable Diseases Risk Factors in Iran. Using latent variable model, we estimated the relation of two correlated responses (waist circumference and obesity) with independent variables including age, gender, PR (Place of Residence), PA (physical activity), smoking status, SBP (Systolic Blood Pressure), DBP (Diastolic Blood Pressure), CHOL (cholesterol), FBG (Fasting Blood Glucose), diabetes, and FHD (family history of diabetes). All variables were related to both obesity and waist circumference (WC). Older age, female sex, being an urban resident, physical inactivity, nonsmoking, hypertension, hypercholesterolemia, hyperglycemia, diabetes, and having family history of diabetes were significant risk factors that increased WC and obesity. Findings from this study of Iranian adult settings offer more insights into factors associated with high WC and high prevalence of obesity in this population.

  10. Assessing Factors Related to Waist Circumference and Obesity: Application of a Latent Variable Model

    Directory of Open Access Journals (Sweden)

    Sahar Dalvand

    2015-01-01

    Full Text Available Background. Because the use of BMI (Body Mass Index alone as a measure of adiposity has been criticized, in the present study our aim was to fit a latent variable model to simultaneously examine the factors that affect waist circumference (continuous outcome and obesity (binary outcome among Iranian adults. Methods. Data included 18,990 Iranian individuals aged 20–65 years that are derived from the third National Survey of Noncommunicable Diseases Risk Factors in Iran. Using latent variable model, we estimated the relation of two correlated responses (waist circumference and obesity with independent variables including age, gender, PR (Place of Residence, PA (physical activity, smoking status, SBP (Systolic Blood Pressure, DBP (Diastolic Blood Pressure, CHOL (cholesterol, FBG (Fasting Blood Glucose, diabetes, and FHD (family history of diabetes. Results. All variables were related to both obesity and waist circumference (WC. Older age, female sex, being an urban resident, physical inactivity, nonsmoking, hypertension, hypercholesterolemia, hyperglycemia, diabetes, and having family history of diabetes were significant risk factors that increased WC and obesity. Conclusions. Findings from this study of Iranian adult settings offer more insights into factors associated with high WC and high prevalence of obesity in this population.

  11. Aggressors and Victims in Bullying and Cyberbullying: A Study of Personality Profiles using the Five-Factor Model.

    Science.gov (United States)

    Alonso, Cristina; Romero, Estrella

    2017-12-04

    Bullying and cyberbullying are highly prevalent in today's society. However, the personality profiles of different roles involved in this phenomenon remain little known. This study aims (1) to examine the association between bullying and cyberbullying in adolescents; and (2) to analyze the relationship between bullying and cyberbullying in terms of the domains and facets of the five-factor model (FFM). A total of 910 adolescents aged 12 to 19 years old participated. They were administered self-report assessments of aggression and victimization in bullying and cyberbullying, as well as the JS-NEO-S questionnaire. The results provide evidence of co-occurrence between bullying and cyberbullying (p cyberbullying groups showed that cybervictims score higher in neuroticism and openness, cybervictims and non-cybervictims non-cyberaggressors score higher in agreeableness and non-cybervictims non-cyberaggressors score higher in conscientiousness (p cyberbullying.

  12. Confirmatory Factor Analysis of the Combined Social Phobia Scale and Social Interaction Anxiety Scale: Support for a Bifactor Model

    Science.gov (United States)

    Gomez, Rapson; Watson, Shaun D.

    2017-01-01

    For the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) together, this study examined support for a bifactor model, and also the internal consistency reliability and external validity of the factors in this model. Participants (N = 526) were adults from the general community who completed the SPS and SIAS. Confirmatory factor analysis (CFA) of their ratings indicated good support for the bifactor model. For this model, the loadings for all but six items were higher on the general factor than the specific factors. The three positively worded items had negligible loadings on the general factor. The general factor explained most of the common variance in the SPS and SIAS, and demonstrated good model-based internal consistency reliability (omega hierarchical) and a strong association with fear of negative evaluation and extraversion. The practical implications of the findings for the utilization of the SPS and SIAS, and the theoretical and clinical implications for social anxiety are discussed. PMID:28210232

  13. Confirmatory Factor Analysis of the Combined Social Phobia Scale and Social Interaction Anxiety Scale: Support for a Bifactor Model.

    Science.gov (United States)

    Gomez, Rapson; Watson, Shaun D

    2017-01-01

    For the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) together, this study examined support for a bifactor model, and also the internal consistency reliability and external validity of the factors in this model. Participants ( N = 526) were adults from the general community who completed the SPS and SIAS. Confirmatory factor analysis (CFA) of their ratings indicated good support for the bifactor model. For this model, the loadings for all but six items were higher on the general factor than the specific factors. The three positively worded items had negligible loadings on the general factor. The general factor explained most of the common variance in the SPS and SIAS, and demonstrated good model-based internal consistency reliability (omega hierarchical) and a strong association with fear of negative evaluation and extraversion. The practical implications of the findings for the utilization of the SPS and SIAS, and the theoretical and clinical implications for social anxiety are discussed.

  14. Assessing posttraumatic stress disorder's latent structure in elderly bereaved European trauma survivors: evidence for a five-factor dysphoric and anxious arousal model.

    Science.gov (United States)

    Armour, Cherie; O'Connor, Maja; Elklit, Ask; Elhai, Jon D

    2013-10-01

    The three-factor structure of posttraumatic stress disorder (PTSD) specified by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, is not supported in the empirical literature. Two alternative four-factor models have received a wealth of empirical support. However, a consensus regarding which is superior has not been reached. A recent five-factor model has been shown to provide superior fit over the existing four-factor models. The present study investigated the fit of the five-factor model against the existing four-factor models and assessed the resultant factors' association with depression in a bereaved European trauma sample (N = 325). The participants were assessed for PTSD via the Harvard Trauma Questionnaire and depression via the Beck Depression Inventory. The five-factor model provided superior fit to the data compared with the existing four-factor models. In the dysphoric arousal model, depression was equally related to both dysphoric arousal and emotional numbing, whereas depression was more related to dysphoric arousal than to anxious arousal.

  15. Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling.

    Science.gov (United States)

    Golay, Philippe; Reverte, Isabelle; Rossier, Jérôme; Favez, Nicolas; Lecerf, Thierry

    2013-06-01

    The interpretation of the Wechsler Intelligence Scale for Children--Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all cross-loadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  16. [Does the GHQ-12 scoring system affect its factor structure? An exploratory study of Ibero American students].

    Science.gov (United States)

    Urzúa, Alfonso; Caqueo-Urízar, Alejandra; Bargsted, Mariana; Irarrázaval, Matías

    2015-06-01

    This study aimed to evaluate whether the scoring system of the General Health Questionnaire (GHQ-12) alters the instrument's factor structure. The method considered 1,972 university students from nine Ibero American countries. Modeling was performed with structural equations for 1, 2, and 3 latent factors. The mechanism for scoring the questions was analyzed within each type of structure. The results indicate that models with 2 and 3 factors show better goodness-of-fit. In relation to scoring mechanisms, procedure 0-1-1-1 for models with 2 and 3 factors showed the best fit. In conclusion, there appears to be a relationship between the response format and the number of factors identified in the instrument's structure. The model with the best fit was 3-factor 0-1-1-1-formatted, but 0-1-2-3 has acceptable and more stable indicators and provides a better format for two- and three-dimensional models.

  17. A Model of Factors Contributing to STEM Learning and Career Orientation

    Science.gov (United States)

    Nugent, Gwen; Barker, Bradley; Welch, Greg; Grandgenett, Neal; Wu, ChaoRong; Nelson, Carl

    2015-05-01

    The purpose of this research was to develop and test a model of factors contributing to science, technology, engineering, and mathematics (STEM) learning and career orientation, examining the complex paths and relationships among social, motivational, and instructional factors underlying these outcomes for middle school youth. Social cognitive career theory provided the foundation for the research because of its emphasis on explaining mechanisms which influence both career orientations and academic performance. Key constructs investigated were youth STEM interest, self-efficacy, and career outcome expectancy (consequences of particular actions). The study also investigated the effects of prior knowledge, use of problem-solving learning strategies, and the support and influence of informal educators, family members, and peers. A structural equation model was developed, and structural equation modeling procedures were used to test proposed relationships between these constructs. Results showed that educators, peers, and family-influenced youth STEM interest, which in turn predicted their STEM self-efficacy and career outcome expectancy. STEM career orientation was fostered by youth-expected outcomes for such careers. Results suggest that students' pathways to STEM careers and learning can be largely explained by these constructs, and underscore the importance of youth STEM interest.

  18. Identification and synthetic modeling of factors affecting American black duck populations

    Science.gov (United States)

    Conroy, Michael J.; Miller, Mark W.; Hines, James E.

    2002-01-01

    We reviewed the literature on factors potentially affecting the population status of American black ducks (Anas rupribes). Our review suggests that there is some support for the influence of 4 major, continental-scope factors in limiting or regulating black duck populations: 1) loss in the quantity or quality of breeding habitats; 2) loss in the quantity or quality of wintering habitats; 3) harvest, and 4) interactions (competition, hybridization) with mallards (Anas platyrhychos) during the breeding and/or wintering periods. These factors were used as the basis of an annual life cycle model in which reproduction rates and survival rates were modeled as functions of the above factors, with parameters of the model describing the strength of these relationships. Variation in the model parameter values allows for consideration of scientific uncertainty as to the degree each of these factors may be contributing to declines in black duck populations, and thus allows for the investigation of the possible effects of management (e.g., habitat improvement, harvest reductions) under different assumptions. We then used available, historical data on black duck populations (abundance, annual reproduction rates, and survival rates) and possible driving factors (trends in breeding and wintering habitats, harvest rates, and abundance of mallards) to estimate model parameters. Our estimated reproduction submodel included parameters describing negative density feedback of black ducks, positive influence of breeding habitat, and negative influence of mallard densities; our survival submodel included terms for positive influence of winter habitat on reproduction rates, and negative influences of black duck density (i.e., compensation to harvest mortality). Individual models within each group (reproduction, survival) involved various combinations of these factors, and each was given an information theoretic weight for use in subsequent prediction. The reproduction model with highest

  19. Can we replace CAPM and the Three-Factor model with Implied Cost of Capital?

    OpenAIRE

    Löthman, Robert; Pettersson, Eric

    2014-01-01

    Researchers criticize predominant expected return models for being imprecise and based on fundamentally flawed assumptions. This dissertation evaluates Implied Cost of Capital, CAPM and the Three-Factor model abilities to estimate returns. We study each models expected return association to realized return and test for abnormal returns. Our sample covers the period 2000 to 2012 and includes 2916 US firms. We find that Implied Cost of Capital has a stronger association with realized returns th...

  20. Computer modeling the boron compound factor in normal brain tissue

    International Nuclear Information System (INIS)

    Gavin, P.R.; Huiskamp, R.; Wheeler, F.J.; Griebenow, M.L.

    1993-01-01

    The macroscopic distribution of borocaptate sodium (Na 2 B 12 H 11 SH or BSH) in normal tissues has been determined and can be accurately predicted from the blood concentration. The compound para-borono-phenylalanine (p-BPA) has also been studied in dogs and normal tissue distribution has been determined. The total physical dose required to reach a biological isoeffect appears to increase directly as the proportion of boron capture dose increases. This effect, together with knowledge of the macrodistribution, led to estimates of the influence of the microdistribution of the BSH compound. This paper reports a computer model that was used to predict the compound factor for BSH and p-BPA and, hence, the equivalent radiation in normal tissues. The compound factor would need to be calculated for other compounds with different distributions. This information is needed to design appropriate normal tissue tolerance studies for different organ systems and/or different boron compounds

  1. Predicting Factors Associated with Regular Physical Activity among College Students: Applying BASNEF Model

    Directory of Open Access Journals (Sweden)

    B. Moeini

    2011-10-01

    Full Text Available Introduction & Objective: One of the important problems in modern society is people's sedentary life style. The aim of this study was to determine factors associated with regular physical activity among college students based on BASNEF model.Materials & Methods: This study was a cross-sectional study carried out on 400 students in Hamadan University of Medical Sciences. Based on the assignment among different schools, classified sampling method was chosen for data gathering using a questionnaire in three parts including: demographic information, constructs of BASNEF model, and standard international physical activity questionnaire (IPAQ. Data were analyzed by SPSS-13, and using appropriate statistical tests (Chi-square, T-test and regression. Results: Based on the results, 271 students(67.8 % had low, 124 (31% moderate ,and 5 (1.2% vigorous physical activity. There was a significant relationship (c2=6.739, df= 1, P= 0.034 between their residence and physical activity and students living in dormitory were reported to have higher level of physical activity. Behavioral intention and enabling factors from the constructs of BASNEF model were the best predictors for having physical activity in students (OR=1.215, P = 0.000 and (OR=1.119, P= 0.000 respectively.Conclusion: With regard to the fact that majority of the students did not engage in enough physical activity and enabling factors were the most effective predictors for having regular physical activity in them, it seems that providing sports facilities can promote physical activity among the students.(Sci J Hamadan Univ Med Sci 2011;18(3:70-76

  2. Prediction of human pharmacokinetics of activated recombinant factor VII and B-domain truncated factor VIII from animal population pharmacokinetic models of haemophilia

    DEFF Research Database (Denmark)

    Larsen, Malte Selch; Juul, Rasmus Vestergaard; Groth, Andreas Velsing

    2018-01-01

    activated factor VII (rFVIIa) and recombinant factor VIII (rFVIII) in several experimental animal models using population PK modelling, and apply a simulation-based approach to evaluate how well the developed animal population PK models predict human PK. PK models were developed for rFVIIa and r...

  3. Heart rate variation and electroencephalograph--the potential physiological factors for thermal comfort study.

    Science.gov (United States)

    Yao, Y; Lian, Z; Liu, W; Jiang, C; Liu, Y; Lu, H

    2009-04-01

    Human thermal comfort researches mainly focus on the relation between the environmental factors (e.g. ambient temperature, air humidity, and air velocity, etc.) and the thermal comfort sensation based on a large amount of subjective field investigations. Although some physiological factors, such as skin temperature and metabolism were used in many thermal comfort models,they are not enough to establish a perfect thermal comfort model. In this paper,another two physiological factors, i.e. heart rate variation (HRV) and electroencephalograph (EEG), are explored for the thermal comfort study. Experiments were performed to investigate how these physiological factors respond to the environmental temperatures, and what is the relationship between HRV and EEG and thermal comfort. The experimental results indicate that HRV and EEG may be related to thermal comfort, and they may be useful to understand the mechanism of thermal comfort.

  4. Multiscale Spatial Assessment of Determinant Factors of Land Use Change: Study at Urban Area of Yogyakarta

    Science.gov (United States)

    Susilo, Bowo

    2017-12-01

    Studies of land use change have been undertaken by different researchers using various methods. Among those methods, modelling is widely utilized. Modelling land use change required several components remarked as model variables. Those represent any conditions or factors which considered relevant or have some degree of correlation to the changes of land use. Variables which have significant correlation to land use change are referred as determinant factors or driving forces. Those factors as well as changes of land use are distributed across space and therefore referred as spatial determinant factors. The main objective of the research was to examine land use change and its determinant factors. Area and location of land use change were analysed based on three different years of land use maps, which are 1993, 2000 and 2007. Spatial and temporal analysis were performed which emphasize to the influence of scale to both of analysis’s. Urban area of Yogyakarta was selected as study area. Study area covered three different districts (kabupaten), involving 20 sub districts and totally consists of 74 villages. Result of this study shows that during 14 years periods (1993 to 2007), there were about 1,460 hectares of land use change had been taken place. Dominant type of land use change is agricultural to residential. The uses of different spatial and temporal scale in analysis were able to reveal different factors related to land use change. In general, factors influencing the quantities of land use change in the study area were population growth and the availability of land. The use of data with different spatial resolution can reveal the presence of various factors associated with the location of the change. Locations of land use change were influenced or determined by accessibility factors.

  5. DISTANCE AS KEY FACTOR IN MODELLING STUDENTS’ RECRUITMENT BY UNIVERSITIES

    Directory of Open Access Journals (Sweden)

    SIMONA MĂLĂESCU

    2015-10-01

    Full Text Available Distance as Key Factor in Modelling Students’ Recruitment by Universities. In a previous paper analysing the challenge of keeping up with the current methodologies in the analysis and modelling of students’ recruitment by universities in the case of some ECE countries which still don’t register or develop key data to take advantage from the state of the art knowledge on the domain, we have promised to approach the factor distance in a future work due to the extent of the topic. This paper fulfill that promise bringing a review of the literature especially dealing with modelling the geographical area of recruiting students of an university, where combining distance with the proximate key factors previously reviewed, complete the meta-analysis of existing literature we have started a year ago. Beyond the theoretical benefit from a practical perspective, the metaanalysis aimed at synthesizing elements of good practice that can be applied to the local university system.

  6. Unidimensional factor models imply weaker partial correlations than zero-order correlations.

    Science.gov (United States)

    van Bork, Riet; Grasman, Raoul P P P; Waldorp, Lourens J

    2018-06-01

    In this paper we present a new implication of the unidimensional factor model. We prove that the partial correlation between two observed variables that load on one factor given any subset of other observed variables that load on this factor lies between zero and the zero-order correlation between these two observed variables. We implement this result in an empirical bootstrap test that rejects the unidimensional factor model when partial correlations are identified that are either stronger than the zero-order correlation or have a different sign than the zero-order correlation. We demonstrate the use of the test in an empirical data example with data consisting of fourteen items that measure extraversion.

  7. Relationship between stress-related psychosocial work factors and suboptimal health among Chinese medical staff: a cross-sectional study.

    Science.gov (United States)

    Liang, Ying-Zhi; Chu, Xi; Meng, Shi-Jiao; Zhang, Jie; Wu, Li-Juan; Yan, Yu-Xiang

    2018-03-06

    The study aimed to develop and validate a model to measure psychosocial factors at work among medical staff in China based on confirmatory factor analysis (CFA). The second aim of the current study was to clarify the association between stress-related psychosocial work factors and suboptimal health status. The cross-sectional study was conducted using clustered sampling method. Xuanwu Hospital, a 3A grade hospital in Beijing. Nine hundred and fourteen medical staff aged over 40 years were sampled. Seven hundred and ninety-seven valid questionnaires were collected and used for further analyses. The sample included 94% of the Han population. The Copenhagen Psychosocial Questionnaire (COPSOQ) and the Suboptimal Health Status Questionnaires-25 were used to assess the psychosocial factors at work and suboptimal health status, respectively. CFA was conducted to establish the evaluating method of COPSOQ. A multivariate logistic regression model was used to estimate the relationship between suboptimal health status and stress-related psychosocial work factors among Chinese medical staff. There was a strong correlation among the five dimensions of COPSOQ based on the first-order factor model. Then, we established two second-order factors including negative and positive psychosocial work stress factors to evaluate psychosocial factors at work, and the second-order factor model fit well. The high score in negative (OR (95% CI)=1.47 (1.34 to 1.62), Pwork factors increased and decreased the risk of suboptimal health, respectively. This relationship remained statistically significant after adjusting for confounders and when using different cut-offs of suboptimal health status. Among medical staff, the second-order factor model was a suitable method to evaluate the COPSOQ. The negative and positive psychosocial work stress factors might be the risk and protective factors of suboptimal health, respectively. Moreover, negative psychosocial work stress was the most associated

  8. Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change.

    Science.gov (United States)

    Feng, Yongjiu; Tong, Xiaohua

    2017-09-22

    Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.

  9. The use of the bi-factor model to test the uni-dimensionality of a battery of reasoning tests.

    Science.gov (United States)

    Primi, Ricardo; Rocha da Silva, Marjorie Cristina; Rodrigues, Priscila; Muniz, Monalisa; Almeida, Leandro S

    2013-02-01

    The Battery of Reasoning Tests 5 (BPR-5) aims to assess the reasoning ability of individuals, using sub-tests with different formats and contents that require basic processes of inductive and deductive reasoning for their resolution. The BPR has three sequential forms: BPR-5i (for children from first to fifth grade), BPR-5 - Form A (for children from sixth to eighth grade) and BPR-5 - form B (for high school and undergraduate students). The present study analysed 412 questionnaires concerning BPR-5i, 603 questionnaires concerning BPR-5 - Form A and 1748 questionnaires concerning BPR-5 - Form B. The main goal was to test the uni-dimensionality of the battery and its tests in relation to items using the bi-factor model. Results suggest that the g factor loadings (extracted by the uni-dimensional model) do not change when the data is adjusted for a more flexible multi-factor model (bi-factor model). A general reasoning factor underlying different contents items is supported.

  10. Factors Facilitating the Implementation of Church-Based Heart Health Promotion Programs for Older Adults: A Qualitative Study Guided by the Precede-Proceed Model.

    Science.gov (United States)

    Banerjee, Ananya Tina; Kin, R; Strachan, Patricia H; Boyle, Michael H; Anand, Sonia S; Oremus, Mark

    2015-01-01

    To describe the factors facilitating the implementation of heart health promotion programs for older adults in Anglican, United, and Catholic churches. The study used qualitative methods comprising semistructured interviews and focus groups. The interviews and focus groups were conducted in Anglican, Catholic, and United churches located in the Canadian cities of Toronto and Hamilton, Ontario. Twelve ordained pastors and 21 older parishioners who attended church regularly and who had no health conditions were recruited to best explain how churches could be suitable locations for health promotion activities targeting older adults. Twelve semistructured interviews with the pastors and three focus groups with the 21 parishioners were undertaken. A component of the Precede-Proceed model (a model for planning health education and health promotion programs and policies) was applied to the findings after direct content analysis of the data. Participants identified pastor leadership, funding for a parish nurse, community-focused interventions, secured infrastructure, and social support from congregation members as pertinent factors required for implementing health promotion programs in Anglican, United, and Catholic churches. The findings have particular relevance for health promotion and public health because they suggest factors that would be necessary to design church-based heart health promotion programs for older adults at risk of chronic diseases.

  11. Behavioral phenotypes in schizophrenic animal models with multiple combinations of genetic and environmental factors.

    Science.gov (United States)

    Hida, Hirotake; Mouri, Akihiro; Noda, Yukihiro

    2013-01-01

    Schizophrenia is a multifactorial psychiatric disorder in which both genetic and environmental factors play a role. Genetic [e.g., Disrupted-in-schizophrenia 1 (DISC1), Neuregulin-1 (NRG1)] and environmental factors (e.g., maternal viral infection, obstetric complications, social stress) may act during the developmental period to increase the incidence of schizophrenia. In animal models, interactions between susceptibility genes and the environment can be controlled in ways not possible in humans; therefore, such models are useful for investigating interactions between or within factors in the pathogenesis and pathophysiology of schizophrenia. We provide an overview of schizophrenic animal models investigating interactions between or within factors. First, we reviewed gene-environment interaction animal models, in which schizophrenic candidate gene mutant mice were subjected to perinatal immune activation or adolescent stress. Next, environment-environment interaction animal models, in which mice were subjected to a combination of perinatal immune activation and adolescent administration of drugs, were described. These animal models showed interaction between or within factors; behavioral changes, which were obscured by each factor, were marked by interaction of factors and vice versa. Appropriate behavioral approaches with such models will be invaluable for translational research on novel compounds, and also for providing insight into the pathogenesis and pathophysiology of schizophrenia.

  12. Granularity as a Cognitive Factor in the Effectiveness of Business Process Model Reuse

    Science.gov (United States)

    Holschke, Oliver; Rake, Jannis; Levina, Olga

    Reusing design models is an attractive approach in business process modeling as modeling efficiency and quality of design outcomes may be significantly improved. However, reusing conceptual models is not a cost-free effort, but has to be carefully designed. While factors such as psychological anchoring and task-adequacy in reuse-based modeling tasks have been investigated, information granularity as a cognitive concept has not been at the center of empirical research yet. We hypothesize that business process granularity as a factor in design tasks under reuse has a significant impact on the effectiveness of resulting business process models. We test our hypothesis in a comparative study employing high and low granularities. The reusable processes provided were taken from widely accessible reference models for the telecommunication industry (enhanced Telecom Operations Map). First experimental results show that Recall in tasks involving coarser granularity is lower than in cases of finer granularity. These findings suggest that decision makers in business process management should be considerate with regard to the implementation of reuse mechanisms of different granularities. We realize that due to our small sample size results are not statistically significant, but this preliminary run shows that it is ready for running on a larger scale.

  13. HOCOMOCO: expansion and enhancement of the collection of transcription factor binding sites models

    KAUST Repository

    Kulakovskiy, Ivan V.

    2015-11-19

    Models of transcription factor (TF) binding sites provide a basis for a wide spectrum of studies in regulatory genomics, from reconstruction of regulatory networks to functional annotation of transcripts and sequence variants. While TFs may recognize different sequence patterns in different conditions, it is pragmatic to have a single generic model for each particular TF as a baseline for practical applications. Here we present the expanded and enhanced version of HOCOMOCO (http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco10), the collection of models of DNA patterns, recognized by transcription factors. HOCOMOCO now provides position weight matrix (PWM) models for binding sites of 601 human TFs and, in addition, PWMs for 396 mouse TFs. Furthermore, we introduce the largest up to date collection of dinucleotide PWM models for 86 (52) human (mouse) TFs. The update is based on the analysis of massive ChIP-Seq and HT-SELEX datasets, with the validation of the resulting models on in vivo data. To facilitate a practical application, all HOCOMOCO models are linked to gene and protein databases (Entrez Gene, HGNC, UniProt) and accompanied by precomputed score thresholds. Finally, we provide command-line tools for PWM and diPWM threshold estimation and motif finding in nucleotide sequences.

  14. Applying total interpretive structural modeling to study factors affecting construction labour productivity

    OpenAIRE

    Sayali Shrikrishna Sandbhor; Rohan P. Botre

    2014-01-01

    Construction sector has always been dependent on manpower. Most of the activities carried out on any construction site are labour intensive. Since productivity of any project depends directly on productivity of labour, it is a prime responsibility of the employer to enhance labour productivity. Measures to improve the same depend on analysis of positive and negative factors affecting productivity. Major attention should be given to factors that decrease the productivity of labour. Factor anal...

  15. Study of factors affecting the productivity of nurses based on the ACHIEVE model and prioritizing them using analytic hierarchy process technique, 2012

    Directory of Open Access Journals (Sweden)

    Payam Farhadi

    2013-01-01

    Full Text Available Objective: Improving productivity is one of the most important strategies for social-economic development. Human resources are known as the most important resources in the organizations′ survival and success. Aims: To determine the factors affecting the human resource productivity using the ACHIEVEa model from the nurses′ perspective and then prioritize them from the perspective of head nurses using Analytic Hierarchy Process (AHP technique. Settings and Design: Iran, Shiraz University of Medical Sciences teaching hospitals in 2012. Materials and Methods: This was an applied, cross-sectional and analytical-descriptive study conducted in two phases. In the first phase, to determine the factors affecting the human resource productivity from nurses′ perspective, 110 nurses were selected using a two-stage cluster sampling method. Required data were collected using the Persian version of Hersey and Goldsmith′s Human Resource Productivity Questionnaire. In the second phase, in order to prioritize the factors affecting human resource productivity based on the ACHIEVE model using AHP technique, pairwise comparisons matrices were given to the 19 randomly selected head nurses to express their opinions about those factors relative priorities or importance. Statistical Analysis Used: Collected data and matrices in two mentioned phases were analyzed using SPSS 15.0 and some statistical tests including Independent-Samples T-Test and Pearson Correlation coefficient, as well as, Super Decisions software (Latest Beta. Results: The human resource productivity had significant relationships with nurses′ sex (P = 0.008, marital status (P < 0.001, education level (P < 0.001, and all questionnaire factors (P < 0.05. Nurses′ productivity from their perspective was below average (44.97 ΁ 7.43. Also, the priorities of factors affecting the productivity of nurses based on the ACHIEVE model from the head nurses′ perspective using AHP technique, from the

  16. The effects of motivational factors on car use : a multidisciplinary modelling approach

    NARCIS (Netherlands)

    Steg, L; Geurs, K; Ras, M

    Current transport models usually do not take motivational factors into account, and if they do, it is only implicitly. This paper presents a modelling approach aimed at explicitly examining the effects of motivational factors on present and future car use in the Netherlands. A car-use forecasting

  17. Three-factor models versus time series models: quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data.

    Science.gov (United States)

    Frank, Till D; Kiyatkin, Anatoly; Cheong, Alex; Kholodenko, Boris N

    2017-06-01

    Signal integration determines cell fate on the cellular level, affects cognitive processes and affective responses on the behavioural level, and is likely to be involved in psychoneurobiological processes underlying mood disorders. Interactions between stimuli may subjected to time effects. Time-dependencies of interactions between stimuli typically lead to complex cell responses and complex responses on the behavioural level. We show that both three-factor models and time series models can be used to uncover such time-dependencies. However, we argue that for short longitudinal data the three factor modelling approach is more suitable. In order to illustrate both approaches, we re-analysed previously published short longitudinal data sets. We found that in human embryonic kidney 293 cells cells the interaction effect in the regulation of extracellular signal-regulated kinase (ERK) 1 signalling activation by insulin and epidermal growth factor is subjected to a time effect and dramatically decays at peak values of ERK activation. In contrast, we found that the interaction effect induced by hypoxia and tumour necrosis factor-alpha for the transcriptional activity of the human cyclo-oxygenase-2 promoter in HEK293 cells is time invariant at least in the first 12-h time window after stimulation. Furthermore, we applied the three-factor model to previously reported animal studies. In these studies, memory storage was found to be subjected to an interaction effect of the beta-adrenoceptor agonist clenbuterol and certain antagonists acting on the alpha-1-adrenoceptor / glucocorticoid-receptor system. Our model-based analysis suggests that only if the antagonist drug is administer in a critical time window, then the interaction effect is relevant. © The authors 2016. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

  18. Modelling the critical success factors of agile software development projects in South Africa

    Directory of Open Access Journals (Sweden)

    Tawanda B. Chiyangwa

    2017-10-01

    Full Text Available Background: The continued in failure of agile and traditional software development projects have led to the consideration, attention and dispute to critical success factors that are the aspects which are most vital to make a software engineering methodology fruitful. Although there is an increasing variety of critical success factors and methodologies, the conceptual frameworks which have causal relationship are limited. Objective: The objective of this study was to identify and provide insights into the critical success factors that influence the success of software development projects using agile methodologies in South Africa. Method: Quantitative method of collecting data was used. Data were collected in South Africa through a Web-based survey using structured questionnaires. Results: These results show that organisational factors have a great influence on performance expectancy characteristics. Conclusion: The results of this study discovered a comprehensive model that could provide guidelines to the agile community and to the agile professionals.

  19. Quantifying lead-time bias in risk factor studies of cancer through simulation.

    Science.gov (United States)

    Jansen, Rick J; Alexander, Bruce H; Anderson, Kristin E; Church, Timothy R

    2013-11-01

    Lead-time is inherent in early detection and creates bias in observational studies of screening efficacy, but its potential to bias effect estimates in risk factor studies is not always recognized. We describe a form of this bias that conventional analyses cannot address and develop a model to quantify it. Surveillance Epidemiology and End Results (SEER) data form the basis for estimates of age-specific preclinical incidence, and log-normal distributions describe the preclinical duration distribution. Simulations assume a joint null hypothesis of no effect of either the risk factor or screening on the preclinical incidence of cancer, and then quantify the bias as the risk-factor odds ratio (OR) from this null study. This bias can be used as a factor to adjust observed OR in the actual study. For this particular study design, as average preclinical duration increased, the bias in the total-physical activity OR monotonically increased from 1% to 22% above the null, but the smoking OR monotonically decreased from 1% above the null to 5% below the null. The finding of nontrivial bias in fixed risk-factor effect estimates demonstrates the importance of quantitatively evaluating it in susceptible studies. Copyright © 2013 Elsevier Inc. All rights reserved.

  20. Selection of asset investment models by hospitals: examination of influencing factors, using Switzerland as an example.

    Science.gov (United States)

    Eicher, Bernhard

    2016-10-01

    Hospitals are responsible for a remarkable part of the annual increase in healthcare expenditure. This article examines one of the major cost drivers, the expenditure for investment in hospital assets. The study, conducted in Switzerland, identifies factors that influence hospitals' investment decisions. A suggestion on how to categorize asset investment models is presented based on the life cycle of an asset, and its influencing factors defined based on transaction cost economics. The influence of five factors (human asset specificity, physical asset specificity, uncertainty, bargaining power, and privacy of ownership) on the selection of an asset investment model is examined using a two-step fuzzy-set Qualitative Comparative Analysis. The research shows that outsourcing-oriented asset investment models are particularly favored in the presence of two combinations of influencing factors: First, if technological uncertainty is high and both human asset specificity and bargaining power of a hospital are low. Second, if assets are very specific, technological uncertainty is high and there is a private hospital with low bargaining power, outsourcing-oriented asset investment models are favored too. Using Qualitative Comparative Analysis, it can be demonstrated that investment decisions of hospitals do not depend on isolated influencing factors but on a combination of factors. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  1. Dome effect of black carbon and its key influencing factors: a one-dimensional modelling study

    Science.gov (United States)

    Wang, Zilin; Huang, Xin; Ding, Aijun

    2018-02-01

    Black carbon (BC) has been identified to play a critical role in aerosol-planetary boundary layer (PBL) interaction and further deterioration of near-surface air pollution in megacities, which has been referred to as the dome effect. However, the impacts of key factors that influence this effect, such as the vertical distribution and aging processes of BC, as well as the underlying land surface, have not been quantitatively explored yet. Here, based on available in situ measurements of meteorology and atmospheric aerosols together with the meteorology-chemistry online coupled model WRF-Chem, we conduct a set of parallel simulations to quantify the roles of these factors in influencing the BC dome effect and surface haze pollution. Furthermore, we discuss the main implications of the results to air pollution mitigation in China. We found that the impact of BC on the PBL is very sensitive to the altitude of aerosol layer. The upper-level BC, especially that near the capping inversion, is more essential in suppressing the PBL height and weakening the turbulent mixing. The dome effect of BC tends to be significantly intensified as BC mixed with scattering aerosols during winter haze events, resulting in a decrease in PBL height by more than 15 %. In addition, the dome effect is more substantial (up to 15 %) in rural areas than that in the urban areas with the same BC loading, indicating an unexpected regional impact of such an effect to air quality in countryside. This study indicates that China's regional air pollution would greatly benefit from BC emission reductions, especially those from elevated sources from chimneys and also domestic combustion in rural areas, through weakening the aerosol-boundary layer interactions that are triggered by BC.

  2. Parametric study of a thorium model

    International Nuclear Information System (INIS)

    Lourenco, M.C.; Lipztein, J.L.; Szwarcwald, C.L.

    1997-01-01

    Full text. Models for radionuclides distribution in the human body and dosimetry involve assumptions on the biokinetic behaviour of the material among compartments representing organs and tissues in the body. The lack of knowledge about the metabolic behaviour of a radionuclide represents a factor of uncertainty in estimates of committed dose equivalent. An important problem in biokinetic modeling is the correct assignment of transfer coefficients and biological half-lives to body compartments. The purpose of this study is to analyze the variability in the activities of the body compartments in relation to the variations in the transfer coefficients and compartments biological half-lives in a certain model. A thorium specific recycling model for continuous exposure was used. Multiple regression analysis methods were applied to analyze the results

  3. Multi-factor energy price models and exotic derivatives pricing

    Science.gov (United States)

    Hikspoors, Samuel

    The high pace at which many of the world's energy markets have gradually been opened to competition have generated a significant amount of new financial activity. Both academicians and practitioners alike recently started to develop the tools of energy derivatives pricing/hedging as a quantitative topic of its own. The energy contract structures as well as their underlying asset properties set the energy risk management industry apart from its more standard equity and fixed income counterparts. This thesis naturally contributes to these broad market developments in participating to the advances of the mathematical tools aiming at a better theory of energy contingent claim pricing/hedging. We propose many realistic two-factor and three-factor models for spot and forward price processes that generalize some well known and standard modeling assumptions. We develop the associated pricing methodologies and propose stable calibration algorithms that motivate the application of the relevant modeling schemes.

  4. Strategic environmental assessment performance factors and their interaction: An empirical study in China

    Energy Technology Data Exchange (ETDEWEB)

    Li, Tianwei, E-mail: li.tianwei@mep.gov.cn [Appraisal Center for Environment and Engineering, MEP (China); Wang, Huizhi, E-mail: huizhiwangnk@163.com [Tianjin Academy of Social Sciences (China); Deng, Baole, E-mail: dengbaolekobe@126.com [Tianjin Environmental Monitoring Center (China); Ren, Wei, E-mail: wei.ren1012@gmail.com [School of the Built Environment, Oxford Brookes University (United Kingdom); Xu, He, E-mail: seacenter@nankai.edu.cn [Research center for Strategic Environmental Assessment, Nankai University (China)

    2016-07-15

    Strategic Environmental Assessment (SEA) has been seen as a preventive and participatory environmental management tool designed to integrate environmental protection into the decision-making process. However, the debate about SEA performance and effectiveness has increased in recent decades. Two main challenges exist in relation to this issue. The first is identifying the key influencing factors that affect SEA effectiveness, and the second is analyzing the relationship between SEA and these influencing factors. In this study, influencing factors were investigated through questionnaire surveys in the Chinese context, and then a Structural Equation Model (SEM) was developed and tested to identify potential links and causal relationships among factors. The associations between the independent factors were divided into direct and indirect causal associations. The results indicate that the decision-making process and policy context directly affect SEA implementation, while information and data sharing, public participation, expertise and SEA institutions are indirectly related with SEA. The results also suggest that a lack of cooperation between different sectors is an obstacle to the implementation of SEA. These findings could potentially contribute to the future management and implementation of SEA or enhance existing knowledge of SEA. The results show that the proposed model has a degree of feasibility and applicability. - Highlights: • Influencing factors were identified and investigated through questionnaire surveys. • Structural Equation Model (SEM) was developed and tested to identify potential links and causal relationships among factors. • Decision-making process and policy context directly affect SEA implementation. • Lack of cooperation among different sectors is an obstacle to the implementation of SEA. • The proposed model has a degree of feasibility and applicability.

  5. Strategic environmental assessment performance factors and their interaction: An empirical study in China

    International Nuclear Information System (INIS)

    Li, Tianwei; Wang, Huizhi; Deng, Baole; Ren, Wei; Xu, He

    2016-01-01

    Strategic Environmental Assessment (SEA) has been seen as a preventive and participatory environmental management tool designed to integrate environmental protection into the decision-making process. However, the debate about SEA performance and effectiveness has increased in recent decades. Two main challenges exist in relation to this issue. The first is identifying the key influencing factors that affect SEA effectiveness, and the second is analyzing the relationship between SEA and these influencing factors. In this study, influencing factors were investigated through questionnaire surveys in the Chinese context, and then a Structural Equation Model (SEM) was developed and tested to identify potential links and causal relationships among factors. The associations between the independent factors were divided into direct and indirect causal associations. The results indicate that the decision-making process and policy context directly affect SEA implementation, while information and data sharing, public participation, expertise and SEA institutions are indirectly related with SEA. The results also suggest that a lack of cooperation between different sectors is an obstacle to the implementation of SEA. These findings could potentially contribute to the future management and implementation of SEA or enhance existing knowledge of SEA. The results show that the proposed model has a degree of feasibility and applicability. - Highlights: • Influencing factors were identified and investigated through questionnaire surveys. • Structural Equation Model (SEM) was developed and tested to identify potential links and causal relationships among factors. • Decision-making process and policy context directly affect SEA implementation. • Lack of cooperation among different sectors is an obstacle to the implementation of SEA. • The proposed model has a degree of feasibility and applicability.

  6. Some factors that will affect the next generation of forest growth models

    International Nuclear Information System (INIS)

    Leary, R.A.

    1988-01-01

    This paper discusses several types of factors that affect the form and referents of future growth models. These include philosophical, scientific, technological, educational, and organizational factors. Each factor is presented individually

  7. Demographic and Operational Factors Predicting Study Completion in a Multisite Case-Control Study of Preschool Children.

    Science.gov (United States)

    Bradley, Chyrise B; Browne, Erica N; Alexander, Aimee A; Collins, Jack; Dahm, Jamie L; DiGuiseppi, Carolyn G; Levy, Susan E; Moody, Eric J; Schieve, Laura A; Windham, Gayle C; Young, Lisa; Daniels, Julie L

    2018-03-01

    Participant attrition can limit inferences drawn from study results and inflate research costs. We examined factors associated with completion of the Study to Explore Early Development (2007-2011), a multiple-component, case-control study of risk factors for autism spectrum disorder in preschoolers, conducted in California, Colorado, Georgia, Maryland, North Carolina, and Pennsylvania. Participants (n = 3,769) were asked to complete phone interviews, questionnaires, an in-person evaluation, and biologic sampling. We examined whether participant demographic and administrative factors predicted completion using mixed-effects logistic regression models. Completion of individual key study components was generally 70% or higher. However, 58% of families completed all per-protocol data elements (defined a priori as key study components). Per-protocol completion differed according to mother's age, race, educational level, driving distance to clinic, number of contact attempts to enroll, and number of telephone numbers provided (all P < 0.05). Case status was not associated with completion, despite additional data collection for case-confirmation. Analysis of a subset that completed an early interview revealed no differences in completion by household factors of income, primary language spoken, number of adults, or number of children with chronic conditions. Differences in completion by race and education were notable and need to be carefully considered in developing future recruitment and completion strategies.

  8. High Resolution Modeling of the Impacts of Exogenous Factors on Power Systems—Case Study of Germany

    Directory of Open Access Journals (Sweden)

    Antriksh Singh

    2015-12-01

    Full Text Available In order to reliably design the planning and operation of large interconnected power systems that can incorporate a high penetration of renewables, it is necessary to have a detailed knowledge of the potential impacts of exogenous factors on individual components within the systems. Previously, the assessment has often been conducted with nodes that are aggregated at the country or regional scale; this makes it impossible to reliably extrapolate the impact of higher penetration of renewables on individual transmission lines and/or power plants within an aggregated node. In order to be able to develop robust power systems this study demonstrates an integrated framework that employs high resolution spatial and temporal, physical modeling of power generation, electricity transmission and electricity demand, across the scale of a continent or country. Using Germany as a test case, an assessment of the impacts of exogenous factors, including local changes in ambient weather conditions, effect of timely implementation of policy, and contingency for scenarios in 2020 are demonstrated. It is shown that with the increased penetration of renewables, while the power production opportunities of conventional power plants are reduced, these power plants are required during periods of low renewables production due to the inherent variability of renewables. While the planned reinforcements in Germany, including high voltage direct current lines, reduce congestion on the grid and alleviate the differentials in power price across the country, on the other hand the reinforcements make the interconnected transmission system more vulnerable as local perturbations have a more widespread impact.

  9. Predictive model of thrombospondin-1 and vascular endothelial growth factor in breast tumor tissue.

    Science.gov (United States)

    Rohrs, Jennifer A; Sulistio, Christopher D; Finley, Stacey D

    2016-01-01

    Angiogenesis, the formation of new blood capillaries from pre-existing vessels, is a hallmark of cancer. Thus far, strategies for reducing tumor angiogenesis have focused on inhibiting pro-angiogenic factors, while less is known about the therapeutic effects of mimicking the actions of angiogenesis inhibitors. Thrombospondin-1 (TSP1) is an important endogenous inhibitor of angiogenesis that has been investigated as an anti-angiogenic agent. TSP1 impedes the growth of new blood vessels in many ways, including crosstalk with pro-angiogenic factors. Due to the complexity of TSP1 signaling, a predictive systems biology model would provide quantitative understanding of the angiogenic balance in tumor tissue. Therefore, we have developed a molecular-detailed, mechanistic model of TSP1 and vascular endothelial growth factor (VEGF), a promoter of angiogenesis, in breast tumor tissue. The model predicts the distribution of the angiogenic factors in tumor tissue, revealing that TSP1 is primarily in an inactive, cleaved form due to the action of proteases, rather than bound to its cellular receptors or to VEGF. The model also predicts the effects of enhancing TSP1's interactions with its receptors and with VEGF. To provide additional predictions that can guide the development of new anti-angiogenic drugs, we simulate administration of exogenous TSP1 mimetics that bind specific targets. The model predicts that the CD47-binding TSP1 mimetic dramatically decreases the ratio of receptor-bound VEGF to receptor-bound TSP1, in favor of anti-angiogenesis. Thus, we have established a model that provides a quantitative framework to study the response to TSP1 mimetics.

  10. Finite-lattice form factors in free-fermion models

    International Nuclear Information System (INIS)

    Iorgov, N; Lisovyy, O

    2011-01-01

    We consider the general Z 2 -symmetric free-fermion model on the finite periodic lattice, which includes as special cases the Ising model on the square and triangular lattices and the Z n -symmetric BBS τ (2) -model with n = 2. Translating Kaufman's fermionic approach to diagonalization of Ising-like transfer matrices into the language of Grassmann integrals, we determine the transfer matrix eigenvectors and observe that they coincide with the eigenvectors of a square lattice Ising transfer matrix. This allows us to find exact finite-lattice form factors of spin operators for the statistical model and the associated finite-length quantum chains, of which the most general is equivalent to the XY chain in a transverse field

  11. Probability Model of Allele Frequency of Alzheimer’s Disease Genetic Risk Factor

    Directory of Open Access Journals (Sweden)

    Afshin Fayyaz-Movaghar

    2016-06-01

    Full Text Available Background and Purpose: The identification of genetics risk factors of human diseases is very important. This study is conducted to model the allele frequencies (AFs of Alzheimer’s disease. Materials and Methods: In this study, several candidate probability distributions are fitted on a data set of Alzheimer’s disease genetic risk factor. Unknown parameters of the considered distributions are estimated, and some criterions of goodness-of-fit are calculated for the sake of comparison. Results: Based on some statistical criterions, the beta distribution gives the best fit on AFs. However, the estimate values of the parameters of beta distribution lead us to the standard uniform distribution. Conclusion: The AFs of Alzheimer’s disease follow the standard uniform distribution.

  12. Form factors in the projected linear chiral sigma model

    International Nuclear Information System (INIS)

    Alberto, P.; Coimbra Univ.; Bochum Univ.; Ruiz Arriola, E.; Fiolhais, M.; Urbano, J.N.; Coimbra Univ.; Goeke, K.; Gruemmer, F.; Bochum Univ.

    1990-01-01

    Several nucleon form factors are computed within the framework of the linear chiral soliton model. To this end variational means and projection techniques applied to generalized hedgehog quark-boson Fock states are used. In this procedure the Goldberger-Treiman relation and a virial theorem for the pion-nucleon form factor are well fulfilled demonstrating the consistency of the treatment. Both proton and neutron charge form factors are correctly reproduced, as well as the proton magnetic one. The shapes of the neutron magnetic and of the axial form factors are good but their absolute values at the origin are too large. The slopes of all the form factors at zero momentum transfer are in good agreement with the experimental data. The pion-nucleon form factor exhibits to great extent a monopole shape with a cut-off mass of Λ=690 MeV. Electromagnetic form factors for the vertex γNΔ and the nucleon spin distribution are also evaluated and discussed. (orig.)

  13. Confirmatory Factor Analysis of the Combined Social Phobia Scale and Social Interaction Anxiety Scale: Support for a Bifactor Model

    OpenAIRE

    Gomez, Rapson; Watson, Shaun D.

    2017-01-01

    For the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) together, this study examined support for a bifactor model, and also the internal consistency reliability and external validity of the factors in this model. Participants (N = 526) were adults from the general community who completed the SPS and SIAS. Confirmatory factor analysis (CFA) of their ratings indicated good support for the bifactor model. For this model, the loadings for all but six items were higher o...

  14. Quinn’s Leadership Roles: A Confirmatory Factor Analysis Study in Portuguese Health Services

    Directory of Open Access Journals (Sweden)

    Pedro Parreira

    2015-08-01

    Full Text Available Purpose: To assess the psychometric properties of Quinn’s leadership questionnaire (CFV questionnaire; 1988 in Portuguese health services. Design: Cross-sectional study, using Quinn’s leadership questionnaire, administered to registered nurses and physicians in Portuguese health services (N = 687. Method: Self-administered survey applied to two samples. In the first sample (convenience; N = 249 Portuguese health professionals, exploratory factor and reliability analyses were performed to the CFV questionnaire. In the second sample (stratified; N = 50 surgical units of 33 Portuguese hospitals, confirmatory factor analyses were performed using LISREL 8.80. Findings: In the first sample, an eight-factor solution emerged accounting for 65.46% of the total variance, in an interpretable factor structure (loadings> .50, with Cronbach’s α greater than .79. This factor structure, replicated in the second sample, showed reasonable goodness-of-fit of the model to each of the leadership roles, that is, to the eight quadrants and global model. Overall, the models showed nomological validity, with scores between good and acceptable (.235 < x2/df < 2.055 and .00 < RMSEA < .077. Conclusions: Quinn’s leadership questionnaire showed good reliability and validity for the eight leadership roles, proving to be suitable for use in health care/hospital settings.

  15. Modeling of Iranian Cheetah Habitat using Ecological Niche Factor Analysis (Case Study: Dare Anjir Wildlife Refuge

    Directory of Open Access Journals (Sweden)

    N. Zamani

    2016-03-01

    Full Text Available Evaluation of habitat sustainability indexes is essential in wildlife management and conservation of rare species. Suitable habitats are required in wildlife managements and conservation also, they increase reproduction and survival rate of species. In this study in order to mapping habitat sustainability and recognizing habitat requirements of Iranian Cheetah (Acinonyx jubatus venaticus, field data from Dare Anjir  wildlife refuge were collected since autumn 2009 until summer 2011. Ecological Niche Factor Analysis approach has been used to develop habitat suitability model. In this method primary maps of  habitat variables including elevation, slope, aspect, vegetation cover, distance from water sources and environmental monitoring stations have been produced by Idrisi and Biomapper software and imported in Biomapper. The output scores obtained from the analysis showed that Iranian cheetah tends to mountain areas where has more topographical features for camouflage in order to hunting, and northern aspects which have more humidity, denser vegetation cover and more preys . Our result showed that the Iranian cheetah has medium niche width and prefer marginal habitats.

  16. Modeling of human factor Va inactivation by activated protein C

    Directory of Open Access Journals (Sweden)

    Bravo Maria

    2012-05-01

    analysis of in vitro experiments and mathematical constructs we are able to produce a final validated model that includes 24 chemical reactions and interactions with 14 unique rate constants which describe the flux in concentrations of 24 species. Conclusion This study highlights the complexity of the inactivation process and provides a module of equations describing the Protein C pathway that can be integrated into existing comprehensive mathematical models describing tissue factor initiated coagulation.

  17. An Early Model for Value and Sustainability in Health Information Exchanges: Qualitative Study.

    Science.gov (United States)

    Feldman, Sue S

    2018-04-30

    The primary value relative to health information exchange has been seen in terms of cost savings relative to laboratory and radiology testing, emergency department expenditures, and admissions. However, models are needed to statistically quantify value and sustainability and better understand the dependent and mediating factors that contribute to value and sustainability. The purpose of this study was to provide a basis for early model development for health information exchange value and sustainability. A qualitative study was conducted with 21 interviews of eHealth Exchange participants across 10 organizations. Using a grounded theory approach and 3.0 as a relative frequency threshold, 5 main categories and 16 subcategories emerged. This study identifies 3 core current perceived value factors and 5 potential perceived value factors-how interviewees predict health information exchanges may evolve as there are more participants. These value factors were used as the foundation for early model development for sustainability of health information exchange. Using the value factors from the interviews, the study provides the basis for early model development for health information exchange value and sustainability. This basis includes factors from the research: fostering consumer engagement; establishing a provider directory; quantifying use, cost, and clinical outcomes; ensuring data integrity through patient matching; and increasing awareness, usefulness, interoperability, and sustainability of eHealth Exchange. ©Sue S Feldman. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 30.04.2018.

  18. Learning with Interactive Whiteboards: Determining the Factors on Promoting Interactive Whiteboards to Students by Technology Acceptance Model

    Science.gov (United States)

    Kilic, Eylem; Güler, Çetin; Çelik, H. Eray; Tatli, Cemal

    2015-01-01

    Purpose: The purpose of this study is to investigate the factors which might affect the intention to use interactive whiteboards (IWBs) by university students, using Technology Acceptance Model by the structural equation modeling approach. The following hypothesis guided the current study: H1. There is a positive relationship between IWB…

  19. Critical Factors Analysis for Offshore Software Development Success by Structural Equation Modeling

    Science.gov (United States)

    Wada, Yoshihisa; Tsuji, Hiroshi

    In order to analyze the success/failure factors in offshore software development service by the structural equation modeling, this paper proposes to follow two approaches together; domain knowledge based heuristic analysis and factor analysis based rational analysis. The former works for generating and verifying of hypothesis to find factors and causalities. The latter works for verifying factors introduced by theory to build the model without heuristics. Following the proposed combined approaches for the responses from skilled project managers of the questionnaire, this paper found that the vendor property has high causality for the success compared to software property and project property.

  20. Personality profile of binge drinking in university students is modulated by sex. A study using the Alternative Five Factor Model.

    Science.gov (United States)

    Adan, Ana; Navarro, José Francisco; Forero, Diego A

    2016-08-01

    The prevalence of binge drinking (BD), found especially among young people, is increasing worldwide and has become an important social and health concern. We studied, for the first time, the personality profile, using the Alternative Five Factor Model, among university students with BD and healthy controls, taking into account the possible influence of sex. 70 participants with BD (30 men) and 70 healthy controls (30 men) were included, selected to control for characteristics that are known to be related to BD (physical and mental disorders, consumption of other drugs, circadian rhythms), completed the Zuckerman-Kuhlman Personality Questionnaire (ZKPQ). The scores on Neuroticism-Anxiety and Impulsive Sensation-Seeking were higher in the BD group compared to the controls (pAnxiety are due to higher scores in the women's group (p=0.014), while those in Impulsive Sensation-Seeking are due to higher scores in the men's group (p=0.009), both in the Impulsivity and in the Sensation-Seeking subscales (p<0.045). Sex could be a factor that modulates the endophenotype of drug dependence (impulsive and anxious personality) and the prevention and/or treatment programs for BD should include not only the management of the personality risk factors but also different tailored approaches according to sex. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  1. Factors influencing exacerbation-related self-management in patients with COPD: a qualitative study.

    Science.gov (United States)

    Korpershoek, Yjg; Vervoort, Scjm; Nijssen, Lit; Trappenburg, Jca; Schuurmans, M J

    2016-01-01

    In patients with COPD, self-management skills are important to reduce the impact of exacerbations. However, both detection and adequate response to exacerbations appear to be difficult for some patients. Little is known about the underlying process of exacerbation-related self-management. Therefore, the objective of this study was to identify and explain the underlying process of exacerbation-related self-management behavior. A qualitative study using semi-structured in-depth interviews was performed according to the grounded theory approach, following a cyclic process in which data collection and data analysis alternated. Fifteen patients (male n=8; age range 59-88 years) with mild to very severe COPD were recruited from primary and secondary care settings in the Netherlands, in 2015. Several patterns in exacerbation-related self-management behavior were identified, and a conceptual model describing factors influencing exacerbation-related self-management was developed. Acceptance, knowledge, experiences with exacerbations, perceived severity of symptoms and social support were important factors influencing exacerbation-related self-management. Specific factors influencing recognition of exacerbations were heterogeneity of exacerbations and habituation to symptoms. Feelings of fear, perceived influence on exacerbation course, patient beliefs, ambivalence toward treatment, trust in health care providers and self-empowerment were identified as specific factors influencing self-management actions. This study provided insight into factors influencing exacerbation-related self-management behavior in COPD patients. The conceptual model can be used as a framework for health care professionals providing self-management support. In the development of future self-management interventions, factors influencing the process of exacerbation-related self-management should be taken into account.

  2. Psychosocial work environment factors and weight change: a prospective study among Danish health care workers.

    Science.gov (United States)

    Gram Quist, Helle; Christensen, Ulla; Christensen, Karl Bang; Aust, Birgit; Borg, Vilhelm; Bjorner, Jakob B

    2013-01-17

    Lifestyle variables may serve as important intermediate factors between psychosocial work environment and health outcomes. Previous studies, focussing on work stress models have shown mixed and weak results in relation to weight change. This study aims to investigate psychosocial factors outside the classical work stress models as potential predictors of change in body mass index (BMI) in a population of health care workers. A cohort study, with three years follow-up, was conducted among Danish health care workers (3982 women and 152 men). Logistic regression analyses examined change in BMI (more than +/- 2 kg/m(2)) as predicted by baseline psychosocial work factors (work pace, workload, quality of leadership, influence at work, meaning of work, predictability, commitment, role clarity, and role conflicts) and five covariates (age, cohabitation, physical work demands, type of work position and seniority). Among women, high role conflicts predicted weight gain, while high role clarity predicted both weight gain and weight loss. Living alone also predicted weight gain among women, while older age decreased the odds of weight gain. High leadership quality predicted weight loss among men. Associations were generally weak, with the exception of quality of leadership, age, and cohabitation. This study of a single occupational group suggested a few new risk factors for weight change outside the traditional work stress models.

  3. A proposed model of factors influencing hydrogen fuel cell vehicle acceptance

    Science.gov (United States)

    Imanina, N. H. Noor; Kwe Lu, Tan; Fadhilah, A. R.

    2016-03-01

    Issues such as environmental problem and energy insecurity keep worsening as a result of energy use from household to huge industries including automotive industry. Recently, a new type of zero emission vehicle, hydrogen fuel cell vehicle (HFCV) has received attention. Although there are argues on the feasibility of hydrogen as the future fuel, there is another important issue, which is the acceptance of HFCV. The study of technology acceptance in the early stage is a vital key for a successful introduction and penetration of a technology. This paper proposes a model of factors influencing green vehicle acceptance, specifically HFCV. This model is built base on two technology acceptance theories and other empirical studies of vehicle acceptance. It aims to provide a base for finding the key factors influencing new sustainable energy fuelled vehicle, HFCV acceptance which is achieved by explaining intention to accept HFCV. Intention is influenced by attitude, subjective norm and perceived behavioural control from Theory of Planned Behaviour and personal norm from Norm Activation Theory. In the framework, attitude is influenced by perceptions of benefits and risks, and social trust. Perceived behavioural control is influenced by government interventions. Personal norm is influenced by outcome efficacy and problem awareness.

  4. Experimental study of a model and parameters calculating annual mean atmospheric dispersion factor for a nuclear power plant to be build in coastal site

    International Nuclear Information System (INIS)

    Hu Erbang; Chen Jiayi; Zhang Maoshuan; Gao Zhanrong; Yao Rentai; Jia Peirong; Qiao Qingdang

    1999-01-01

    The author tries to develop a new model calculating annual mean atmospheric dispersion factor for a nuclear power plant to be build in coastal site based on field experiments. This model considers not only the difference between shore ward and off-shore but also the comprehensive effect of following factors: mixed layer and thermal internal boundary layer, mixing release and variation of diffusion parameters due to the distance from coast and so on. The various parameters needed in the model are obtained from the field atmospheric experiments done on the NPP site during 1995∼1996. There dimension joint frequency is got from wind and temperature measurements at 4 heights of a tower of 100 m; diffusion parameters shore ward and off-shore from turbulent measurement and wind tunnel simulation test; the parameters relative to sea and land breeze and thermal internal boundary layer are obtained from tests with low altitude radiosonde and lost balloon at 3 sites during two periods of Summer and Winter. Finally a comparison of the results given by this model and commonly used model provided by relative guides is done. The comparison shows that about 1 times under estimation is found for the maximum of annual mean atmospheric dispersion factor in common model because the effect from thermal internal boundary layer and other factors are neglected

  5. Testing of technology readiness index model based on exploratory factor analysis approach

    Science.gov (United States)

    Ariani, AF; Napitupulu, D.; Jati, RK; Kadar, JA; Syafrullah, M.

    2018-04-01

    SMEs readiness in using ICT will determine the adoption of ICT in the future. This study aims to evaluate the model of technology readiness in order to apply the technology on SMEs. The model is tested to find if TRI model is relevant to measure ICT adoption, especially for SMEs in Indonesia. The research method used in this paper is survey to a group of SMEs in South Tangerang. The survey measures the readiness to adopt ICT based on four variables which is Optimism, Innovativeness, Discomfort, and Insecurity. Each variable contains several indicators to make sure the variable is measured thoroughly. The data collected through survey is analysed using factor analysis methodwith the help of SPSS software. The result of this study shows that TRI model gives more descendants on some indicators and variables. This result can be caused by SMEs owners’ knowledge is not homogeneous about either the technology that they are used, knowledge or the type of their business.

  6. Brief report: Bifactor modeling of general vs. specific factors of religiousness differentially predicting substance use risk in adolescence.

    Science.gov (United States)

    Kim-Spoon, Jungmeen; Longo, Gregory S; Holmes, Christopher J

    2015-08-01

    Religiousness is important to adolescents in the U.S., and the significant link between high religiousness and low substance use is well known. There is a debate between multidimensional and unidimensional perspectives of religiousness (Gorsuch, 1984); yet, no empirical study has tested this hierarchical model of religiousness related to adolescent health outcomes. The current study presents the first attempt to test a bifactor model of religiousness related to substance use among adolescents (N = 220, 45% female). Our bifactor model using structural equation modeling suggested the multidimensional nature of religiousness as well as the presence of a superordinate general religiousness factor directly explaining the covariation among the specific factors including organizational and personal religiousness and religious social support. The general religiousness factor was inversely related to substance use. After accounting for the contribution of the general religiousness factor, high organizational religiousness related to low substance use, whereas personal religiousness and religious support were positively related to substance use. The findings present the first evidence that supports hierarchical structures of adolescent religiousness that contribute differentially to adolescent substance use. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

  7. Empirical Study on Total Factor Productive Energy Efficiency in Beijing-Tianjin-Hebei Region-Analysis based on Malmquist Index and Window Model

    Science.gov (United States)

    Xu, Qiang; Ding, Shuai; An, Jingwen

    2017-12-01

    This paper studies the energy efficiency of Beijing-Tianjin-Hebei region and to finds out the trend of energy efficiency in order to improve the economic development quality of Beijing-Tianjin-Hebei region. Based on Malmquist index and window analysis model, this paper estimates the total factor energy efficiency in Beijing-Tianjin-Hebei region empirically by using panel data in this region from 1991 to 2014, and provides the corresponding political recommendations. The empirical result shows that, the total factor energy efficiency in Beijing-Tianjin-Hebei region increased from 1991 to 2014, mainly relies on advances in energy technology or innovation, and obvious regional differences in energy efficiency to exist. Throughout the window period of 24 years, the regional differences of energy efficiency in Beijing-Tianjin-Hebei region shrank. There has been significant convergent trend in energy efficiency after 2000, mainly depends on the diffusion and spillover of energy technologies.

  8. Psychosocial factors, musculoskeletal disorders and work-related fatigue amongst nurses in Brunei: structural equation model approach.

    Science.gov (United States)

    Abdul Rahman, Hanif; Abdul-Mumin, Khadizah; Naing, Lin

    2017-09-01

    Psychosocial factors, musculoskeletal disorders and work-related fatigue have adverse effects on individual nurses and place a substantial financial burden on health care. Evidence of an association has been reported in the literature, but no theoretical explanation has been published to date. To explore and develop a structural model to provide a theoretical explanation for this relationship. A cross-sectional study using data from 201 valid samples of emergency and critical care nurses across public hospitals in Brunei was performed via self-administered questionnaire. The structural equation model was assessed using partial least squares analysis. A valid and robust structural model was constructed. This revealed that 61.5% of the variance in chronic fatigue could be explained by psychosocial factors and musculoskeletal disorders pathways. Among the psychosocial factors, work-family conflict was identified as a key mediator for progression of musculoskeletal problems and subsequent fatigue through stress and burnout. This report provides a novel theoretical contribution to understanding the relationship between psychosocial factors, musculoskeletal disorders and work-related fatigue. These preliminary results may be useful for future studies on the development of work-related fatigue and musculoskeletal disorders, particularly the central role of work-family conflict. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Relativistic form factors for hadrons with quark-model wave functions

    International Nuclear Information System (INIS)

    Stanley, D.P.; Robson, D.

    1982-01-01

    The relationship between relativistic form factors and quark-potential-model wave functions is examined using an improved version of an approach by Licht and Pagnamenta. Lorentz-contraction effects are expressed in terms of an effective hadron mass which varies as the square root of the number of quark constituents. The effective mass is calculated using the rest-frame wave functions from the mean-square momentum along the direction of the momentum transfer. Applications with the parameter-free approach are made to the elastic form factors of the pion, proton, and neutron using a Hamiltonian which simultaneously describes mesons and baryons. A comparison of the calculated radii for pions and kaons suggests that the measured kaon radius should be slightly smaller than the corresponding pion radius. The large negative squared charge radius for the neutron is partially explained via the quark model but a full description requires the inclusion of a small component of a pion ''cloud'' configuration. The problematic connection between the sizes of hadrons deduced from form factors and the ''measured'' values of average transverse momenta is reconciled in the present model

  10. Using Factor Mixture Models to Evaluate the Type A/B Classification of Alcohol Use Disorders in a Heterogeneous Treatment Sample

    Science.gov (United States)

    Hildebrandt, Tom; Epstein, Elizabeth E.; Sysko, Robyn; Bux, Donald A.

    2017-01-01

    Background The type A/B classification model for alcohol use disorders (AUDs) has received considerable empirical support. However, few studies examine the underlying latent structure of this subtyping model, which has been challenged as a dichotomization of a single drinking severity dimension. Type B, relative to type A, alcoholics represent those with early age of onset, greater familial risk, and worse outcomes from alcohol use. Method We examined the latent structure of the type A/B model using categorical, dimensional, and factor mixture models in a mixed gender community treatment-seeking sample of adults with an AUD. Results Factor analytic models identified 2-factors (drinking severity/externalizing psychopathology and internalizing psychopathology) underlying the type A/B indicators. A factor mixture model with 2-dimensions and 3-classes emerged as the best overall fitting model. The classes reflected a type A class and two type B classes (B1 and B2) that differed on the respective level of drinking severity/externalizing pathology and internalizing pathology. Type B1 had a greater prevalence of women and more internalizing pathology and B2 had a greater prevalence of men and more drinking severity/externalizing pathology. The 2-factor, 3-class model also exhibited predictive validity by explaining significant variance in 12-month drinking and drug use outcomes. Conclusions The model identified in the current study may provide a basis for examining different sources of heterogeneity in the course and outcome of AUDs. PMID:28247423

  11. Confirmation of the three-factor model of problematic internet use on off-line adolescent and adult samples.

    Science.gov (United States)

    Koronczai, Beatrix; Urbán, Róbert; Kökönyei, Gyöngyi; Paksi, Borbála; Papp, Krisztina; Kun, Bernadette; Arnold, Petra; Kállai, János; Demetrovics, Zsolt

    2011-11-01

    As the Internet became widely used, problems associated with its excessive use became increasingly apparent. Although for the assessment of these problems several models and related questionnaires have been elaborated, there has been little effort made to confirm them. The aim of the present study was to test the three-factor model of the previously created Problematic Internet Use Questionnaire (PIUQ) by data collection methods formerly not applied (off-line group and face-to-face settings), on the one hand, and by testing on different age groups (adolescent and adult representative samples), on the other hand. Data were collected from 438 high-school students (44.5 percent boys; mean age: 16.0 years; standard deviation=0.7 years) and also from 963 adults (49.9 percent males; mean age: 33.6 years; standard deviation=11.8 years). We applied confirmatory factor analysis to confirm the measurement model of problematic Internet use. The results of the analyses carried out inevitably support the original three-factor model over the possible one-factor solution. Using latent profile analysis, we identified 11 percent of adults and 18 percent of adolescent users characterized by problematic use. Based on exploratory factor analysis, we also suggest a short form of the PIUQ consisting of nine items. Both the original 18-item version of PIUQ and its short 9-item form have satisfactory reliability and validity characteristics, and thus, they are suitable for the assessment of problematic Internet use in future studies.

  12. Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

    Science.gov (United States)

    Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

    2018-03-01

    Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

  13. Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

    Science.gov (United States)

    Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

    2017-01-01

    Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

  14. Capturing the DSM-5 Alternative Personality Disorder Model Traits in the Five-Factor Model's Nomological Net.

    Science.gov (United States)

    Suzuki, Takakuni; Griffin, Sarah A; Samuel, Douglas B

    2017-04-01

    Several studies have shown structural and statistical similarities between the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) alternative personality disorder model and the Five-Factor Model (FFM). However, no study to date has evaluated the nomological network similarities between the two models. The relations of the Revised NEO Personality Inventory (NEO PI-R) and the Personality Inventory for DSM-5 (PID-5) with relevant criterion variables were examined in a sample of 336 undergraduate students (M age  = 19.4; 59.8% female). The resulting profiles for each instrument were statistically compared for similarity. Four of the five domains of the two models have highly similar nomological networks, with the exception being FFM Openness to Experience and PID-5 Psychoticism. Further probing of that pair suggested that the NEO PI-R domain scores obscured meaningful similarity between PID-5 Psychoticism and specific aspects and lower-order facets of Openness. The results support the notion that the DSM-5 alternative personality disorder model trait domains represent variants of the FFM domains. Similarities of Openness and Psychoticism domains were supported when the lower-order aspects and facets of Openness domain were considered. The findings support the view that the DSM-5 trait model represents an instantiation of the FFM. © 2015 Wiley Periodicals, Inc.

  15. Emission of hydrogen sulfide (H2S) at a waterfall in a sewer: study of main factors affecting H2S emission and modeling approaches.

    Science.gov (United States)

    Jung, Daniel; Hatrait, Laetitia; Gouello, Julien; Ponthieux, Arnaud; Parez, Vincent; Renner, Christophe

    2017-11-01

    Hydrogen sulfide (H 2 S) represents one of the main odorant gases emitted from sewer networks. A mathematical model can be a fast and low-cost tool for estimating its emission. This study investigates two approaches to modeling H 2 S gas transfer at a waterfall in a discharge manhole. The first approach is based on an adaptation of oxygen models for H 2 S emission at a waterfall and the second consists of a new model. An experimental set-up and a statistical data analysis allowed the main factors affecting H 2 S emission to be studied. A new model of the emission kinetics was developed using linear regression and taking into account H 2 S liquid concentration, waterfall height and fluid velocity at the outlet pipe of a rising main. Its prediction interval was estimated by the residual standard deviation (15.6%) up to a rate of 2.3 g H 2 S·h -1 . Finally, data coming from four sampling campaigns on sewer networks were used to perform simulations and compare predictions of all developed models.

  16. Mathematical Model of Growth Factor Driven Haptotaxis and Proliferation in a Tissue Engineering Scaffold

    KAUST Repository

    Pohlmeyer, J. V.

    2013-01-29

    Motivated by experimental work (Miller et al. in Biomaterials 27(10):2213-2221, 2006, 32(11):2775-2785, 2011) we investigate the effect of growth factor driven haptotaxis and proliferation in a perfusion tissue engineering bioreactor, in which nutrient-rich culture medium is perfused through a 2D porous scaffold impregnated with growth factor and seeded with cells. We model these processes on the timescale of cell proliferation, which typically is of the order of days. While a quantitative representation of these phenomena requires more experimental data than is yet available, qualitative agreement with preliminary experimental studies (Miller et al. in Biomaterials 27(10):2213-2221, 2006) is obtained, and appears promising. The ultimate goal of such modeling is to ascertain initial conditions (growth factor distribution, initial cell seeding, etc.) that will lead to a final desired outcome. © 2013 Society for Mathematical Biology.

  17. Linear and nonlinear models for predicting fish bioconcentration factors for pesticides.

    Science.gov (United States)

    Yuan, Jintao; Xie, Chun; Zhang, Ting; Sun, Jinfang; Yuan, Xuejie; Yu, Shuling; Zhang, Yingbiao; Cao, Yunyuan; Yu, Xingchen; Yang, Xuan; Yao, Wu

    2016-08-01

    This work is devoted to the applications of the multiple linear regression (MLR), multilayer perceptron neural network (MLP NN) and projection pursuit regression (PPR) to quantitative structure-property relationship analysis of bioconcentration factors (BCFs) of pesticides tested on Bluegill (Lepomis macrochirus). Molecular descriptors of a total of 107 pesticides were calculated with the DRAGON Software and selected by inverse enhanced replacement method. Based on the selected DRAGON descriptors, a linear model was built by MLR, nonlinear models were developed using MLP NN and PPR. The robustness of the obtained models was assessed by cross-validation and external validation using test set. Outliers were also examined and deleted to improve predictive power. Comparative results revealed that PPR achieved the most accurate predictions. This study offers useful models and information for BCF prediction, risk assessment, and pesticide formulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Empirical Research on China’s Carbon Productivity Decomposition Model Based on Multi-Dimensional Factors

    Directory of Open Access Journals (Sweden)

    Jianchang Lu

    2015-04-01

    Full Text Available Based on the international community’s analysis of the present CO2 emissions situation, a Log Mean Divisia Index (LMDI decomposition model is proposed in this paper, aiming to reflect the decomposition of carbon productivity. The model is designed by analyzing the factors that affect carbon productivity. China’s contribution to carbon productivity is analyzed from the dimensions of influencing factors, regional structure and industrial structure. It comes to the conclusions that: (a economic output, the provincial carbon productivity and energy structure are the most influential factors, which are consistent with China’s current actual policy; (b the distribution patterns of economic output, carbon productivity and energy structure in different regions have nothing to do with the Chinese traditional sense of the regional economic development patterns; (c considering the regional protectionism, regional actual situation need to be considered at the same time; (d in the study of the industrial structure, the contribution value of industry is the most prominent factor for China’s carbon productivity, while the industrial restructuring has not been done well enough.

  19. The Five-Factor Model personality traits in schizophrenia: A meta-analysis.

    Science.gov (United States)

    Ohi, Kazutaka; Shimada, Takamitsu; Nitta, Yusuke; Kihara, Hiroaki; Okubo, Hiroaki; Uehara, Takashi; Kawasaki, Yasuhiro

    2016-06-30

    Personality is one of important factors in the pathogenesis of schizophrenia because it affects patients' symptoms, cognition and social functioning. Several studies have reported specific personality traits in patients with schizophrenia compared with healthy subjects. However, the results were inconsistent among studies. The NEO Five-Factor Inventory (NEO-FFI) measures five personality traits: Neuroticism (N), Extraversion (E), Openness (O), Agreeableness (A) and Conscientiousness (C). Here, we performed a meta-analysis of these personality traits assessed by the NEO-FFI in 460 patients with schizophrenia and 486 healthy subjects from the published literature and investigated possible associations between schizophrenia and these traits. There was no publication bias for any traits. Because we found evidence of significant heterogeneity in all traits among the studies, we applied a random-effect model to perform the meta-analysis. Patients with schizophrenia showed a higher score for N and lower scores for E, O, A and C compared with healthy subjects. The effect sizes of these personality traits ranged from moderate to large. These differences were not affected by possible moderator factors, such as gender distribution and mean age in each study, expect for gender effect for A. These findings suggest that patients with schizophrenia have a different personality profile compared with healthy subjects. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  20. Assessing Heterogeneity for Factor Analysis Model with Continuous and Ordinal Outcomes

    Directory of Open Access Journals (Sweden)

    Ye-Mao Xia

    2016-01-01

    Full Text Available Factor analysis models with continuous and ordinal responses are a useful tool for assessing relations between the latent variables and mixed observed responses. These models have been successfully applied to many different fields, including behavioral, educational, and social-psychological sciences. However, within the Bayesian analysis framework, most developments are constrained within parametric families, of which the particular distributions are specified for the parameters of interest. This leads to difficulty in dealing with outliers and/or distribution deviations. In this paper, we propose a Bayesian semiparametric modeling for factor analysis model with continuous and ordinal variables. A truncated stick-breaking prior is used to model the distributions of the intercept and/or covariance structural parameters. Bayesian posterior analysis is carried out through the simulation-based method. Blocked Gibbs sampler is implemented to draw observations from the complicated posterior. For model selection, the logarithm of pseudomarginal likelihood is developed to compare the competing models. Empirical results are presented to illustrate the application of the methodology.

  1. Modelling environmental factors correlated with podoconiosis: a geospatial study of non-filarial elephantiasis.

    Science.gov (United States)

    Molla, Yordanos B; Wardrop, Nicola A; Le Blond, Jennifer S; Baxter, Peter; Newport, Melanie J; Atkinson, Peter M; Davey, Gail

    2014-06-20

    The precise trigger of podoconiosis - endemic non-filarial elephantiasis of the lower legs - is unknown. Epidemiological and ecological studies have linked the disease with barefoot exposure to red clay soils of volcanic origin. Histopathology investigations have demonstrated that silicon, aluminium, magnesium and iron are present in the lower limb lymph node macrophages of both patients and non-patients living barefoot on these clays. We studied the spatial variation (variations across an area) in podoconiosis prevalence and the associated environmental factors with a goal to better understanding the pathogenesis of podoconiosis. Fieldwork was conducted from June 2011 to February 2013 in 12 kebeles (administrative units) in northern Ethiopia. Geo-located prevalence data and soil samples were collected and analysed along with secondary geological, topographic, meteorological and elevation data. Soil data were analysed for chemical composition, mineralogy and particle size, and were interpolated to provide spatially continuous information. Exploratory, spatial, univariate and multivariate regression analyses of podoconiosis prevalence were conducted in relation to primary (soil) and secondary (elevation, precipitation, and geology) covariates. Podoconiosis distribution showed spatial correlation with variation in elevation and precipitation. Exploratory analysis identified that phyllosilicate minerals, particularly clay (smectite and kaolinite) and mica groups, quartz (crystalline silica), iron oxide, and zirconium were associated with podoconiosis prevalence. The final multivariate model showed that the quantities of smectite (RR = 2.76, 95% CI: 1.35, 5.73; p = 0.007), quartz (RR = 1.16, 95% CI: 1.06, 1.26; p = 0.001) and mica (RR = 1.09, 95% CI: 1.05, 1.13; p < 0.001) in the soil had positive associations with podoconiosis prevalence. More quantities of smectite, mica and quartz within the soil were associated with podoconiosis prevalence. Together with previous

  2. Modeling the Travel Behavior Impacts of Micro-Scale Land Use and Socio-Economic Factors

    Directory of Open Access Journals (Sweden)

    Houshmand Ebrahimpour Masoumi

    2013-06-01

    Full Text Available The effects of neighborhood-level land use characteristics on urban travel behavior of Iranian cities are under-researched. The present paper examines such influences in a microscopic scale. In this study the role of socio-economic factors is also studies and compared to that of urban form. Two case-study neighborhoods in west of Tehran are selected and considered, first of which is a centralized and compact neighborhood and the other is a sprawled and centerless one. A Multinomial Logit Regression model is developed to consider the effects of socio-economic and land use factors on urban travel pattern. In addition, to consider the effective factors, cross-sectional comparison between the influences of local accessibility and attractiveness of the neighborhood centers of the two case-study areas are undertaken. Also the causality relationships are considered according to the findings of the survey. The findings indicate significant effects of age and household income as socio-economic factors on transportation mode choice in neighborhoods with central structure. One the other hand, no meaningful association between socio-economic or land use variables are resulted by the model for the sprawled case. The most effective land use concept in micro-scale is considered to be satisfaction of entertainment facilities of the neighborhood. Also the descriptive findings show that the centralized neighborhood that gives more local accessibility to shops and retail generates less shopping trips. In considering the causal relations, the study shows that providing neighborhood infrastructures that increase or ease the accessibility to neighborhood amenities can lead to higher shares of sustainable transportation modes like walking, biking, or public transportation use.

  3. Assessing Factors Related to Waist Circumference and Obesity: Application of a Latent Variable Model

    OpenAIRE

    Dalvand, Sahar; Koohpayehzadeh, Jalil; Karimlou, Masoud; Asgari, Fereshteh; Rafei, Ali; Seifi, Behjat; Niksima, Seyed Hassan; Bakhshi, Enayatollah

    2015-01-01

    Background. Because the use of BMI (Body Mass Index) alone as a measure of adiposity has been criticized, in the present study our aim was to fit a latent variable model to simultaneously examine the factors that affect waist circumference (continuous outcome) and obesity (binary outcome) among Iranian adults. Methods. Data included 18,990 Iranian individuals aged 20–65 years that are derived from the third National Survey of Noncommunicable Diseases Risk Factors in Iran. Using latent variabl...

  4. Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

    Science.gov (United States)

    Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

    2017-01-01

    The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

  5. The incidence of injuries in young people: II. Log-linear multivariable models for risk factors in a collaborative study in Brazil, Chile, Cuba and Venezuela.

    Science.gov (United States)

    Bangdiwala, S I; Anzola-Pérez, E

    1990-03-01

    Injuries and accidents are acknowledged as leading causes of morbidity and mortality among children and adolescents in the developing countries of the world. The Pan American Health Organization sponsored a collaborative study in four selected countries in Latin America to study the extent of the problem as well as to examine the potential risk factors associated with selected non-fatal injuries in the countries. The study subjects were injured children and adolescents (0-19 years of age) presenting at the study hospitals in chosen urban centres, as well as injured that were surveyed in households in the catchment areas of the hospitals. Study methods and descriptive frequency results were presented earlier. In this paper, log-linear multivariate regression models are used to examine the potentiating effects within country of several measured variables on specific types of injuries. The significance of risk factors varied between countries; however, some general patterns emerged. Falls were more likely in younger children, and occurred at home. The main risk factor for home accidents was the age of the child. The education of the head of the household was an important risk factor for the type of injury suffered. The likelihood of traffic accident injury varied with time of day and day of the week, but also was more likely in higher educated households. The results found are consistent with those found in other studies in the developed world and suggest specific areas of concern for health planners to address.

  6. Reliability Analysis of a Composite Wind Turbine Blade Section Using the Model Correction Factor Method: Numerical Study and Validation

    DEFF Research Database (Denmark)

    Dimitrov, Nikolay Krasimirov; Friis-Hansen, Peter; Berggreen, Christian

    2013-01-01

    by the composite failure criteria. Each failure mode has been considered in a separate component reliability analysis, followed by a system analysis which gives the total probability of failure of the structure. The Model Correction Factor method used in connection with FORM (First-Order Reliability Method) proved...

  7. Using a multidimensional approach to measure the impact of classroom-level factors upon student achievement : a study testing the validity of the dynamic model

    NARCIS (Netherlands)

    Kyriakides, Leonidas; Creemers, Bert P. M.

    The dynamic model does not only refer to different effectiveness factors and groupings of factors operating at different levels but also supports that each factor can be defined and measured using 5 dimensions: frequency, focus, stage, quality, and differentiation. The importance of taking each

  8. The Effects of Transformational Leadership and Mediating Factors on the Organizational Success Using Structural Equation Modeling: A Case Study.

    Science.gov (United States)

    Ravangard, Ramin; Karimi, Sakine; Farhadi, Payam; Sajjadnia, Zahra; Shokrpour, Nasrin

    This study was undertaken to determine the effects of transformational leadership (TL) and mediating factors on organizational success (OS) from the administrative, financial, and support employees' perspective in teaching hospitals affiliated with Shiraz University of Medical Sciences using structural equation modeling. Three hundred administrative and financial employees were selected, using stratified sampling proportional to size and simple random sampling. Data were collected using 5 questionnaires and analyzed using SPSS 21.0 and Lisrel 8.5 through Pearson correlation coefficient and path analysis and confirmatory factor analysis methods. Results showed that TL had significant positive effects on the 3 mediating factors, including organizational culture (t = 15.31), organizational citizenship behavior (OCB) (t = 10.06), and social capital (t = 10.25). Also, the organizational culture (t = 2.26), OCB (t = 3.48), and social capital (t = 7.41) had significant positive effects on OS. According to the results, TL had an indirect effect on OS. Therefore, organizations can achieve more success by strengthening organizational culture, OCB, and social capital through using transformational leadership style. Therefore, in order to increase OS, the following recommendations are made: supporting and encouraging new ideas in the organization, promoting teamwork, strengthening intergroup and intragroup relationships, planning to strengthen and enrich the social and organizational culture, considering the promotion of social capital in the employee training, establishing a system to give rewards to the employees performing extra-role activities, providing a suitable environment for creative employees, and so on.

  9. Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

    Science.gov (United States)

    Abumeri, Galib H.; Chamis, Christos C.

    2010-01-01

    Complex material behavior is represented by a single equation of product form to account for interaction among the various factors. The factors are selected by the physics of the problem and the environment that the model is to represent. For example, different factors will be required for each to represent temperature, moisture, erosion, corrosion, etc. It is important that the equation represent the physics of the behavior in its entirety accurately. The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the external launch tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points - the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used were obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated. The problem lies in how to represent the divot weight with a single equation. A unique solution to this problem is a multi-factor equation of product form. Each factor is of the following form (1 xi/xf)ei, where xi is the initial value, usually at ambient conditions, xf the final value, and ei the exponent that makes the curve represented unimodal that meets the initial and final values. The exponents are either evaluated by test data or by technical judgment. A minor disadvantage may be the selection of exponents in the absence of any empirical data. This form has been used successfully in describing the foam ejected in simulated space environmental conditions. Seven factors were required

  10. Using Hierarchical Linear Modelling to Examine Factors Predicting English Language Students' Reading Achievement

    Science.gov (United States)

    Fung, Karen; ElAtia, Samira

    2015-01-01

    Using Hierarchical Linear Modelling (HLM), this study aimed to identify factors such as ESL/ELL/EAL status that would predict students' reading performance in an English language arts exam taken across Canada. Using data from the 2007 administration of the Pan-Canadian Assessment Program (PCAP) along with the accompanying surveys for students and…

  11. Factors Influencing F/OSS Cloud Computing Software Product Success: A Quantitative Study

    Science.gov (United States)

    Letort, D. Brian

    2012-01-01

    Cloud Computing introduces a new business operational model that allows an organization to shift information technology consumption from traditional capital expenditure to operational expenditure. This shift introduces challenges from both the adoption and creation vantage. This study evaluates factors that influence Free/Open Source Software…

  12. The Factors Influencing Satisfaction with Public City Transport: A Structural Equation Modelling Approach

    Directory of Open Access Journals (Sweden)

    Pawlasova Pavlina

    2015-12-01

    Full Text Available Satisfaction is one of the key factors which influences customer loyalty. We assume that the satisfied customer will be willing to use the ssame service provider again. The overall passengers´ satisfaction with public city transport may be affected by the overall service quality. Frequency, punctuality, cleanliness in the vehicle, proximity, speed, fare, accessibility and safety of transport, information and other factors can influence passengers´ satisfaction. The aim of this paper is to quantify factors and identify the most important factors influencing customer satisfaction with public city transport within conditions of the Czech Republic. Two methods of analysis are applied in order to fulfil the aim. The method of factor analysis and the method Varimax were used in order to categorize variables according to their mutual relations. The method of structural equation modelling was used to evaluate the factors and validate the model. Then, the optimal model was found. The logistic parameters, including service continuity and frequency, and service, including information rate, station proximity and vehicle cleanliness, are the factors influencing passengers´ satisfaction on a large scale.

  13. Modelling and predicting electricity consumption in Spain using the stochastic Gamma diffusion process with exogenous factors

    International Nuclear Information System (INIS)

    Nafidi, A.; Gutiérrez, R.; Gutiérrez-Sánchez, R.; Ramos-Ábalos, E.; El Hachimi, S.

    2016-01-01

    The aim of this study is to model electric power consumption during a period of economic crisis, characterised by declining gross domestic product. A novel aspect of this study is its use of a Gamma-type diffusion process for short and medium-term forecasting – other techniques that have been used to describe such consumption patterns are not valid in this situation. In this study, we consider a new extension of the stochastic Gamma diffusion process by introducing time functions (exogenous factors) that affect its trend. This extension is defined in terms of Kolmogorov backward and forward equations. After obtaining the transition probability density function and the moments (specifically, the trend function), the inference on the process parameters is obtained by discrete sampling of the sample paths. Finally, this stochastic process is applied to model total net electricity consumption in Spain, when affected by the following set of exogenous factors: Gross Domestic Product (GDP), Gross Fixed Capital Formation (GFCF) and Final Domestic Consumption (FDC). - Highlights: • The aim is modelling and predicting electricity consumption in Spain. • We propose a Gamma-type diffusion process for short and medium-term forecasting. • We compared the fit using diffusion processes with different exogenous factors.

  14. Post-Partum Depression, Personality, and Cognitive-Emotional Factors: A Longitudinal Study on Spanish Pregnant Women.

    Science.gov (United States)

    Peñacoba-Puente, Cecilia; Marín-Morales, Dolores; Carmona-Monge, Francisco Javier; Velasco Furlong, Lilian

    2016-01-01

    In this study, our purpose was to examine whether personality and cognitive factors could be related to post-partum depression (PPD), mediated by anxiety, in Spanish women. Women were evaluated for personality and cognitive factors after the first trimester, for anxiety in the third trimester, and for PPD 4 months after childbirth. A structural equation model revealed that personality and cognitive factors were associated with anxiety and PPD as predictors. Neuroticism and extroversion proved to be the most relevant factors. Conscientiousness was associated with pregnancy anxiety. Pregnancy anxiety appeared as an independent predictor of PPD. The model presented here includes personality and cognitive and emotional factors as predictors of PPD. Comprehensive care for pregnant women should contemplate assessment and intervention on all these aspects. Special focus should be on cognitive factors and emotional regulation strategies, so as to minimize the risk of later development of emotional disorders during puerperal phases.

  15. Factors Affecting the Choice of Professors as a Role Model from the Viewpoint of Medical Students

    Directory of Open Access Journals (Sweden)

    Masome Rahimi

    2018-01-01

    Full Text Available The role of professors as a model can have a beneficial impact on the mental, psychological and educational conditions of medical students. This also plays an important role in improving professionalism and academic achievements among medical students. Therefore, the present study was aimed at evaluating the standpoint of students on factors influencing the selection of professors as a role model. This descriptive cross-sectional study was conducted on the students of different disciplines studying in Jahrom University of Medical Sciences in 2016. A randomized sampling method was conducted on 217 students. Their viewpoints were collected using a 30- question researcher-made questionnaire. The questionnaire consisted of three parts, each containing ten items. In addition, this questionnaire was distributed among 20 people (as a pilot survey, the alpha coefficient of which was equal to 0.88; and its measurement was based on Likert scale "from very low to very high". Data were analyzed using SPSS 18 and descriptive statistics. Most respondents were nursing students and the highest influence of professors as a role model was associated with their role as a research leader (future specialized courses in the clinical choices and selection of future specialized fields. The factors influencing the selection of professors as a role model included their respectful attitude toward students, and the high level of their knowledge and skills. On the other hand, the most important factors that caused professors not to be regarded as a role model included their inappropriate relationship with the students and refusing to listen to them. Role model professors can have a beneficial impact on the future of students and scientific communities, as far as the science and education is concerned. Therefore, it is necessary for professors to pay particular attention to strengthening their role as a model at universities.

  16. Assessment of Ex-Vitro Anaerobic Digestion Kinetics of Crop Residues Through First Order Exponential Models: Effect of LAG Phase Period and Curve Factor

    Directory of Open Access Journals (Sweden)

    Abdul Razaque Sahito

    2013-04-01

    Full Text Available Kinetic studies of AD (Anaerobic Digestion process are useful to predict the performance of digesters and design appropriate digesters and also helpful in understanding inhibitory mechanisms of biodegradation. The aim of this study was to assess the anaerobic kinetics of crop residues digestion with buffalo dung. Seven crop residues namely, bagasse, banana plant waste, canola straw, cotton stalks, rice straw, sugarcane trash and wheat straw were selected from the field and were analyzed on MC (Moisture Contents, TS (Total Solids and VS (Volatile Solids with standard methods. In present study, three first order exponential models namely exponential model, exponential lag phase model and exponential curve factor model were used to assess the kinetics of the AD process of crop residues and the effect of lag phase and curve factor was analyzed based on statistical hypothesis testing and on information theory. Assessment of kinetics of the AD of crop residues and buffalo dung follows the first order kinetics. Out of the three models, the simple exponential model was the poorest model, while the first order exponential curve factor model is the best fit model. In addition to statistical hypothesis testing, the exponential curve factor model has least value of AIC (Akaike's Information Criterion and can generate methane production data more accurately. Furthermore, there is an inverse linear relationship between the lag phase period and the curve factor.

  17. Assessment of ex-vitro anaerobic digestion kinetics of crop residues through first order exponential models: effect of lag phase period and curve factor

    International Nuclear Information System (INIS)

    Sahito, A.R.; Brohi, K.M.

    2013-01-01

    Kinetic studies of AD (Anaerobic Digestion) process are useful to predict the performance of digesters and design appropriate digesters and also helpful in understanding inhibitory mechanisms of biodegradation. The aim of this study was to assess the anaerobic kinetics of crop residues digestion with buffalo dung. Seven crop residues namely, bagasse, banana plant waste, canola straw, cotton stalks, rice straw, sugarcane trash and wheat straw were selected from the field and were analyzed on MC (Moisture Contents), TS (Total Solids) and VS (Volatile Solids) with standard methods. In present study, three first order exponential models namely exponential model, exponential lag phase model and exponential curve factor model were used to assess the kinetics of the AD process of crop residues and the effect of lag phase and curve factor was analyzed based on statistical hypothesis testing and on information theory. Assessment of kinetics of the AD of crop residues and buffalo dung follows the first order kinetics. Out of the three models, the simple exponential model was the poorest model, while the first order exponential curve factor model is the best fit model. In addition to statistical hypothesis testing, the exponential curve factor model has least value of AIC (Akaike's Information Criterion) and can generate methane production data more accurately. Furthermore, there is an inverse linear relationship between the lag phase period and the curve factor. (author)

  18. Does Sluggish Cognitive Tempo Fit within a Bi-factor Model of Attention-Deficit/Hyperactivity Disorder?

    Science.gov (United States)

    Garner, Annie A.; Peugh, James; Becker, Stephen P.; Kingery, Kathleen M.; Tamm, Leanne; Vaughn, Aaron J.; Ciesielski, Heather; Simon, John O.; Loren, Richard E. A.; Epstein, Jeffery N.

    2014-01-01

    Objective Studies demonstrate sluggish cognitive tempo (SCT) symptoms to be distinct from inattentive and hyperactive-impulsive dimensions of Attention-Deficit/Hyperactivity Disorder (ADHD). No study has examined SCT within a bi-factor model of ADHD whereby SCT may form a specific factor distinct from inattention and hyperactivity/impulsivity while still fitting within a general ADHD factor, which was the purpose of the current study. Method 168 children were recruited from an ADHD clinic. Most (92%) met diagnostic criteria for ADHD. Parents and teachers completed measures of ADHD and SCT. Results Although SCT symptoms were strongly associated with inattention they loaded onto a factor independent of ADHD ‘g’. Results were consistent across parent and teacher ratings. Conclusions SCT is structurally distinct from inattention as well as from the general ADHD latent symptom structure. Findings support a growing body of research suggesting SCT to be distinct and separate from ADHD. PMID:25005039

  19. Personality factors in the Long Life Family Study

    DEFF Research Database (Denmark)

    Andersen, Stacy L; Sun, Jenny X; Sebastiani, Paola

    2013-01-01

    Objectives. To evaluate personality profiles of Long Life Family Study participants relative to population norms and offspring of centenarians from the New England Centenarian Study.Method. Personality domains of agreeableness, conscientiousness, extraversion, neuroticism, and openness were...... assessed with the NEO Five-Factor Inventory in 4,937 participants from the Long Life Family Study (mean age 70 years). A linear mixed model of age and gender was implemented adjusting for other covariates. RESULTS: A significant age trend was found in all five personality domains. On average, the offspring...... generation of long-lived families scored low in neuroticism, high in extraversion, and within average values for the other three domains. Older participants tended to score higher in neuroticism and lower in the other domains compared with younger participants, but the estimated scores generally remained...

  20. A factor analytic study of the Italian National Institute of Health Quality of Life – Core Evaluation Form (ISSQoL-CEF

    Directory of Open Access Journals (Sweden)

    M Lauriola

    2010-03-01

    Full Text Available M Lauriola1, R Murri3, M Massella4, M Mirra4, S Donnini4, V Fragola4, J Ivanovic5, M Pavoni6, G Mancini2, R Bucciardini41Department of Social and Developmental Psychology, 2Department of Infectious and Tropical Diseases, University of Rome “La Sapienza”, Rome, Italy; 3Catholic University of “Sacro Cuore”, Rome, Italy; 4Istituto Superiore di Sanità, Rome, Italy; 5National Institute for Infectious Diseases Lazzaro Spallanzani, Rome, Italy; 6Ospedale Civile Santa Maria delle Croci, Ravenna, ItalyObjectives: The Italian National Institute of Health Quality of Life – Core Evaluation Form (ISSQoL-CEF is a specific questionnaire measuring health-related quality of life for human immunodeficiency virus-infected people in the era of highly active antiretroviral therapy. The main goal of this study was to examine the construct validity of this questionnaire by confirmation of its hypothesized dimensional structure.Methods: Baseline quality of life data from four clinical studies were collected and a confirmatory factor analysis of the ISSQoL-CEF items was carried out. Both first-order and secondorder factor models were tested: Model 1 with nine correlated first-order factors; Model 2 with three correlated second-order factors (Physical, Mental, and Social Health; Model 3 with two correlated second-order factors (Physical and Mental/Social Health; Model 4 with only one second-order factor (General Health.Results: A total of 261 patients were surveyed. Model 1 had a good fit to the data. Model 2 had an acceptable fit to the data and it was the best of all hierarchical models. However, Model 2 fitted the data worse than Model 1.Conclusions: The findings of in this study, consistent with the results of previous study, pointed out the construct validity of the ISSQoL-CEF.Keywords: confirmatory factor analysis, HRQoL, patient-reported outcomes

  1. Porcine models for the study of local and systemic regulation of innate immune factors in obesity

    DEFF Research Database (Denmark)

    Højbøge, Tina Rødgaard

    state of low-grade inflammation in the adipose tissues, which involves several factors of the innate immune response having a range of systemic effects and which has been implicated in the development of the metabolic syndrome. To investigate the impact of obesity and obesity-related diseases good...... translational animal models are needed, and as such pigs have been proposed as relevant models for human obesity-induced inflammation as pigs share many genetic, anatomical and physiological features with humans. In this project the up- and downregulation of genes and proteins involved in the innate immune...... the number of animals to be used in a trial to obtain statistical power. For the gene regulation analysis, two platforms for quantitative real-time PCR (qPCR) were employed: The Rotor-Gene Q instrument and the microfluidics-based high-throughput Bio-Mark. For the serum protein concentrations analysis several...

  2. An integrated factor analysis model for product eco-design based on full life cycle assessment

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Z.; Xiao, T.; Li, D.

    2016-07-01

    Among the methods of comprehensive analysis for a product or an enterprise, there exist defects and deficiencies in traditional standard cost analyses and life cycle assessment methods. For example, some methods only emphasize one dimension (such as economic or environmental factors) while neglecting other relevant dimensions. This paper builds a factor analysis model of resource value flow, based on full life cycle assessment and eco-design theory, in order to expose the relevant internal logic between these two factors. The model considers the efficient multiplication of resources, economic efficiency, and environmental efficiency as its core objectives. The model studies the status of resource value flow during the entire life cycle of a product, and gives an in-depth analysis on the mutual logical relationship of product performance, value, resource consumption, and environmental load to reveal the symptoms and potentials in different dimensions. This provides comprehensive, accurate and timely decision-making information for enterprise managers regarding product eco-design, as well as production and management activities. To conclude, it verifies the availability of this evaluation and analysis model using a Chinese SUV manufacturer as an example. (Author)

  3. A Cohort Study on Risk Factors of Lung Cancer in Yunnan Tin Miners

    Directory of Open Access Journals (Sweden)

    Yong JIANG

    2013-04-01

    Full Text Available Background and objective Smoking is a major cause of lung cancer. Studies of lung cancer among miners have shown that occupational exposure also played an important role. The aim of this study is to investigate radon, cigarette use and other risk factors of lung cancer in Yunnan tin miners and to provide a scientific basis for the prevention and control of occupational lung cancer. Methods A prospective cohort study was conducted among Yunnan tin miners, the associations between potential risk factors for lung cancer were analyzed by multivariate Cox regression model. Effects of age at first radon exposure and radon exposure rate on lung cancer risk were analyzed. The relationship between cumulative working level month and lung cancer was analyzed according to smoking status. The joint effect of tobacco use and cumulative radon exposure was analyzed based on additive and multiplicative models. Results Increased risk of lung cancer was associated with age at enrollment, tobacco use, prior bronchitis, and cumulative arsenic and radon exposure, while higher education level was associated with decreased lung cancer risk. An inverse effect of radon exposure rate was observed. There was no significant association between lung cancer risk and first radon exposure age. There was a significant additive interaction between tobacco use and radon exposure on lung cancer risk. Conclusion Several risk factors may contribute to the high incidence of lung cancer in Yunnan tin miners. Further studies are warranted to evaluate joint effect of different risk factors.

  4. Hand function evaluation: a factor analysis study.

    Science.gov (United States)

    Jarus, T; Poremba, R

    1993-05-01

    The purpose of this study was to investigate hand function evaluations. Factor analysis with varimax rotation was used to assess the fundamental characteristics of the items included in the Jebsen Hand Function Test and the Smith Hand Function Evaluation. The study sample consisted of 144 subjects without disabilities and 22 subjects with Colles fracture. Results suggest a four factor solution: Factor I--pinch movement; Factor II--grasp; Factor III--target accuracy; and Factor IV--activities of daily living. These categories differentiated the subjects without Colles fracture from the subjects with Colles fracture. A hand function evaluation consisting of these four factors would be useful. Such an evaluation that can be used for current clinical purposes is provided.

  5. Optimization Scheduling Model for Wind-thermal Power System Considering the Dynamic penalty factor

    Science.gov (United States)

    PENG, Siyu; LUO, Jianchun; WANG, Yunyu; YANG, Jun; RAN, Hong; PENG, Xiaodong; HUANG, Ming; LIU, Wanyu

    2018-03-01

    In this paper, a new dynamic economic dispatch model for power system is presented.Objective function of the proposed model presents a major novelty in the dynamic economic dispatch including wind farm: introduced the “Dynamic penalty factor”, This factor could be computed by using fuzzy logic considering both the variable nature of active wind power and power demand, and it could change the wind curtailment cost according to the different state of the power system. Case studies were carried out on the IEEE30 system. Results show that the proposed optimization model could mitigate the wind curtailment and the total cost effectively, demonstrate the validity and effectiveness of the proposed model.

  6. 1/M corrections to baryonic form factors in the quark model

    International Nuclear Information System (INIS)

    Cheng, H.; Tseng, B.

    1996-01-01

    Weak current-induced baryonic form factors at zero recoil are evaluated in the rest frame of the heavy parent baryon using the nonrelativistic quark model. Contrary to previous similar work in the literature, our quark model results do satisfy the constraints imposed by heavy quark symmetry for heavy-heavy baryon transitions at the symmetric point v·v'=1 and are in agreement with the predictions of the heavy quark effective theory for antitriplet-antitriplet heavy baryon form factors at zero recoil evaluated to order 1/m Q . Furthermore, the quark model approach has the merit that it is applicable to any heavy-heavy and heavy-light baryonic transitions at maximum q 2 . Assuming a dipole q 2 behavior, we have applied the quark model form factors to nonleptonic, semileptonic, and weak radiative decays of the heavy baryons. It is emphasized that the flavor suppression factor occurring in many heavy-light baryonic transitions, which is unfortunately overlooked in most literature, is very crucial towards an agreement between theory and experiment for the semileptonic decay Λ c →Λe + ν e . Predictions for the decay modes Λ b →J/ψΛ, Λ c →pφ, Λ b →Λγ, Ξ b →Ξγ, and for the semileptonic decays of Λ b , Ξ b, c, and Ω b are presented. copyright 1996 The American Physical Society

  7. Specific count model for investing the related factors of cost of GERD and functional dyspepsia

    Science.gov (United States)

    Abadi, Alireza; Chaibakhsh, Samira; Safaee, Azadeh; Moghimi-Dehkordi, Bijan

    2013-01-01

    Aim The purpose of this study is to analyze the cost of GERD and functional dyspepsia for investing its related factors. Background Gastro-oesophageal reflux disease GERD and dyspepsia are the most common symptoms of gastrointestinal disorders. Recent studies showed high prevalence and variety of clinical presentation of these two symptoms imposed enormous economic burden to the society. Cost data that related to economics burden have specific characteristics. So this kind of data needs to specific models. Poisson regression (PR) and negative binomial regression (NB) are the models that were used for analyzing cost data in this paper. Patients and methods This study designed as a cross-sectional household survey from May 2006 to December 2007 on a random sample of individual in the Tehran province, Iran to find the prevalence of gastrointestinal symptoms and disorders and its related factors. The Cost in each item was counted. PR and NB were carried out to the data respectively. Likelihood ratio test was performed for comparison between models. Also Log likelihood, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used to compare performance of the models. Results According to Likelihood ratio test and all three criterions that we used to compare performance of the models, NB was the best model for analyzing this cost data. Sex, age and insurance statues were being significant. Conclusion PR and NB models were carried out for this data and according the results improved fit of the NB model over PR, it clearly indicates that over-dispersion is involved due to unobserved heterogeneity and/or clustering. NB model in cost data more appropriate fit than PR. PMID:24834282

  8. The Multi-state Latent Factor Intensity Model for Credit Rating Transitions

    NARCIS (Netherlands)

    Koopman, S.J.; Lucas, A.; Monteiro, A.

    2008-01-01

    A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic factors. The model has a generalized semi-Markov structure designed to accommodate many of the

  9. Risk factors for breast cancer in the breast cancer risk model study of Guam and Saipan.

    Science.gov (United States)

    Leon Guerrero, Rachael T; Novotny, Rachel; Wilkens, Lynne R; Chong, Marie; White, Kami K; Shvetsov, Yurii B; Buyum, Arielle; Badowski, Grazyna; Blas-Laguaña, Michelle

    2017-10-01

    Chamorro Pacific Islanders in the Mariana Islands have breast cancer incidence rates similar to, but mortality rates higher than, those of U.S. women. As breast cancer risk factors of women of the Mariana Islands may be unique because of ethnic and cultural differences, we studied established and suspected risk factors for breast cancer in this unstudied population. From 2010-2013, we conducted retrospective case-control study of female breast cancer (104 cases and 185 controls) among women in the Mariana Islands. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for each of various lifestyle-related factors from logistic regression of breast cancer, in all women and in pre- and postmenopausal women separately. Tests for interaction of risk factors with ethnicity were based on the Wald statistics for cross-product terms. Of the medical and reproductive factors considered - age at menarche, breastfeeding, number of live births, age at first live birth, hormone use, and menopause - only age at first live birth was confirmed. Age at first live birth, among parous women, was higher among cases (mean 24.9 years) than controls (mean 23.2 years); with increased breast cancer risk (OR=2.53; 95% CI, 1.04-6.19 for age≥30y compared to risk and only in Filipino women. The association with many other established risk factors, such as BMI, hormone use and physical activity, were in the expected direction but were not significant. Associations for family history of breast cancer and alcohol intake were not evident CONCLUSIONS: The results provide a basis for cancer prevention guidance for women in the Mariana Islands. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  10. An exploration study to detect important factors influencing internet marketing: A case study of food industry

    Directory of Open Access Journals (Sweden)

    Shadan Vahabzadeh

    2013-06-01

    Full Text Available Internet marketing plays an important role on profitability of organizations, it can build a bridge between customers and business owners and anyone could purchase products and services through internet. In this paper, we present an empirical investigation to detect important factors influencing internet marketing on Iranian food industry, named Shahrvand. The proposed study selects 280 out of 1040 managers who were involved in this industry during the year of 2012. Structural equation modeling has been performed to detect important factors including internal/external factors, ease of use and electronic marketing. Cronbach alphas have been calculated for these four items were mostly above 0.80, which validated the overall questionnaire of the survey. The results indicate that among internal factors, knowledge management, organizational culture and resources influence on acceptance of internet marketing, while these factors do not show any meaningful impact on ease of use. In addition, external factors including trend on market growth, competition and infrastructure influence on ease of use and acceptance of internet marketing but infrastructure and competition do not impact on ease of internet marketing.

  11. Maladaptive Personality Trait Models: Validating the Five-Factor Model Maladaptive Trait Measures With the Personality Inventory for DSM-5 and NEO Personality Inventory.

    Science.gov (United States)

    Helle, Ashley C; Mullins-Sweatt, Stephanie N

    2017-05-01

    Eight measures have been developed to assess maladaptive variants of the five-factor model (FFM) facets specific to personality disorders (e.g., Five-Factor Borderline Inventory [FFBI]). These measures can be used in their entirety or as facet-based scales (e.g., FFBI Affective Dysregulation) to improve the comprehensiveness of assessment of pathological personality. There are a limited number of studies examining these scales with other measures of similar traits (e.g., DSM-5 alternative model). The current study examined the FFM maladaptive scales in relation to the respective general personality traits of the NEO Personality Inventory-Revised and the pathological personality traits of the DSM-5 alternative model using the Personality Inventory for DSM-5. The results indicated the FFM maladaptive trait scales predominantly converged with corresponding NEO Personality Inventory-Revised, and Personality Inventory for DSM-5 traits, providing further validity for these measures as extensions of general personality traits and evidence for their relation to the pathological trait model. Benefits and applications of the FFM maladaptive scales in clinical and research settings are discussed.

  12. An Early Model for Value and Sustainability in Health Information Exchanges: Qualitative Study

    Science.gov (United States)

    2018-01-01

    Background The primary value relative to health information exchange has been seen in terms of cost savings relative to laboratory and radiology testing, emergency department expenditures, and admissions. However, models are needed to statistically quantify value and sustainability and better understand the dependent and mediating factors that contribute to value and sustainability. Objective The purpose of this study was to provide a basis for early model development for health information exchange value and sustainability. Methods A qualitative study was conducted with 21 interviews of eHealth Exchange participants across 10 organizations. Using a grounded theory approach and 3.0 as a relative frequency threshold, 5 main categories and 16 subcategories emerged. Results This study identifies 3 core current perceived value factors and 5 potential perceived value factors—how interviewees predict health information exchanges may evolve as there are more participants. These value factors were used as the foundation for early model development for sustainability of health information exchange. Conclusions Using the value factors from the interviews, the study provides the basis for early model development for health information exchange value and sustainability. This basis includes factors from the research: fostering consumer engagement; establishing a provider directory; quantifying use, cost, and clinical outcomes; ensuring data integrity through patient matching; and increasing awareness, usefulness, interoperability, and sustainability of eHealth Exchange. PMID:29712623

  13. A survey on important factors influencing brand equity: A case study of banking industry

    Directory of Open Access Journals (Sweden)

    Saeed Sehhat

    2013-01-01

    Full Text Available One of the most important issues in increasing customers' needs is to increase the quality of services through providing better quality services. Customer satisfaction is one of the primary requirements to meet people's needs and to have an efficient customer relationship management (CRM we need to detect the most important factors influencing efficiency and effectiveness in banking industry. In this paper, we present an empirical study to detect these factors in one of private banks in Iran. The proposed study of this paper tries to reach three objectives. We first detect important factors, which build customers' perception towards CRM, then we detect all influencing factors, which impact CRM, and finally, we evaluate the impact of CRM towards brand equity. The proposed study first designs a questionnaire and distributes it among 386 customers. Using structural equation modeling and certified factor analysis, we analyze the results. The results indicate that three factors including information, employee job behavior and suggestions and other factor have meaningful impact on customer brand equity. However, the impact of equipment on customer brand equity was not meaningful.

  14. A retrospective likelihood approach for efficient integration of multiple omics factors in case-control association studies.

    Science.gov (United States)

    Balliu, Brunilda; Tsonaka, Roula; Boehringer, Stefan; Houwing-Duistermaat, Jeanine

    2015-03-01

    Integrative omics, the joint analysis of outcome and multiple types of omics data, such as genomics, epigenomics, and transcriptomics data, constitute a promising approach for powerful and biologically relevant association studies. These studies often employ a case-control design, and often include nonomics covariates, such as age and gender, that may modify the underlying omics risk factors. An open question is how to best integrate multiple omics and nonomics information to maximize statistical power in case-control studies that ascertain individuals based on the phenotype. Recent work on integrative omics have used prospective approaches, modeling case-control status conditional on omics, and nonomics risk factors. Compared to univariate approaches, jointly analyzing multiple risk factors with a prospective approach increases power in nonascertained cohorts. However, these prospective approaches often lose power in case-control studies. In this article, we propose a novel statistical method for integrating multiple omics and nonomics factors in case-control association studies. Our method is based on a retrospective likelihood function that models the joint distribution of omics and nonomics factors conditional on case-control status. The new method provides accurate control of Type I error rate and has increased efficiency over prospective approaches in both simulated and real data. © 2015 Wiley Periodicals, Inc.

  15. Models hosts for the study of oral candidiasis.

    Science.gov (United States)

    Junqueira, Juliana Campos

    2012-01-01

    Oral candidiasis is an opportunistic infection caused by yeast of the Candida genus, primarily Candida albicans. It is generally associated with predisposing factors such as the use of immunosuppressive agents, antibiotics, prostheses, and xerostomia. The development of research in animal models is extremely important for understanding the nature of the fungal pathogenicity, host interactions, and treatment of oral mucosal Candida infections. Many oral candidiasis models in rats and mice have been developed with antibiotic administration, induction of xerostomia, treatment with immunosuppressive agents, or the use of germ-free animals, and all these models has both benefits and limitations. Over the past decade, invertebrate model hosts, including Galleria mellonella, Caenorhabditis elegans, and Drosophila melanogaster, have been used for the study of Candida pathogenesis. These invertebrate systems offer a number of advantages over mammalian vertebrate models, predominantly because they allow the study of strain collections without the ethical considerations associated with studies in mammals. Thus, the invertebrate models may be useful to understanding of pathogenicity of Candida isolates from the oral cavity, interactions of oral microorganisms, and study of new antifungal compounds for oral candidiasis.

  16. Application of the Perceptual Factors, Enabling and Reinforcing Model on Pap Smaear Screening in Iranian Northern Woman

    Directory of Open Access Journals (Sweden)

    Abolhassan Naghibi

    2016-03-01

    Full Text Available Background and Purpose: Cervical cancer is the most prevalent cancer among women in the world. Cervical cancer is no symptoms and can be treated if diagnosed in the first stage of the disease. The aim of this study was to survey the affecting factors of the Pap smears test on perceptual factors, enabling and reinforcing (PEN-3 model constructs in women. Materials and Methods: This study was a descriptive cross-sectional study. The sample size was 416 married women with random sampling. The questionnaire had 50 questions based on PEN-3 model structures. Data were analyzed by descriptive statistics and logistic regression method in software SPSS 20. Results: The mean age of women was 32.70 ± 21.00 years. The knowledge of risk factors and screening methods for cervical cancer was 37.2. About 40% of women had a history of Pap smears. The most important of perception factors were effective, family history of the disease, encourage people to Pap smear, and fear of detecting of cervical cancer. The most important enabling factors were the presence of expert health personnel to provide training and Pap smear test (50.3%, lack of time and too busy to do Pap smear test (23.2%. The reinforcing factors were the media advice (41.3%, doctor’s advice (32.5% and neglect and forgetfulness (36.2%. Conclusion: This study has shown the Pap smear screening behavior affected by personal factors, family, cultural and economic. Application of PEN-3 can effective in planning and designing intervention programs for cervical cancer screening.

  17. Five-Factor Model personality profiles of drug users

    Directory of Open Access Journals (Sweden)

    Crum Rosa M

    2008-04-01

    Full Text Available Abstract Background Personality traits are considered risk factors for drug use, and, in turn, the psychoactive substances impact individuals' traits. Furthermore, there is increasing interest in developing treatment approaches that match an individual's personality profile. To advance our knowledge of the role of individual differences in drug use, the present study compares the personality profile of tobacco, marijuana, cocaine, and heroin users and non-users using the wide spectrum Five-Factor Model (FFM of personality in a diverse community sample. Method Participants (N = 1,102; mean age = 57 were part of the Epidemiologic Catchment Area (ECA program in Baltimore, MD, USA. The sample was drawn from a community with a wide range of socio-economic conditions. Personality traits were assessed with the Revised NEO Personality Inventory (NEO-PI-R, and psychoactive substance use was assessed with systematic interview. Results Compared to never smokers, current cigarette smokers score lower on Conscientiousness and higher on Neuroticism. Similar, but more extreme, is the profile of cocaine/heroin users, which score very high on Neuroticism, especially Vulnerability, and very low on Conscientiousness, particularly Competence, Achievement-Striving, and Deliberation. By contrast, marijuana users score high on Openness to Experience, average on Neuroticism, but low on Agreeableness and Conscientiousness. Conclusion In addition to confirming high levels of negative affect and impulsive traits, this study highlights the links between drug use and low Conscientiousness. These links provide insight into the etiology of drug use and have implications for public health interventions.

  18. A pedestal temperature model with self-consistent calculation of safety factor and magnetic shear

    International Nuclear Information System (INIS)

    Onjun, T; Siriburanon, T; Onjun, O

    2008-01-01

    A pedestal model based on theory-motivated models for the pedestal width and the pedestal pressure gradient is developed for the temperature at the top of the H-mode pedestal. The pedestal width model based on magnetic shear and flow shear stabilization is used in this study, where the pedestal pressure gradient is assumed to be limited by first stability of infinite n ballooning mode instability. This pedestal model is implemented in the 1.5D BALDUR integrated predictive modeling code, where the safety factor and magnetic shear are solved self-consistently in both core and pedestal regions. With the self-consistently approach for calculating safety factor and magnetic shear, the effect of bootstrap current can be correctly included in the pedestal model. The pedestal model is used to provide the boundary conditions in the simulations and the Multi-mode core transport model is used to describe the core transport. This new integrated modeling procedure of the BALDUR code is used to predict the temperature and density profiles of 26 H-mode discharges. Simulations are carried out for 13 discharges in the Joint European Torus and 13 discharges in the DIII-D tokamak. The average root-mean-square deviation between experimental data and the predicted profiles of the temperature and the density, normalized by their central values, is found to be about 14%

  19. A Statistical Study of Socio-economic and Physical Risk Factors of Myocardial Infarction

    Directory of Open Access Journals (Sweden)

    M. Alamgir

    2005-07-01

    Full Text Available A sample of 506 patients from various hospitals in Peshawar was examined to determine significant socio-economic and physical risk factors of Myocardial Infarction (heart attack. The factors examined were smoking (S, hypertension (H, cholesterol (C, diabetes (D, family history (F, residence (R, own a house (OH, number of dependents (ND, household income (I, obesity and lack of exercise (E. The response variable MI was binary. Therefore, logistic regression was applied (using GLIM and SPSS packages to analyze the data and to select a parsimonious model. Logistic regression models have been obtained indicating significant risk factors for both sexes, for males and for females separately. The best-selected model for both sexes is of factors S, F, D, H and C. The best-selected model for males is of factors CIFH, S, H, D, C and F, while the best-selected model for females is of factors D, H, C and F.

  20. Regression-Based Norms for a Bi-factor Model for Scoring the Brief Test of Adult Cognition by Telephone (BTACT).

    Science.gov (United States)

    Gurnani, Ashita S; John, Samantha E; Gavett, Brandon E

    2015-05-01

    The current study developed regression-based normative adjustments for a bi-factor model of the The Brief Test of Adult Cognition by Telephone (BTACT). Archival data from the Midlife Development in the United States-II Cognitive Project were used to develop eight separate linear regression models that predicted bi-factor BTACT scores, accounting for age, education, gender, and occupation-alone and in various combinations. All regression models provided statistically significant fit to the data. A three-predictor regression model fit best and accounted for 32.8% of the variance in the global bi-factor BTACT score. The fit of the regression models was not improved by gender. Eight different regression models are presented to allow the user flexibility in applying demographic corrections to the bi-factor BTACT scores. Occupation corrections, while not widely used, may provide useful demographic adjustments for adult populations or for those individuals who have attained an occupational status not commensurate with expected educational attainment. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  1. Uncovering the influence of social skills and psychosociological factors on pain sensitivity using structural equation modeling.

    Science.gov (United States)

    Tanaka, Yoichi; Nishi, Yuki; Nishi, Yuki; Osumi, Michihiro; Morioka, Shu

    2017-01-01

    Pain is a subjective emotional experience that is influenced by psychosociological factors such as social skills, which are defined as problem-solving abilities in social interactions. This study aimed to reveal the relationships among pain, social skills, and other psychosociological factors by using structural equation modeling. A total of 101 healthy volunteers (41 men and 60 women; mean age: 36.6±12.7 years) participated in this study. To evoke participants' sense of inner pain, we showed them images of painful scenes on a PC screen and asked them to evaluate the pain intensity by using the visual analog scale (VAS). We examined the correlation between social skills and VAS, constructed a hypothetical model based on results from previous studies and the current correlational analysis results, and verified the model's fit using structural equation modeling. We found significant positive correlations between VAS and total social skills values, as well as between VAS and the "start of relationships" subscales. Structural equation modeling revealed that the values for "start of relationships" had a direct effect on VAS values (path coefficient =0.32, p social support. The results indicated that extroverted people are more sensitive to inner pain and tend to get more social support and maintain a better psychological condition.

  2. Testing the CAPM and Three Factors Model in China: Evidence from the Shanghai Stock Exchange

    OpenAIRE

    Wang, Weixi

    2015-01-01

    Since inception, China’s stock market has grown rapidly and has become one of the most important emerging markets in the world. However, many popular financial media depicts China’s stock market as irrational. Besides, empirical studies on asset pricing in China’s stock market do not provide a consistent conclusion for different periods. This study tests the Capital Asset Pricing Model (CAPM) and Fama-French Three Factors Model in Shanghai Stock Exchange, China. For validity test of the CAPM,...

  3. Rotation in the dynamic factor modeling of multivariate stationary time series.

    NARCIS (Netherlands)

    Molenaar, P.C.M.; Nesselroade, J.R.

    2001-01-01

    A special rotation procedure is proposed for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of a q-variate latent factor series and transforms such a component, initially represented as white

  4. Testing multi-factor asset pricing models in the Visegrad countries

    Czech Academy of Sciences Publication Activity Database

    Morgese Borys, Magdalena

    -, č. 323 (2007), s. 1-40 ISSN 1211-3298 R&D Projects: GA MŠk LC542 Institutional research plan: CEZ:AV0Z70850503 Keywords : capital asset pricing model * macroeconomic factor models * cost of capital Subject RIV: AH - Economics http://www.cerge-ei.cz/pdf/wp/Wp323.pdf

  5. Factor Analysis and Modelling for Rapid Quality Assessment of Croatian Wheat Cultivars with Different Gluten Characteristics

    Directory of Open Access Journals (Sweden)

    Želimir Kurtanjek

    2008-01-01

    Full Text Available Factor analysis and multivariate chemometric modelling for rapid assessment of baking quality of wheat cultivars from Slavonia region, Croatia, have been applied. The cultivars Žitarka, Kata, Monika, Ana, Demetra, Divana and Sana were grown under controlled conditions at the experimental field of Agricultural Institute Osijek during three years (2000–2002. Their quality properties were evaluated by 45 different chemical, physical and biochemical variables. The measured variables were grouped as: indirect quality parameters (6, farinographic parameters (7, extensographic parameters (5, baking test parameters (2 and reversed phase-high performance liquid chromatography (RP-HPLC of gluten proteins (25. The aim of this study is to establish minimal number (three, i.e. principal factors, among the 45 variables and to derive multivariate linear regression models for their use in simple and fast prediction of wheat properties. Selection of the principal factors based on the principal component analysis (PCA has been applied. The first three main factors of the analysis include: total glutenins (TGT, total ω-gliadins (Tω- and the ratio of dough resistance/extensibility (R/Ext. These factors account for 76.45 % of the total variance. Linear regression models gave average regression coefficients (R evaluated for the parameter groups: indirect quality R=0.91, baking test R=0.63, farinographic R=0.78, extensographic R=0.95 and RP-HPLC of gluten data R=0.90. Errors in the model predictions were evaluated by the 95 % significance intervals of the calibration lines. Practical applications of the models for rapid quality assessment and laboratory experiment planning were emphasized.

  6. Situational effects of the school factors included in the dynamic model of educational effectiveness

    NARCIS (Netherlands)

    Creerners, Bert; Kyriakides, Leonidas

    We present results of a longitudinal study in which 50 schools, 113 classes and 2,542 Cypriot primary students participated. We tested the validity of the dynamic model of educational effectiveness and especially its assumption that the impact of school factors depends on the current situation of

  7. E-Learning and Social Media Motivation Factor Model

    Science.gov (United States)

    Rosli, Mohd Shafie; Saleh, Nor Shela; Aris, Baharuddin; Ahmad, Maizah Hura; Sejzi, Abbas Abjoli; Shamsudin, Nur Amalina

    2016-01-01

    The aims of this study are to probe into the motivational factors toward the usage of e-learning and social media among educational technology postgraduate students in the Faculty of Education, Universiti Teknologi Malaysia. This study had involved 70 respondents via the means of a questionnaire. Four factors have been studied, named, the factor…

  8. Confirmatory factory analysis of the Neck Disability Index in a general problematic neck population indicates a one-factor model.

    Science.gov (United States)

    Gabel, Charles Philip; Cuesta-Vargas, Antonio I; Osborne, Jason W; Burkett, Brendan; Melloh, Markus

    2014-08-01

    The Neck Disability Index frequently is used to measure outcomes of the neck. The statistical rigor of the Neck Disability Index has been assessed with conflicting outcomes. To date, Confirmatory Factor Analysis of the Neck Disability Index has not been reported for a suitably large population study. Because the Neck Disability Index is not a condition-specific measure of neck function, initial Confirmatory Factor Analysis should consider problematic neck patients as a homogenous group. We sought to analyze the factor structure of the Neck Disability Index through Confirmatory Factor Analysis in a symptomatic, homogeneous, neck population, with respect to pooled populations and gender subgroups. This was a secondary analysis of pooled data. A total of 1,278 symptomatic neck patients (67.5% female, median age 41 years), 803 nonspecific and 475 with whiplash-associated disorder. The Neck Disability Index was used to measure outcomes. We analyzed pooled baseline data from six independent studies of patients with neck problems who completed Neck Disability Index questionnaires at baseline. The Confirmatory Factor Analysis was considered in three scenarios: the full sample and separate sexes. Models were compared empirically for best fit. Two-factor models have good psychometric properties across both the pooled and sex subgroups. However, according to these analyses, the one-factor solution is preferable from both a statistical perspective and parsimony. The two-factor model was close to significant for the male subgroup (pfactor structure when analyzed by Confirmatory Factor Analysis in a pooled, homogenous sample of neck problem patients. However, a two-factor model did approach significance for male subjects where questions separated into constructs of mental and physical function. Further investigations in different conditions, subgroup and sex-specific populations are warranted. Copyright © 2014 Elsevier Inc. All rights reserved.

  9. Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies

    Directory of Open Access Journals (Sweden)

    Hero Alfred

    2010-11-01

    Full Text Available Abstract Background Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP, the Indian Buffet Process (IBP, and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB analysis. Results Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV, Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD, closely related non-Bayesian approaches. Conclusions Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

  10. Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

    Science.gov (United States)

    Chen, Bo; Chen, Minhua; Paisley, John; Zaas, Aimee; Woods, Christopher; Ginsburg, Geoffrey S; Hero, Alfred; Lucas, Joseph; Dunson, David; Carin, Lawrence

    2010-11-09

    Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

  11. Modeling the Factors Affecting the Promotion of the Share of R&T Units in Iran Export Agriculture Product's Added Value: Case Study of Saffron and Barberry

    Directory of Open Access Journals (Sweden)

    Mohammad Ghorbani

    2016-01-01

    Full Text Available In this study we investigate the importance of agricultural sector research and technology organizations (RTO in the national economic system. The main objective of the paper is to identify and rank the factors affecting the promotion of these RTOs share in saffron’s added value. Through the literature review we extracted all the relevant factors that have been mentioned by different researchers. Then, we classified these factors into six components: applied research, technology acquisition, commercialization, market development, industry’s internal factors and national macro factors. We used a Likert scale questionnaire to gather the data about the importance of each factor based on research and technology experts’ points of view. To analyze the data we utilized confirmatory factor analysis and structural equation modeling (SEM methods using SPSS and smart PLS software packages. The results show that the most important factor affecting the share of agricultural RTOs in a products added value  is the promotion of industrial firms to invest in the field of agricultural research and development. Finally, according to the obtained results, some suggestions for improving research and technology have been provided.

  12. Military-Specific Exposure Factors Study

    National Research Council Canada - National Science Library

    Lurker, Peter

    1998-01-01

    ...) provides many factors needed in the assessment of human health risk that were derived from general population studies or studies involving relatively small groups that may not be representative of military populations...

  13. Confirmatory factor analysis of the Neuropsychological Assessment Battery of the LADIS study

    DEFF Research Database (Denmark)

    Moleiro, Carla; Madureira, Sofia; Verdelho, Ana

    2013-01-01

    analysis (CFA) was used to investigate the dimensions of a structured set of neuropsychological tests administered to a multicenter, international sample of independent older adults (LADIS study). Six hundred and thirty-eight older adults completed baseline neuropsychological, clinical, functional...... and motor assessments, which were repeated each year for a 3-year follow-up. CFA provided support for a 3-factor model. These factors involve the dimensions of executive functions, memory functions, and speed and motor control abilities. Performance decreased in most neuropsychological measures. Results...

  14. A comparative study on the influential factors of China's provincial energy intensity

    International Nuclear Information System (INIS)

    Yang, Guangfei; Li, Wenli; Wang, Jianliang; Zhang, Dongqing

    2016-01-01

    China has become the largest energy consumer worldwide, and it is important to study the energy intensity to realize the sustainable development goal of China. This paper focuses on investigating the influential factors of China's energy intensity using provincial-level panel data from 1985 to 2012. More specifically, we try to identify which factor is relatively more important to pay attention to. A novel approach based on evolutionary computation is proposed to intelligently mine the intrinsic relations between observed phenomena and to let the important factors automatically emerge from the discovered nonlinear models. However, due to China's vast territory and significant heterogeneities, this approach may fail to examine some detailed or hidden information when analyzing the country as a whole. Instead, we concentrate on the provincial level because the provinces play vital roles in reducing energy intensity in China. From our analytical results, the main findings are as follows: (1) the Total Population is the most important influential factor across China's provinces, while the Energy Price Index has the least impact; and (2) the provinces could be naturally classified into four categories based on the primary factors emerged from data, and such classification could reveal more about the true underlying features of each area. - Highlights: • Identify the important factors of China's energy intensity by symbolic regression. • Analyze China's energy intensity using provincial-level panel data from 1985 to 2012. • Intelligently investigate nonlinear models and the emergence of important factors. • The Total Population is discovered to be the most important influential factor. • Provinces are naturally classified into four categories by the influential factors.

  15. Form factors of {eta}{sub c} in light-front quark model

    Energy Technology Data Exchange (ETDEWEB)

    Geng, Chao-Qiang [Chongqing University of Posts and Telecommunications, College of Mathematics and Physics, Chongqing (China); National Center for Theoretical Sciences, Physics Division, Hsinchu (China); National Tsing Hua University, Department of Physics, Hsinchu (China); Lih, Chong-Chung [Shu-Zen College of Medicine and Management, Department of Optometry, Kaohsiung Hsien (China); National Center for Theoretical Sciences, Physics Division, Hsinchu (China); National Tsing Hua University, Department of Physics, Hsinchu (China)

    2013-08-15

    We study the form factors of the {eta}{sub c} meson in the light-front quark model. We explicitly show that the transition form factor of {eta}{sub c} {yields} {gamma}{sup *}{gamma} as a function of the momentum transfer is consistent with the experimental data by the BaBar collaboration, while the decay constant of {eta}{sub c} is found to be f{sub {eta}{sub c}} = 230.5{sup +52.2}{sub -61.0} and 303.6{sup +115.2}{sub -116.4} MeV for {eta}{sub c} {proportional_to} c anti c by using two {eta}{sub c} {yields} {gamma}{gamma} decay widths of 5.3 {+-} 0.5 and 7.2 {+-} 2.1 keV, given by Particle Data Group and Lattice QCD calculation, respectively. (orig.)

  16. A social work study using factor analysis on detecting important factors creating stress: A case study of hydro-power employees

    Directory of Open Access Journals (Sweden)

    Batoul Aminjafari

    2012-08-01

    Full Text Available The study performs an empirical study based on the implementation of factor analysis to detect different factors influencing people to have more stress in a hydropower unit located in city of Esfahan, Iran. The study performed the survey among all 81 people who were working for customer service section of this company and consisted of two parts, in the first part; we gather all private information such as age, gender, education, job experience, etc. through seven important questions. In the second part of the survey, there were 66 questions, which included all the relevant factors impacting employees' stress. Cronbach alpha was calculated as 0.946, which is well above the minimum acceptable level. The implementation of factor analysis has detected 16 important groups of factors and each factor is determined by an appropriate name. The results of our factor analysis show that among different factors, difficulty of working condition as well as work pressure are two most important factors increasing stress among employees.

  17. A Monte Carlo study comparing PIV, ULS and DWLS in the estimation of dichotomous confirmatory factor analysis.

    Science.gov (United States)

    Nestler, Steffen

    2013-02-01

    We conducted a Monte Carlo study to investigate the performance of the polychoric instrumental variable estimator (PIV) in comparison to unweighted least squares (ULS) and diagonally weighted least squares (DWLS) in the estimation of a confirmatory factor analysis model with dichotomous indicators. The simulation involved 144 conditions (1,000 replications per condition) that were defined by a combination of (a) two types of latent factor models, (b) four sample sizes (100, 250, 500, 1,000), (c) three factor loadings (low, moderate, strong), (d) three levels of non-normality (normal, moderately, and extremely non-normal), and (e) whether the factor model was correctly specified or misspecified. The results showed that when the model was correctly specified, PIV produced estimates that were as accurate as ULS and DWLS. Furthermore, the simulation showed that PIV was more robust to structural misspecifications than ULS and DWLS. © 2012 The British Psychological Society.

  18. A Study on the Holding Capacity Safety Factors for Torpedo Anchors

    Directory of Open Access Journals (Sweden)

    Luís V. S. Sagrilo

    2012-01-01

    Full Text Available The use of powerful numerical tools based on the finite-element method has been improving the prediction of the holding capacity of fixed anchors employed by the offshore oil industry. One of the main achievements of these tools is the reduction of the uncertainty related to the holding capacity calculation of these anchors. Therefore, it is also possible to reduce the values of the associated design safety factors, which have been calibrated relying on models with higher uncertainty, without impairing the original level of structural safety. This paper presents a study on the calibration of reliability-based safety factors for the design of torpedo anchors considering the statistical model uncertainty evaluated using results from experimental tests and their correspondent finite-element-based numerical predictions. Both working stress design (WSD and load and resistance factors design (LRFD design methodologies are investigated. Considering the WSD design methodology, the single safety is considerably lower than the value typically employed in the design of torpedo anchors. Moreover, a LRFD design code format for torpedo anchors is more appropriate since it leads to designs having less-scattered safety levels around the target value.

  19. Factors associated with student learning processes in primary health care units: a questionnaire study.

    Science.gov (United States)

    Bos, Elisabeth; Alinaghizadeh, Hassan; Saarikoski, Mikko; Kaila, Päivi

    2015-01-01

    Clinical placement plays a key role in education intended to develop nursing and caregiving skills. Studies of nursing students' clinical learning experiences show that these dimensions affect learning processes: (i) supervisory relationship, (ii) pedagogical atmosphere, (iii) management leadership style, (iv) premises of nursing care on the ward, and (v) nursing teachers' roles. Few empirical studies address the probability of an association between these dimensions and factors such as student (a) motivation, (b) satisfaction with clinical placement, and (c) experiences with professional role models. The study aimed to investigate factors associated with the five dimensions in clinical learning environments within primary health care units. The Swedish version of Clinical Learning Environment, Supervision and Teacher, a validated evaluation scale, was administered to 356 graduating nursing students after four or five weeks clinical placement in primary health care units. Response rate was 84%. Multivariate analysis of variance is determined if the five dimensions are associated with factors a, b, and c above. The analysis revealed a statistically significant association with the five dimensions and two factors: students' motivation and experiences with professional role models. The satisfaction factor had a statistically significant association (effect size was high) with all dimensions; this clearly indicates that students experienced satisfaction. These questionnaire results show that a good clinical learning experience constitutes a complex whole (totality) that involves several interacting factors. Supervisory relationship and pedagogical atmosphere particularly influenced students' satisfaction and motivation. These results provide valuable decision-support material for clinical education planning, implementation, and management. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. Canine diabetes mellitus risk factors: A matched case-control study.

    Science.gov (United States)

    Pöppl, Alan Gomes; de Carvalho, Guilherme Luiz Carvalho; Vivian, Itatiele Farias; Corbellini, Luis Gustavo; González, Félix Hilário Díaz

    2017-10-01

    Different subtypes of canine diabetes mellitus (CDM) have been described based on their aetiopathogenesis. Therefore, manifold risk factors may be involved in CDM development. This study aims to investigate canine diabetes mellitus risk factors. Owners of 110 diabetic dogs and 136 healthy controls matched by breed, sex, and age were interviewed concerning aspects related to diet, weight, physical activity, oral health, reproductive history, pancreatitis, and exposure to exogenous glucocorticoids. Two multivariate multivariable statistical models were created: The UMod included males and females without variables related to oestrous cycle, while the FMod included only females with all analysed variables. In the UMod, "Not exclusively commercial diet" (OR 4.86, 95%CI 2.2-10.7, Pdiet" (OR 4.14, 95%CI 1.3-12.7, P=0.01), "Table scraps abuse" (OR 3.62, 95%CI 1.1-12.2, P=0.03), "Overweight" (OR 3.91, 95%CI 1.2-12.6, P=0.02), and "Dioestrus" (OR 5.53, 95%CI 1.9-16.3, P=0.002) were statistically significant. The findings in this study support feeding not exclusively balanced commercial dog food, overweight, treats abuse, and diestrus, as main CDM risk factors. Moreover, those results give subside for preventive care studies against CDM development. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Factors associated with self-medication in Spain: a cross-sectional study in different age groups.

    Science.gov (United States)

    Niclós, Gracia; Olivar, Teresa; Rodilla, Vicent

    2018-06-01

    The identification of factors which may influence a patient's decision to self-medicate. Descriptive, cross-sectional study of the adult population (at least 16 years old), using data from the 2009 European Health Interview Survey in Spain, which included 22 188 subjects. Logistic regression models enabled us to estimate the effect of each analysed variable on self-medication. In total, 14 863 (67%) individuals reported using medication (prescribed and non-prescribed) and 3274 (22.0%) of them self-medicated. Using logistic regression and stratifying by age, four different models have been constructed. Our results include different variables in each of the models to explain self-medication, but the one that appears on all four models is education level. Age is the other important factor which influences self-medication. Self-medication is strongly associated with factors related to socio-demographic, such as sex, educational level or age, as well as several health factors such as long-standing illness or physical activity. When our data are compared to those from previous Spanish surveys carried out in 2003 and 2006, we can conclude that self-medication is increasing in Spain. © 2017 Royal Pharmaceutical Society.

  2. On form factors of the conjugated field in the non-linear Schroedinger model

    Energy Technology Data Exchange (ETDEWEB)

    Kozlowski, K.K.

    2011-05-15

    Izergin-Korepin's lattice discretization of the non-linear Schroedinger model along with Oota's inverse problem provides one with determinant representations for the form factors of the lattice discretized conjugated field operator. We prove that these form factors converge, in the zero lattice spacing limit, to those of the conjugated field operator in the continuous model. We also compute the large-volume asymptotic behavior of such form factors in the continuous model. These are in particular characterized by Fredholm determinants of operators acting on closed contours. We provide a way of defining these Fredholm determinants in the case of generic paramaters. (orig.)

  3. Microscopic models for hadronic form factors and vertex functions

    International Nuclear Information System (INIS)

    Santhanam, I.; Bhatnagar, S.; Mitra, A.N.

    1990-01-01

    We review the status of nucleon (N) and few-nucleon form factors (f.f.'s) from the view-point of a gradual unfolding of successively inner degrees of freedom (d.o.f.) with increase in q 2 . To this end we focus attention on the problem of a microscopic formulation of hadronic vertex functions (v.f.) from the point of view of their key role in understanding the physics of a large variety of few-hadron reactions on the one hand, and their practical usefulness in articulating the internal dynamics of hadron and few-hadron systems on the other hand. The criterion of an integrated view from low-energy spectroscopy to high-q 2 amplitudes is employed to emphasize the desirability of formulations in terms of relativistic dynamical equations based on Lorentz and gauge invariance in preference to phenomenological models, which often require additional assumptions beyond their original premises to extend their applicability domains. In this respect, the practical possibilities of the Bethe-Salpeter equation (BSE) in articulating the necessary dynamical ingredients are emphasized on a two-tier basis, the basis constants (3) being pre-determined from the mass spectral data (1 st stage) in preparation for the construction of the hadron-quark vertex functions (2 nd stage). An explicit construction is outlined for meson-quark and baryon-quark vertex functions as well as of meson-nucleon vertex functions in a stepwise fashion. The role of the latter as basic parameter-free ingredients is discussed for possible use in the more serious treatment in the current literature of quark-meson level (α) and meson-isobar (β) d.o.f. in 2-N and 3-N form factor studies. Since most of these studies are characterized by the use of RGM techniques at the six-quark level, a comparative discussion is also given of several contemporary RGM based models. Finally, the concrete prospects for employing such hardon-quark vertex functions for evaluating pp-bar annihilation amplitudes are briefly indicated

  4. Activity systems modeling as a theoretical lens for social exchange studies

    Directory of Open Access Journals (Sweden)

    Ernest Jones

    2016-01-01

    Full Text Available The social exchange perspective seeks to acknowledge, understand and predict the dynamics of social interactions. Empirical research involving social exchange constructs have grown to be highly technical including confirmatory factor analysis to assess construct distinctiveness and structural equation modeling to assess construct causality. Each study seemingly strives to assess how underlying social exchange theoretic constructs interrelate. Yet despite this methodological depth and resultant explanatory and predictive power, a significant number of studies report findings that, once synthesized, suggest an underlying persistent threat of conceptual or construct validity brought about by a search for epistemological parsimony. Further, it is argued that a methodological approach that embraces inherent complexity such as activity systems modeling facilitates the search for simplified models while not ignoring contextual factors.

  5. Neonatal Risk Factors for Treatment-Demanding Retinopathy of Prematurity: A Danish National Study.

    Science.gov (United States)

    Slidsborg, Carina; Jensen, Aksel; Forman, Julie Lyng; Rasmussen, Steen; Bangsgaard, Regitze; Fledelius, Hans Callø; Greisen, Gorm; la Cour, Morten

    2016-04-01

    One goal of the study was to identify "new" statistically independent risk factors for treatment-demanding retinopathy of prematurity (ROP). Another goal was to evaluate whether any new risk factors could explain the increase in the incidence of treatment-demanding ROP over time in Denmark. A retrospective, register-based cohort study. The study included premature infants (n = 6490) born in Denmark from 1997 to 2008. The study sample and the 31 candidate risk factors were identified in 3 national registers. Data were linked through a unique civil registration number. Each of the 31 candidate risk factors were evaluated in univariate analyses, while adjusted for known risk factors (i.e., gestational age [GA] at delivery, small for gestational age [SGA], multiple births, and male sex). Significant outcomes were analyzed thereafter in a backward selection multiple logistic regression model. Treatment-demanding ROP and its associations to candidate risk factors. Mechanical ventilation (odds ratio [OR], 2.84; 95% confidence interval [CI], 1.99-4.08; P large study population, blood transfusion and mechanical ventilation were the only new statistically independent risk factors to predict the development of treatment-demanding ROP. Modification in the neonatal treatment with mechanical ventilation or blood transfusion did not cause the observed increase in the incidence of preterm infants with treatment-demanding ROP during a recent birth period (2003-2008). Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

  6. Factors influencing nurse-assessed quality nursing care: A cross-sectional study in hospitals.

    Science.gov (United States)

    Liu, Ying; Aungsuroch, Yupin

    2018-04-01

    To propose a hypothesized theoretical model and apply it to examine the structural relationships among work environment, patient-to-nurse ratio, job satisfaction, burnout, intention to leave and quality nursing care. Improving quality nursing care is a first consideration in nursing management globally. A better understanding of factors influencing quality nursing care can help hospital administrators implement effective programmes to improve quality of services. Although certain bivariate correlations have been found between selected factors and quality nursing care in different study models, no studies have examined the relationships among work environment, patient-to-nurse ratio, job satisfaction, burnout, intention to leave and quality nursing care in a more comprehensive theoretical model. A cross-sectional survey. The questionnaires were collected from 510 Chinese nurses in four Chinese tertiary hospitals in January 2015. The validity and internal consistency reliability of research instruments were evaluated. Structural equation modelling was used to test a theoretical model. The findings revealed that the data supported the theoretical model. Work environment had a large total effect size on quality nursing care. Burnout largely and directly influenced quality nursing care, which was followed by work environment and patient-to-nurse ratio. Job satisfaction indirectly affected quality nursing care through burnout. This study shows how work environment past burnout and job satisfaction influences quality nursing care. Apart from nurses' work conditions of work environment and patient-to-nurse ratio, hospital administrators should pay more attention to nurse outcomes of job satisfaction and burnout when designing intervention programmes to improve quality nursing care. © 2017 John Wiley & Sons Ltd.

  7. Factors associated with persons with disability employment in India: a cross-sectional study.

    Science.gov (United States)

    Naraharisetti, Ramya; Castro, Marcia C

    2016-10-07

    Over twenty million persons with disability in India are increasingly being offered poverty alleviation strategies, including employment programs. This study employs a spatial analytic approach to identify correlates of employment among persons with disability in India, considering sight, speech, hearing, movement, and mental disabilities. Based on 2001 Census data, this study utilizes linear regression and spatial autoregressive models to identify factors associated with the proportion employed among persons with disability at the district level. Models stratified by rural and urban areas were also considered. Spatial autoregressive models revealed that different factors contribute to employment of persons with disability in rural and urban areas. In rural areas, having mental disability decreased the likelihood of employment, while being female and having movement, or sight impairment (compared to other disabilities) increased the likelihood of employment. In urban areas, being female and illiterate decreased the likelihood of employment but having sight, mental and movement impairment (compared to other disabilities) increased the likelihood of employment. Poverty alleviation programs designed for persons with disability in India should account for differences in employment by disability types and should be spatially targeted. Since persons with disability in rural and urban areas have different factors contributing to their employment, it is vital that government and service-planning organizations account for these differences when creating programs aimed at livelihood development.

  8. Postpartum Bonding Disorder: Factor Structure, Validity, Reliability and a Model Comparison of the Postnatal Bonding Questionnaire in Japanese Mothers of Infants

    Directory of Open Access Journals (Sweden)

    Yukiko Ohashi

    2016-08-01

    Full Text Available Negative attitudes of mothers towards their infant is conceptualized as postpartum bonding disorder, which leads to serious health problems in perinatal health care. However, its measurement still remains to be standardized. Our aim was to examine and confirm the psychometric properties of the Postnatal Bonding Questionnaire (PBQ in Japanese mothers. We distributed a set of questionnaires to community mothers and studied 392 mothers who returned the questionnaires at 1 month after childbirth. Our model was compared with three other models derived from previous studies. In a randomly halved sample, an exploratory factor analysis yielded a three-factor structure: Anger and Restrictedness, Lack of Affection, and Rejection and Fear. This factor structure was cross-validated by a confirmatory factor analysis using the other halved sample. The three subscales showed satisfactory internal consistency. The three PBQ subscale scores were correlated with depression and psychological abuse scores. Their test–retest reliability between day 5 and 1 month after childbirth was measured by intraclass correlation coefficients between 0.76 and 0.83. The Akaike Information Criteria of our model was better than the original four-factor model of Brockington. The present study indicates that the PBQ is a reliable and valid measure of bonding difficulties of Japanese mothers with neonates.

  9. Chiral-model of weak-interaction form factors and magnetic moments of octet baryons

    International Nuclear Information System (INIS)

    Kubodera, K.; Kohyama, Y.; Tsushima, K.; Yamaguchi, T.

    1989-01-01

    For baryon spectroscopy, magnetic moments and weak interaction form factors provide valuable information, and the impressive amount of available experimental data on these quantities for the octet baryons invites detailed investigations. The authors of this paper have made extensive studies of the weak-interaction form factors and magnetic moments of the octet baryons within the framework of the volume-type cloudy-bag model (v-type CBM). The clouds of all octet mesons have been included. Furthermore, we have taken into account in a unified framework various effects that were so far only individually discussed in the literature. Thus, the gluonic effects, center-of-mass (CM0 corrections, and recoil corrections have been included). In this talk, after giving a brief summary of some salient features of the results, we discuss a very interesting application of our model to the problem of the spin content of nucleons

  10. A Study of Factors Affecting the Demand for Watching Football in Stadiums

    Directory of Open Access Journals (Sweden)

    Ehsan Javanmardi

    2011-01-01

    Full Text Available This paper is to find the factors effective on football matches watching demand in stadiums. The factors effective on the demand are divided into 4 categories; economical, environmental, appeal, and geographical / demographical factors which converted into 23 independent parameters by virtue of the device appropriate to gather related information. In this research, Iranian super league was selected as the subject of the study and We limited our study to three cities; Shiraz, Isfahan, and Tehran. Finally by virtue of estimating the regressions and estimating the Ordinary Least Square and Minitab software three equations were gained to foresee the number of the spectators. Validation of the models was conducted by lack of fit test, studies on the remnants such as Darling - Anderson test of normality, and Durbin Watson statistics for remnant independence test and the issue of their variance being fixed, and the study of lack of complex collinearity between independent variables using Variance Inflation Factor (VIF. We used step - by - step regression method and regression of all probable conditions. By virtue of the conclusions of the regression equations we found that there is a structural difference between capital and the cities and the factors creating attractions such as their recent successes, history and the quality of the teams have the most effects on the fans’ demand to attend in the stadiums.

  11. Comparison of analytic source models for head scatter factor calculation and planar dose calculation for IMRT

    International Nuclear Information System (INIS)

    Yan Guanghua; Liu, Chihray; Lu Bo; Palta, Jatinder R; Li, Jonathan G

    2008-01-01

    The purpose of this study was to choose an appropriate head scatter source model for the fast and accurate independent planar dose calculation for intensity-modulated radiation therapy (IMRT) with MLC. The performance of three different head scatter source models regarding their ability to model head scatter and facilitate planar dose calculation was evaluated. A three-source model, a two-source model and a single-source model were compared in this study. In the planar dose calculation algorithm, in-air fluence distribution was derived from each of the head scatter source models while considering the combination of Jaw and MLC opening. Fluence perturbations due to tongue-and-groove effect, rounded leaf end and leaf transmission were taken into account explicitly. The dose distribution was calculated by convolving the in-air fluence distribution with an experimentally determined pencil-beam kernel. The results were compared with measurements using a diode array and passing rates with 2%/2 mm and 3%/3 mm criteria were reported. It was found that the two-source model achieved the best agreement on head scatter factor calculation. The three-source model and single-source model underestimated head scatter factors for certain symmetric rectangular fields and asymmetric fields, but similar good agreement could be achieved when monitor back scatter effect was incorporated explicitly. All the three source models resulted in comparable average passing rates (>97%) when the 3%/3 mm criterion was selected. The calculation with the single-source model and two-source model was slightly faster than the three-source model due to their simplicity

  12. Comparison of analytic source models for head scatter factor calculation and planar dose calculation for IMRT

    Energy Technology Data Exchange (ETDEWEB)

    Yan Guanghua [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611 (United States); Liu, Chihray; Lu Bo; Palta, Jatinder R; Li, Jonathan G [Department of Radiation Oncology, University of Florida, Gainesville, FL 32610-0385 (United States)

    2008-04-21

    The purpose of this study was to choose an appropriate head scatter source model for the fast and accurate independent planar dose calculation for intensity-modulated radiation therapy (IMRT) with MLC. The performance of three different head scatter source models regarding their ability to model head scatter and facilitate planar dose calculation was evaluated. A three-source model, a two-source model and a single-source model were compared in this study. In the planar dose calculation algorithm, in-air fluence distribution was derived from each of the head scatter source models while considering the combination of Jaw and MLC opening. Fluence perturbations due to tongue-and-groove effect, rounded leaf end and leaf transmission were taken into account explicitly. The dose distribution was calculated by convolving the in-air fluence distribution with an experimentally determined pencil-beam kernel. The results were compared with measurements using a diode array and passing rates with 2%/2 mm and 3%/3 mm criteria were reported. It was found that the two-source model achieved the best agreement on head scatter factor calculation. The three-source model and single-source model underestimated head scatter factors for certain symmetric rectangular fields and asymmetric fields, but similar good agreement could be achieved when monitor back scatter effect was incorporated explicitly. All the three source models resulted in comparable average passing rates (>97%) when the 3%/3 mm criterion was selected. The calculation with the single-source model and two-source model was slightly faster than the three-source model due to their simplicity.

  13. Evaluation factors for verification and validation of low-level waste disposal site models

    International Nuclear Information System (INIS)

    Moran, M.S.; Mezga, L.J.

    1982-01-01

    The purpose of this paper is to identify general evaluation factors to be used to verify and validate LLW disposal site performance models in order to assess their site-specific applicability and to determine their accuracy and sensitivity. It is intended that the information contained in this paper be employed by model users involved with LLW site performance model verification and validation. It should not be construed as providing protocols, but rather as providing a framework for the preparation of specific protocols or procedures. A brief description of each evaluation factor is provided. The factors have been categorized according to recommended use during either the model verification or the model validation process. The general responsibilities of the developer and user are provided. In many cases it is difficult to separate the responsibilities of the developer and user, but the user is ultimately accountable for both verification and validation processes. 4 refs

  14. Application of Delphi method for determining the affecting factors upon audit risk model

    Directory of Open Access Journals (Sweden)

    Zohreh Hajiha

    2012-01-01

    Full Text Available The assessment of risks in an audit work could directly influence the costs, timing, and strategies as well as audit quality. The purpose of this paper is to identify the critical affecting factors on risks proposed in Audit Risk Model (ARM, in Iranian audit environment of Iran. In the present, the Delphi Method consists of 60 audit partners and managers is employed. The panel consists of two equally divided groups, one from audit organization, a governmental organization, and the other from private audit firms. We employ two rounds of Delphi and 58 critical risk factors extracted from auditing literature and Iranian auditing standards and present them to the experts. There are 43 factors categorized as important factors to assess the risks in ARM. The results are considerable in an Iranian audit environment, findings show the most important factors are in inherent risk factors. Finally, we made a comparison with a similar study in Taiwan. Differences indicate that in professional judgment issues like risk assessment, the consideration of particular culture and environment could help enhance the precision of assessments, especially in assessing control risk factors.

  15. A study on factors influencing customer satisfaction: A case study of hospital dialysis patients

    Directory of Open Access Journals (Sweden)

    Zahra Jamalizadeh

    2013-10-01

    Full Text Available Quality of services is considered as one of the most important factors for customer retention as well as having a healthy business. In this paper, we present an empirical investigation to determine the most important factors influencing patients’ satisfaction in one of Iranian hospitals. The proposed model of this paper uses fuzzy analytical network process (FANP to rank different factors. The proposed model considers four major criteria including employee, management as well as organization, physicians and nurses. Our survey indicates that management and organizational issues are the most important factors followed by issues associated with physicians, nurses and employees. In terms of management and organization, waiting time to receive services is the most important factor followed by geographic location of the hospital, peaceful and quiet environment and quality of services. In addition, our surveyed patients expected their patients to listen to them very carefully and this is the most important item. They also expect nurses to provide a fast and reliable response while they expect employees to treat them with respect.

  16. Factors Affecting the Attractiveness of Medical Tourism Destination: An Empirical Study on India- Review Article

    Science.gov (United States)

    SULTANA, Seyama; HAQUE, Ahasanul; MOMEN, Abdul; YASMIN, Farzana

    2014-01-01

    Abstract Background In this edge, medical tourism is not a new idea. Medical treatment is one of the essential demands of human beings and it requires high quality and intensive care. Beside western world, few developing countries are playing key roles as medical tourism destinations. India is one of the leading names among these countries. The purpose of the paper is to find the factors influencing the attractiveness of India as a health tourism destination. Methods The study has found the major contributing factors and their relative importance in the attractiveness of the health tourism destination that is India from consumers’ perspectives by conducting survey with an application of structural equation modelling approach. Results In Indian context, medical tourists consider service quality and cost mostly to select any medical destination. In addition they also give value to the destination competitiveness but tourist attitude is less important in comparison with other factors affecting their destination choice. Since the study has used structural equation modelling approach to test the hypothesis and figure out the relative importance of the factors, the fundamental indices such as Normed Chi square(less than 3), RMSEA (less than 0.08) and CFI (more than 0.90) values show the overall model fit of the proposed model. Conclusion In order to transform a country such as India as an attractive and competitive medical tourist destination in this time of globalization, a step should be taken to control cost ensuring the quality of services. PMID:25909055

  17. Factors affecting the attractiveness of medical tourism destination: an empirical study on India- review article.

    Science.gov (United States)

    Sultana, Seyama; Haque, Ahasanul; Momen, Abdul; Yasmin, Farzana

    2014-07-01

    In this edge, medical tourism is not a new idea. Medical treatment is one of the essential demands of human beings and it requires high quality and intensive care. Beside western world, few developing countries are playing key roles as medical tourism destinations. India is one of the leading names among these countries. The purpose of the paper is to find the factors influencing the attractiveness of India as a health tourism destination. The study has found the major contributing factors and their relative importance in the attractiveness of the health tourism destination that is India from consumers' perspectives by conducting survey with an application of structural equation modelling approach. In Indian context, medical tourists consider service quality and cost mostly to select any medical destination. In addition they also give value to the destination competitiveness but tourist attitude is less important in comparison with other factors affecting their destination choice. Since the study has used structural equation modelling approach to test the hypothesis and figure out the relative importance of the factors, the fundamental indices such as Normed Chi square(less than 3), RMSEA (less than 0.08) and CFI (more than 0.90) values show the overall model fit of the proposed model. In order to transform a country such as India as an attractive and competitive medical tourist destination in this time of globalization, a step should be taken to control cost ensuring the quality of services.

  18. Influencing Factors and Simplified Model of Film Hole Irrigation

    Directory of Open Access Journals (Sweden)

    Yi-Bo Li

    2017-07-01

    Full Text Available Film hole irrigation is an advanced low-cost and high-efficiency irrigation method, which can improve water conservation and water use efficiency. Given its various advantages and potential applications, we conducted a laboratory study to investigate the effects of soil texture, bulk density, initial soil moisture, irrigation depth, opening ratio (ρ, film hole diameter (D, and spacing on cumulative infiltration using SWMS-2D. We then proposed a simplified model based on the Kostiakov model for infiltration estimation. Error analyses indicated SWMS-2D to be suitable for infiltration simulation of film hole irrigation. Additional SWMS-2D-based investigations indicated that, for a certain soil, initial soil moisture and irrigation depth had the weakest effects on cumulative infiltration, whereas ρ and D had the strongest effects on cumulative infiltration. A simplified model with ρ and D was further established, and its use was then expanded to different soils. Verification based on seven soil types indicated that the established simplified double-factor model effectively estimates cumulative infiltration for film hole irrigation, with a small mean average error of 0.141–2.299 mm, a root mean square error of 0.177–2.722 mm, a percent bias of −2.131–1.479%, and a large Nash–Sutcliffe coefficient that is close to 1.0.

  19. Multiple Statistical Models Based Analysis of Causative Factors and Loess Landslides in Tianshui City, China

    Science.gov (United States)

    Su, Xing; Meng, Xingmin; Ye, Weilin; Wu, Weijiang; Liu, Xingrong; Wei, Wanhong

    2018-03-01

    Tianshui City is one of the mountainous cities that are threatened by severe geo-hazards in Gansu Province, China. Statistical probability models have been widely used in analyzing and evaluating geo-hazards such as landslide. In this research, three approaches (Certainty Factor Method, Weight of Evidence Method and Information Quantity Method) were adopted to quantitively analyze the relationship between the causative factors and the landslides, respectively. The source data used in this study are including the SRTM DEM and local geological maps in the scale of 1:200,000. 12 causative factors (i.e., altitude, slope, aspect, curvature, plan curvature, profile curvature, roughness, relief amplitude, and distance to rivers, distance to faults, distance to roads, and the stratum lithology) were selected to do correlation analysis after thorough investigation of geological conditions and historical landslides. The results indicate that the outcomes of the three models are fairly consistent.

  20. Factors Influencing Smallholder Farmers' Climate Change Perceptions: A Study from Farmers in Ethiopia.

    Science.gov (United States)

    Habtemariam, Lemlem Teklegiorgis; Gandorfer, Markus; Kassa, Getachew Abate; Heissenhuber, Alois

    2016-08-01

    Factors influencing climate change perceptions have vital roles in designing strategies to enrich climate change understanding. Despite this, factors that influence smallholder farmers' climate change perceptions have not yet been adequately studied. As many of the smallholder farmers live in regions where climate change is predicted to have the most negative impact, their climate change perception is of particular interest. In this study, based on data collected from Ethiopian smallholder farmers, we assessed farmers' perceptions and anticipations of past and future climate change. Furthermore, the factors influencing farmers' climate change perceptions and the relation between farmers' perceptions and available public climate information were assessed. Our findings revealed that a majority of respondents perceive warming temperatures and decreasing rainfall trends that correspond with the local meteorological record. Farmers' perceptions about the past climate did not always reflect their anticipations about the future. A substantial number of farmers' anticipations of future climate were less consistent with climate model projections. The recursive bivariate probit models employed to explore factors affecting different categories of climate change perceptions illustrate statistical significance for explanatory variables including location, gender, age, education, soil fertility status, climate change information, and access to credit services. The findings contribute to the literature by providing evidence not just on farmers' past climate perceptions but also on future climate anticipations. The identified factors help policy makers to provide targeted extension and advisory services to enrich climate change understanding and support appropriate farm-level climate change adaptations.

  1. Factors Influencing Smallholder Farmers' Climate Change Perceptions: A Study from Farmers in Ethiopia

    Science.gov (United States)

    Habtemariam, Lemlem Teklegiorgis; Gandorfer, Markus; Kassa, Getachew Abate; Heissenhuber, Alois

    2016-08-01

    Factors influencing climate change perceptions have vital roles in designing strategies to enrich climate change understanding. Despite this, factors that influence smallholder farmers' climate change perceptions have not yet been adequately studied. As many of the smallholder farmers live in regions where climate change is predicted to have the most negative impact, their climate change perception is of particular interest. In this study, based on data collected from Ethiopian smallholder farmers, we assessed farmers' perceptions and anticipations of past and future climate change. Furthermore, the factors influencing farmers' climate change perceptions and the relation between farmers' perceptions and available public climate information were assessed. Our findings revealed that a majority of respondents perceive warming temperatures and decreasing rainfall trends that correspond with the local meteorological record. Farmers' perceptions about the past climate did not always reflect their anticipations about the future. A substantial number of farmers' anticipations of future climate were less consistent with climate model projections. The recursive bivariate probit models employed to explore factors affecting different categories of climate change perceptions illustrate statistical significance for explanatory variables including location, gender, age, education, soil fertility status, climate change information, and access to credit services. The findings contribute to the literature by providing evidence not just on farmers' past climate perceptions but also on future climate anticipations. The identified factors help policy makers to provide targeted extension and advisory services to enrich climate change understanding and support appropriate farm-level climate change adaptations.

  2. Examining the Factors Affecting PDA Acceptance among Physicians: An Extended Technology Acceptance Model.

    Science.gov (United States)

    Basak, Ecem; Gumussoy, Cigdem Altin; Calisir, Fethi

    2015-01-01

    This study aims at identifying the factors affecting the intention to use personal digital assistant (PDA) technology among physicians in Turkey using an extended Technology Acceptance Model (TAM). A structural equation-modeling approach was used to identify the variables that significantly affect the intention to use PDA technology. The data were collected from 339 physicians in Turkey. Results indicated that 71% of the physicians' intention to use PDA technology is explained by perceived usefulness and perceived ease of use. On comparing both, the perceived ease of use has the strongest effect, whereas the effect of perceived enjoyment on behavioral intention to use is found to be insignificant. This study concludes with the recommendations for managers and possible future research.

  3. The Influence On Factors In Attitudes Toward Acceptance Of The Information System Using Technology Acceptance Model TAM Case Study SPAN System In Indonesia

    Directory of Open Access Journals (Sweden)

    Donny Maha Putra

    2015-08-01

    Full Text Available Theoretically and practically Technology Acceptance Model TAM is a model that is considered most appropriate in explaining how the user receives a system. This study aimed to analyze the factors that influence the attitudes towards the acceptance of Sistem Perbendaharaan Anggaran Negara SPAN using TAM approach. The problems raised in this research aims to determine the attitude of the use of the transition process lagecy system to the new system which for many users create conflict in the process of adaptation. On the basis of this proposed theoretical models to test hypotheses using Structural Equation Model SEM and analysis tool using lisrel. This research was conducted in all offices DG of Treasury of Ministry of Finance with 210 respondents were chosen at random to represent each office. The results of this study prove 4 hypothesis is accepted from 8 hypothesis namely a a negative affect with the results demonstrabilty b computer self-efficacy with the output quality c computer self-efficacy with the perceived ease of use d perceived ease of use with the perceived of usefulness. Overall indicates that the application of the SPAN system in the Ministry of Finance of In Indonesia can be accepted by users.

  4. A comparison of the VAR model and the PC factor model in forecasting inflation in Montenegro

    Directory of Open Access Journals (Sweden)

    Lipovina-Božović Milena

    2013-01-01

    Full Text Available Montenegro started using the euro in 2002 and regained independence in 2006. Its main economic partners are European countries, yet inflation movements in Montenegro do not coincide with consumer price fluctuations in the eurozone. Trying to develop a useful forecasting model for Montenegrin inflation, we compare the results of a three-variable vector autoregression (VAR model, and a principle component (PC factor model starting with twelve variables. The estimation period is January 2001 to December 2012, and the control months are the first six months of 2013. The results show that in forecasting inflation, despite a high level of Montenegrin economic dependence on international developments, more reliable forecasts are achieved with the use of additional information on a larger number of factors, which includes domestic economic activity.

  5. A characteristic study of CCF modeling techniques and optimization of CCF defense strategies

    International Nuclear Information System (INIS)

    Kim, Min Chull

    2000-02-01

    Common Cause Failures (CCFs ) are among the major contributors to risk and core damage frequency (CDF ) from operating nuclear power plants (NPPs ). Our study on CCF focused on the following aspects : 1) a characteristic study on the CCF modeling techniques and 2) development of the optimal CCF defense strategy. Firstly, the characteristics of CCF modeling techniques were studied through sensitivity study of CCF occurrence probability upon system redundancy. The modeling techniques considered in this study include those most widely used worldwide, i.e., beta factor, MGL, alpha factor, and binomial failure rate models. We found that MGL and alpha factor models are essentially identical in terms of the CCF probability. Secondly, in the study for CCF defense, the various methods identified in the previous studies for defending against CCF were classified into five different categories. Based on these categories, we developed a generic method by which the optimal CCF defense strategy can be selected. The method is not only qualitative but also quantitative in nature: the selection of the optimal strategy among candidates is based on the use of analytic hierarchical process (AHP). We applied this method to two motor-driven valves for containment sump isolation in Ulchin 3 and 4 nuclear power plants. The result indicates that the method for developing an optimal CCF defense strategy is effective

  6. Rotation in the Dynamic Factor Modeling of Multivariate Stationary Time Series.

    Science.gov (United States)

    Molenaar, Peter C. M.; Nesselroade, John R.

    2001-01-01

    Proposes a special rotation procedure for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of a q-variate latent factor series and transforms such a component, initially represented as white noise, into a univariate moving-average.…

  7. Measurement Invariance and the Five-Factor Model of Personality: Asian International and Euro American Cultural Groups.

    Science.gov (United States)

    Rollock, David; Lui, P Priscilla

    2016-10-01

    This study examined measurement invariance of the NEO Five-Factor Inventory (NEO-FFI), assessing the five-factor model (FFM) of personality among Euro American (N = 290) and Asian international (N = 301) students (47.8% women, Mage = 19.69 years). The full 60-item NEO-FFI data fit the expected five-factor structure for both groups using exploratory structural equation modeling, and achieved configural invariance. Only 37 items significantly loaded onto the FFM-theorized factors for both groups and demonstrated metric invariance. Threshold invariance was not supported with this reduced item set. Groups differed the most in the item-factor relationships for Extraversion and Agreeableness, as well as in response styles. Asian internationals were more likely to use midpoint responses than Euro Americans. While the FFM can characterize broad nomothetic patterns of personality traits, metric invariance with only the subset of NEO-FFI items identified limits direct group comparisons of correlation coefficients among personality domains and with other constructs, and of mean differences on personality domains. © The Author(s) 2015.

  8. Organizational and psychosocial risk factors for carpal tunnel syndrome: a cross-sectional study of French workers.

    Science.gov (United States)

    Rigouin, Pascal; Ha, Catherine; Bodin, Julie; Le Manac'h, Audrey Petit; Descatha, Alexis; Goldberg, Marcel; Roquelaure, Yves

    2014-02-01

    The aim of the study was to examine the organizational and psychosocial risk factors for carpal tunnel syndrome (CTS) in workers exposed to various levels of work-related constraints, with a special focus on factors related to the work organization. From 3,710 workers, representative of a French region's working population, trained occupational physicians diagnosed a total of 156 cases of CTS between 2002 and 2005. Diagnoses were established by standardized physical examination, while personal factors and work exposure were assessed by self-administered questionnaires. Statistical associations between CTS and personal and work-related factors were analyzed for each gender using logistic regression modeling. Among the factors related to work organization, working with temporary workers was associated with CTS for women (OR = 1.99, 95 % CI 1.23-3.25), but not for men. Task rotation during the job (OR = 2.45 95 % CI 1.41-4.24) and work pace dependent on quantified targets (OR = 1.93 95 % CI 1.08-3.46) were associated with CTS only for men. The work-related psychosocial factors highlighted by the logistic modeling were high psychological demand for women (OR = 1.90, 95 % CI 1.17-3.09) and low skill discretion (OR = 1.77, 95 % CI 1.01-3.11) for men. This study has identified some psychosocial factors and factors related to work organization associated with clinically diagnosed and symptom-only cases of CTS as well as personal and biomechanical factors. However, due to the cross-sectional design of the study, no causal conclusion could be drawn and longitudinal studies are necessary to confirm these results.

  9. ACSNI study group on human factors

    International Nuclear Information System (INIS)

    1993-01-01

    Organisational failures are now recognised as being as important as mechanical failures or individual human errors in causing major accidents such as the capsize of the Herald of Free Enterprise or the Pipa Alpha disaster. The Human Factors Study Group of the Advisory Committee on the Safety of Nuclear Installations was set up to look at the part played by human factors in nuclear risk and its reduction. The third report of the Study Group considers the role played by organisational factors and management in promoting nuclear safety. Actions to review and promote a safety culture are suggested. Three main conclusions are drawn and several recommendations made. (UK)

  10. Risk and protective factors for psychological distress among adolescents: a family study in the Nord-Trøndelag Health Study.

    Science.gov (United States)

    Myklestad, Ingri; Røysamb, Espen; Tambs, Kristian

    2012-05-01

    The study aimed to investigate potential adolescent and parental psychosocial risk and protective factors for psychological distress among adolescents and, in addition, to examine potential gender and age differences in the effects of risk factors on adolescent psychological distress. Data were collected among 8,984 Norwegian adolescents (13-19 years) and their parents in the Nord-Trøndelag Health Study (HUNT). The outcome measure was psychological distress (SCL-5). Bivariate regression analysis with generalized estimating equation (GEE) model showed that all parental self-reported variables (mental distress, substance use, social network, economic problems, unemployment and family structure) and adolescents' self-reported variables (leisure activities, social support from friends, school-related problems and substance use) were significantly associated with psychological distress among adolescents. Results revealed that in a multiple regression analysis with a GEE model, adolescent psychosocial variables, specifically academic-related problems and being bullied at school, emerged as the strongest predictors of psychological distress among adolescents after controlling for age, gender, and all parental and adolescent variables. The following psychosocial risk factors were significantly more important for girl's psychological distress compared to boys: problems with academic achievement, conduct problems in school, frequency of being drunk, smoking, dissatisfaction in school, living alone and seen parents being drunk. Academic achievement and being bullied at school were the psychosocial factors most strongly associated with psychological distress among adolescents. Parental factors had an indirect effect on adolescent psychological distress, through adolescents' psychosocial factors.

  11. A study on the effects of sales related factors on brand equity

    Directory of Open Access Journals (Sweden)

    Naser Azad

    2014-07-01

    Full Text Available This paper presents an empirical investigation to study the effects of sales related factors on brand equity. The study designs a questionnaire and distributes it among all 353 sales representatives who work for a dairy producer in province of Mazandaran, Iran. Using principal component analysis, seven variables including qualification criteria, motivation, personality, empowering sales representative, information size, personal characteristics and sales interest in job on brand equity are extracted. The implementation of structural equation modeling has confirmed that there were positive and meaningful relationships between seven factors and brand equity. The highest impact belongs to empowering sales representative followed by qualification criteria, quantity of information, personality and sales motivation.

  12. Factors influencing the satisfaction of rural physician assistants: a cross-sectional study.

    Science.gov (United States)

    Filipova, Anna A

    2014-01-01

    The purpose of the study was to determine factors that attract physician assistants (PAs) to rural settings, and what they found satisfying about their practice and community. A cross-sectional survey design was used. All PAs who were practicing in both nonmetropolitan counties and rural communities in metropolitan counties, in a single midwestern US state, served as the population for the study. A total of 414 usable questionnaires were returned of the 1,072 distributed, a 39% response rate. Factor analysis, descriptive statistics, Pearson's correlation analysis, and robust regression analyses were used. Statistical models were tested to identify antecedents of four job satisfaction factors (satisfaction with professional respect, satisfaction with supervising physician, satisfaction with authority/ autonomy, and satisfaction with workload/salary). The strongest predictor of all four job satisfaction factors was community satisfaction, followed by importance of job practice. Additionally, the four job satisfaction factors had some significant associations with importance of socialization, community importance, practice attributes (years of practice, years in current location, specialty, and facility type), job responsibilities (percentage of patient load not discussed with physician, weekly hours as PA, inpatient visits), and demographics (marital status, race, age, education).

  13. Structural equation modeling analysis of factors influencing architects' trust in project design teams

    Institute of Scientific and Technical Information of China (English)

    DING Zhi-kun; NG Fung-fai; WANG Jia-yuan

    2009-01-01

    This paper describes a structural equation modeling (SEM) analysis of factors influencing architects' trust in project design teams. We undertook a survey of architects, during which we distributed 193 questionnaires in 29 A-level architectural We used Amos 6.0 for SEM to identify significant personal construct based factors affecting interpersonal trust. The results show that only social interaction between architects significantly affects their interpersonal trust. The explained variance of trust is not very high in the model. Therefore, future research should add more factors into the current model. The practical implication is that team managers should promote the social interactions between team members such that the interpersonal trust level between team members can be improved.

  14. A study on influencing factors on brand loyalty: A case study of Mobile industry

    Directory of Open Access Journals (Sweden)

    Bahman Dehestani

    2013-07-01

    Full Text Available Brand loyalty plays essential role on product development especially in mobile industry. In this paper, we present an empirical survey to study the effects of different factors including brand associate, brand awareness, distribution intensity and quality perception on brand loyalty. The proposed model of this paper is examined by designing a questionnaire consists of 16 questions in Likert scale and distributing it among 200 people who use a particular brand in mobile industry called Nokia. The results are analyzed using structural equation modeling where Cronbach alpha is calculated as 0.84. The results indicate that there is a positive relationship between perception quality as well as brand awareness and brand loyalty. In addition, there is a positive relationship between brand awareness and perception quality.

  15. Linear model analysis of the influencing factors of boar longevity in Southern China.

    Science.gov (United States)

    Wang, Chao; Li, Jia-Lian; Wei, Hong-Kui; Zhou, Yuan-Fei; Jiang, Si-Wen; Peng, Jian

    2017-04-15

    This study aimed to investigate the factors influencing the boar herd life month (BHLM) in Southern China. A total of 1630 records of culling boars from nine artificial insemination centers were collected from January 2013 to May 2016. A logistic regression model and two linear models were used to analyze the effects of breed, housing type, age at herd entry, and seed stock herd on boar removal reason and BHLM, respectively. Boar breed and the age at herd entry had significant effects on the removal reasons (P linear models (with or without removal reason including) showed boars raised individually in stalls exhibited shorter BHLM than those raised in pens (P introduction. Copyright © 2017. Published by Elsevier Inc.

  16. Influencing Factors and Consequences of Workplace Bullying among Nurses: A Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Seonyoung Yun, PhD, RN

    2018-03-01

    Full Text Available Purpose: The purpose of this study was to build and test a model outlining the factors related to workplace bullying among nurses. The hypothesized model included authentic leadership and a relationship-oriented organizational culture as influencing factors, symptom experience and turnover intention as consequences, and positive psychological capital as a mediator of workplace bullying among nurses. Methods: We obtained structured questionnaire data from 301 nurses working at hospitals in South Korea. Based on these data, the developed model was verified via a structural equation modeling analysis using SPSS and AMOS program. Results: The fit indices of the hypothesized model satisfied recommended levels; χ2 = 397.58 (p < .001, normed χ2 (χ2/df = 1.82, RMR = .05, TLI = .93, CFI = .94, RMSEA = .05. A relationship-oriented organizational culture had a direct effect on workplace bullying (β = −.48, p < .001. Furthermore, workplace bullying had a direct effect on symptom experience (β = .36, p < .001, and this relationship was mediated by positive psychological capital (β = .15, p = .003. Workplace bullying also had an indirect effect on turnover intention (β = .20, p = .007. Finally, symptom experience had a direct effect on turnover intention (β = .31, p = .002. Conclusion: These results suggest that workplace bullying among nurses may be prevented by constructing a relationship-oriented organizational culture, as long as employees have sufficient positive psychological capital. In this regard, workplace bullying among nurses should be addressed using a comprehensive strategy that considers both individual and organizational factors. Keywords: bullying, leadership, nurses, organizational culture, personnel turnover

  17. Success and failure factors in the regional health information system design process--results from a constructive evaluation study.

    Science.gov (United States)

    Nykänen, P; Karimaa, E

    2006-01-01

    To identify success and failure factors in the design process of a regional health information system. A constructive evaluation study including interviews, observations, usability study and document analysis. Modelling was found to be a key element for the successful implementation of a health information system. The developed service chain model helped to define use cases and to implement seamless service chains. User participation in the design process was a success factor resulting in good user acceptance and signs of positive impacts on work practices. Evaluation study also helped system developers to guide the system's further development. An important failure factor identified was the lack of semantic interoperability of the system components. The results emphasize the socio-technical nature of health information systems. The starting point for development should be thorough insight into the health care work practices where the information systems are to be used. Successful system design should start from modelling of work processes, data and information flows and definition of concepts and their relations. Health informatics as a scientific discipline provides theories and models for the design and development process.

  18. A Study of E-services Adoption Factors

    DEFF Research Database (Denmark)

    Scupola, Ada; Nicolajsen, Hanne Westh

    2011-01-01

    University Library (RUB). The conclusion of this research is that both external environmental factors and internal organizational factors are important factors in adoption of e-services at Roskilde University Library. However the study shows that external factors such as government intervention...... and technological development might have been having a more important role than other external factors and that top management might have more influence on radical e-services adoption than other factors in the organizational context....

  19. A confirmatory factor analytic study of a self-leadership measure in South Africa

    Directory of Open Access Journals (Sweden)

    Bright Mahembe

    2013-07-01

    Full Text Available Orientation: Self-leadership is considered to be essential for effective individual functioning in occupational and academic contexts. The revised self-leadership questionnaire (RSLQ is widely utilised for measuring self-leadership, but its psychometric properties have not been established on a South African sample. By implication, important questions also exist about the theoretical structure of self-leadership in the South African context. Research purpose: The research aim of this study was to investigate the reliability and factorial validity of the revised self-leadership questionnaire on a South African sample. In doing so, the results of the research would also provide valuable insights into the latent factor structure of the self-leadership construct. Motivation for the study: On a practical level, the research sought internal validity evidence for the use of the RSLQ in the South African context. On a theoretical level, questions remain about the best conceptual representation of self-leadership as a construct. Research design, approach and method: The revised self-leadership questionnaire was administered to a non-probability sample of 375 South African young adults. The first and second-order factor structure underlying contemporary models of self-leadership using confirmatory factor analytic techniques was tested. Main findings: Results showed that the RSLQ measured self-leadership with suitable reliability and internal validity. All eight subscales had high internal consistency coefficients. Confirmatory factor analysis (CFA of the first and second-order models conclusively demonstrated good factorial validity. Practical/managerial implications: The study found that the RSLQ has good measurement properties for a South African context. Academics, practitioners and managers are urged to use the measure in its present form for applications such as leadership development and promoting self-management. Contribution/value-addition: The

  20. Child maltreatment in the "children of the nineties" a longitudinal study of parental risk factors.

    Science.gov (United States)

    Sidebotham, P; Golding, J

    2001-09-01

    To identify and validate factors within the parental background affecting risk of child maltreatment. A nested case-control study based on the Avon Longitudinal Study of Parents and Children ("Children of the Nineties"), a cohort of children born in Avon in 1991 through 1992. Data on the childhood and psychiatric histories of the parents, along with other data on the social and family environments, have been collected through postal questionnaires from early antenatal booking onwards. Out of 14,138 participating children, 162 have been identified as having been maltreated. Using logistic regression analysis, significant risk factors within the mothers' backgrounds were age factors in the fathers' backgrounds were age factors on univariate, but not multivariate analysis included a parental history of childhood physical abuse; divorce or separation of the mother's parents; a maternal history of having been in care, or separated from her mother; parental alcohol or drug abuse; and a maternal history of depression. This study, the first of its kind in the UK, supports the findings of others that parental age, educational achievement, and a history of psychiatric illness are of prime importance in an understanding of child maltreatment. With the exception of maternal sexual abuse, a history of abuse in childhood is not significant once adjusted for other background factors. The study suggests that psychodynamic models are inadequate to explain child maltreatment, and wider models incorporating other ecological domains are needed.

  1. Studies of atmospheric pollutants concentration factors from La Reina reactor

    International Nuclear Information System (INIS)

    Vera, I.; Alegria, E.

    1983-01-01

    Results of an atmospheric diffusion model for pollutant gases re shown, in which the nuclear reactor of the La Reina Nuclear Centre is considered as the emitting source. The model uses a gaussian shape steady state cloud of concentration of pollutants and actual topographical and meteorological statistics data os the zone. Expected and maximum probable concentration factors are computed in a polar lattice in 16 wind directions. It was found that peaks for expected concentration factors and maximum probable concentration factors at ground level fall within the N and ESE directions at distances where hills or mountains reach the emitted cloud. A discussion of the practical value of these calculations is given. (Author)

  2. Studies of atmospheric pollutants concentration factors from La Reina reactor

    Energy Technology Data Exchange (ETDEWEB)

    Vera, I; Alegria, E [Comision Chilena de Energia Nuclear, Santiago. Div. de Seguridade Nuclear y Radioproteccion

    1983-11-01

    Results of an atmospheric diffusion model for pollutant gases are shown, in which the nuclear reactor of the La Reina Nuclear Centre is considered as the emitting source. The model uses a gaussian shape steady state cloud of concentration of pollutants and actual topographical and meteorological statistics data of the zone. Expected and maximum probable concentration factors are computed in a polar lattice in 16 wind directions. It was found that peaks for expected concentration factors and maximum probable concentration factors at ground level fall within the N and ESE directions at distances where hills or mountains reach the emitted cloud. A discussion of the practical value of these calculations is given.

  3. Modeling the potential risk factors of bovine viral diarrhea prevalence in Egypt using univariable and multivariable logistic regression analyses

    Directory of Open Access Journals (Sweden)

    Abdelfattah M. Selim

    2018-03-01

    Full Text Available Aim: The present cross-sectional study was conducted to determine the seroprevalence and potential risk factors associated with Bovine viral diarrhea virus (BVDV disease in cattle and buffaloes in Egypt, to model the potential risk factors associated with the disease using logistic regression (LR models, and to fit the best predictive model for the current data. Materials and Methods: A total of 740 blood samples were collected within November 2012-March 2013 from animals aged between 6 months and 3 years. The potential risk factors studied were species, age, sex, and herd location. All serum samples were examined with indirect ELIZA test for antibody detection. Data were analyzed with different statistical approaches such as Chi-square test, odds ratios (OR, univariable, and multivariable LR models. Results: Results revealed a non-significant association between being seropositive with BVDV and all risk factors, except for species of animal. Seroprevalence percentages were 40% and 23% for cattle and buffaloes, respectively. OR for all categories were close to one with the highest OR for cattle relative to buffaloes, which was 2.237. Likelihood ratio tests showed a significant drop of the -2LL from univariable LR to multivariable LR models. Conclusion: There was an evidence of high seroprevalence of BVDV among cattle as compared with buffaloes with the possibility of infection in different age groups of animals. In addition, multivariable LR model was proved to provide more information for association and prediction purposes relative to univariable LR models and Chi-square tests if we have more than one predictor.

  4. Bayes factor between Student t and Gaussian mixed models within an animal breeding context

    Directory of Open Access Journals (Sweden)

    García-Cortés Luis

    2008-07-01

    Full Text Available Abstract The implementation of Student t mixed models in animal breeding has been suggested as a useful statistical tool to effectively mute the impact of preferential treatment or other sources of outliers in field data. Nevertheless, these additional sources of variation are undeclared and we do not know whether a Student t mixed model is required or if a standard, and less parameterized, Gaussian mixed model would be sufficient to serve the intended purpose. Within this context, our aim was to develop the Bayes factor between two nested models that only differed in a bounded variable in order to easily compare a Student t and a Gaussian mixed model. It is important to highlight that the Student t density converges to a Gaussian process when degrees of freedom tend to infinity. The twomodels can then be viewed as nested models that differ in terms of degrees of freedom. The Bayes factor can be easily calculated from the output of a Markov chain Monte Carlo sampling of the complex model (Student t mixed model. The performance of this Bayes factor was tested under simulation and on a real dataset, using the deviation information criterion (DIC as the standard reference criterion. The two statistical tools showed similar trends along the parameter space, although the Bayes factor appeared to be the more conservative. There was considerable evidence favoring the Student t mixed model for data sets simulated under Student t processes with limited degrees of freedom, and moderate advantages associated with using the Gaussian mixed model when working with datasets simulated with 50 or more degrees of freedom. For the analysis of real data (weight of Pietrain pigs at six months, both the Bayes factor and DIC slightly favored the Student t mixed model, with there being a reduced incidence of outlier individuals in this population.

  5. How Do Various Maize Crop Models Vary in Their Responses to Climate Change Factors?

    Science.gov (United States)

    Bassu, Simona; Brisson, Nadine; Grassini, Patricio; Durand, Jean-Louis; Boote, Kenneth; Lizaso, Jon; Jones, James W.; Rosenzweig, Cynthia; Ruane, Alex C.; Adam, Myriam; hide

    2014-01-01

    Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(sup 1) per degC. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

  6. Factors Contributing to Research Team Effectiveness: Testing a Model of Team Effectiveness in an Academic Setting

    Science.gov (United States)

    Omar, Zoharah; Ahmad, Aminah

    2014-01-01

    Following the classic systems model of inputs, processes, and outputs, this study examined the influence of three input factors, team climate, work overload, and team leadership, on research project team effectiveness as measured by publication productivity, team member satisfaction, and job frustration. This study also examined the mediating…

  7. Emotional intelligence is a second-stratum factor of intelligence: evidence from hierarchical and bifactor models.

    Science.gov (United States)

    MacCann, Carolyn; Joseph, Dana L; Newman, Daniel A; Roberts, Richard D

    2014-04-01

    This article examines the status of emotional intelligence (EI) within the structure of human cognitive abilities. To evaluate whether EI is a 2nd-stratum factor of intelligence, data were fit to a series of structural models involving 3 indicators each for fluid intelligence, crystallized intelligence, quantitative reasoning, visual processing, and broad retrieval ability, as well as 2 indicators each for emotion perception, emotion understanding, and emotion management. Unidimensional, multidimensional, hierarchical, and bifactor solutions were estimated in a sample of 688 college and community college students. Results suggest adequate fit for 2 models: (a) an oblique 8-factor model (with 5 traditional cognitive ability factors and 3 EI factors) and (b) a hierarchical solution (with cognitive g at the highest level and EI representing a 2nd-stratum factor that loads onto g at λ = .80). The acceptable relative fit of the hierarchical model confirms the notion that EI is a group factor of cognitive ability, marking the expression of intelligence in the emotion domain. The discussion proposes a possible expansion of Cattell-Horn-Carroll theory to include EI as a 2nd-stratum factor of similar standing to factors such as fluid intelligence and visual processing.

  8. Retrospective cohort study of prognostic factors in patients with oral cavity and oropharyngeal squamous cell carcinoma.

    Science.gov (United States)

    Carrillo, José F; Carrillo, Liliana C; Cano, Ana; Ramirez-Ortega, Margarita C; Chanona, Jorge G; Avilés, Alejandro; Herrera-Goepfert, Roberto; Corona-Rivera, Jaime; Ochoa-Carrillo, Francisco J; Oñate-Ocaña, Luis F

    2016-04-01

    Prognostic factors in oral cavity and oropharyngeal squamous cell carcinoma (SCC) are debated. The purpose of this study was to investigate the association of prognostic factors with oncologic outcomes. Patients with oral cavity and oropharyngeal SCC treated from 1997 to 2012 were included in this retrospective cohort study. Associations of prognostic factors with locoregional recurrence (LRR) or overall survival (OS) were analyzed using the logistic regression and the Cox models. Six hundred thirty-four patients were included in this study; tumor size, surgical margins, and N classification were associated with LRR (p oral cavity and oropharyngeal SCC. © 2015 Wiley Periodicals, Inc.

  9. What Factors Lead Companies to Adopt Social Media in their processes: Proposal and Test of a Measurement Model

    Directory of Open Access Journals (Sweden)

    Jozé Braz de Araújo

    2016-01-01

    Full Text Available The objective of this study was to understand which factors lead companies to use social media to achieve results. For that, a theoretical model was proposed and tested. Data was collected using a survey of 237 companies. In the analysis we analysis used the structural eq uation modeling technique. The results show that the social media relative advantage and its observability were important factors to social media organizational adoption. We also found that big companies with more formalized organizational structure (OS t end to adopt social media more than small ones with no formal OS. The companies studied showed strong organizational disposition for innovation adoption.

  10. Parental Expression of Disappointment: Should It Be a Factor in Hoffman's Model of Parental Discipline?

    Science.gov (United States)

    Patrick, Renee B.; Gibbs, John C.

    2007-01-01

    The authors addressed whether parental expression of disappointment should be included as a distinct factor in M. L. Hoffman's (2000) well-established typology of parenting styles (induction, love withdrawal, power assertion). Hoffman's 3-factor model, along with a more inclusive 4-factor model (induction, love withdrawal, power assertion, and…

  11. Loneliness and solitude in adolescence: A confirmatory factor analysis of alternative models

    DEFF Research Database (Denmark)

    Goossens, Luc; Lasgaard, Mathias; Luyckx, Koen

    2009-01-01

    completed by a sample of mid-adolescents (N = 534) from Grades 10 through 12 (aged 15-18 years) in the Dutch-speaking part of Belgium. As expected, the four-factor solution provided a better fit to the data than did alternative models that comprised just a single factor, or two and three factors. Use...

  12. A review of the models for evaluating organizational factors in human reliability analysis

    International Nuclear Information System (INIS)

    Alvarenga, Marco Antonio Bayout; Fonseca, Renato Alves da; Melo, Paulo Fernando Ferreira Frutuoso e

    2009-01-01

    Human factors should be evaluated in three hierarchical levels. The first level should concern the cognitive behavior of human beings during the control of processes that occur through the man-machine interface. Here, one evaluates human errors through human reliability models of first and second generation, like THERP, ASEP and HCR (first generation) and ATHEANA and CREAM (second generation). In the second level, the focus is in the cognitive behavior of human beings when they work in groups, as in nuclear power plants. The focus here is in the anthropological aspects that govern the interaction among human beings. In the third level, one is interested in the influence that the organizational culture exerts on human beings as well as on the tasks being performed. Here, one adds to the factors of the second level the economical and political aspects that shape the company organizational culture. Nowadays, the methodologies of HRA incorporate organizational factors in the group and organization levels through performance shaping factors. This work makes a critical evaluation of the deficiencies concerning human factors and evaluates the potential of quantitative techniques that have been proposed in the last decade to model organizational factors, including the interaction among groups, with the intention of eliminating this chronic deficiency of HRA models. Two important techniques will be discussed in this context: STAMP, based on system theory and FRAM, which aims at modeling the nonlinearities of socio-technical systems. (author)

  13. A review of the models for evaluating organizational factors in human reliability analysis

    Energy Technology Data Exchange (ETDEWEB)

    Alvarenga, Marco Antonio Bayout; Fonseca, Renato Alves da [Comissao Nacional de Energia Nuclear (CNEN), Rio de Janeiro, RJ (Brazil)], e-mail: bayout@cnen.gov.br, e-mail: rfonseca@cnen.gov.br; Melo, Paulo Fernando Ferreira Frutuoso e [Coordenacao dos Programas de Pos-graduacao de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear], e-mail: frutuoso@con.ufrj.br

    2009-07-01

    Human factors should be evaluated in three hierarchical levels. The first level should concern the cognitive behavior of human beings during the control of processes that occur through the man-machine interface. Here, one evaluates human errors through human reliability models of first and second generation, like THERP, ASEP and HCR (first generation) and ATHEANA and CREAM (second generation). In the second level, the focus is in the cognitive behavior of human beings when they work in groups, as in nuclear power plants. The focus here is in the anthropological aspects that govern the interaction among human beings. In the third level, one is interested in the influence that the organizational culture exerts on human beings as well as on the tasks being performed. Here, one adds to the factors of the second level the economical and political aspects that shape the company organizational culture. Nowadays, the methodologies of HRA incorporate organizational factors in the group and organization levels through performance shaping factors. This work makes a critical evaluation of the deficiencies concerning human factors and evaluates the potential of quantitative techniques that have been proposed in the last decade to model organizational factors, including the interaction among groups, with the intention of eliminating this chronic deficiency of HRA models. Two important techniques will be discussed in this context: STAMP, based on system theory and FRAM, which aims at modeling the nonlinearities of socio-technical systems. (author)

  14. The Investigate Factors on Screening of the Breast Cancer Based on PEN-3 Model in Iranian Northern Women

    Directory of Open Access Journals (Sweden)

    Seyed Abolhassan Naghibi

    2015-09-01

    Materials and Methods: The present study was cross-sectional. The samples studied were women above 20 years and the sample size was 1416 people. The method of sampling was a random cluster. The tools of data collection questionnaire with 70 questions which approved its content validity and reliability. Data were analyzed by using software of SPSS Ver. 20. Results: The average age of samples was 35.71±6.1. Only 14.3% of samples are regularly conducted to the self-examination. Also, 38.5% of women had a history of the clinical examination. The difference of observed in performance the breast self-examination and clinical breast examination were the statistical significant by variables of rural or urban (P= 0.005, the marital status (P = 0.013 and a background of having breast cancer (P <0.001. The results of the study based on PEN-3 model were showed that there were a statistical significant relationship between the structure of perceptual factors and reinforcing factors (P=0.002 and between the perceptual factors and enabling factors (P=0.006. Conclusion: According to the results of presented, the women`s performance in using the screening was low. Also, the components status of the PEN-3 Model (factors of perceptual, enabling, and reinforcing for the breast cancer screening in women studied were not suitable.

  15. Development and application of a complex numerical model and software for the computation of dose conversion factors for radon progenies.

    Science.gov (United States)

    Farkas, Árpád; Balásházy, Imre

    2015-04-01

    A more exact determination of dose conversion factors associated with radon progeny inhalation was possible due to the advancements in epidemiological health risk estimates in the last years. The enhancement of computational power and the development of numerical techniques allow computing dose conversion factors with increasing reliability. The objective of this study was to develop an integrated model and software based on a self-developed airway deposition code, an own bronchial dosimetry model and the computational methods accepted by International Commission on Radiological Protection (ICRP) to calculate dose conversion coefficients for different exposure conditions. The model was tested by its application for exposure and breathing conditions characteristic of mines and homes. The dose conversion factors were 8 and 16 mSv WLM(-1) for homes and mines when applying a stochastic deposition model combined with the ICRP dosimetry model (named PM-A model), and 9 and 17 mSv WLM(-1) when applying the same deposition model combined with authors' bronchial dosimetry model and the ICRP bronchiolar and alveolar-interstitial dosimetry model (called PM-B model). User friendly software for the computation of dose conversion factors has also been developed. The software allows one to compute conversion factors for a large range of exposure and breathing parameters and to perform sensitivity analyses. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  16. Modeling Structural, Dyadic, and Individual Factors: The Inclusion and Exclusion Model of HIV Related Behavior

    OpenAIRE

    Albarracin, Dolores; Tannenbaum, Melanie B.; Glasman, Laura R.; Rothman, Alexander J.

    2010-01-01

    Changing HIV-related behaviors requires addressing the individual, dyadic, and structural influences that shape them. This supplement of AIDS & Behavior presents frameworks that integrate these three influences on behavior. Concepts from these frameworks were selected to model the processes by which structural factors affect individual HIV-related behavior. In the Inclusion/Exclusion Model, material and symbolic inclusions and exclusions (sharing versus denying resources) regulate individuals...

  17. Models of Anaylzing the Influence of Factors on Forming Profit Rate

    Directory of Open Access Journals (Sweden)

    Klara S. Jakovčević

    2014-04-01

    Full Text Available The analysis in this paper is focused on identifying the impact of individual factors on the elements of the profit rate. The primary aim of this work is a methodological overview of solutions for understanding the full content of the profit rate as a cause of economic quality as well as indicators of the results of reproduction. Application of model analysis of profit rate factors was performed in an enterprise from Serbia that manufactures construction materials from baked clay. The aim is of application is to test the range in determining elements and factors of economic success of the enterprise, and quantification of changes in its assumptions. The results are useful guideline for the management to take organizational measures to increase the economic success of the enterprise. This means eliminating the negative, emphasizing the positive impact of objectively, and organizational factors to make higher economic success. Based on empirical research, it could be concluded that the proposed quantitative models of analyzing the dynamics of enterprise business quality could be applied in practice.

  18. An empirical and model study on automobile market in Taiwan

    Science.gov (United States)

    Tang, Ji-Ying; Qiu, Rong; Zhou, Yueping; He, Da-Ren

    2006-03-01

    We have done an empirical investigation on automobile market in Taiwan including the development of the possession rate of the companies in the market from 1979 to 2003, the development of the largest possession rate, and so on. A dynamic model for describing the competition between the companies is suggested based on the empirical study. In the model each company is given a long-term competition factor (such as technology, capital and scale) and a short-term competition factor (such as management, service and advertisement). Then the companies play games in order to obtain more possession rate in the market under certain rules. Numerical simulation based on the model display a competition developing process, which qualitatively and quantitatively agree with our empirical investigation results.

  19. A matched case-control study of risk factors for neonatal tetanus in Karachi, Pakistan

    Directory of Open Access Journals (Sweden)

    Raza Syed

    2004-10-01

    Full Text Available Background: Previous studies have identified various risk factors for neonatal tetanus (NNT in rural areas of Pakistan. The present matched case control study was conducted to further evaluate these risk factors in an urban setting. Aim: The study was carried out to identify risk factors for NNT in Karachi. Materials and Methods: Patients of NNT (n = 125 diagnosed from January 1998 to February 2001 were recruited through a surveillance system of Expanded Programme on Immunization (EPI. Two neighbourhood controls (n = 250 were matched for each case for gender and date of birth of the case. Statistical Analysis: Conditional logistic regression was performed to assess the independent effect of factors associated with NNT. Results: The final multivariable model identified subsequent application of substances on the umbilical cord (adjusted matched odds ratio [adj. mOR] = 5.1 [2.7-9.7], home delivery (adj. mOR = 1.8; 95% CI: 1.1- 3.1 and illiterate mother (adj. mOR = 1.6; 95% CI: 1.0- 2.0 as risk factors for NNT after adjusting for other variables in the model. Population attributable risk per cent (PAR % for subsequent cord application was 69% and PAR % for home delivery was 31%. Conclusion: Health planners, while formulating control strategies through immunization programmes should also take into account the impact of post-delivery practices, such as 'subsequent cord application' along with pre-delivery practices. Health awareness regarding appropriate post-delivery practices should be promoted and counselling of pregnant women for giving preference to health care setting for delivery is also crucial.

  20. An Exploratory Study of the Critical Factors Affecting the Acceptability of Automated Teller Machine (ATM) in Nigeria

    OpenAIRE

    Olusegun Folorunso; Oluwafunmilayo Ayobami Ateji; Gabriel Oludare Awe

    2010-01-01

    This paper uses the Technology Acceptance Model (TAM) as a basis for studying critical factors that affects the acceptability of Automated Teller Machine (ATM) in Nigeria. Questionnaire approach was used with the respondents predominantly between 20-29 years old. Factor analysis was used to test which of the factors are the main factors affecting the adoption of the technology in Nigeria. It was discovered that the major factors affecting people’s intention to accept ATM are the security issu...

  1. Analysis of automotive rolling lobe air spring under alternative factors with finite element model

    International Nuclear Information System (INIS)

    Wong, Pak Kin; Xie, Zhengchao; Zhao, Jing; Xu, Tao; He, Feng

    2014-01-01

    Air springs are widely used in automotive suspensions for their superior performance in terms of low friction motion, adjustable load carrying capacity and user-friendly ride height control. However, it has posed great difficulties in constructing an accurate model as well as the analysis of the influence of alternative factors, such as cord angle, cord diameter and initial pressure. In this paper, a numerical model of the rolling lobe air spring (RLAS) is built by using finite element method and compared with an existing analytical model. An experiment with respect to the vertical stiffness of the RLAS is carried out to validate the accuracy of the proposed model. Evaluation result reveals that the existing analytical model cannot represent the performance of the RLAS very well, whereas the accuracy of the numerical model is very good. With the verified numerical model, the impacts of many alternative factors on the characteristics of the RLAS are analyzed. Numerical results show that the newly proposed model is reliable to determine the vertical characteristic and physical dimensions of the RLAS under the alternative factors.

  2. Study of the in-medium nucleon electromagnetic form factors using a light-front nucleon wave function combined with the quark-meson coupling model

    Science.gov (United States)

    de Araújo, W. R. B.; de Melo, J. P. B. C.; Tsushima, K.

    2018-02-01

    We study the nucleon electromagnetic (EM) form factors in symmetric nuclear matter as well as in vacuum within a light-front approach using the in-medium inputs calculated by the quark-meson coupling model. The same in-medium quark properties are used as those used for the study of in-medium pion properties. The zero of the proton EM form factor ratio in vacuum, the electric to magnetic form factor ratio μpGEp (Q2) /GMp (Q2) (Q2 = -q2 > 0 with q being the four-momentum transfer), is determined including the latest experimental data by implementing a hard constituent quark component in the nucleon wave function. A reasonable fit is achieved for the ratio μpGEp (Q2) /GMp (Q2) in vacuum, and we predict that the Q02 value to cross the zero of the ratio to be about 15 GeV2. In addition the double ratio data of the proton EM form factors in 4He and H nuclei, [GEp4He (Q2) /G4HeMp (Q2) ] / [GEp1H (Q2) /GMp1H (Q2) ], extracted by the polarized (e → ,e‧ p →) scattering experiment on 4He at JLab, are well described. We also predict that the Q02 value satisfying μpGEp (Q02) /GMp (Q0 2) = 0 in symmetric nuclear matter, shifts to a smaller value as increasing nuclear matter density, which reflects the facts that the faster falloff of GEp (Q2) as increasing Q2 and the increase of the proton mean-square charge radius. Furthermore, we calculate the neutron EM form factor double ratio in symmetric nuclear matter for 0.1 neutron double ratio is enhanced relative to that in vacuum, while for the proton it is quenched, and agrees with an existing theoretical prediction.

  3. Factors of adoption of mobile information technology by homecare nurses: a technology acceptance model 2 approach.

    Science.gov (United States)

    Zhang, Huiying; Cocosila, Mihail; Archer, Norm

    2010-01-01

    Pervasive healthcare support through mobile information technology solutions is playing an increasing role in the attempt to improve healthcare and reduce costs. Despite the apparent attractiveness, many mobile applications have failed or have not been implemented as predicted. Among factors possibly leading to such outcomes, technology adoption is a key problem. This must be investigated early in the development process because healthcare is a particularly sensitive area with vital social implications. Moreover, it is important to investigate technology acceptance using the support of scientific tools validated for relevant information systems research. This article presents an empirical study based on the Technology Acceptance Model 2 in mobile homecare nursing. The study elicited the perceptions of 91 Canadian nurses who used personal digital assistants for 1 month in their daily activities. A partial least squares modeling data analysis revealed that nurse's perception of usefulness is the main factor in the adoption of mobile technology, having subjective norm and image within the organization as significant antecedents. Overall, this study was the first attempt at investigating scientifically, through a pertinent information systems research model, user adoption of mobile systems by homecare nursing personnel.

  4. Risk factors of suicide attempt among people with suicidal ideation in South Korea: a cross-sectional study

    Directory of Open Access Journals (Sweden)

    Soo Beom Choi

    2017-06-01

    Full Text Available Abstract Background Suicide is a serious public health concern worldwide, and the fourth leading cause of death in Korea. Few studies have focused on risk factors for suicide attempt among people with suicidal ideation. The aim of the present study was to investigate the risk factors and develop prediction models for suicide attempt among people with suicidal ideation in the Korean population. Method This study included 1567 men and 3726 women aged 20 years and older who had suicidal ideation from the Korea National Health and Nutrition Examination Survey from 2007 to 2012. Among them, 106 men and 188 women attempted suicide. Multivariate logistic regression analysis with backward stepwise elimination was performed to find risk factors for suicide attempt. Sub-group analysis, dividing participants into under 50 and at least 50 years old was also performed. Results Among people with suicidal ideation, age, education, cancer, and depressive disorder were selected as risk factors for suicide attempt in men. Age, education, national basic livelihood security, daily activity limitation, depressive disorder, stress, smoking, and regular exercise were selected in women. Area under curves of our prediction models in men and women were 0.728 and 0.716, respectively. Conclusions It is important to pay attention to populations with suicidal ideation and the risk factors mentioned above. Prediction models using the determined risk factors could be useful to detect high-risk groups early for suicide attempt among people with suicidal ideation. It is necessary to develop specific action plans for these high-risk groups to prevent suicide.

  5. Risk factors of suicide attempt among people with suicidal ideation in South Korea: a cross-sectional study.

    Science.gov (United States)

    Choi, Soo Beom; Lee, Wanhyung; Yoon, Jin-Ha; Won, Jong-Uk; Kim, Deok Won

    2017-06-15

    Suicide is a serious public health concern worldwide, and the fourth leading cause of death in Korea. Few studies have focused on risk factors for suicide attempt among people with suicidal ideation. The aim of the present study was to investigate the risk factors and develop prediction models for suicide attempt among people with suicidal ideation in the Korean population. This study included 1567 men and 3726 women aged 20 years and older who had suicidal ideation from the Korea National Health and Nutrition Examination Survey from 2007 to 2012. Among them, 106 men and 188 women attempted suicide. Multivariate logistic regression analysis with backward stepwise elimination was performed to find risk factors for suicide attempt. Sub-group analysis, dividing participants into under 50 and at least 50 years old was also performed. Among people with suicidal ideation, age, education, cancer, and depressive disorder were selected as risk factors for suicide attempt in men. Age, education, national basic livelihood security, daily activity limitation, depressive disorder, stress, smoking, and regular exercise were selected in women. Area under curves of our prediction models in men and women were 0.728 and 0.716, respectively. It is important to pay attention to populations with suicidal ideation and the risk factors mentioned above. Prediction models using the determined risk factors could be useful to detect high-risk groups early for suicide attempt among people with suicidal ideation. It is necessary to develop specific action plans for these high-risk groups to prevent suicide.

  6. Three-dimensional flow analysis and improvement of slip factor model for forward-curved blades centrifugal fan

    International Nuclear Information System (INIS)

    Guo, En Min; Kim, Kwang Yong

    2004-01-01

    This work developed improved slip factor model and correction method to predict flow through impeller in forward-curved centrifugal fan. Both steady and unsteady three-dimensional CFD analyses were performed to validate the slip factor model and the correction method. The results show that the improved slip factor model presented in this paper could provide more accurate predictions for forward-curved centrifugal impeller than the other slip factor models since the present model takes into account the effect of blade curvature. The correction method is provided to predict mass-averaged absolute circumferential velocity at the exit of impeller by taking account of blockage effects induced by the large-scale backflow near the front plate and flow separation within blade passage. The comparison with CFD results also shows that the improved slip factor model coupled with the present correction method provides accurate predictions for mass-averaged absolute circumferential velocity at the exit of impeller near and above the flow rate of peak total pressure coefficient

  7. Exploring Environmental Factors in Nursing Workplaces That Promote Psychological Resilience: Constructing a Unified Theoretical Model.

    Science.gov (United States)

    Cusack, Lynette; Smith, Morgan; Hegney, Desley; Rees, Clare S; Breen, Lauren J; Witt, Regina R; Rogers, Cath; Williams, Allison; Cross, Wendy; Cheung, Kin

    2016-01-01

    Building nurses' resilience to complex and stressful practice environments is necessary to keep skilled nurses in the workplace and ensuring safe patient care. A unified theoretical framework titled Health Services Workplace Environmental Resilience Model (HSWERM), is presented to explain the environmental factors in the workplace that promote nurses' resilience. The framework builds on a previously-published theoretical model of individual resilience, which identified the key constructs of psychological resilience as self-efficacy, coping and mindfulness, but did not examine environmental factors in the workplace that promote nurses' resilience. This unified theoretical framework was developed using a literary synthesis drawing on data from international studies and literature reviews on the nursing workforce in hospitals. The most frequent workplace environmental factors were identified, extracted and clustered in alignment with key constructs for psychological resilience. Six major organizational concepts emerged that related to a positive resilience-building workplace and formed the foundation of the theoretical model. Three concepts related to nursing staff support (professional, practice, personal) and three related to nursing staff development (professional, practice, personal) within the workplace environment. The unified theoretical model incorporates these concepts within the workplace context, linking to the nurse, and then impacting on personal resilience and workplace outcomes, and its use has the potential to increase staff retention and quality of patient care.

  8. The dog as a naturally-occurring model for insulin-like growth factor type 1 receptor-overexpressing breast cancer: an observational cohort study

    International Nuclear Information System (INIS)

    Jaillardon, Laetitia; Abadie, Jérome; Godard, Tiffanie; Campone, Mario; Loussouarn, Delphine; Siliart, Brigitte; Nguyen, Frédérique

    2015-01-01

    Dogs spontaneously develop invasive mammary carcinoma with a high prevalence of the triple-negative (TN) subtype (lack of ER-Estrogen Receptor and PR-Progesterone Receptor expression, lack of HER2-Human Epidermal Growth Factor Receptor 2 overexpression), making this animal model relevant for investigating new therapeutic pathways. Insulin-like growth factor Type-1 receptor (IGF1R) is frequently overexpressed in primary human breast cancers, with a growing role in the TN phenotype. The purpose of this study was to investigate the Dog as a candidate model for IGF1R-overexpressing mammary carcinoma. 150 bitches with canine mammary carcinoma (CMC) and a known 2-year follow-up were retrospectively included. IGF1R expression was assessed by immunohistochemistry (IHC) using a similar scoring system as for HER2 in breast cancer. The prognostic value of the IGF1R expression was assessed in terms of overall and specific survival as well as disease-free interval (DFI). 47 CMC (31 %) were classified as luminal and 103 (69 %) as triple-negative (TN-CMC). 41 % of CMC overexpressed IGF1R (IHC score 3+) of which 76 % were TN-CMC and 62 % grade III. IGF1R overexpression was associated with aggressive features including lymphovascular invasion, histological grade III, low ER expression and the TN phenotype. Univariate and multivariate analyses revealed that IGF1R overexpression was associated with shorter overall and specific survivals and shorter DFI in TN-CMC. IGF1R overexpression is common and related to a poor outcome in canine invasive mammary carcinoma, particularly in the triple negative subtype, as in human breast cancer. Preclinical studies using the Dog as a spontaneous animal model could be considered to investigate new therapies targeting IGF1R in triple-negative breast cancer. The online version of this article (doi:10.1186/s12885-015-1670-6) contains supplementary material, which is available to authorized users

  9. The Five-Factor Model of Personality and Career Success.

    Science.gov (United States)

    Seibert, Scott E.; Kraimer, Maria L.

    2001-01-01

    Measures of career success and an inventory of the Five-Factor Model of Personality were completed by 496 workers. Extraversion was related positively to salary, promotion, and career satisfaction; neuroticism was related negatively to satisfaction. A significant negative relationship between agreeableness and salary was found for workers in…

  10. Solvable light-front model of the electromagnetic form factor of the relativistic two-body bound state in 1+1 dimensions

    International Nuclear Information System (INIS)

    Mankiewicz, L.; Sawicki, M.

    1989-01-01

    Within a relativistically correct yet analytically solvable model of light-front quantum mechanics we construct the electromagnetic form factor of the two-body bound state and we study the validity of the static approximation to the full form factor. Upon comparison of full form factors calculated for different values of binding energy we observe an unexpected effect that for very strongly bound states further increase in binding leads to an increase in the size of the bound system. A similar effect is found for another quantum-mechanical model of relativistic dynamics

  11. The effect of choosing three different C factor formulae derived from NDVI on a fully raster-based erosion modelling

    Science.gov (United States)

    Sulistyo, Bambang

    2016-11-01

    The research was aimed at studying the efect of choosing three different C factor formulae derived from NDVI on a fully raster-based erosion modelling of The USLE using remote sensing data and GIS technique. Methods applied was by analysing all factors affecting erosion such that all data were in the form of raster. Those data were R, K, LS, C and P factors. Monthly R factor was evaluated based on formula developed by Abdurachman. K factor was determined using modified formula used by Ministry of Forestry based on soil samples taken in the field. LS factor was derived from Digital Elevation Model. Three C factors used were all derived from NDVI and developed by Suriyaprasit (non-linear) and by Sulistyo (linear and non-linear). P factor was derived from the combination between slope data and landcover classification interpreted from Landsat 7 ETM+. Another analysis was the creation of map of Bulk Density used to convert erosion unit. To know the model accuracy, model validation was done by applying statistical analysis and by comparing Emodel with Eactual. A threshold value of ≥ 0.80 or ≥ 80% was chosen to justify. The research result showed that all Emodel using three formulae of C factors have coeeficient of correlation value of > 0.8. The results of analysis of variance showed that there was significantly difference between Emodel and Eactual when using C factor formula developed by Suriyaprasit and Sulistyo (non-linear). Among the three formulae, only Emodel using C factor formula developed by Sulistyo (linear) reached the accuracy of 81.13% while the other only 56.02% as developed by Sulistyo (nonlinear) and 4.70% as developed by Suriyaprasit, respectively.

  12. Factors affecting increased risk for substance use disorders following traumatic brain injury: What we can learn from animal models.

    Science.gov (United States)

    Merkel, Steven F; Cannella, Lee Anne; Razmpour, Roshanak; Lutton, Evan; Raghupathi, Ramesh; Rawls, Scott M; Ramirez, Servio H

    2017-06-01

    Recent studies have helped identify multiple factors affecting increased risk for substance use disorders (SUDs) following traumatic brain injury (TBI). These factors include age at the time of injury, repetitive injury and TBI severity, neurocircuits, neurotransmitter systems, neuroinflammation, and sex differences. This review will address each of these factors by discussing 1) the clinical and preclinical data identifying patient populations at greatest risk for SUDs post-TBI, 2) TBI-related neuropathology in discrete brain regions heavily implicated in SUDs, and 3) the effects of TBI on molecular mechanisms that may drive substance abuse behavior, like dopaminergic and glutamatergic transmission or neuroimmune signaling in mesolimbic regions of the brain. Although these studies have laid the groundwork for identifying factors that affect risk of SUDs post-TBI, additional studies are required. Notably, preclinical models have been shown to recapitulate many of the behavioral, cellular, and neurochemical features of SUDs and TBI. Therefore, these models are well suited for answering important questions that remain in future investigations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Model of medicines sales forecasting taking into account factors of influence

    Science.gov (United States)

    Kravets, A. G.; Al-Gunaid, M. A.; Loshmanov, V. I.; Rasulov, S. S.; Lempert, L. B.

    2018-05-01

    The article describes a method for forecasting sales of medicines in conditions of data sampling, which is insufficient for building a model based on historical data alone. The developed method is applicable mainly to new drugs that are already licensed and released for sale but do not yet have stable sales performance in the market. The purpose of this study is to prove the effectiveness of the suggested method forecasting drug sales, taking into account the selected factors of influence, revealed during the review of existing solutions and analysis of the specificity of the area under study. Three experiments were performed on samples of different volumes, which showed an improvement in the accuracy of forecasting sales in small samples.

  14. Empiric model for mean generation time adjustment factor for classic point kinetics equations

    Energy Technology Data Exchange (ETDEWEB)

    Goes, David A.B.V. de; Martinez, Aquilino S.; Goncalves, Alessandro da C., E-mail: david.goes@poli.ufrj.br, E-mail: aquilino@lmp.ufrj.br, E-mail: alessandro@con.ufrj.br [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Departamento de Engenharia Nuclear

    2017-11-01

    Point reactor kinetics equations are the easiest way to observe the neutron production time behavior in a nuclear reactor. These equations are derived from the neutron transport equation using an approximation called Fick's law leading to a set of first order differential equations. The main objective of this study is to review classic point kinetics equation in order to approximate its results to the case when it is considered the time variation of the neutron currents. The computational modeling used for the calculations is based on the finite difference method. The results obtained with this model are compared with the reference model and then it is determined an empirical adjustment factor that modifies the point reactor kinetics equation to the real scenario. (author)

  15. Empiric model for mean generation time adjustment factor for classic point kinetics equations

    International Nuclear Information System (INIS)

    Goes, David A.B.V. de; Martinez, Aquilino S.; Goncalves, Alessandro da C.

    2017-01-01

    Point reactor kinetics equations are the easiest way to observe the neutron production time behavior in a nuclear reactor. These equations are derived from the neutron transport equation using an approximation called Fick's law leading to a set of first order differential equations. The main objective of this study is to review classic point kinetics equation in order to approximate its results to the case when it is considered the time variation of the neutron currents. The computational modeling used for the calculations is based on the finite difference method. The results obtained with this model are compared with the reference model and then it is determined an empirical adjustment factor that modifies the point reactor kinetics equation to the real scenario. (author)

  16. Risk factors and a prediction model for lower limb lymphedema following lymphadenectomy in gynecologic cancer: a hospital-based retrospective cohort study.

    Science.gov (United States)

    Kuroda, Kenji; Yamamoto, Yasuhiro; Yanagisawa, Manami; Kawata, Akira; Akiba, Naoya; Suzuki, Kensuke; Naritaka, Kazutoshi

    2017-07-25

    Lower limb lymphedema (LLL) is a chronic and incapacitating condition afflicting patients who undergo lymphadenectomy for gynecologic cancer. This study aimed to identify risk factors for LLL and to develop a prediction model for its occurrence. Pelvic lymphadenectomy (PLA) with or without para-aortic lymphadenectomy (PALA) was performed on 366 patients with gynecologic malignancies at Yaizu City Hospital between April 2002 and July 2014; we retrospectively analyzed 264 eligible patients. The intervals between surgery and diagnosis of LLL were calculated; the prevalence and risk factors were evaluated using the Kaplan-Meier and Cox proportional hazards methods. We developed a prediction model with which patients were scored and classified as low-risk or high-risk. The cumulative incidence of LLL was 23.1% at 1 year, 32.8% at 3 years, and 47.7% at 10 years post-surgery. LLL developed after a median 13.5 months. Using regression analysis, body mass index (BMI) ≥25 kg/m 2 (hazard ratio [HR], 1.616; 95% confidence interval [CI], 1.030-2.535), PLA + PALA (HR, 2.323; 95% CI, 1.126-4.794), postoperative radiation therapy (HR, 2.469; 95% CI, 1.148-5.310), and lymphocyst formation (HR, 1.718; 95% CI, 1.120-2.635) were found to be independently associated with LLL; age, type of cancer, number of lymph nodes, retroperitoneal suture, chemotherapy, lymph node metastasis, herbal medicine, self-management education, or infection were not associated with LLL. The predictive score was based on the 4 associated variables; patients were classified as high-risk (scores 3-6) and low-risk (scores 0-2). LLL incidence was significantly greater in the high-risk group than in the low-risk group (HR, 2.19; 95% CI, 1.440-3.324). The cumulative incidence at 5 years was 52.1% [95% CI, 42.9-62.1%] for the high-risk group and 28.9% [95% CI, 21.1-38.7%] for the low-risk group. The area under the receiver operator characteristics curve for the prediction model was 0.631 at 1 year, 0

  17. Quantification of source impact to PM using three-dimensional weighted factor model analysis on multi-site data

    Science.gov (United States)

    Shi, Guoliang; Peng, Xing; Huangfu, Yanqi; Wang, Wei; Xu, Jiao; Tian, Yingze; Feng, Yinchang; Ivey, Cesunica E.; Russell, Armistead G.

    2017-07-01

    Source apportionment technologies are used to understand the impacts of important sources of particulate matter (PM) air quality, and are widely used for both scientific studies and air quality management. Generally, receptor models apportion speciated PM data from a single sampling site. With the development of large scale monitoring networks, PM speciation are observed at multiple sites in an urban area. For these situations, the models should account for three factors, or dimensions, of the PM, including the chemical species concentrations, sampling periods and sampling site information, suggesting the potential power of a three-dimensional source apportionment approach. However, the principle of three-dimensional Parallel Factor Analysis (Ordinary PARAFAC) model does not always work well in real environmental situations for multi-site receptor datasets. In this work, a new three-way receptor model, called "multi-site three way factor analysis" model is proposed to deal with the multi-site receptor datasets. Synthetic datasets were developed and introduced into the new model to test its performance. Average absolute error (AAE, between estimated and true contributions) for extracted sources were all less than 50%. Additionally, three-dimensional ambient datasets from a Chinese mega-city, Chengdu, were analyzed using this new model to assess the application. Four factors are extracted by the multi-site WFA3 model: secondary source have the highest contributions (64.73 and 56.24 μg/m3), followed by vehicular exhaust (30.13 and 33.60 μg/m3), crustal dust (26.12 and 29.99 μg/m3) and coal combustion (10.73 and 14.83 μg/m3). The model was also compared to PMF, with general agreement, though PMF suggested a lower crustal contribution.

  18. Assimilation of enterprise technology upgrades: a factor-based study

    Science.gov (United States)

    Claybaugh, Craig C.; Ramamurthy, Keshavamurthy; Haseman, William D.

    2017-02-01

    The purpose of this study is to gain a better understanding of the differences in the propensity of firms to initiate and commit to the assimilation of an enterprise technology upgrade. A research model is proposed that examines the influences that four technological and four organisational factors have on predicting assimilation of a technology upgrade. Results show that firms with a greater propensity to assimilate the new enterprise resource planning (ERP) version have a higher assessment of relative advantage, IS technical competence, and the strategic role of IS relative to those firms with a lower propensity to assimilate a new ERP version.

  19. The Effect of Personality Traits on Sales Performance: An Empirical Investigation to Test the Five-Factor Model (FFM in Pakistan

    Directory of Open Access Journals (Sweden)

    Abdul Waheed

    2017-04-01

    Full Text Available Aim/Purpose: The present study investigates the relationship between the five-factor model (FFM of personality traits and sales performance in Pakistan. Background: Personality is a well-researched area in which numerous studies have examined the correlation between personality traits and job performance. In this study, a positive effect between the various dimensions of the five-factor model (extraversion, agreeableness, conscientiousness, emotional stability, and open to experience and sales performance in Pakistan is investigated. Methodology: Pearson’s correlation values as well as analysis methodologies were employed to gather descriptive statistics, reliability analysis, correlation analysis, and use the analytical hierarchy process (AHP. Cronbach’s alpha value helped determine the internal consistency of the group items. Questionnaires were distributed among 600 salespersons in various cities of Pakistan from April 2015 to January 2016. Subsequently, 510 questionnaires were acquired for the sample. Contribution: The current study contributes to the literature on personality traits and sales performance by applying empirical evidence from sales managers in three industries of Pakistan: pharmaceutical, insurance, and electronics. Findings: The results affirmed a positive effect of the five-factor model on sales performance among various industries in Pakistan. The effect of each sub-factor from the five-factor model was examined autonomously. There is a favorable benefit to sales managers in considering FFM when making hiring decisions. Impact on Society: FFM offers important insights into personality traits that work well within Pakistani sales industry structure. Future Research: A broader rendering of the effects of FFM on sales organizations in other geographical locations around Pakistan should be considered. Additionally, an extended study should be conducted to investigate the effects of FFM on female sales employees involving

  20. Motivation and personality: relationships between putative motive dimensions and the five factor model of personality.

    Science.gov (United States)

    Bernard, Larry C

    2010-04-01

    There are few multidimensional measures of individual differences in motivation available. The Assessment of Individual Motives-Questionnaire assesses 15 putative dimensions of motivation. The dimensions are based on evolutionary theory and preliminary evidence suggests the motive scales have good psychometric properties. The scales are reliable and there is evidence of their consensual validity (convergence of self-other ratings) and behavioral validity (relationships with self-other reported behaviors of social importance). Additional validity research is necessary, however, especially with respect to current models of personality. The present study tested two general and 24 specific hypotheses based on proposed evolutionary advantages/disadvantages and fitness benefits/costs of the five-factor model of personality together with the new motive scales in a sample of 424 participants (M age=28.8 yr., SD=14.6). Results were largely supportive of the hypotheses. These results support the validity of new motive dimensions and increase understanding of the five-factor model of personality.